CN115290597B

CN115290597B - Terahertz technology-based method and system for detecting coating adhesion-free defect

Info

Publication number: CN115290597B
Application number: CN202211219712.3A
Authority: CN
Inventors: 张振伟; 吴迎红; 郭佳悦; 张强; 张存林; 赵跃进
Original assignee: Xi'an Aerospace Chemical Propulsion Co ltd; Beijing Institute of Technology BIT; Capital Normal University; Xian Aerospace Propulsion Institute
Current assignee: Xi'an Aerospace Chemical Propulsion Co ltd; Beijing Institute of Technology BIT; Capital Normal University; Xian Aerospace Propulsion Institute
Priority date: 2022-10-08
Filing date: 2022-10-08
Publication date: 2023-03-17
Anticipated expiration: 2042-10-08
Also published as: CN115290597A

Abstract

The invention provides a terahertz technology-based coating tight-fitting type non-adhesive defect detection method and system, and belongs to the technical field of nondestructive detection. The method comprises the following steps: preparing a coating standard test piece, wherein the coating standard test piece simultaneously comprises a close-fitting non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection matrix layer; after the terahertz waves are emitted to the coating of the object to be detected, returning original echo signals; preprocessing an original echo signal to obtain a preprocessed echo signal; preprocessing comprises effective signal interception and phase alignment; performing dimension reduction on the preprocessed echo signal based on a principal component analysis method to obtain characteristic parameters of the object to be detected; classifying the object to be detected by using a support vector machine model according to the characteristic parameters of the object to be detected, and classifying the class of the object to be detected into a close-fitting non-adhesive area and a well-adhered area. The invention can accurately distinguish the close-fitting non-adhesive area from the adhesive area, can carry out nondestructive detection on an object to be detected and has strong anti-interference capability.

Description

Terahertz technology-based method and system for detecting coating tight-fitting type non-adhesion defect

Technical Field

The invention relates to the technical field of nondestructive testing, in particular to a coating tight-fitting type non-adhesion defect detection method and system based on a terahertz technology.

Background

The solid rocket engine has the advantages of simple and compact structure, quick start, high reliability, easy maintenance and the like, and is widely applied to the field of modern aerospace and other delivery as a power source. The structure of the solid rocket engine comprises an outer anti-coating layer, a shell, a heat insulating layer, a lining and a propellant from outside to inside in sequence. The shell plays a supporting role, the outer anti-coating layer reduces the influence of pneumatic heating on the performance of the engine in the flying process of the engine, and the heat insulating layer isolates the effect of high-temperature, high-pressure and high-speed fuel gas on the combustion chamber shell in the working process of the engine. Therefore, in order to ensure the normal operation of the engine, the forming quality of the external protective coating and the heat insulating layer has high requirements, and a high-precision nondestructive testing means is required for detecting defects.

The quality of the various interfaces of the engine play a crucial role in the performance and operational safety of the engine. If the interface between the two parts is abnormal, such as debonding, gaps, foreign matters, cracks and the like, the structure of the rocket engine is unstable, and the rocket engine is easy to explode when running, so that irreparable results are caused. In particular, some interfaces are not bonded together by an adhesive, but are formed by spraying, deposition, growth, or the like. The coating material gradually stabilizes and bonds to the base material, forming a close contact interface, with sufficient bonding force. The adhesive force is a force formed by a plurality of forces such as mechanical embedding force, van der waals force, hydrogen bond force, chemical bond force and the like between the shell and the outer anti-coating layer and between the shell and the adhesive interface of the heat-insulating layer.

Due to various reasons such as imperfect process preparation, external environmental influence, acceleration impact and the like, the solid rocket engine shell, the external anti-coating and the heat insulating layer have no bonding defect, directly threaten the safety of the engine and possibly cause flight failure. The obvious interface is not tightly attached, which means that the shell is completely separated from the outer anti-coating layer and the heat insulating layer, and obvious gaps are formed. Such features are easily identified from appearance, or are easily discovered using existing detection techniques. The good interface bonding condition is divided into a good bonding area and a bonding-free area, and the interfaces are still bonded with each other. The bonded regions have sufficient cohesive force to interact with each other. And the bonding area has insufficient bonding force. The close-fitting type cohesionless structure is generally mistaken as a good-adhesion area, the defects are high in concealment and high in harmfulness, protection failure can be caused in serious cases, and flight failure is caused. Particularly, along with the continuous increase of the flying speed, the method is necessary and urgent for the close-fitting non-destructive detection without bonding defects between the solid rocket engine shell and the coating.

The current detection methods mainly comprise ultrasonic detection, ray detection, infrared thermal wave detection and the like. The ultrasonic method generally detects from one side of a metal material, the attenuation in a medium is increased, and the detection from the medium side is difficult; and the contact type generally needs a coupling agent, which is easy to cause pollution and damage to a detected sample, while the air coupling ultrasound solves the problem of non-contact detection, but the error is larger when the defect is smaller, and the capability of detecting a thin layer structure still needs to be further improved. The ray detection can generate radiation effect, and protection is needed during detection, so that the damage to detection personnel and the detected object is prevented; and the detection effect on the layering defect is not good, and particularly, the close-fitting type non-adhesive defect can hardly be detected. The infrared thermal wave detection is sensitive to the ambient temperature around the detected object and has limited capability of detecting the defects. None of the above-mentioned methods provides a visually close-fitting image distribution free from sticking defects.

