1. A terahertz active wind blade foam core material nondestructive testing method is characterized by comprising the following steps

The method comprises the steps that a terahertz transmission source of a continuous terahertz wave detection system is used for transmitting terahertz electromagnetic waves to a foam core material of a sample wind power blade, and a terahertz image of the sample is obtained according to the intensity of the terahertz waves transmitted and/or reflected by the foam core material;

the continuous terahertz wave detection system performs scanning type imaging on the wind blade core material; the continuous terahertz wave detection system enables terahertz waves to be focused on the wind blade foam core material, particularly at the position of the bonding layer, the wind blade foam core material can generate loss on the terahertz waves, the intensity distribution of the terahertz waves can be influenced by the scattering effect of the edge of the bonding defect on the terahertz waves, a chromatographic image, particularly at the position of the bonding layer, is obtained, and the defect-free bonding surface can be visually judged according to the image near the focal plane;

one-time two-dimensional scanning of the continuous terahertz wave detection system can simultaneously acquire terahertz reflection echoes of the foam core materials of the wind blade at different depths to form tomography, so that terahertz nondestructive detection is realized.

2. The nondestructive testing method for the terahertz active wind blade foam core material is characterized by comprising the following steps:

after a foam core material terahertz image is obtained, converting the obtained original RGB image into a corresponding gray image, performing median filtering, and eliminating isolated noise points; and selecting an image segmentation algorithm to segment the defects according to the gray value distribution characteristics of the defects in the continuous terahertz image, so that the defect foreground is extracted, and the defect area quantification is realized.

3. The nondestructive testing method for the terahertz active wind blade foam core material is characterized by comprising the following steps:

the shape, the defect and the edge position of the interior of the sample object can be obtained by linearly quantizing the intensity signal into an RGB image; terahertz waves with different frequencies are converged to different depths of the sample piece by the lens, the terahertz waves are reflected by the metal substrate after passing through the foam core material and the bonding layer, are mixed with incident signals in the mixer and are received by the terahertz detector, wherein the information contains measured relative distance information, and the information is amplified and transmitted to an upper computer through a signal of the lock-in amplifier for image processing.

4. The nondestructive testing method for the terahertz active wind blade foam core material is characterized by comprising the following steps:

the working mode and operation of the continuous terahertz wave detection system are as follows:

the time taken for the signal to be transmitted and received is tau,

initial frequency f emitted by terahertz source₀，

The bandwidth of the bandwidth B is set to be,

the period T is set to a value equal to,

the chirp rate mu is B/T,

the distance from the terahertz emission head to the target is set as R,

ct is the propagation speed of the terahertz wave in the air, so that tau is 2R/ct,

the emission frequency ft of the terahertz source and the frequency fr of the terahertz wave after reflection by the metal substrate are respectively represented by a solid line and a dotted line,

f₀is the initial value of ft and is,

f₁then it is the final value of fr,

t is the time of detection and t is the time of detection,

the frequency of the transmitted signal is ft-f₀+ u t type (1)

The frequency of the reflected signal is fr-ft (t-tau) f₀+ mu (t-tau) formula (2)

The mixer is used for subtracting the frequency of the transmitted signal from the frequency of the reflected signal to obtain the frequency f of the intermediate frequency signal_ifIs represented by f_if＝ft－fr＝μτ＝2BR/(T_cT) Formula (3)

Then R ═ T_cTf_if/(2B) formula (4)

Frequency bandwidth B and period T under specific conditions, and intermediate frequency signal output f of mixer_ifProportional to the distance R to the material, according to the intermediate frequency signal f_ifThe distance from the terahertz lens to the material can be obtained, the amplitude of the intermediate frequency signal reflects the refractive index of the material to be detected, and the amplitude and phase imaging of the target material can be realized through a beat signal emitted by the mixer; the phase-locked amplifier amplifies the signals and sends the signals to an upper computer, and after image processing, the terahertz image of the X-Y two-dimensional cross section in the direction of any depth sample piece in the depth range of 0-1000 mm in the Z thickness direction can be displayed.

5. The nondestructive testing method for the terahertz active wind blade foam core material is characterized in that:

and processing the defect image by combining the obtained terahertz image with median filtering and adopting a fuzzy c-means FCM clustering algorithm, segmenting to obtain a binary image containing target defect information, positioning the defect position shown by the target defect information, and calculating pixel points to obtain the defect area.

