1. A bridge settlement early warning method based on Beidou is applied to a bridge settlement early warning system, the system is in communication connection with a first height acquisition device and a second height acquisition device, and the method comprises the following steps:

obtaining first basic information of a first bridge;

obtaining a first analysis instruction, and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information;

acquiring a first coordinate point distribution instruction, and analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction to acquire a first coordinate distribution point of the first bridge;

obtaining a first coordinate system construction instruction, and constructing a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction;

obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system;

obtaining a first measured coordinate distribution set of the first coordinate distribution points through the first height acquisition equipment;

obtaining a second measured coordinate distribution set of the first coordinate distribution points through the second height acquisition equipment, wherein the second height acquisition equipment and the first height acquisition equipment are height acquisition equipment at different positions;

inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result;

obtaining a first coordinate deformation set according to the first coordinate comparison result;

and carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

2. The method of claim 1, wherein inputting the first measured coordinate distribution set, the second measured coordinate distribution set, and the first coordinate set into a first coordinate deviation analysis model further comprises, before obtaining a first coordinate comparison result:

obtaining a first coordinate deviation value through the first measured coordinate distribution set and the second measured coordinate distribution set, wherein the first coordinate deviation value is a maximum deviation value of the same coordinate in the first measured coordinate distribution set and the second measured coordinate distribution set;

obtaining a first coordinate deviation preset threshold;

judging whether the first coordinate deviation value meets a first coordinate deviation preset threshold value or not;

and when the first coordinate deviation value meets the first coordinate deviation preset threshold value, inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result.

3. The method of claim 2, wherein the determining whether the first coordinate deviation value satisfies the first coordinate deviation preset threshold further comprises:

when the first coordinate deviation value does not meet the first coordinate deviation preset threshold value, a first coordinate correction instruction is obtained;

obtaining a first reference coordinate measuring point according to the first coordinate correcting instruction;

and performing benchmark correction on the first height acquisition equipment and the second height acquisition equipment based on the first benchmark coordinate measurement point.

4. The method of claim 1, wherein the system is further communicatively coupled to a first image acquisition device, further comprising:

obtaining a first acquisition time of the first height acquisition device;

obtaining a first time expansion instruction, and performing time expansion on the first acquisition time according to the first time expansion instruction to obtain a first time interval;

obtaining, by the first image acquisition device, a first image set of the first time interval, wherein the first image set is a vehicle distribution set of the first bridge in the first time interval;

obtaining a first load-bearing distribution prediction result based on the first image set;

evaluating the rationality of the first coordinate deformation set based on the first load-bearing distribution pre-estimation result to obtain a first rationality evaluation result;

and carrying out real-time settlement deformation early warning on the first bridge based on the first rationality evaluation result.

5. The method of claim 4, wherein said obtaining a first load-bearing distribution predictor based on said first set of images further comprises:

obtaining corresponding vehicle information based on the images in the first image set, wherein the vehicle information comprises real-time speed, real-time position and real-time weight information of the vehicle;

obtaining a vehicle distribution position estimation result at the first acquisition time according to the vehicle information;

and obtaining the first load-bearing distribution estimation result according to the vehicle distribution position estimation result and the vehicle information.

6. The method of claim 1, wherein the method further comprises:

obtaining a first historical coordinate deformation set of the first bridge;

obtaining a first historical coordinate deformation image of the first bridge according to the first historical coordinate deformation set;

acquiring deformation abnormal characteristics of a first unit time;

performing feature traversal on the first historical coordinate deformation image based on the first unit time deformation abnormal feature to obtain a first feature traversal result;

and carrying out settlement deformation early warning on the first bridge based on the first characteristic traversal result.

7. The method of claim 1, wherein said inputting said first measured coordinate distribution set, said second measured coordinate distribution set, and said first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result, further comprises:

constructing a first coordinate deviation analysis model, wherein the first coordinate deviation analysis model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set, the first coordinate set and identification information identifying a coordinate comparison result;

and inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into the first coordinate deviation analysis model to obtain a first coordinate comparison result.

8. The utility model provides a bridge subsides early warning system based on big dipper, wherein, the system includes:

the first obtaining unit is used for obtaining first basic information of a first bridge;

the second obtaining unit is used for obtaining a first analysis instruction and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information;

the third obtaining unit is used for obtaining a first coordinate point distribution instruction, analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction, and obtaining a first coordinate distribution point of the first bridge;

a fourth obtaining unit, configured to obtain a first coordinate system construction instruction, and construct a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction;

a fifth obtaining unit, configured to obtain a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system;

a sixth obtaining unit, configured to obtain a first actually-measured coordinate distribution set of the first coordinate distribution point through a first height acquisition device;

a seventh obtaining unit, configured to obtain a second actually-measured coordinate distribution set of the first coordinate distribution point through a second height collecting device, where the second height collecting device and the first height collecting device are height collecting devices at different positions;

an eighth obtaining unit, configured to input the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set, and the first coordinate set into a first coordinate deviation analysis model, and obtain a first coordinate comparison result;

a ninth obtaining unit, configured to obtain a first coordinate deformation set according to the first coordinate comparison result;

and the first early warning unit is used for carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

9. A Beidou-based bridge settlement early warning system comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the program.