Disclosure of Invention

The invention provides a method and a system for detecting a coating close-contact type non-bonding defect based on a terahertz technology, which are used for solving the technical problems that a close-contact type non-bonding area is easily mistaken as a good-bonding area and is difficult to detect, realizing close-contact type non-bonding defect nondestructive detection based on a terahertz wave and having strong anti-interference capability.

The invention provides a terahertz technology-based detection method for coating tight-fitting type non-adhesion defects, which comprises the following steps:

preparing a coating standard test piece which simultaneously comprises a close-fitting type non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following items: metals, carbon fibers, graphene, composite materials;

after the terahertz waves are emitted to the coating of the object to be detected, returning original echo signals;

preprocessing the original echo signal to obtain a preprocessed echo signal; the pre-processing includes effective signal interception and phase alignment;

performing dimension reduction on the preprocessed echo signal based on a principal component analysis method to obtain characteristic parameters of the object to be detected;

classifying the object to be detected by using a support vector machine model according to the characteristic parameters of the object to be detected, and dividing the class of the object to be detected into a close-fitting type non-bonding area and a bonding area, wherein the support vector machine model is obtained by training based on the characteristic parameters of the reference signal obtained by the coating standard test piece.

According to the method for detecting the coating clinging type non-bonding defects based on the terahertz technology, provided by the invention, the original echo signal comprises a first main peak signal and a second main peak signal;

the step of returning an original echo signal after the terahertz wave is emitted to the coating of the object to be detected comprises the following steps:

when the terahertz waves are incident to the outer surface of the coating of the object to be detected, returning to the first main peak signal;

and when the terahertz wave penetrates through the coating of the object to be detected and reaches the bonding interface between the coating and the strong reflection matrix layer, returning to the second main peak signal.

According to the method for detecting the coating close-fitting type non-bonding defects based on the terahertz technology, the pretreatment of the original echo signals comprises the following steps:

intercepting a second main peak signal corresponding to each sample point on the coating of the object to be detected;

performing phase alignment on all the second main peak signals corresponding to each sample point by taking the phase position of the characteristic value in the second main peak signal corresponding to each sample point as a reference, wherein the characteristic value comprises at least one of the following: maximum, minimum, zero crossing point, echo energy center of gravity.

According to the method for detecting the coating close-fitting type non-bonding defects based on the terahertz technology, provided by the invention, the dimension reduction is carried out on the preprocessed echo signals based on a principal component analysis method, and the characteristic parameters of the object to be detected are obtained, and the method comprises the following steps:

taking each sample point on the coating of the object to be detected as a research object, and reducing the dimension of the preprocessed echo signal corresponding to each sample point by adopting the principal component analysis method to obtain a dimension-reduced echo signal;

calculating the cumulative contribution rates of the front k principal components in the echo signals after dimension reduction, and determining the k value corresponding to the cumulative contribution rate larger than a preset threshold value;

and selecting the principal component corresponding to the minimum k value as the characteristic parameter of the object to be detected.

According to the terahertz technology-based detection method for the coating close-fitting type non-adhesive defects, before the object to be detected is classified by using a support vector machine model, the method further comprises the following steps:

the reference signal is subjected to the pretreatment to obtain a pretreated reference signal, and the reference signal is an echo signal returned after the terahertz wave is emitted to the coating of the coating standard test piece;

performing dimensionality reduction on the preprocessed reference signal based on the principal component analysis method to obtain a reference signal characteristic parameter;

and training the support vector machine model based on a training set constructed by the reference signal characteristic parameters.

The invention also provides a terahertz technology-based coating tight-fitting type non-adhesion defect detection system, which comprises:

the preparation module is used for preparing a coating standard test piece which simultaneously comprises a close-fitting type non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following materials: metal, carbon fiber, graphene, composite materials;

the detection module is used for returning an original echo signal after the terahertz wave is emitted to the coating of the object to be detected;

the first processing module is used for preprocessing the original echo signal to obtain a preprocessed echo signal; the preprocessing comprises effective signal interception and phase alignment;

the first dimension reduction module is used for reducing the dimension of the preprocessed echo signal based on a principal component analysis method to obtain the characteristic parameters of the object to be detected;

and the classification module is used for classifying the object to be detected by using a support vector machine model according to the characteristic parameters of the object to be detected, and classifying the class of the object to be detected into a close-fitting type non-bonding area and a bonding area, wherein the support vector machine model is obtained by training based on the reference signal characteristic parameters obtained by the coating standard test piece.

According to the terahertz technology-based coating clinging type non-bonding defect detection system provided by the invention, the original echo signal comprises a first main peak signal and a second main peak signal;

the detection module is further configured to:

and when the terahertz wave penetrates through the coating of the object to be detected and reaches the bonding interface between the coating and the strong reflection base body layer, returning to the second main peak signal.

The invention also provides electronic equipment 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 executes the program to realize the method for detecting the coating close contact type non-bonding defect based on the terahertz technology.

The invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method for detecting the adhesion-free defect of the coating adhesion type based on the terahertz technology.

The invention also provides a computer program product which comprises a computer program, wherein the computer program is used for realizing the method for detecting the coating close-fitting type non-bonding defect based on the terahertz technology when being executed by a processor.