6. The nondestructive testing method for the terahertz active wind blade foam core material is characterized by comprising the following steps:

the defect image processing method comprises two steps of [1] defect image segmentation and [2] defect area estimation detection;

[1] defect image segmentation

The defect image segmentation algorithm realizes a target function through iterative operation: continuously optimizing an intra-class error square sum function, wherein the application of image segmentation is to perform iterative optimization on an objective function for multiple times according to the weighted membership degree between pixels in an image and each center of c clustering centers to obtain a clustering center matrix P and a fuzzy partition matrix U when the number J of the clustering objective functions is minimum;

u_ijrepresenting the degree of membership of the jth sample to the ith cluster, U being defined by U_ijForming; in the fuzzy clustering algorithm,the clustering objective function J is as follows:

in formula (5):

n is the total number of pixels in the image;

m is a weighting index, and the classification fuzzy degree is determined;

d_ij＝||p_i-x_jis the sample x_jAnd the cluster center p_iEuclidean distance between the two, all p_iForming P;

to restrainIntroducing a lagrange multiplier λ, the clustering objective function can be written as:

in order to obtain a fuzzy partition matrix U when the clustering target function J is minimum, the relation between lambda and U is solved for the target function J_ijLet it be 0, then there is:

is obtained by the following formula (7) and formula (8):

let the objective function be about the cluster center p_iHas a partial derivative of 0, then:

finally obtain p_iThe update formula of (2):

the algorithm is mainly realized by the following steps:

(1) determining the number c of clustering centers and a weighting index m, setting an iteration threshold epsilon to be more than 0, setting the initial iteration frequency to be 0, and initializing a clustering center matrix P;

(2) compute update U^(N),P^(N)；

(3) If P | |^(N+1)-P^(N)Stopping iteration if | < epsilon, otherwise, setting an iteration coefficient N to be N +1, and returning to the step (2) to continue iteration;

aiming at continuous terahertz images of defects of the foam core material of the wind blade, target defects are a type; the main idea of the algorithm is as follows: the criterion function for evaluating the clustering performance is optimal after a plurality of iterative processes, and the data set is divided into different clusters, so that each generated cluster is internally compact and independent among the clusters; the defects in the bonding layer enable the intensity of reflected echoes to be different, and the bonding defects are embodied as a single cluster on the continuous terahertz wave image, and the pixel cluster is consistent with the image segmentation, so that the defect image is separated from other classes;

[2] defect area estimation

Dividing the terahertz image of the bonding layer into images to obtain a binary image containing defect information, traversing all defect pixel points in the images, and then obtaining the sum of the defect pixel points;

because the X-axis stepping precision and the Y-axis stepping precision of the continuous terahertz system are both 1mm, the real area represented by each pixel point is 1mm²(ii) a Therefore, the total value of the defect pixels is the value of the defect area.

7. The nondestructive testing method for the terahertz active wind blade foam core material is characterized by comprising the following steps:

the terahertz wave emitted by a terahertz emission source of the continuous terahertz wave detection system adopts a reflective continuous terahertz wave with the frequency range of 0.3-1.5 THz; the terahertz signal with a stable frequency range can be transmitted by integrating a frequency source and a signal source, and the power of the terahertz wave is 300 mW-5W;

the detection frequency range of the terahertz detector of the continuous terahertz wave detection system is 0.1-2.0 THZ.

8. The nondestructive testing method for the terahertz active wind blade foam core material is characterized by comprising the following steps:

the wind blade core material is a nonmetal core material of glass fiber reinforced plastic, ceramic, graphite, polymer composite material, plastic or foam.

9. A device for realizing the nondestructive testing method of the terahertz active type wind blade foam core material as claimed in any one of claims 1 to 4 is characterized in that the structure of the device is as follows:

a horn antenna, a frequency mixer, a terahertz lens, a sample wind blade foam core material and a reflecting plate are arranged on the emission axis of the terahertz emission source,

a mixer is arranged upstream of the terahertz lens in the terahertz transmission axis direction,

a terahertz detector is arranged in the vertical direction at the intersection point of the frequency mixer and the transmitting axis,

the terahertz detector is connected with a phase-locked amplifier, and the phase-locked amplifier is connected with an upper computer;

the continuous terahertz wave detection system is formed in the above way.