Background

With the continuous improvement of the bridge construction level in China, new processes, new technologies and new materials are increasingly applied to the bridge construction process, so that the large-span bridge appears like a spring bamboo shoot after rain. The bridge body is influenced by external factors such as travelling load, wind power, temperature and sudden natural disasters during operation, and also influenced by internal factors such as concrete shrinkage and creep, concrete aging, concrete carbonization, steel bar relaxation, steel bar corrosion, stay cable corrosion, abutment foundation settlement and the like.

The bridge settlement monitoring device can accurately monitor the settlement of the bridge, effectively guarantee the real-time state of the bridge, and guarantee the safety of the bridge. However, the settlement detection of the bridge is not intelligent and accurate enough in real life, and the accurate settlement early warning cannot be carried out.

However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:

the technical problem that the real-time parameters of bridge settlement cannot be accurately detected and evaluated and further the bridge cannot be accurately early warned exists in the prior art.

Disclosure of Invention

The embodiment of the application provides a bridge settlement early warning method and system based on the Beidou, solves the technical problems that in the prior art, accurate detection and assessment cannot be carried out on the real-time parameter of bridge settlement, and then early warning cannot be accurately carried out on the bridge, achieves the technical effect of combining the Beidou satellite, carrying out real-time and accurate supervision and analysis on the parameter of the bridge, and then achieving accurate early warning on the settlement state of the bridge.

In view of the above problems, the embodiment of the application provides a bridge settlement early warning method and system based on the big dipper.

In a first aspect, the application provides a bridge settlement early warning method based on Beidou, wherein the method is applied to a bridge settlement early warning system, the system is in communication connection with a first height acquisition device and a second height acquisition device, and the method comprises the following steps: obtaining first basic information of a first bridge; obtaining a first analysis instruction, and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information; acquiring a first coordinate point distribution instruction, and analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction to acquire a first coordinate distribution point of the first bridge; obtaining a first coordinate system construction instruction, and constructing a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction; obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system; obtaining a first measured coordinate distribution set of the first coordinate distribution points through the first height acquisition equipment; obtaining a second measured coordinate distribution set of the first coordinate distribution points through the second height acquisition equipment, wherein the second height acquisition equipment and the first height acquisition equipment are height acquisition equipment at different positions; inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result; obtaining a first coordinate deformation set according to the first coordinate comparison result; and carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

On the other hand, this application still provides a bridge settlement early warning system based on big dipper, the system includes: the first obtaining unit is used for obtaining first basic information of a first bridge; the second obtaining unit is used for obtaining a first analysis instruction and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information; the third obtaining unit is used for obtaining a first coordinate point distribution instruction, analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction, and obtaining a first coordinate distribution point of the first bridge; a fourth obtaining unit, configured to obtain a first coordinate system construction instruction, and construct a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction; a fifth obtaining unit, configured to obtain a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system; a sixth obtaining unit, configured to obtain a first actually-measured coordinate distribution set of the first coordinate distribution point through a first height acquisition device; a seventh obtaining unit, configured to obtain a second actually-measured coordinate distribution set of the first coordinate distribution point through a second height collecting device, where the second height collecting device and the first height collecting device are height collecting devices at different positions; an eighth obtaining unit, configured to input the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set, and the first coordinate set into a first coordinate deviation analysis model, and obtain a first coordinate comparison result; a ninth obtaining unit, configured to obtain a first coordinate deformation set according to the first coordinate comparison result; and the first early warning unit is used for carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

In a third aspect, the invention provides a bridge settlement early warning system based on the Beidou, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.

One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

the method comprises the steps of obtaining first basic information of a first bridge, obtaining a first deformation early warning distribution map based on the first basic information, analyzing according to the first deformation early warning distribution map to obtain a first coordinate distribution point, obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system through the first coordinate distribution point, obtaining a first actually-measured coordinate distribution set of the first coordinate distribution point through the first coordinate collection equipment, obtaining a second actually-measured coordinate distribution set of the first coordinate distribution point through the second height collection device, inputting the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result, and obtaining a first coordinate deformation set according to the first coordinate comparison result, and performing real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map, so that the technical effect of accurately performing early warning on the settlement state of the bridge by combining a Beidou satellite and accurately supervising and analyzing the parameters of the bridge in real time is achieved.

