1. A macroscopic characterization method for the microscopic state of a low-voltage alternating current arc is characterized by comprising the following steps: the method is used for characterizing the process from generation to extinction of the electric arc, and comprises the following steps:

s1, obtaining arc voltage data through the electric system measuring module (1), and simultaneously obtaining continuous arc spectral line data of the arc plasma on a time domain through the optical system measuring module (2);

step S2, performing wavelet energy spectrum transformation on the arc voltage data to obtain an arc voltage waveform characteristic value and a voltage wavelet energy spectrum waveform;

s3, calculating Stark of the arc spectral line to obtain the electron density of the arc between the arc gaps;

and step S4, selecting voltage wavelet energy spectrum waveforms consistent with the electron density variation trend, and selecting corresponding arc voltage waveform characteristic values according to the selected voltage wavelet energy spectrum waveforms to represent the arc burning state and the trend of the arc.

2. The macroscopic characterization method of a microscopic state of a low-voltage alternating-current arc according to claim 1, wherein: in step S4, when the arc electron density between the arc gaps is kept at a preset magnitude; the characteristic value of the arc voltage waveform is an arc voltage waveform characteristic value representing an arc in a stable arcing state, and the characteristic value of the voltage wavelet energy spectrum is stabilized at a stable arcing threshold determined by a sampling rate and a voltage grade; the electron density of the arc at this time is in the order of magnitude of stable arcing.

3. A method for macroscopic characterization of the microscopic state of a low-voltage ac arc according to claim 2, characterized in that: in step S4, when the electron density of the arc in the arc gap has unstable and drastic change and the voltage wavelet energy spectrum characteristic value increases to 2.5 times of the stable arcing threshold, the arc voltage waveform characteristic value is an arc voltage waveform characteristic value representing the arc in a state tending to be extinguished.

4. A method for macroscopic characterization of the microscopic state of a low-voltage ac arc according to claim 3, characterized in that: in the step S4, when the electron density of the arc between the arc gaps has unstable and drastic change and when the voltage wavelet energy spectrum characteristic value is increased to more than three times of the stable arcing threshold value, it can be determined that the arc has been extinguished.

5. The macroscopic characterization method of the microscopic state of the low-voltage alternating-current arc according to claim 4, wherein: in step S4, when the electron density of the arc in the arc gap has unstable and drastic change and when the voltage wavelet energy spectrum characteristic value is smaller than the stable arcing threshold, the arc voltage waveform characteristic value is the arc voltage waveform characteristic value characterizing the arc in the stage of going to more violent reignition.

6. The macroscopic characterization method of the microscopic state of the low-voltage alternating-current arc according to claim 5, wherein: when the medium recovery strength is gradually increased in the extinguishing process of the low-voltage alternating-current arc, the voltage wavelet energy spectrum characteristic value represents the competitive relationship between the medium recovery strength and the voltage recovery strength;

when the voltage wavelet energy spectrum characteristic value is larger, the medium recovery strength is larger, and the electric arc tends to be extinguished;

when the voltage wavelet energy spectrum characteristic value is smaller, the medium recovery intensity is smaller, and the electric arc tends to be re-ignited.

7. The macroscopic characterization method of a microscopic state of a low-voltage alternating-current arc according to claim 1, wherein: the electrical system measurement module (1) comprises a module A1, a module C1; the light system measurement module (2) comprises a module A2 and a module C2;

the module A1 and the module A2 detect the electric arc in real time to obtain a voltage waveform B1 of a voltage signal of the electric arc and a spectrum waveform B2 of an electric arc plasma spectrum which can be compared with the B1;

the module C1 carries out wavelet energy spectrum transformation on the arc voltage signal to obtain a wavelet energy spectrum value D1 and the track change of the wavelet energy spectrum value in the time domain;

the module C2 performs Stark calculation and Boltzmann diagram processing on the arc plasma spectrum to obtain the arc plasma electron density D2 and the time-domain trajectory change thereof which are internally related to D1.