10. The device for realizing the nondestructive testing method of the terahertz active wind blade foam core material is characterized in that:

the terahertz wave emitted by a terahertz emission source of the continuous terahertz wave detection system adopts a reflective continuous terahertz wave with the frequency range of 0.3-1.5 THz; the terahertz signal with a stable frequency range can be transmitted by integrating a frequency source and a signal source, and the power of the terahertz wave is 300 mW-5W;

the detection frequency range of the terahertz detector of the continuous terahertz wave detection system is 0.1-2.0 THZ;

the horn antenna is made of metal gold, and the emission angle ranges from-60 degrees to 60 degrees;

a mixer: subtracting the frequency of the transmitted signal from the frequency of the reflected signal to obtain an intermediate frequency signal, wherein the amplitude of the intermediate frequency signal reflects the refractive index of the material to be detected, and the amplitude and phase imaging of the target material can be realized through a beat signal sent by a mixer;

the lock-in amplifier is an amplifier which separates a signal with a specific carrier frequency from an interference environment;

the terahertz lens is a high-purity silicon terahertz lens with the diameter of 40cm and the focal length of 30 cm.

Background

Generally, as the investment of wind power generation increases year by year, the preparation and development of wind power generation equipment are enhanced year by year, but the problems found in the preparation, development and use processes of the actual wind power generation blade are also particularly prominent. The foam core material of the wind power generation blade has the defects of cracks, gaps, hollowness and the like due to the influence of uncontrollable factors in the processing process; the wind power blade with the defective foam core material is easy to break, deform and even topple and damage the whole generator set due to continuous multi-directional shearing force action of wind power in actual operation.

The existing X-ray detection technology is not suitable for the difficulty of the defects of the foam core material, because the X-ray belongs to high-energy rays, the X-ray can completely penetrate the foam core material with relatively low density, and no imaging effect is generated.

The existing ultrasonic nondestructive detection technology cannot accurately provide the defect types, the defect positioning time is slow, and the like, and cannot effectively guide the defect searching and repairing work.

The major drawback of other existing inspection or detection techniques that have a destructive effect on the wind blade foam core is the large size. The important problem to be overcome at the present stage is how to carry out nondestructive testing on the wind blade foam core material on the premise of ensuring that the wind blade foam core material is not damaged.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provides a terahertz active wind blade foam core material nondestructive testing method and device.

The technical scheme is realized in the following mode, the method comprises the steps that a terahertz emission source of a continuous terahertz wave detection system is used for emitting terahertz electromagnetic waves to a sample wind power blade foam core material, and a terahertz image of the sample is obtained according to the intensity of the terahertz waves transmitted and/or reflected by the foam core material;

the continuous terahertz wave detection system performs scanning type imaging on the wind blade core material; the continuous terahertz wave detection system enables terahertz waves to be focused on the wind blade foam core material, particularly at the position of the bonding layer, the wind blade foam core material can generate loss on the terahertz waves, the intensity distribution of the terahertz waves can be influenced by the scattering effect of the edge of the bonding defect on the terahertz waves, a chromatographic image, particularly at the position of the bonding layer, is obtained, and the defect-free bonding surface can be visually judged according to the image near the focal plane;

one-time two-dimensional scanning of the continuous terahertz wave detection system can simultaneously acquire terahertz reflection echoes of the foam core materials of the wind blade at different depths to form tomography, so that terahertz nondestructive detection is realized.

After a foam core material terahertz image is obtained, converting the obtained original RGB image into a corresponding gray image, performing median filtering, and eliminating isolated noise points; and selecting an image segmentation algorithm to segment the defects according to the gray value distribution characteristics of the defects in the continuous terahertz image, so that the defect foreground is extracted, and the defect area quantification is realized.

The shape, the defect and the edge position of the interior of the sample object can be obtained by linearly quantizing the intensity signal into an RGB image; terahertz waves with different frequencies are converged to different depths of the sample piece by the lens, the terahertz waves are reflected by the metal substrate after passing through the foam core material and the bonding layer, are mixed with incident signals in the mixer and are received by the terahertz detector, wherein the information contains measured relative distance information, and the information is amplified and transmitted to an upper computer through a signal of the lock-in amplifier for image processing.