The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.

Drawings

Fig. 1 is a schematic flow diagram of a bridge settlement early warning method based on the big dipper in the embodiment of the application;

FIG. 2 is a schematic structural diagram of a bridge settlement early warning system based on Beidou in the embodiment of the application;

fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.

Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a sixth obtaining unit 16, a seventh obtaining unit 17, an eighth obtaining unit 18, a ninth obtaining unit 19, a first warning unit 20, an electronic device 50, a processor 51, a memory 52, an input device 53, and an output device 54.

Detailed Description

The embodiment of the application provides a bridge settlement early warning method and system based on the Beidou, solves the technical problems that in the prior art, accurate detection and assessment cannot be carried out on the real-time parameter of bridge settlement, and then early warning cannot be accurately carried out on the bridge, achieves the technical effect of combining the Beidou satellite, carrying out real-time and accurate supervision and analysis on the parameter of the bridge, and then achieving accurate early warning on the settlement state of the bridge. Embodiments of the present application are described below with reference to the accompanying drawings. As can be known to those skilled in the art, with the development of technology and the emergence of new scenarios, the technical solution provided in the embodiments of the present application is also applicable to similar technical problems.

The terms "first," "second," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances and are merely descriptive of the various embodiments of the application and how objects of the same nature can be distinguished. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

Summary of the application

With the continuous improvement of the bridge construction level in China, new processes, new technologies and new materials are increasingly applied to the bridge construction process, so that the large-span bridge appears like a spring bamboo shoot after rain. The bridge body is influenced by external factors such as travelling load, wind power, temperature and sudden natural disasters during operation, and also influenced by internal factors such as concrete shrinkage and creep, concrete aging, concrete carbonization, steel bar relaxation, steel bar corrosion, stay cable corrosion, abutment foundation settlement and the like.

The bridge settlement monitoring device can accurately monitor the settlement of the bridge, effectively guarantee the real-time state of the bridge, and guarantee the safety of the bridge. However, the settlement detection of the bridge is not intelligent and accurate enough in real life, and the accurate settlement early warning cannot be carried out.

In view of the above technical problems, the technical solution provided by the present application has the following general idea:

the embodiment of the application provides a bridge settlement early warning method based on Beidou, wherein the method is applied to a bridge settlement early warning system, the system is in communication connection with a first height acquisition device and a second height acquisition device, and the method comprises the following steps: obtaining first basic information of a first bridge; obtaining a first analysis instruction, and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information; acquiring a first coordinate point distribution instruction, and analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction to acquire a first coordinate distribution point of the first bridge; obtaining a first coordinate system construction instruction, and constructing a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction; obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system; obtaining a first measured coordinate distribution set of the first coordinate distribution points through the first height acquisition equipment; obtaining a second measured coordinate distribution set of the first coordinate distribution points through the second height acquisition equipment, wherein the second height acquisition equipment and the first height acquisition equipment are height acquisition equipment at different positions; inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result; obtaining a first coordinate deformation set according to the first coordinate comparison result; and carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.

Example one

As shown in fig. 1, an embodiment of the present application provides a bridge settlement early warning method based on the big dipper, wherein the method is applied to a bridge settlement early warning system, the system is in communication connection with a first height acquisition device and a second height acquisition device, and the method includes:

step S100: obtaining first basic information of a first bridge;

particularly, the bridge subsides early warning system carries out analysis processes for each item monitoring data to the bridge in real time, realizes the system of the real-time early warning of the settlement state of bridge, the system and first high collection equipment, the high collection equipment communication connection of second, first high collection equipment and the high collection equipment of second are the equipment of different positions, wherein, first high collection equipment and the high collection equipment of second are big dipper positioning unit, can with the data real-time transmission of real-time collection, share extremely the bridge subsides early warning system. The first bridge is used for settlement assessment and early warning, and first basic information of the first bridge is obtained, wherein the first basic information comprises a drawing when the bridge is built and related basic information such as materials and bearing.

Step S200: obtaining a first analysis instruction, and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information;

step S300: acquiring a first coordinate point distribution instruction, and analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction to acquire a first coordinate distribution point of the first bridge;

specifically, the first analysis instruction is an instruction for performing digital analysis on the first bridge according to the material, structure, drawing information and the like of the first bridge, the first bridge is divided into position areas according to data information of a main pier, a main girder structure and concrete of the first bridge, early warning deformation calculation is performed according to different importance degrees, bearing capacity and deformation conditions of bridges in different position areas, deformation size threshold values of different area positions are obtained, and the first deformation early warning distribution map is obtained based on the deformation size threshold values and the area positions. And distributing coordinate points according to the region positions, wherein the coordinate points are key points for monitoring the settlement deformation of the first bridge, and distributing the coordinate points of the first bridge based on the first coordinate point distribution instruction to obtain first coordinate distribution points.