According to the method and the system for detecting the coating close contact type non-adhesion defects based on the terahertz technology, the original echo signal is obtained by adopting the terahertz wave non-contact nondestructive incidence of the object to be detected, the contact coupling with the object to be detected is not needed, and the detection is simpler and more convenient; after the original echo signals are preprocessed, the original echo signals are classified by a principal component analysis method and a support vector machine, various regions corresponding to an object to be detected can be accurately detected, the sensitivity of an ultra-wide band vector spectrum of a terahertz frequency order to an interface microscopic interaction structure is higher by several orders of magnitude than that of the conventional detection technology, so that time domain signals are extremely sensitive to tiny differences, for example, responses of different bonding energy levels can be distinguished, terahertz waves can realize close-fitting type non-adhesive defect nondestructive detection, and meanwhile, the anti-interference capability of the transient characteristics of the time domain of picosecond orders is greatly enhanced; by adopting a principal component analysis algorithm, the high-dimensional terahertz echo signals can be reduced to low-dimensional characteristic parameters, useful information of the signals is reserved, and the calculated amount is reduced; the support vector machine is used for realizing the automatic identification of the close-fitting type non-cohesive defect, the detection efficiency is improved, and the working strength of human experts is reduced. The invention provides a non-contact nondestructive and sensitive detection method and system capable of automatically realizing close-fitting type non-adhesive defect identification feature recognition, overcomes the defects of the prior detection technology, greatly improves the detection capability and the intelligent degree compared with the prior art, and obviously improves the production capability.

Drawings

In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

FIG. 1 is a schematic flow diagram of a terahertz technology-based method for detecting a coating close-fitting type non-adhesive defect provided by the invention;

FIG. 2 is a schematic structural diagram of a standard test piece in the terahertz technology-based coating close-fitting type cohesionless defect detection method provided by the invention;

FIG. 3 is a schematic real object gray scale diagram of a coating standard test piece in the terahertz technology-based coating close-fitting type non-adhesive defect detection method provided by the invention;

FIG. 4 is a schematic diagram of transmission of terahertz pulses in the terahertz technology-based coating adhesion-free defect detection method provided by the invention;

FIG. 5 is a second schematic flow chart of the method for detecting adhesion-free defects of a coating layer based on terahertz technology according to the present invention;

FIG. 6 is a schematic diagram of an original echo signal in the terahertz technology-based detection method for detecting the adhesion-free defect of the coating in the close contact manner;

FIG. 7 is a schematic diagram of maximum value imaging in the terahertz technology-based method for detecting the close contact type non-adhesive defect of the coating;

FIG. 8 is a schematic diagram of minimum value imaging in the terahertz technology-based method for detecting the close contact type non-adhesive defect of the coating;

FIG. 9 is a schematic diagram of peak-peak imaging in the terahertz technology-based detection method for detecting the close-fitting type non-adhesive defects of the coating;

FIG. 10 is a schematic diagram of the scores of the first two principal components of an original echo signal in the terahertz technology-based detection method for detecting the adhesion-free defect of the coating;

FIG. 11 is a schematic diagram of a second main peak signal intercepted from an original echo signal in the terahertz technology-based coating close-fitting type non-adhesive defect detection method provided by the invention;

FIG. 12 is a schematic diagram of the first two principal component scores of a second principal peak signal intercepted from an original echo signal in the terahertz technology-based coating close-fitting type non-adhesive defect detection method provided by the invention;

FIG. 13 is a schematic diagram of a second main peak alignment signal in the terahertz technology-based method for detecting adhesion-free defects of a coating layer;

FIG. 14 is a schematic diagram showing the scores of the first two principal components of a second principal peak alignment signal in the terahertz technology-based method for detecting a coating close-fitting type non-adhesive defect provided by the invention;

FIG. 15 is a schematic diagram of the first two principal components of an echo signal in the terahertz technology-based detection method for detecting adhesion-free defects of a coating layer;

FIG. 16 is a schematic diagram of the first three principal components of an echo signal in the terahertz technology-based detection method for detecting the adhesion-free defect of the coating in a close contact manner;

FIG. 17 is a schematic diagram of the first four principal components of an echo signal in the terahertz technology-based detection method for detecting adhesion-free defects of a coating layer;

FIG. 18 is a schematic structural diagram of a coating-tight-type non-adhesive defect detection system based on terahertz technology provided by the invention;

fig. 19 is a schematic structural diagram of an electronic device provided by the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention is described below with reference to fig. 1, and the method for detecting the coating close-fitting type non-adhesive defect based on the terahertz technology comprises the following steps: step 110, step 120, step 130, step 140 and step 150.

110, preparing a coating standard test piece, wherein the coating standard test piece simultaneously comprises a close-fitting type non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following items: metal, carbon fiber, graphene, composite materials.

In this step, the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the coating can be room temperature curing type silicon rubber, and the material of the strong reflection base layer can comprise one or more of metal, carbon fiber, graphene and composite material.

The coating standard test piece comprises a close-fitting type non-bonding area and a bonding area, wherein the close-fitting type non-bonding area is obtained by manually separating the coating from the metal matrix layer and then tightly bonding the two layers through a pressurizing and curing process.

It should be noted that the form of the interface defect is: one substance is coated on the other substance to form an interface, the two substances are tightly attached, wherein the physical property of one substance gradually changes, and due to accidental factors, the two substances can be in a state without enough adhesive force, but the interface between the two substances is still tightly attached, so that the adhesive-free type is called as an adhesive-free type; having sufficient cohesive force is referred to as a "good adhesion zone".