The working operation of the continuous terahertz wave detection system is as follows:

the time taken for the signal to be transmitted and received is tau,

initial frequency f emitted by terahertz source₀，

The bandwidth of the bandwidth B is set to be,

the period T is set to a value equal to,

the chirp rate mu is B/T,

the distance from the terahertz emission head to the target is set as R,

ct is the propagation speed of the terahertz wave in the air, and τ is 2R/c_t，

The emission frequency ft of the terahertz source and the frequency fr of the terahertz wave after reflection by the metal substrate are respectively represented by a solid line and a dotted line,

f₀is the initial value of ft and is,

f₁then it is the final value of fr,

t is the time of detection and t is the time of detection,

the frequency of the transmitted signal is ft-f₀+ u t type (1)

The frequency of the reflected signal is fr-ft (t-tau) f₀+ mu (t-tau) formula (2)

The mixer is used for subtracting the frequency of the transmitted signal from the frequency of the reflected signal to obtain the frequency f of the intermediate frequency signal_ifIs represented by f_if＝ft－fr＝μτ＝2BR/(T_cT) Formula (3)

Then R ═ T_cTf_if/(2B) formula (4)

Frequency bandwidth B and period T under specific conditions, and intermediate frequency signal output f of mixer_ifProportional to the distance R to the material, according to the intermediate frequency signal f_ifThe distance from the terahertz lens to the material can be obtained, the amplitude of the intermediate frequency signal reflects the refractive index of the material to be detected, and the amplitude and phase imaging of the target material can be realized through a beat signal emitted by the mixer; the phase-locked amplifier amplifies the signals and sends the signals to an upper computer, and after image processing, the terahertz image of the X-Y two-dimensional cross section in the direction of any depth sample piece in the depth range of 0-1000 mm in the Z thickness direction can be displayed.

And processing the defect image by combining the obtained terahertz image with median filtering and adopting a fuzzy c-means FCM clustering algorithm, segmenting to obtain a binary image containing target defect information, positioning the defect position shown by the target defect information, and calculating pixel points to obtain the defect area.

The defect image processing method comprises two steps of [1] defect image segmentation and [2] defect area estimation detection;

[1] defect image segmentation

The defect image segmentation algorithm realizes a target function through iterative operation: continuously optimizing an intra-class error square sum function, wherein the application of image segmentation is to perform iterative optimization on an objective function for multiple times according to the weighted membership degree between pixels in an image and each center of c clustering centers to obtain a clustering center matrix P and a fuzzy partition matrix U when the number J of the clustering objective functions is minimum;

u_ijrepresenting the degree of membership of the jth sample to the ith cluster, U being defined by U_ijForming; in the fuzzy clustering algorithm,the clustering objective function J is as follows:

in formula (5):

n is the total number of pixels in the image;

m is a weighting index, and the classification fuzzy degree is determined;

d_ij＝||p_i-x_jis the sample x_jAnd the cluster center p_iEuclidean distance between the two, all p_iForming P;

to restrainIntroducing a lagrange multiplier λ, the clustering objective function can be written as:

in order to obtain a fuzzy partition matrix U when the clustering target function J is minimum, the relation between lambda and U is solved for the target function J_ijLet it be 0, then there is:

is obtained by the following formula (7) and formula (8):

let the objective function be about the cluster center p_iHas a partial derivative of 0, then:

finally obtain p_iThe update formula of (2):

the algorithm is mainly realized by the following steps:

(4) determining the number c of clustering centers and a weighting index m, setting an iteration threshold epsilon to be more than 0, setting the initial iteration frequency to be 0, and initializing a clustering center matrix P;

(5) compute update U^(N),P^(N)；

(6) If P | |^(N+1)-P^(N)Stopping iteration if | < epsilon, otherwise, setting an iteration coefficient N to be N +1, and returning to the step (2) to continue iteration;

aiming at continuous terahertz images of defects of the foam core material of the wind blade, target defects are a type; the main idea of the algorithm is as follows: the criterion function for evaluating the clustering performance is optimal after a plurality of iterative processes, and the data set is divided into different clusters, so that each generated cluster is internally compact and independent among the clusters; the defects in the bonding layer enable the intensity of reflected echoes to be different, and the bonding defects are embodied as a single cluster on the continuous terahertz wave image, and the pixel cluster is consistent with the image segmentation, so that the defect image is separated from other classes;

[2] defect area estimation

Dividing the terahertz image of the bonding layer into images to obtain a binary image containing defect information, traversing all defect pixel points in the images, and then obtaining the sum of the defect pixel points;

because the X-axis stepping precision and the Y-axis stepping precision of the continuous terahertz system are both 1mm, the real area represented by each pixel point is 1mm²(ii) a Therefore, the total value of the defect pixels is the value of the defect area.