Step S400: obtaining a first coordinate system construction instruction, and constructing a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction;

step S500: obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system;

specifically, the coordinate system constructing instruction is a process of constructing a three-dimensional rectangular coordinate system by using a calibrated coordinate origin, the first rectangular coordinate system is constructed after an X, Y, Z-axis direction is set by setting the coordinate origin, further, calculation and generation of subsequent coordinates are completed in the first rectangular coordinate system, each coordinate information of the first coordinate distribution point is obtained based on the first rectangular coordinate system, and the first coordinate set is formed based on the coordinate information.

Step S600: obtaining a first measured coordinate distribution set of the first coordinate distribution points through the first height acquisition equipment;

step S700: obtaining a second measured coordinate distribution set of the first coordinate distribution points through the second height acquisition equipment, wherein the second height acquisition equipment and the first height acquisition equipment are height acquisition equipment at different positions;

particularly, first height acquisition equipment is big dipper positioning unit, based on first height acquisition equipment passes through the big dipper satellite, obtains first coordinate acquisition result, promptly first measured coordinate distribution set, it is further, the collection process of coordinate is for passing through the big dipper satellite carries out the collection and the analysis and processing of signal, carries out empirical mode decomposition with the signal of gathering and carries out the signal decomposition of making an uproar that falls, carries out the wavelet to the signal that contains the noise and falls the processing back of making an uproar, carries out the first measured coordinate distribution set that big dipper acquisition signal reconsitution obtained. Furthermore, the second height collecting device is a collecting device at a position different from that of the first height collecting device, and a second measured coordinate distribution set of the first coordinate distribution point is obtained through the second height collecting device. Through the measurement of two different measured height distribution sets, the foundation is tamped for the follow-up accurate coordinate of obtaining the bridge, and then more accurate settlement analysis results can be obtained, and then the technical effect of carrying out accurate early warning is achieved.

Step S800: inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result;

specifically, the first coordinate deviation analysis model is a model that performs coordinate deviation analysis according to different coordinates to further obtain a deformation analysis result, a first pre-coordinate deformation set is obtained based on the first measured coordinate distribution set and the first coordinate set, a second pre-coordinate deformation set is obtained based on the second measured coordinate distribution set and the first coordinate set, and coordinate deformation with relatively large deformation in the first pre-coordinate deformation set and the second pre-coordinate deformation set is taken to form the first coordinate comparison result.

Step S900: obtaining a first coordinate deformation set according to the first coordinate comparison result;

step S1000: and carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

Specifically, a first coordinate deformation set is obtained based on the first coordinate comparison result, the first deformation early warning distribution map is compared based on the first coordinate deformation set, the comparison result between the actual deformation amount of each position area in the first coordinate deformation set and each deformation amount of each position area in the first deformation early warning distribution map is obtained, real-time detection information of the bridge is obtained according to the comparison result, and whether settlement early warning of the bridge is carried out or not is judged based on the detection information. The technical effect that the parameter of the bridge is accurately monitored and analyzed in real time by combining the Beidou satellite is achieved, and then the early warning on the settlement state of the bridge is accurately achieved.

Further, before the inputting the first measured coordinate distribution set, the second measured coordinate distribution set, and the first coordinate set into the first coordinate deviation analysis model and obtaining the first coordinate comparison result, step S800 in this embodiment of the present application further includes:

step S810: obtaining a first coordinate deviation value through the first measured coordinate distribution set and the second measured coordinate distribution set, wherein the first coordinate deviation value is a maximum deviation value of the same coordinate in the first measured coordinate distribution set and the second measured coordinate distribution set;

step S820: obtaining a first coordinate deviation preset threshold;

step S830: judging whether the first coordinate deviation value meets a first coordinate deviation preset threshold value or not;

step S840: and when the first coordinate deviation value meets the first coordinate deviation preset threshold value, inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result.

Specifically, a first coordinate deviation value is obtained based on the first measured coordinate distribution set and the second measured coordinate distribution set, and further, the process of obtaining the deviation value is a process of comparing coordinates one by one, the same coordinate information in the first measured coordinate distribution set and the second measured coordinate distribution set is obtained, the measured coordinate values of the same coordinates are compared in real time, a deviation value of each coordinate in the two measured coordinate distribution values is obtained, the coordinates of the deviation value are compared, and the coordinate information with the largest deviation value, namely the first coordinate deviation value, is obtained. Presetting a coordinate deviation threshold value, judging whether the first coordinate deviation value meets the first coordinate deviation value preset threshold value, when the first deviation value meets the first coordinate deviation value threshold value, indicating that the precision of the first height acquisition equipment and the second height acquisition equipment can meet the requirement, and inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result.