8. The method of claim 7, wherein the step of macroscopically characterizing the microscopic state of the low-voltage ac arc comprises the steps of: the electric system measuring module (1) is an alternating current arc detection system for collecting arc voltage waveform in real time, and a wavelet energy spectrum algorithm module capable of extracting the voltage waveform is embedded in the alternating current arc detection system; and the wavelet energy spectrum algorithm module sets a threshold value of a waveform characteristic value according to an actual sampling result.

9. The method of claim 7, wherein the step of macroscopically characterizing the microscopic state of the low-voltage ac arc comprises the steps of: the optical system measuring module performs continuous measurement on the low-voltage alternating current electric arc in a time domain by a spectrum detection method to obtain a spectrum change curve of the low-voltage alternating current electric arc, selects proper element wavelengths according to the spectrum curve and the types of electrode materials, inquires and obtains corresponding spectrum parameters to calculate an electron temperature change track of the electric arc plasma, and then calculates and obtains a required electron density change track according to the temperature.

Background

The study of low voltage ac arcs and their reduction of damage has been an important direction of research in low voltage switchgear. With the development of intelligent technology, the arc suppression technology based on intelligent control has become an important research content for intelligent control of low-voltage switchgear, and adaptive control for online monitoring of arc state and implementing arc quenching process has become an objective of intelligent control, but the main difficulties in practical research are: 1. the arc real-time condition lacks an effective detection method; 2. the effect of arc suppression cannot be effectively compared and judged, and the improvement of intelligent control performance is limited. The macroscopic representation and real-time feedback of the arc state are the key problems in the zero current breaking control process of the existing intelligent switching equipment.

At present, a lot of achievements are obtained in research on dynamic characteristics of a low-voltage alternating current arc, an arc simulation technology provides important guiding significance for design of an arc extinguishing system, but the difficult problem of intuitively judging arc combustion characteristics still cannot be solved, three state processes of arc combustion cannot be uniformly analyzed, and it is still a technical bottleneck to provide a quantitative arc combustion characteristic parameter in a visualized manner. Macroscopic characteristics of a low-voltage alternating-current arc that can be directly observed during operation are its circuit characteristics and image characteristics, which are more easily obtained by advanced measurement techniques and reflect the arcing process and the arcing characteristics of the arc. On the basis of simulation research, domestic and foreign scholars carry out deep research on the circuit characteristics of the electric arc through experiments and test means and analyze the influence of parameters such as electric arc temperature, electric arc energy and recovery voltage on electric arc movement. However, these studies can only perform off-line analysis on the circuit characteristics or image characteristics of the arc, and for example, quantitative characteristic parameters such as the brightness and size of the arc obtained by using a high-speed camera and the like cannot provide real-time on-line analysis and processing, and the research results cannot be combined with the intelligent control process of the low-voltage apparatus due to the lack of effective arc state characterization parameters.

The invention quantitatively feeds back the state and the trend of the arc by researching the characteristics of the arc voltage waveform and the relation between the distribution track of the arc voltage waveform in a time domain and the microscopic mechanism of the arc state, identifies and extracts stable and effective arc state characteristic parameters by using an arc identification model, and explains the arc state characteristic parameters in terms of mechanism through plasma spectral line measurement and electron density calculation, thereby laying a theoretical foundation for realizing the macroscopic characterization of the arc state.

Disclosure of Invention

The invention provides a macroscopic characterization method for the microscopic state of a low-voltage alternating-current arc, which can quantitatively feed back the state and the trend of the arc by utilizing quantized macroscopic characteristic parameters.

The invention adopts the following technical scheme.

A macroscopic characterization method for microscopic states of a low-voltage alternating-current arc, which characterizes the process from arc generation to arc extinction, comprises the following steps:

s1, obtaining arc voltage data through the electric system measuring module (1), and simultaneously obtaining continuous arc spectral line data of the arc plasma on a time domain through the optical system measuring module (2);

step S2, performing wavelet energy spectrum transformation on the arc voltage data to obtain an arc voltage waveform characteristic value and a voltage wavelet energy spectrum waveform;

s3, calculating Stark of the arc spectral line to obtain the electron density of the arc between the arc gaps;

and step S4, selecting voltage wavelet energy spectrum waveforms consistent with the electron density variation trend, and selecting corresponding arc voltage waveform characteristic values according to the selected voltage wavelet energy spectrum waveforms to represent the arc burning state and the trend of the arc.