The embodiment of the invention is illustrated with a strongly reflective substrate layer as the metal substrate layer, and as shown in fig. 2, the coating standard test piece comprises a coating and a metal substrate layer. Optionally, the size of the test piece is 100mm × 100mm, room Temperature cured Silicone Rubber (RTV) is used as a coating material of the test piece, a polytetrafluoroethylene film can be preset between the coating and the metal substrate layer, the two layers are separated first, the film is removed, and then the two layers are tightly attached through a pressurization curing process, so that an attached region without bonding defects is obtained.

FIG. 3 is a schematic gray scale diagram of a coating standard test piece, which includes a close-fitting non-adhesive area, an adhesive area and a metal area. The upper surface of the metal area is not coated and is a naked metal matrix, which is easy to be found in the detection process, and the metal area is not specifically analyzed in the embodiment. It is difficult to directly distinguish between a good-adhesion region and a tight-fitting non-adhesion region.

The good adhesion area shows that the coating is tightly adhered to the upper surface of the metal matrix layer, has strong interaction force, completely qualified quality and presents a tight adhesion state; the close-fitting type non-bonding area means that the coating layer and the surface of the metal substrate layer are in contact with each other, but has no bonding force. The good adhesion region also has a small area defect for inspecting the detection capability of the present embodiment for micro defects.

And step 120, returning an original echo signal after the terahertz wave is emitted to the coating of the object to be detected.

In this step, the terahertz wave has an electromagnetic wave frequency of 0.1 to 10THz, between the microwave and the infrared radiation, and a wavelength of 0.03 to 3mm. Compared with ultrasonic detection, the terahertz wave has stronger penetrating power to the material, can carry out non-contact detection, can directly detect the internal characteristics of the material without coupling media and other auxiliary substances, and can not damage the material structure; compared with the ray detection, the terahertz energy is very low, and the property of the detected material cannot be damaged when the material is irradiated by terahertz, and an operator cannot be influenced, so that the terahertz energy detection device has very strong safety; compared with infrared thermal wave detection, terahertz nondestructive detection has high anti-interference capability and reliability under complex and severe environments.

The object to be detected in the embodiment can be a high-speed flight vehicle such as a rocket engine and the like, and comprises a metal matrix layer and a coating, wherein the coating is attached to the surface of the metal matrix layer. The coating may be an outer protective coating or a thermal insulation layer. Therefore, the present embodiment is suitable for detecting the bonding between the rocket motor case and the outer anti-coating layer and the bonding between the rocket motor case and the heat insulating layer. The embodiment is suitable for all objects to be detected which need to carry out close-fitting type non-bonding detection on the coating.

Due to the superiority of full-coverage detection and convenience of in-situ implementation, the terahertz technology can be used for testing the bonding condition of each interface and the structural integrity of a combustion chamber of the solid rocket engine, can also be used for foreign matter prevention detection in a charging process, quality and defect of an outer anti-coating layer and health monitoring of a service engine, improves the detection efficiency, reduces the quality loss, ensures the consistency of the performance of the engine and improves the reliability of the solid rocket engine.

In the embodiment, a self-developed reflection-type terahertz spectrum system is adopted to vertically irradiate terahertz waves to one surface of a coating of an object to be detected, reflected terahertz beams carry information of the object to be detected, and reflected original echo signals are obtained through a series of conversion.

Step 130, preprocessing the original echo signal to obtain a preprocessed echo signal; the pre-processing includes effective signal interception and phase alignment.

In this step, it is difficult to distinguish the good adhesion region and some regions of the close-fitting type without adhesion based on the original echo signal, so the original echo signal needs to be preprocessed first, which is convenient to realize the accurate classification of the original echo signal,

the preprocessing may include, for example, effective signal interception and phase alignment, specifically: and intercepting the second main peak signal of the original echo signal, aligning by taking the maximum value of the second main peak signal as a reference, and obtaining the intercepted and aligned signal as the preprocessed echo signal.

According to the embodiment, the accuracy of classifying the original echo signals can be improved by preprocessing the original echo signals.

And 140, reducing the dimension of the preprocessed echo signal based on a principal component analysis method, and acquiring characteristic parameters of the object to be detected.

In this step, a Principal Component Analysis (PCA) method is used to perform dimensionality reduction on the preprocessed echo signal, and a characteristic parameter of the object to be detected is obtained, where the characteristic parameter of the object to be detected is a Principal Component of the preprocessed echo signal that meets the condition.

The dimension reduction is carried out on the preprocessed echo signals by adopting a principal component analysis method, so that the data volume of the original echo signals can be reduced, the detection speed is improved, and meanwhile, the good adhesion area and the tight adhesion area of the coating can be better distinguished.

And 150, classifying the objects to be detected by using a support vector machine model according to the characteristic parameters of the objects to be detected, and classifying the classes of the objects to be detected into a close-fitting type non-adhesive area and a well-adhered area.

In the step, characteristic parameters of the object to be detected, namely principal components meeting the conditions, are input into a support vector machine, and the whole coating area is classified and predicted, namely a bonding area and a close-fitting non-bonding area in the coating area are distinguished, so that whether the close-fitting non-bonding defect exists in the coating is determined.

In some embodiments, before classifying the object to be detected using the support vector machine model, the method further comprises:

preprocessing the reference signal to obtain a preprocessed reference signal, wherein the reference signal is an echo signal returned after a terahertz wave is emitted to a coating of a coating standard test piece;

performing dimensionality reduction on the preprocessed reference signal based on a principal component analysis method to obtain a reference signal characteristic parameter;

and training a support vector machine model based on a training set constructed by the reference signal characteristic parameters.