Further, the determining whether the first coordinate deviation value meets the first coordinate deviation preset threshold value, in step S830 of this embodiment of the present application, further includes:

step S831: when the first coordinate deviation value does not meet the first coordinate deviation preset threshold value, a first coordinate correction instruction is obtained;

step S832: obtaining a first reference coordinate measuring point according to the first coordinate correcting instruction;

step S833: and performing benchmark correction on the first height acquisition equipment and the second height acquisition equipment based on the first benchmark coordinate measurement point.

Specifically, when the first coordinate deviation value cannot meet the first coordinate deviation value preset threshold, it indicates that the acquired information deviation of the first height acquiring device and the second height acquiring device is large at this time. At the moment, a first comparison instruction is obtained, the other point acquisition information of the first height acquisition equipment and the second height acquisition equipment is compared according to the first comparison instruction, whether the other point acquisition information of the first height acquisition equipment and the second height acquisition equipment is abnormal or not is judged, and when only single-point information is abnormal, the single-point information is possibly interfered by the information, and at the moment, only the coordinates corresponding to the first coordinate deviation value are re-sampled, when other acquisition point information is abnormal, the first height acquisition equipment and the second height acquisition equipment are indicated to have abnormal equipment, at the moment, a first reference coordinate measurement point is obtained to carry out equipment correction, and the first height acquisition equipment and the second height acquisition equipment are subjected to reference correction based on the first reference coordinate measurement point. Through carrying out the simultaneous measurement of two equipment to same coordinate, make the measuring result can carry out real-time contrast, is convenient for discover abnormal conditions, reduces the influence of the unusual to the measuring result of equipment, and then reaches and combines big dipper satellite, carries out real-time accurate supervision and analysis to the parameter of bridge, and then reaches the technological effect that the accuracy carries out the early warning to the settlement state of bridge.

Further, the system is further connected to a first image capturing device in a communication manner, and step S1100 in this embodiment of the present application further includes:

step S1110: obtaining a first acquisition time of the first height acquisition device;

step S1120: obtaining a first time expansion instruction, and performing time expansion on the first acquisition time according to the first time expansion instruction to obtain a first time interval;

step S1130: obtaining, by the first image acquisition device, a first image set of the first time interval, wherein the first image set is a vehicle distribution set of the first bridge in the first time interval;

step S1140: obtaining a first load-bearing distribution prediction result based on the first image set;

step S1150: evaluating the rationality of the first coordinate deformation set based on the first load-bearing distribution pre-estimation result to obtain a first rationality evaluation result;

step S1160: and carrying out real-time settlement deformation early warning on the first bridge based on the first rationality evaluation result.

Specifically, the first height collecting device and the second height collecting device perform coordinate collection simultaneously to obtain collecting time of the first height collecting device, and perform time expansion according to the first collecting time to obtain a first time interval, wherein the amount of the first time interval is determined according to the length and the speed limit of the bridge. The method comprises the steps of acquiring an image of a first bridge through a first image acquisition device, estimating vehicles of the first bridge at a first acquisition time node according to the acquired vehicle information, acquiring distribution positions of the vehicles at the first acquisition time node according to the estimation results, acquiring weight information of different vehicles according to a first image set, and acquiring a first bearing distribution result of the first bridge based on the weight information and the distribution position information. And evaluating the rationality of the first coordinate deformation set according to the first load-bearing distribution result to obtain a first rationality evaluation result. And carrying out real-time bridge settlement deformation early warning on the first bridge based on the first rationality evaluation result.

Further, in step S1140 of obtaining a first estimated weight-bearing distribution based on the first image set, an embodiment of the present application further includes:

step S1141: obtaining corresponding vehicle information based on the images in the first image set, wherein the vehicle information comprises real-time speed, real-time position and real-time weight information of the vehicle;

step S1142: obtaining a vehicle distribution position estimation result at the first acquisition time according to the vehicle information;

step S1143: and obtaining the first load-bearing distribution estimation result according to the vehicle distribution position estimation result and the vehicle information.

Specifically, vehicle information in the first time interval is captured based on the images in the first image set, relevant information of the vehicle in the first time interval is obtained, the relevant information comprises vehicle speed information, real-time position information and weight information, the weight information can be obtained through obtaining license plate information, owner information corresponding to the vehicle is obtained, and then the weight information is obtained. And estimating the position of the vehicle at the first acquisition time according to the acquired vehicle information to acquire a vehicle distribution position estimation result. And estimating the first bearing distribution result based on the estimation result of the distribution position of the vehicle and by combining the weight information of different vehicles to obtain the first bearing distribution estimation result. Through the collection to vehicle information, make real-time bearing of bridge distributes and acquires more accurately, and then carries out accurate aassessment to whether bridge amount deformation is unusual, and then reaches the parameter of bridge and carries out real-time accurate supervision and analysis, and then reaches the technological effect that the accuracy carries out the early warning to the settlement state of bridge.