In step S4, when the arc electron density between the arc gaps is kept at a preset magnitude; the characteristic value of the arc voltage waveform is an arc voltage waveform characteristic value representing an arc in a stable arcing state, and the characteristic value of the voltage wavelet energy spectrum is stabilized at a stable arcing threshold determined by a sampling rate and a voltage grade; the electron density of the arc at this time is in the order of magnitude of stable arcing.

In step S4, when the electron density of the arc in the arc gap has unstable and drastic change and the voltage wavelet energy spectrum characteristic value increases to 2.5 times of the stable arcing threshold, the arc voltage waveform characteristic value is an arc voltage waveform characteristic value representing the arc in a state tending to be extinguished.

In the step S4, when the electron density of the arc between the arc gaps has unstable and drastic change and when the voltage wavelet energy spectrum characteristic value is increased to more than three times of the stable arcing threshold value, it can be determined that the arc has been extinguished.

In step S4, when the electron density of the arc in the arc gap has unstable and drastic change and when the voltage wavelet energy spectrum characteristic value is smaller than the stable arcing threshold, the arc voltage waveform characteristic value is the arc voltage waveform characteristic value characterizing the arc in the stage of going to more violent reignition.

When the medium recovery strength is gradually increased in the extinguishing process of the low-voltage alternating-current arc, the voltage wavelet energy spectrum characteristic value represents the competitive relationship between the medium recovery strength and the voltage recovery strength;

when the voltage wavelet energy spectrum characteristic value is larger, the medium recovery strength is larger, and the electric arc tends to be extinguished;

when the voltage wavelet energy spectrum characteristic value is smaller, the medium recovery intensity is smaller, and the electric arc tends to be re-ignited.

The electrical system measurement module (1) comprises a module A1, a module C1; the light system measurement module (2) comprises a module A2 and a module C2;

the module A1 and the module A2 detect the electric arc in real time to obtain a voltage waveform B1 of a voltage signal of the electric arc and a spectrum waveform B2 of an electric arc plasma spectrum which can be compared with the B1;

the module C1 carries out wavelet energy spectrum transformation on the arc voltage signal to obtain a wavelet energy spectrum value D1 and the track change of the wavelet energy spectrum value in the time domain;

the module C2 performs Stark calculation and Boltzmann diagram processing on the arc plasma spectrum to obtain the arc plasma electron density D2 and the time-domain trajectory change thereof which are internally related to D1.

The electric system measuring module (1) is an alternating current arc detection system for collecting arc voltage waveform in real time, and a wavelet energy spectrum algorithm module capable of extracting the voltage waveform is embedded in the alternating current arc detection system; and the wavelet energy spectrum algorithm module sets a threshold value of a waveform characteristic value according to an actual sampling result.

The optical system measuring module performs continuous measurement on the low-voltage alternating current electric arc in a time domain by a spectrum detection method to obtain a spectrum change curve of the low-voltage alternating current electric arc, selects proper element wavelengths according to the spectrum curve and the types of electrode materials, inquires and obtains corresponding spectrum parameters to calculate an electron temperature change track of the electric arc plasma, and then calculates and obtains a required electron density change track according to the temperature.

The invention quantitatively feeds back the state and the trend of the arc by researching the characteristics of the arc voltage waveform and the relation between the distribution track of the arc voltage waveform in a time domain and the microscopic mechanism of the arc state, identifies and extracts stable and effective arc state characteristic parameters by using an arc identification model, and explains the arc state characteristic parameters in terms of mechanism through plasma spectral line measurement and electron density calculation, thereby laying a theoretical foundation for realizing the macroscopic characterization of the arc state.

The invention has the creativity that:

1. the method for measuring the continuous spectrum in the time domain is introduced into the arc characteristic analysis, and theoretical support is provided for macroscopic representation of the micro state of the arc through a data track obtained by continuously measuring the plasma spectrum information in the arc gap in the time domain.