In actual implementation, as shown in fig. 5, an echo signal returned after a terahertz wave is emitted to a coating of a standard test piece is used as a reference signal, and a reference signal characteristic parameter obtained after the reference signal is preprocessed and subjected to dimensionality reduction is used as a training set to train a support vector machine model.

The classification area of the coating standard test piece is known, the main component of the known classification area subjected to dimensionality reduction is input into a support vector machine model to predict the whole measured area, and the parameters of the support vector machine model are adjusted to enable the predicted image classification area to be matched with the actual classification area.

And randomly selecting 40% of the data of the whole sample point as a training set, and using the data of the whole sample point as a testing set. Firstly, inputting a training set into a support vector machine model, and obtaining two classification models of a bonded area and a close-fitting type non-bonded area through training of the support vector machine model. And inputting the test set into a two-classification model to obtain a final prediction result.

The basic idea of the support vector machine is to map the original data to a high-dimensional space through transformation, and maximize the interval between the two types of data by finding an optimal hyperplane. The mapping needs to be done by selecting a kernel function. In this embodiment, a Radial Basis Function (RBF) is selected as the kernel Function.

According to the embodiment, the original echo signal is obtained by adopting the terahertz wave to irradiate the object to be detected, and after the original echo signal is preprocessed, the principal component analysis method is adopted to reduce the dimensionality and support vector machine classification is adopted, so that various regions corresponding to the object to be detected can be accurately detected, wherein the terahertz wave is used for realizing the close-fitting type non-cohesive defect nondestructive detection, and the anti-interference capability is strong; by adopting a principal component analysis algorithm, the high-dimensional terahertz echo signal can be reduced to a low-dimensional characteristic parameter, useful information of the signal is reserved, and the calculated amount is reduced; the support vector machine is used for realizing the automatic identification of the close-fitting type non-adhesive defect and improving the detection efficiency.

On the basis of the above embodiment, in this embodiment, the original echo signal includes a first main peak signal and a second main peak signal; step 110 specifically includes:

when the terahertz waves are incident to the outer surface of the coating of the object to be detected, returning a first main peak signal;

and when the terahertz wave penetrates through the coating of the object to be detected and reaches the bonding interface between the coating and the strong reflection matrix layer, returning a second main peak signal.

In the embodiment, the object to be detected is placed on the two-dimensional translation table by building the reflection type terahertz spectrum system. The terahertz pulse vertically enters an object to be detected, and when the terahertz wave reaches the upper surface of the coating, a first main peak signal is obtained; the terahertz wave has strong penetrating power and can penetrate through the coating to reach the bonding interface between the coating and the metal substrate layer to obtain a second main peak signal.

On the basis of the foregoing embodiment, in this embodiment, the preprocessing the original echo signal includes:

and taking the phase position of the characteristic value in the second main peak signal corresponding to each sample point as a reference, and performing phase alignment on all the second main peak signals corresponding to each sample point, wherein the characteristic value comprises at least one of the following items: maximum, minimum, zero crossing point, echo energy center of gravity.

As shown in fig. 4, S0 is a vertically incident terahertz pulse, R0 is a coating upper surface reflection signal, and R1 is a bonding interface reflection signal. Wherein, R1 is shown as the second main peak in the echo signal, and whether the bonding is reflected mainly as the difference of the second main peak. Thus, the second major peak is used to distinguish between a bonded region and a tight-fitting non-bonded region.

FIG. 6 is a diagram showing the original echo signals of the bonded area and the bonded area of the standard test piece. It can be seen that the original echo signals of the bonded area and the bonded area are overlapped. It is difficult to accurately distinguish the two types of regions only by the difference of the pulse signals.

And (4) carrying out image reconstruction on a large dotted line frame in the figure 3, namely the right half part of the standard test piece in the modes of imaging the maximum value of the second main peak of the echo signal, imaging the minimum value and imaging the peak value and the peak value.

Fig. 7 is a diagram showing the maximum value in the echo signal curve corresponding to each sample point in the right half of the standard test piece selected for imaging. The upper half part of the adhesive tape is provided with a dark color area which is a close-contact non-adhesive area, and the lower half part of the adhesive tape is provided with a light color area which is an adhesive area. The distribution conditions of the sticky region and the close-fitting type non-sticky region of the standard test piece can be preliminarily judged through the reconstructed image, but color aliasing exists in some regions of the sticky region and the close-fitting type non-sticky region in the image. Fig. 8 and 9 are minimum value imaging and peak value imaging, respectively, and color aliasing of a good adhesion region and a close-fitting type non-adhesion region is more serious, and it is difficult to distinguish the two types of regions.

And performing dimensionality reduction on the original echo signal by adopting a PCA dimensionality reduction method. Two-dimensional visual classification is carried out on the original echo signals by adopting the first principal component and the second principal component, and as shown in figure 10, two types of regions are seriously mixed.

The second main peak in the original echo signal is the reflected signal of the bonding interface, and whether bonding is mainly reflected as the difference of the second main peak or not. The second main peak of the original echo signal is truncated, and the truncated second main peak is shown in fig. 11. And carrying out PCA (principal component analysis) dimension reduction processing on the second main peak signal. As can be seen from the two-dimensional visual scatter diagram in fig. 12, the two types of signals are also severely aliased and cannot be distinguished.