Further, step S1200 in the embodiment of the present application further includes:

step 1210: obtaining a first historical coordinate deformation set of the first bridge;

step S1220: obtaining a first historical coordinate deformation image of the first bridge according to the first historical coordinate deformation set;

step S1230: acquiring deformation abnormal characteristics of a first unit time;

step S1240: performing feature traversal on the first historical coordinate deformation image based on the first unit time deformation abnormal feature to obtain a first feature traversal result;

step S1250: and carrying out settlement deformation early warning on the first bridge based on the first characteristic traversal result.

Specifically, the first historical coordinate deformation set is historical data for measuring the first bridge, images of deformation of all positions of the first bridge changing along with time are drawn based on the historical coordinate deformation set, the first historical coordinate deformation image is formed according to an image set of the deformation changing along with time, deformation abnormal features of a first unit time are obtained, the deformation abnormal features of the first unit time are used as convolution features, feature traversal is conducted on the first historical coordinate deformation image, a first feature traversal result is obtained, whether an image with a high association degree with the first unit time deformation feature exists in the first historical coordinate deformation image or not is judged according to the first feature traversal result, and when the image exists, early warning processing is conducted on settlement deformation of the first bridge of the event.

Further, the step S800 of the embodiment of the present application further includes inputting the first measured coordinate distribution set, the second measured coordinate distribution set, and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result, where:

step S850: constructing a first coordinate deviation analysis model, wherein the first coordinate deviation analysis model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set, the first coordinate set and identification information identifying a coordinate comparison result;

step S860: and inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into the first coordinate deviation analysis model to obtain a first coordinate comparison result.

Specifically, the first coordinate deviation analysis model is a model for performing coordinate analysis and comparison evaluation of coordinates, and the model is obtained by training a large amount of training data. Firstly, a large amount of data required by experiments are collected, namely a first measured coordinate distribution set and a second measured coordinate distribution set are subjected to mapping relation construction on the first coordinate set based on big data, and then a training data set is constructed based on the data after the mapping relation construction. And training the first coordinate deviation analysis model through the training data set.

Further, the training process is substantially a supervised learning process, each group of supervised data includes the first measured coordinate distribution set, the second measured coordinate distribution set, and identification information identifying a coordinate comparison result, the first group of the first measured coordinate distribution set, the second measured coordinate distribution set, and the first coordinate set are input into the neural network model, supervised learning is performed according to the first group of identification information identifying a coordinate comparison result, so that the supervised learning of the first group of training data is finished when the output data of the first coordinate deviation analysis model is consistent with the supervised data, and in the same way, the data in the training data set are continuously self-corrected and adjusted by the neural network model until the obtained output result is consistent with each identification information, and ending the supervised learning of the data set, and ending the supervised learning process when the neural network model is in a convergence state. Through supervised learning of the model, the model can process the input information more accurately, and a more accurate and reasonable first coordinate comparison result is obtained.

To sum up, the bridge settlement early warning method and system based on the Beidou have the following technical effects:

1. the method comprises the steps of obtaining first basic information of a first bridge, obtaining a first deformation early warning distribution map based on the first basic information, analyzing according to the first deformation early warning distribution map to obtain a first coordinate distribution point, obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system through the first coordinate distribution point, obtaining a first actually-measured coordinate distribution set of the first coordinate distribution point through the first coordinate collection equipment, obtaining a second actually-measured coordinate distribution set of the first coordinate distribution point through the second height collection device, inputting the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result, and obtaining a first coordinate deformation set according to the first coordinate comparison result, and performing real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map, so that the technical effect of accurately performing early warning on the settlement state of the bridge by combining a Beidou satellite and accurately supervising and analyzing the parameters of the bridge in real time is achieved.

2. Due to the fact that the mode of simultaneous measurement of the two devices on the same coordinate is adopted, the measurement results can be compared in real time, abnormal conditions can be found conveniently, the influence of the abnormality of the devices on the measurement results is reduced, and therefore the technical effect that the Beidou satellite is combined to supervise and analyze the parameters of the bridge accurately in real time and accurately early warn the settlement state of the bridge is achieved.