2. An effective macroscopic characterization parameter of the arc state is provided, and the real-time observation of the low-voltage alternating current arc state can be realized.

Drawings

The invention is described in further detail below with reference to the following figures and detailed description:

FIG. 1 is a schematic diagram of the principles of the present invention;

in the figure: 1-an electrical system measurement module; 2-optical system measurement module.

Detailed Description

As shown in the figure, the macro characterization method of the microscopic state of the low-voltage alternating current arc characterizes the process from the generation to the extinction of the arc, and comprises the following steps:

step S1, acquiring arc voltage data through the electric system measuring module 1, and acquiring continuous arc spectral line data of the arc plasma in a time domain through the optical system measuring module 2;

step S2, performing wavelet energy spectrum transformation on the arc voltage data to obtain an arc voltage waveform characteristic value and a voltage wavelet energy spectrum waveform;

s3, calculating Stark of the arc spectral line to obtain the electron density of the arc between the arc gaps;

and step S4, selecting voltage wavelet energy spectrum waveforms consistent with the electron density variation trend, and selecting corresponding arc voltage waveform characteristic values according to the selected voltage wavelet energy spectrum waveforms to represent the arc burning state and the trend of the arc.

In step S4, when the arc electron density between the arc gaps is kept at a preset magnitude; the characteristic value of the arc voltage waveform is an arc voltage waveform characteristic value representing an arc in a stable arcing state, and the characteristic value of the voltage wavelet energy spectrum is stabilized at a stable arcing threshold determined by a sampling rate and a voltage grade; the electron density of the arc at this time is in the order of magnitude of stable arcing.

In step S4, when the electron density of the arc in the arc gap has unstable and drastic change and the voltage wavelet energy spectrum characteristic value increases to 2.5 times of the stable arcing threshold, the arc voltage waveform characteristic value is an arc voltage waveform characteristic value representing the arc in a state tending to be extinguished.

In the step S4, when the electron density of the arc between the arc gaps has unstable and drastic change and when the voltage wavelet energy spectrum characteristic value is increased to more than three times of the stable arcing threshold value, it can be determined that the arc has been extinguished.

In step S4, when the electron density of the arc in the arc gap has unstable and drastic change and when the voltage wavelet energy spectrum characteristic value is smaller than the stable arcing threshold, the arc voltage waveform characteristic value is the arc voltage waveform characteristic value characterizing the arc in the stage of going to more violent reignition.

When the medium recovery strength is gradually increased in the extinguishing process of the low-voltage alternating-current arc, the voltage wavelet energy spectrum characteristic value represents the competitive relationship between the medium recovery strength and the voltage recovery strength;

when the voltage wavelet energy spectrum characteristic value is larger, the medium recovery strength is larger, and the electric arc tends to be extinguished;

when the voltage wavelet energy spectrum characteristic value is smaller, the medium recovery intensity is smaller, and the electric arc tends to be re-ignited.

The electrical system measurement module 1 comprises a module A1, a module C1; the light system measurement module 2 comprises a module A2 and a module C2;

the module A1 and the module A2 detect the electric arc in real time to obtain a voltage waveform B1 of a voltage signal of the electric arc and a spectrum waveform B2 of an electric arc plasma spectrum which can be compared with the B1;

the module C1 carries out wavelet energy spectrum transformation on the arc voltage signal to obtain a wavelet energy spectrum value D1 and the track change of the wavelet energy spectrum value in the time domain;

the module C2 performs Stark calculation and Boltzmann diagram processing on the arc plasma spectrum to obtain the arc plasma electron density D2 and the time-domain trajectory change thereof which are internally related to D1.

The electric system measuring module 1 is an alternating current arc detection system for collecting arc voltage waveform in real time, and a wavelet energy spectrum algorithm module capable of extracting the voltage waveform is embedded in the electric system measuring module; and the wavelet energy spectrum algorithm module sets a threshold value of a waveform characteristic value according to an actual sampling result.