The terahertz wave emitted by a terahertz emission source of the continuous terahertz wave detection system adopts a reflective continuous terahertz wave with the frequency range of 0.3-1.5 THz; the terahertz signal with a stable frequency range can be transmitted by integrating a frequency source and a signal source, and the power of the terahertz wave is 300 mW-5W;

the detection frequency range of the terahertz detector of the continuous terahertz wave detection system is 0.1-2.0 THZ.

The wind blade core material is a non-metal core material made of ceramics, graphite, polymer composite materials, plastics or foams. The foam used by the wind power generation blade is mainly a core material of a glass fiber reinforced plastic sandwich structure.

A device for realizing a terahertz active wind blade foam core material nondestructive testing method is structurally characterized in that:

a horn antenna, a frequency mixer, a terahertz lens, a sample wind blade foam core material and a reflecting plate are arranged on the emission axis of the terahertz emission source,

a mixer is arranged upstream of the terahertz lens in the terahertz transmission axis direction,

a terahertz detector is arranged in the vertical direction at the intersection point of the frequency mixer and the transmitting axis,

the terahertz detector is connected with a phase-locked amplifier, and the phase-locked amplifier is connected with an upper computer;

the continuous terahertz wave detection system is formed in the above way.

The terahertz wave emitted by a terahertz emission source of the continuous terahertz wave detection system adopts a reflective continuous terahertz wave with the frequency range of 0.3-1.5 THz; the terahertz signal with a stable frequency range can be transmitted by integrating a frequency source and a signal source, and the power of the terahertz wave is 300 mW-5W;

the detection frequency range of the terahertz detector of the continuous terahertz wave detection system is 0.1-2.0 THZ;

the horn antenna is made of metal gold, and the emission angle ranges from-60 degrees to 60 degrees;

a mixer: subtracting the frequency of the transmitted signal from the frequency of the reflected signal to obtain an intermediate frequency signal, wherein the amplitude of the intermediate frequency signal reflects the refractive index of the material to be detected, and the amplitude and phase imaging of the target material can be realized through a beat signal sent by a mixer;

the lock-in amplifier is an amplifier which separates a signal with a specific carrier frequency from an interference environment;

the terahertz lens is a high-purity silicon terahertz lens with the diameter of 40cm and the focal length of 30 cm.

Compared with the prior art, the invention has the following beneficial effects:

the terahertz active wind blade foam core material nondestructive testing method and device provided by the invention utilize a terahertz active wind blade foam core material nondestructive testing device to perform scanning type imaging on the foam core material; the resolution ratio of the terahertz detection foam core material is 10-20 mu m, the defect foam core material is effectively distinguished by analyzing the imaging characteristics of various defects through high-resolution imaging of the foam core material, and the overall safety of the operation of the wind power generation blade is improved.

Compared with an ultrasonic nondestructive testing technology, the terahertz active wind blade foam core material nondestructive testing device is more intuitive and easier to distinguish defect type defect positions by adopting a two-dimensional image imaging mode, so that the waste of foam core material resources is reduced while the detection efficiency is improved.

The method can detect the defects of the foam core material by determining the defect positions in the wind power generation foam core material, so that the detection efficiency of the wind blade foam core material is improved; meanwhile, the overall safety performance of the wind power generation blade is improved. By feeding back the defect type and position information to the defect processing unit, the recycling of the defective foam board is realized, and the waste of resources is reduced.

The terahertz active wind blade foam core material nondestructive testing method and device provided by the invention are reasonable in design, simple in structure, safe, reliable, convenient to use, easy to maintain and good in popularization and use value.

Drawings

FIG. 1 is a schematic structural view of a detecting unit according to the present invention;

FIG. 2 is a schematic diagram of a sawtooth wave modulation continuous terahertz emission and echo time-frequency curve of the continuous terahertz wave detection system.