Example two

Based on the same inventive concept as the bridge settlement early warning method based on the Beidou in the foregoing embodiment, the invention also provides a bridge settlement early warning system based on the Beidou, and as shown in fig. 2, the system comprises:

a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first basic information of a first bridge;

the second obtaining unit 12 is configured to obtain a first parsing instruction, and obtain a first deformation early warning distribution map of the first bridge according to the first parsing instruction and the first basic information;

the third obtaining unit 13 is configured to obtain a first coordinate point distribution instruction, and analyze the first deformation early warning distribution map according to the first coordinate point distribution instruction to obtain a first coordinate distribution point of the first bridge;

a fourth obtaining unit 14, where the fourth obtaining unit 14 is configured to obtain a first coordinate system building instruction, and build a first rectangular coordinate system of the first bridge according to the first coordinate system building instruction;

a fifth obtaining unit 15, where the fifth obtaining unit 15 is configured to obtain a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system;

a sixth obtaining unit 16, where the sixth obtaining unit 16 is configured to obtain a first measured coordinate distribution set of the first coordinate distribution point through a first height collecting device;

a seventh obtaining unit 17, where the seventh obtaining unit 17 is configured to obtain a second actually-measured coordinate distribution set of the first coordinate distribution point through a second height collecting device, where the second height collecting device and the first height collecting device are height collecting devices at different positions;

an eighth obtaining unit 18, where the eighth obtaining unit 18 is configured to input the first measured coordinate distribution set, the second measured coordinate distribution set, and the first coordinate set into a first coordinate deviation analysis model, so as to obtain a first coordinate comparison result;

a ninth obtaining unit 19, where the ninth obtaining unit 19 is configured to obtain a first coordinate deformation set according to the first coordinate comparison result;

and the first early warning unit 20 is used for carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map.

Further, the system further comprises:

a tenth obtaining unit, configured to obtain a first coordinate deviation value through the first measured coordinate distribution set and the second measured coordinate distribution set, where the first coordinate deviation value is a maximum deviation value of a same coordinate in the first measured coordinate distribution set and the second measured coordinate distribution set;

an eleventh obtaining unit, configured to obtain a first coordinate deviation preset threshold;

the first judgment unit is used for judging whether the first coordinate deviation value meets a first coordinate deviation preset threshold value or not;

a twelfth obtaining unit, configured to, when the first coordinate deviation value satisfies the first coordinate deviation preset threshold, input the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set, and the first coordinate set into a first coordinate deviation analysis model, and obtain the first coordinate comparison result.

Further, the system further comprises:

a thirteenth obtaining unit configured to obtain a first coordinate correction instruction when the first coordinate deviation value does not satisfy the first coordinate deviation preset threshold;

a fourteenth obtaining unit configured to obtain a first reference coordinate measurement point according to the first coordinate correction instruction;

a first correction unit for performing reference correction on the first height acquisition device and the second height acquisition device based on the first reference coordinate measurement point.

Further, the system further comprises:

a fifteenth obtaining unit configured to obtain a first acquisition time of the first height acquisition apparatus;

a sixteenth obtaining unit, configured to obtain a first time expansion instruction, and perform time expansion on the first acquisition time according to the first time expansion instruction to obtain a first time interval;

a seventeenth obtaining unit, configured to obtain, by the first image acquisition device, a first image set of the first time interval, where the first image set is a vehicle distribution set of the first bridge in the first time interval;

an eighteenth obtaining unit, configured to obtain a first load-bearing distribution pre-estimate based on the first set of images;

a nineteenth obtaining unit, configured to evaluate the rationality of the first coordinate deformation set based on the first load-bearing distribution estimation result, and obtain a first rationality evaluation result;

and the second early warning unit is used for carrying out real-time settlement deformation early warning on the first bridge based on the first rationality evaluation result.

Further, the system further comprises:

a twentieth obtaining unit, configured to obtain corresponding vehicle information based on the images in the first image set, where the vehicle information includes a real-time vehicle speed, a real-time position, and a real-time weight information of the vehicle;

a twenty-first obtaining unit, configured to obtain, according to the vehicle information, a vehicle distribution position estimation result at the first acquisition time;

and the twenty-second obtaining unit is used for obtaining the first load bearing distribution estimation result according to the vehicle distribution position estimation result and the vehicle information.

Further, the system further comprises:

a twenty-third obtaining unit, configured to obtain a first historical coordinate deformation set of the first bridge;

a twenty-fourth obtaining unit, configured to obtain a first historical coordinate deformation image of the first bridge according to the first historical coordinate deformation set;

a twenty-fifth obtaining unit, configured to obtain a deformation abnormal feature of a first unit time;

a twenty-sixth obtaining unit, configured to perform feature traversal on the first historical coordinate deformation image based on the deformation abnormal feature in the first unit time, and obtain a first feature traversal result;

and the third early warning unit is used for carrying out settlement deformation early warning on the first bridge based on the first characteristic traversal result.

Further, the system further comprises:

the system comprises a first construction unit and a second construction unit, wherein the first construction unit is used for constructing a first coordinate deviation analysis model, the first coordinate deviation analysis model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises a first measured coordinate distribution set, a second measured coordinate distribution set, a first coordinate set and identification information for identifying a coordinate comparison result;

a twenty-seventh obtaining unit, configured to input the first actually-measured coordinate distribution set, the second actually-measured coordinate distribution set, and the first coordinate set into the first coordinate deviation analysis model, and obtain the first coordinate comparison result.