The optical system measuring module performs continuous measurement on the low-voltage alternating current electric arc in a time domain by a spectrum detection method to obtain a spectrum change curve of the low-voltage alternating current electric arc, selects proper element wavelengths according to the spectrum curve and the types of electrode materials, inquires and obtains corresponding spectrum parameters to calculate an electron temperature change track of the electric arc plasma, and then calculates and obtains a required electron density change track according to the temperature.

Example (b):

as shown in the figure, the module 1 is an electrical system detection module, and the module 2 is an optical system detection module. The module A1 and the module A2 detect the arc in real time to obtain B1 and B2, and can complete the comparison of the voltage waveform and the spectrum waveform of the arc. The module C1 realizes wavelet energy spectrum transformation of the arc voltage signal, the module C2 realizes Stark calculation and Boltzmann diagram method of the arc plasma spectrum, D1 and D2 are respectively obtained, the wavelet energy spectrum value of the arc voltage and the trajectory change of the electron density of the arc plasma in the time domain are compared, the intrinsic relevance of the wavelet energy spectrum value and the electron density along with the change of the arc state can be determined, and the characteristic parameters extracted from the arc voltage waveform by utilizing a wavelet energy spectrum algorithm can effectively represent the arc state.

The implementation of the method in this example mainly includes two modules of an optical system and an electrical system:

(1) electrical system measurement module (module 1): the alternating current arc detection system collects the arc voltage waveform in real time, and the characteristic value of the voltage waveform is extracted through an embedded wavelet energy spectrum algorithm. The threshold value of the characteristic value is set according to the result of actual sampling, and the detection and judgment of the real-time state of the arc can be realized by comparing the wavelet characteristic value with the threshold value according to the real-time detection of the arc voltage: if the characteristic value is greater than the threshold value, the electric arc tends to be extinguished; if the characteristic value is less than the threshold value, the arc is in a reignition phase. The physical meaning of the wavelet energy spectrum characteristic value as the characterization parameter of the arc state and the theoretical analysis of the wavelet energy spectrum characteristic value are completed by a light system detection module.

(2) Photosystem measurement module (module 2): the spectrum detection means is introduced into the field of low-voltage alternating current arcs, and a novel method for continuous measurement in a time domain is provided. The module 2 can measure the arc spectrum in real time, obtain the spectrum change curve of the arc process by continuously measuring the time domain of the arc process, select proper element wavelength according to the arc spectrum curve detected by the optical system and the electrode material type, and find out the corresponding spectrum parameter to calculate the electron temperature change track of the arc plasma, and then calculate the required electron density change track according to the temperature.

When the electric arc is generated to be extinguished, the electric system acquires electric arc voltage data, and meanwhile, the optical system acquires continuous spectral line data of the electric arc plasma in a time domain. And performing wavelet energy spectrum transformation on the arc voltage to obtain a characteristic value, and calculating the Stark of an arc spectral line to obtain the electron density of the arc between the arc gaps. The consistency of the electric system and the optical system is demonstrated by comparing the results of the detection modules, namely the voltage wavelet energy spectrum waveform and the electron density change process, with the combustion trend of the electric arc. In a stable arcing stage in which the electron density keeps a certain order of magnitude, the characteristic value of the electric arc voltage wavelet energy spectrum is stabilized at a certain order of magnitude, and the order of magnitude depends on the sampling rate and the voltage level; when the electron density is in an unstable arcing stage with unstable and violent change and the electric arc tends to be extinguished, the characteristic value is 2.5 times of the magnitude of the stable arcing time; when the arc is extinguished, the characteristic value increases by more than 3 times of the order of the number of stable arcing hours. The characteristic value can generally represent the change trend of the arc state, and the physical meaning of the characteristic value is as follows: the medium recovery intensity is gradually increased during the extinguishing process of the low-voltage alternating-current arc, and the competition result of the medium recovery intensity and the voltage recovery intensity can be characterized by a wavelet energy spectrum characteristic value. A larger value indicates a higher medium recovery strength, and the arc tends to extinguish; smaller values indicate less medium recovery strength and the arc tends to re-ignite.