Because the standard test piece is pressed and cured, the upper interface and the lower interface of the close-fitting type non-bonding area are mutually bonded, so that the time delay of signals is ignored, the influence of the phase inconsistency of the lower surface of the coating is eliminated, and only the difference of the shapes of the signals is reserved for classification detection. And (3) carrying out alignment treatment on the second main peak signal in the echo signal corresponding to each sample point in the right half part of the test piece by taking the phase position of the maximum value as a reference, and only considering the difference of the shapes of the signals. The aligned second main peak signal is shown in fig. 13. PCA dimensionality reduction is performed on the second main peak alignment signal to obtain a two-dimensional visible scatter diagram, as shown in fig. 14. The two types of regions can be obviously distinguished, and the pre-classification and visualization of the original high-dimensional terahertz reflection signal data are realized.

Whether bonding is mainly reflected as the difference of the second main peak or not in the embodiment, and the close-fitting type is not bonded as interface bonding, so that the influence of signal time delay is ignored, and only the difference of the signal shapes is kept. And carrying out second main peak interception on the original echo signal, aligning by taking the phase position of the maximum value of the second main peak as a reference, carrying out dimensionality reduction on the intercepted and aligned signal by adopting a principal component analysis method, and then, combining a support vector machine to distinguish a sticky region and a close-type non-sticky region. Therefore, the close-fitting type non-bonding defect of the rocket engine shell can be automatically and accurately identified.

On the basis of the foregoing embodiments, in this embodiment, the performing dimension reduction on the preprocessed echo signal based on a principal component analysis method to obtain the characteristic parameters of the object to be detected includes:

taking each sample point on the coating of the object to be detected as a research object, and reducing the dimension of the preprocessed echo signal corresponding to each sample point by adopting a principal component analysis method to obtain the echo signal after dimension reduction;

calculating the accumulated contribution rates of the front k principal components in the echo signals after dimension reduction, and determining the k value corresponding to the accumulated contribution rate larger than a preset threshold value;

The principle of principal component analysis is to recombine many original indexes with a certain correlation into a group of new linear irrelevant comprehensive indexes to replace the original variables as new comprehensive indexes. A common way is to express this by a variance of a linear combination. The larger the variance, the more information is contained. The first linear combination has the largest variance and is therefore called the first principal component, which also contains the most information. When the first linear combination is not enough to express the original data, the next largest linear combination is selected as the second principal component, and the second principal component contains information smaller than that of the first principal component. And so on until the component combinations can substantially represent the original information.

The total variance of the principal component is equal to the total variance of the original variable, i.e. the sum of the total variances of the original variables

The sum of the variances of the linearly independent principal components is equal. This also shows that the transformed principal component contains all the information of the original variable. Will be first

A main component

Is defined as the ratio of the variance of (c) to the total variance

The contribution rate of each principal component is recorded as:

the contribution rate of the principal component reflects the ability of the principal component to interpret the original variables, so the first component in the principal component has the greatest contribution rate, meaning that it is the component of all principal components that can reflect the original data most. The sum of the contribution rates of the first k principal components is referred to as the cumulative contribution rate of the first k principal components.

In this example, the contribution ratios of the first k principal components after dimensionality reduction are shown in table 1.

TABLE 1 contribution ratio of the front four principal components of the preprocessed echo signal

The first two principal components have an accumulated contribution rate of 52.84%, the first three principal components have an accumulated contribution rate of 68.79%, and the first four principal components have an accumulated contribution rate of 77.43%. The first two principal components and the first three principal components are input into the support vector machine model as input variables, and the obtained prediction results are shown in fig. 15 and 16, and aliasing occurs at the boundary between the close-fitting type non-adhesive region and the good-adhesive region. The first four main components are used as input variables, the obtained prediction result is shown in fig. 17, aliasing does not exist at the junction of the close-contact non-bonding area and the bonded area, the prediction result is compared with a real object, and the first four main components can basically distinguish two types of areas, namely the bonded area and the close-contact non-bonding area. When the first four main components are selected, no aliasing exists at the junction of the bonded area and the close-type non-bonded area, which shows that when the contribution rate of the main components is increased to a certain value, the prediction result tends to be stable and basically accords with the actual two types of areas. Therefore, the principal component having the cumulative contribution rate of 78% or more can be selected, and the sample to be measured can be classified and identified, so that a prediction result according with the actual situation can be obtained. Selecting a principal component that accumulates more consumes more computing resources.

Wherein, a part of the area of the right lower corner of the three prediction images is identified as a close-fitting non-bonding area, which is matched with the defect characteristics. From the prediction results, the present embodiment is effective in identifying minute defects and has high resolution.

In conclusion, after the second main peak is subjected to phase alignment, the main component analysis algorithm is adopted to extract the main components of the signals, so that the visual pre-classification of the signals can be realized, and the effective information is the morphology of the second main peak.