The reference numerals in the drawings denote:

1. the terahertz wave radiation source comprises a terahertz wave radiation source, 2, a horn antenna, 3, a mixer, 4, a terahertz wave detector, 5, a lock-in amplifier, 6, an upper computer, 7, a terahertz lens, 8, a wind power blade foam core material, 9 and a reflecting plate.

Detailed Description

The following detailed description of the method and the device for nondestructive testing of the terahertz active type wind blade foam core material is provided with reference to the accompanying drawings.

As shown in the attached drawings, the nondestructive testing method and the nondestructive testing device for the terahertz active type wind blade foam core material adopt a reflection type continuous terahertz wave detection system with the frequency range of 0.3-1.5 THz to carry out nondestructive testing on the wind blade foam core material. The terahertz waves are focused on the bonding layer to obtain a chromatographic image, and the defect-free bonding surface can be visually judged according to the image near the focal plane. And (4) combining median filtering, adopting a fuzzy c-means (FCM) clustering algorithm to segment the defect image to obtain a binary image containing target defect information, and calculating pixel points to obtain the defect area.

The terahertz electromagnetic wave emitted by the terahertz emission source with the emission frequency range of 0.1-10 THz cannot penetrate through a metal material, but can penetrate through materials such as ceramics, graphite, polymer composite materials, plastics, foams and the like.

According to the terahertz image of the sample, the terahertz image of the sample is obtained according to the intensity of the terahertz wave transmitted or reflected by the foam core material. The wind blade foam core material can generate loss on the terahertz waves, and the intensity distribution of the terahertz waves can be influenced by the scattering effect of the edges of the bonding defects on the terahertz waves.

The shape, defect and edge position of the interior of the object can be obtained by linearly quantizing the intensity signal into an RGB image. Terahertz waves with different frequencies are converged to different depths of the sample piece by the lens, the terahertz waves are reflected by the metal substrate after passing through the foam core material and the bonding layer, are mixed with incident signals in the mixer and are received by the terahertz detector, wherein the information contains measured relative distance information, and the information is amplified and transmitted to an upper computer through a signal of the lock-in amplifier for image processing. The device is used for one-time two-dimensional scanning, terahertz reflection echoes of different depths of the foam core material of the wind blade can be collected simultaneously, tomography is formed, and terahertz nondestructive testing is achieved.

Continuous terahertz wave detection system:

the time for transmitting and receiving the signal is tau, and the initial frequency f emitted by the terahertz source₀The bandwidth B, the period T, the chirp rate μ ═ B/T, let the distance from the terahertz emission head to the target be R, and ct be the propagation speed of the terahertz wave in the air, then τ ═ 2R/c_t。

In FIG. 2, the emission frequency ft of the terahertz source and the frequencies fr, f of the terahertz wave after reflection by the metal substrate are indicated by solid lines and dotted lines, respectively₀Is an initial value of ft, f₁Then fr is the final value and t is the detection time.

The frequency of the transmitted signal is ft-f₀+ u t type (1)

The frequency of the reflected signal is fr-ft (t-tau) f₀+ mu (t-tau) formula (2)

The mixer is used for subtracting the frequency of the transmitted signal from the frequency of the reflected signal to obtain the frequency f of the intermediate frequency signal_ifIs represented by f_if＝ft－fr＝μτ＝2BR/(T_cT) Formula (3)

Then R ═ T_cTf_if/(2B) formula (4)

Frequency bandwidth B and period T under specific conditions, and intermediate frequency signal output f of mixer_ifProportional to the distance R to the material, according to the intermediate frequency signal f_ifThe distance from the terahertz lens to the material can be obtained, the refractive index of the material to be detected is reflected by the amplitude of the intermediate frequency signal, and the amplitude and phase imaging of the target material can be realized through the beat signal emitted by the mixer. Phase-locked amplifier will signalThe terahertz image is sent to an upper computer after being amplified, and the terahertz image of the X-Y two-dimensional cross section of the sample piece with any depth within the depth range of 0-1000 mm in the Z (thickness direction) direction can be displayed after image processing.

The frequency range of the terahertz emission source is 0.3 THZ-1.5 THZ, terahertz signals in a stable frequency range can be emitted through integration of the frequency source and the signal source, and the power of terahertz waves is 300 mW-5W.