Various changes and specific examples of the bridge settlement early warning method based on the big dipper in the first embodiment of fig. 1 are also applicable to the bridge settlement early warning system based on the big dipper in the present embodiment, and through the foregoing detailed description of the bridge settlement early warning method based on the big dipper, those skilled in the art can clearly know the implementation method of the bridge settlement early warning system based on the big dipper in the present embodiment, so for the brevity of the description, detailed description is not repeated here.

Exemplary electronic device

The electronic device of the embodiment of the present application is described below with reference to fig. 3.

Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.

Based on the inventive concept of the bridge settlement early warning method based on the Beidou in the foregoing embodiments, the invention further provides a bridge settlement early warning system based on the Beidou, and hereinafter, the electronic device according to the embodiment of the application is described with reference to fig. 3. The electronic device may be a removable device itself or a stand-alone device independent thereof, on which a computer program is stored which, when being executed by a processor, carries out the steps of any one of the methods of semantic mapping based object classification methods described hereinbefore.

As shown in fig. 3, the electronic device 50 includes one or more processors 51 and memory 52.

The processor 51 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 50 to perform desired functions.

The memory 52 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium and executed by the processor 51 to implement the driving behavior decision methods of the various embodiments of the present application described above and/or other desired functionality.

In one example, the electronic device 50 may further include: an input device 53 and an output device 54, which are interconnected by a bus system and/or other form of connection mechanism (not shown).

The embodiment of the invention provides a bridge settlement early warning method based on Beidou, wherein the method is applied to a bridge settlement early warning system, the system is in communication connection with a first height acquisition device and a second height acquisition device, and the method comprises the following steps: obtaining first basic information of a first bridge; obtaining a first analysis instruction, and obtaining a first deformation early warning distribution map of the first bridge according to the first analysis instruction and the first basic information; acquiring a first coordinate point distribution instruction, and analyzing the first deformation early warning distribution map according to the first coordinate point distribution instruction to acquire a first coordinate distribution point of the first bridge; obtaining a first coordinate system construction instruction, and constructing a first rectangular coordinate system of the first bridge according to the first coordinate system construction instruction; obtaining a first coordinate set of the first coordinate distribution point based on the first rectangular coordinate system; obtaining a first measured coordinate distribution set of the first coordinate distribution points through the first height acquisition equipment; obtaining a second measured coordinate distribution set of the first coordinate distribution points through the second height acquisition equipment, wherein the second height acquisition equipment and the first height acquisition equipment are height acquisition equipment at different positions; inputting the first measured coordinate distribution set, the second measured coordinate distribution set and the first coordinate set into a first coordinate deviation analysis model to obtain a first coordinate comparison result; obtaining a first coordinate deformation set according to the first coordinate comparison result; and carrying out real-time settlement deformation early warning on the first bridge based on the first coordinate deformation set and the first deformation early warning distribution map. The technical problem that in the prior art, accurate detection and assessment can not be carried out on the real-time parameters of bridge settlement accurately, and then early warning can not be accurately carried out on the bridge is solved, and the technical effects that the parameters of the bridge are accurately supervised and analyzed in real time by combining a Beidou satellite, and then early warning is accurately carried out on the settlement state of the bridge are achieved.

Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus necessary general-purpose hardware, and certainly can also be implemented by special-purpose hardware including special-purpose integrated circuits, special-purpose CPUs, special-purpose memories, special-purpose components and the like. Generally, functions performed by computer programs can be easily implemented by corresponding hardware, and specific hardware structures for implementing the same functions may be various, such as analog circuits, digital circuits, or dedicated circuits. However, for the present application, the implementation of a software program is more preferable. Based on such understanding, the technical solutions of the present application may be substantially embodied in the form of a software product, which is stored in a readable storage medium, such as a floppy disk, a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk of a computer, and includes several instructions for causing a computer device to execute the method according to the embodiments of the present application.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product.

The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on or transmitted from a computer-readable storage medium to another computer-readable storage medium, which may be magnetic (e.g., floppy disks, hard disks, tapes), optical (e.g., DVDs), or semiconductor (e.g., Solid State Disks (SSDs)), among others.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Additionally, the terms "system" and "network" are often used interchangeably herein. The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

It should be understood that in the embodiment of the present application, "B corresponding to a" means that B is associated with a, from which B can be determined. It should also be understood that determining B from a does not mean determining B from a alone, but may be determined from a and/or other information.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In short, the above description is only a preferred embodiment of the present disclosure, and is not intended to limit the scope of the present disclosure. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.