According to the method and the system for detecting the coating close contact type non-adhesion defects based on the terahertz technology, the original echo signal is obtained by adopting the terahertz wave non-contact nondestructive incidence of the object to be detected, the contact coupling with the object to be detected is not needed, and the detection is simpler and more convenient; after the original echo signals are preprocessed, the original echo signals are classified by a principal component analysis method and a support vector machine, various regions corresponding to an object to be detected can be accurately detected, the sensitivity of an ultra-wide band vector spectrum of a terahertz frequency order to an interface microscopic interaction structure is higher by several orders of magnitude than that of the conventional detection technology, so that time domain signals are extremely sensitive to tiny differences, for example, responses of different bonding energy levels can be distinguished, terahertz waves can realize close-fitting type non-adhesive defect nondestructive detection, and meanwhile, the anti-interference capability of the transient characteristics of the time domain of picosecond orders is greatly enhanced; by adopting a principal component analysis algorithm, the high-dimensional terahertz echo signal can be reduced to a low-dimensional characteristic parameter, useful information of the signal is reserved, and the calculated amount is reduced; the support vector machine is used for realizing the automatic identification of the close-fitting type non-adhesive defect, the detection efficiency is improved, and the working strength of human experts is reduced. The invention provides a non-contact nondestructive and sensitive detection method and system capable of automatically realizing close-fitting type non-adhesive defect identification feature recognition, overcomes the defects of the prior detection technology, greatly improves the detection capability and the intelligent degree compared with the prior art, and obviously improves the production capability.

The terahertz technology-based coating-tight-type non-bonding defect detection system provided by the invention is described below, and the terahertz technology-based coating-tight-type non-bonding defect detection system described below and the terahertz technology-based coating-tight-type non-bonding defect detection method described above can be referred to correspondingly.

As shown in fig. 18, the system includes the following modules:

a preparation module 1801, configured to prepare a coating standard test piece, where the coating standard test piece includes a close-fitting non-adhesive region and an adhesive region; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following items: metals, carbon fibers, graphene, composite materials;

the detection module 1802 is used for returning an original echo signal after the terahertz wave is emitted to a coating of an object to be detected;

a first processing module 1803, configured to pre-process the original echo signal to obtain a pre-processed echo signal; the preprocessing comprises effective signal interception and phase alignment;

a first dimension reduction module 1804, configured to perform dimension reduction on the preprocessed echo signal based on a principal component analysis method, so as to obtain a characteristic parameter of the object to be detected;

a classification module 1805, configured to classify the object to be detected by using a support vector machine model according to the characteristic parameters of the object to be detected, and divide the class of the object to be detected into a close-fitting type non-adhesive region and an adhesive region, where the support vector machine model is obtained by training based on the reference signal characteristic parameters obtained by the coating standard test piece.

According to the embodiment, the terahertz waves are incident to the object to be detected to obtain echo signals, the obtained terahertz reflection echo signals are preprocessed, and then principal component analysis and reduction and support vector machine classification are adopted, so that various regions can be accurately detected, wherein the terahertz waves are used for realizing close-fitting type non-adhesive defect nondestructive detection, and the anti-interference capability is strong; by adopting a principal component analysis algorithm, the high-dimensional terahertz echo signals can be reduced to low-dimensional characteristic parameters, useful information of the signals is reserved, and the calculated amount is reduced; the support vector machine is used for realizing the automatic identification of the close-fitting type non-adhesive defect and improving the detection efficiency.

In some embodiments, the raw echo signal comprises a first main peak signal and a second main peak signal;

the detection module 1802 is further configured to:

In some embodiments, the first processing module 1803 is further configured to:

In some embodiments, the first dimension reduction module 1804 is further configured to:

In some embodiments, the apparatus further comprises:

the second processing module is used for preprocessing the reference signal to obtain a preprocessed reference signal, and the reference signal is an echo signal returned after the terahertz wave is emitted to the coating of the coating standard test piece;

the second dimension reduction module is used for reducing the dimension of the preprocessed reference signal based on the principal component analysis method to obtain a reference signal characteristic parameter;

and the training module is used for training the support vector machine model based on a training set constructed by the reference signal characteristic parameters.

Fig. 19 illustrates a physical structure diagram of an electronic device, and as shown in fig. 19, the electronic device may include: a processor (processor) 1910, a communication Interface (Communications Interface) 1920, a memory (memory) 1930 and a communication bus 1940, wherein processor 1910, communication Interface 1920 and memory 1930 communicate with each other via communication bus 1940. The processor 1910 can call logic instructions in the memory 1930 to execute a terahertz technology-based coating adhesion-free defect detection method, and the method comprises the following steps:

preparing a coating standard test piece which simultaneously comprises a close-fitting type non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following materials: metals, carbon fibers, graphene, composite materials;

the terahertz waves are emitted to the coating of the object to be detected, and then the original echo signals are returned;

preprocessing the original echo signal to obtain a preprocessed echo signal; the preprocessing comprises effective signal interception and phase alignment;

In addition, the logic instructions in the memory 1930 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In another aspect, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a non-transitory computer readable storage medium, when the computer program is executed by a processor, the computer can execute the method for detecting the adhesion-free defect of the coating adhesion type based on the terahertz technology, which includes:

preparing a coating standard test piece which simultaneously comprises a close-fitting type non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following items: metal, carbon fiber, graphene, composite materials;

In still another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program, when being executed by a processor, is implemented to perform the method for detecting adhesion-free defects of coating adhesion type based on terahertz technology, provided by the above methods, the method including:

preparing a coating standard test piece, wherein the coating standard test piece simultaneously comprises a close-fitting non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following materials: metals, carbon fibers, graphene, composite materials;