The horn antenna is made of metal gold, and has an emission angle range of-60 °

And the mixer subtracts the frequency of the transmitted signal from the frequency of the reflected signal to obtain an intermediate frequency signal, the amplitude of the intermediate frequency signal reflects the refractive index of the measured material, and the amplitude and phase imaging of the target material can be realized through a beat signal sent by the mixer.

The terahertz detector is used for detecting the THZ within the frequency range of 0.1-2.0.

A lock-in amplifier, also known as a phase detector, is an amplifier that can separate a signal at a particular carrier frequency from a very noisy environment (signal-to-noise ratio can be as low as-60 dB, or even lower).

The terahertz lens is made of high-purity silicon, the diameter of the terahertz lens is 40cm, and the focal length of the terahertz lens is 30 cm.

In practice, the major defect that has a destructive effect on the wind blade foam core is significant. And after the terahertz image of the foam core material is obtained, converting the obtained original RGB image into a corresponding gray image, and performing median filtering, thereby eliminating an isolated noise point. And selecting an image segmentation algorithm to segment the defects according to the gray value distribution characteristics of the defects in the continuous terahertz image, so that the defect foreground is extracted, and the defect area quantification is realized. The image processing method comprises two steps of defect image segmentation and defect area detection.

1) Defect image segmentation

The algorithm realizes continuous optimization of a target function (in-class error sum of squares function) through iterative operation, and is applied to image segmentation to perform iterative optimization on the target function for many times according to the weighted membership degree between pixels in an image and each center of c clustering centers to obtain a clustering center matrix P and a fuzzy partition matrix U when the number J of the clustering target functions is minimum.

u_ijRepresenting the degree of membership of the jth sample to the ith cluster, U being defined by U_ijAnd (4) forming. In the fuzzy clustering algorithm,the clustering objective function J is as follows:

in the formula:

n is the total number of pixels in the image;

m is a weighting index, and the classification fuzzy degree is determined;

d_ij＝||p_i-x_jis the sample x_jAnd the cluster center p_iEuclidean distance between the two, all p_iConstituting P.

To restrainIntroducing a lagrange multiplier λ, the clustering objective function can be written as:

in order to obtain a fuzzy partition matrix U when the clustering target function J is minimum, the relation between lambda and U is solved for the target function J_ijLet it be 0, then there is:

obtained from (7) and (8):

let the objective function be about the cluster center p_iHas a partial derivative of 0, then:

finally obtain p_iThe update formula of (2):

the algorithm is mainly realized by the following steps:

(1) determining the number c of clustering centers and a weighting index m, setting an iteration threshold epsilon to be more than 0, setting the initial iteration frequency to be 0, and initializing a clustering center matrix P;

(2) compute update U^(N),P^(N)；

(3) If P | |^(N+1)-P^(N)Stopping iteration if | < epsilon, otherwise, setting the iteration coefficient N to be N +1, and returning to the step (2) to continue iteration.

Aiming at continuous terahertz images of defects of the foam core material of the wind blade, the target defects are the same.

The algorithm has the main idea that a criterion function for evaluating the clustering performance is optimal after multiple iteration processes, and a data set is divided into different clusters, so that each generated cluster is internally compact and independent among the clusters. The defects in the bonding layer cause the intensity of the reflected echo to be different, and the bonding defects are embodied as a single cluster on the continuous terahertz wave image, and the pixel cluster is consistent with the image segmentation, so that the defect image is separated from other classes.

2) Defect area estimation

And (4) carrying out image segmentation on the terahertz image of the bonding layer to obtain a binary image containing defect information, traversing all defect pixel points in the image, and then solving the sum of the defect pixel points. Due to continuous terahertzThe stepping precision of the X axis and the stepping precision of the Y axis of the system are both 1mm, and the real area represented by each pixel point is 1mm². Therefore, the total value of the defect pixels is the value of the defect area.

The method can detect the defects of the foam core material by determining the defect positions in the wind power generation foam core material, so that the detection efficiency of the wind blade foam core material is improved; meanwhile, the overall safety performance of the wind power generation blade is improved. The defect type and the position information are fed back to the defect processing unit, so that the defective foam board is recycled, and the waste of resources is reduced.