The above-described system embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A coating tight type non-adhesion defect detection method based on a terahertz technology is characterized by comprising the following steps:

preparing a coating standard test piece, wherein the coating standard test piece simultaneously comprises a close-fitting non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following items: metal, carbon fiber, graphene, composite materials;

the sticking area shows that the coating is tightly attached to the strong reflection base layer, the close attaching degree of the coating and the strong reflection base layer reaches the distance range in which interface bonding can function, an interaction force meeting the process quality requirement is formed, and the interaction force is ensured to be effective through a preparation process;

the close-fitting type cohesionless zone indicates that the coating is tightly adhered to the strong reflection base layer, the close-fitting degree of the coating and the strong reflection base layer also reaches the distance range in which interface bonding can function, but no interaction force meeting the process quality requirement is formed, and the insufficient or failure of the interaction force is ensured through the preparation process;

the preparation of the coating standard test piece comprises the following steps:

selecting the material of the strong reflection base layer and the material of the coating, and presetting a polytetrafluoroethylene film in a partial region between the coating and the strong reflection base layer;

solidifying the coating and the strong reflection base layer in a region with a polytetrafluoroethylene film and a region without the polytetrafluoroethylene film through the same technological process, taking out the polytetrafluoroethylene film in the region with the polytetrafluoroethylene film, closely attaching the coating and the strong reflection base layer through a pressurizing process to obtain the close-fitting type non-bonding region, and forming the bonding region in the region without the polytetrafluoroethylene film;

the material and the structure of the bonded area are the same as those of the close-fitting type non-bonded area, and the interface bonding characteristics of the bonded area and the close-fitting type non-bonded area are different;

the interface bonding characteristic is embodied as an adhesion force between the good adhesion area and the close-fitting type non-adhesion area, wherein the adhesion force is used for indicating an acting force between the engine shell and the external anti-coating layer or an acting force between the engine shell and the heat insulation layer, and the acting force is formed based on a mechanical embedding force, a van der waals force, a hydrogen bond force and a chemical bond force;

classifying the object to be detected by using a support vector machine model according to the characteristic parameters of the object to be detected, and dividing the class of the object to be detected into a close-fitting type non-bonding area and a bonding area, wherein the support vector machine model is obtained by training based on the characteristic parameters of the reference signal obtained by the coating standard test piece;

the original echo signal comprises a first main peak signal and a second main peak signal;

the step of returning the original echo signal after the terahertz wave is emitted to the coating of the object to be detected comprises the following steps:

2. The method for detecting the adhesion-free defect of the coating close-fitting type based on the terahertz technology as claimed in claim 1, wherein the preprocessing the original echo signal comprises:

3. The terahertz technology-based detection method for the coating close-fitting type non-adhesive defects, as set forth in claim 1 or 2, is characterized in that the dimension reduction is performed on the preprocessed echo signals based on a principal component analysis method to obtain the characteristic parameters of the object to be detected, and comprises the following steps:

4. The method for detecting the adhesion-free defect of the coating close-fitting type based on the terahertz technology as claimed in claim 1 or 2, wherein before classifying the object to be detected by using a support vector machine model, the method further comprises:

5. The utility model provides a coating hugs closely type based on terahertz technology does not have and coheres defect detecting system which characterized in that includes:

the preparation module is used for preparing a coating standard test piece which simultaneously comprises a close-fitting non-bonding area and a bonding area; the coating standard test piece comprises a coating and a strong reflection base layer, wherein the material of the strong reflection base layer comprises at least one of the following items: metal, carbon fiber, graphene, composite materials;

the detection module is used for returning an original echo signal after the terahertz waves are emitted to the coating of the object to be detected;

the classification module is used for classifying the object to be detected by using a support vector machine model according to the characteristic parameters of the object to be detected, and classifying the class of the object to be detected into a close-fitting type non-bonding area and a bonding area, wherein the support vector machine model is obtained by training based on the reference signal characteristic parameters obtained by the coating standard test piece;

the detection module is further configured to:

when the terahertz wave penetrates through the coating of the object to be detected and reaches the bonding interface between the coating and the strong reflection base body layer, returning to the second main peak signal;

the close-fitting type cohesionless zone indicates that the coating is tightly attached to the strong reflection base layer, the close-fitting degree of the coating and the strong reflection base layer also reaches the distance range in which interface bonding can function, but no interaction force meeting the process quality requirement is formed, and the insufficient or failure of the interaction force is ensured through the preparation process;

the preparation module is further configured to:

selecting the material of the strong reflection base layer and the material of the coating, and presetting a polytetrafluoroethylene film in a partial area between the coating and the strong reflection base layer;

curing the coating and the strong reflection base layer in a region with a polytetrafluoroethylene film and a region without the polytetrafluoroethylene film through the same technological process, taking out the polytetrafluoroethylene film from the region with the polytetrafluoroethylene film, closely attaching the coating and the strong reflection base layer through a pressurizing process to obtain the close-fitting type non-adhesive region, and forming the adhesive region in the region without the polytetrafluoroethylene film;

the interface bonding characteristic is embodied as an adhesion force between the well-adhered region and the close-fitting type non-adhesive region, the adhesion force is used for indicating an acting force between the engine shell and the outer anti-coating layer or an acting force between the engine shell and the heat-insulating layer, and the acting force is formed based on a mechanical embedding force, a van der waals force, a hydrogen bond force and a chemical bond force.

6. An electronic device comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the method for detecting the adhesion-free defect of the coating adhesion type based on the terahertz technology according to any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method for detecting adhesion-free defect of coating adhesion based on terahertz technology as claimed in any one of claims 1 to 4.