CN116625974A - Reflection terahertz time-domain spectral tomography method based on adaptive genetic algorithm - Google Patents
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Abstract
The invention discloses a reflection-type terahertz time-domain spectral tomography method based on a self-adaptive genetic algorithm, which comprises the following steps: a three-dimensional displacement motion platform is adopted to place a multi-layer composite material coating sample with defects to be detected, and the position of the sample is adjusted through visible light signals so that light spots are focused on the surface of the sample; setting control parameters of the system to enable the displacement platform to move according to a pre-designed path; carrying out time domain peak-to-peak tomography on a terahertz time-domain waveform diagram acquired by a terahertz time-domain spectrum imaging system in the sample moving process, finding out the slice position where the defect is located, and observing the slice imaging result; establishing a self-adaptive genetic algorithm model, calculating a threshold parameter which is most suitable for image segmentation through a self-adaptive adjustment mechanism of the crossover probability and the variation probability, and segmenting the image; denoising the segmented image by using a morphological corrosion expansion algorithm, wherein the finally obtained image is used as a tomography result of the sample.
Description
Technical Field
The invention relates to the technical field of terahertz time-domain spectrum detection, in particular to a reflection-type terahertz time-domain spectrum tomography method based on a self-adaptive genetic algorithm.
Background
With the rapid development of composite material preparation technology, new materials and new processes are continuously emerging, and new composite material products are continuously developed and utilized. Composite products have gradually replaced materials such as metal and wood in various fields due to their excellent properties such as light weight, high strength, corrosion resistance, good electrical insulation properties, good thermal insulation properties, easy coloring, strong designability, and excellent process. However, in the production or use process of the composite material, the damage and the destruction of the interior of the composite material are inevitably caused due to the influences of factors such as imperfect production process, human negligence, use environment and the like, the bearing capacity and other performances of the material are reduced, and potential safety hazards are buried. Because terahertz waves have strong penetrating power to nonmetallic materials, nondestructive detection and evaluation of the damage type and damage degree inside the composite materials by means of terahertz waves are expected.
The nondestructive testing technology is to detect the morphological characteristics of the surface and the inside of the material by physical information such as sound, light, magnetism, electricity and the like on the premise of not damaging the structure and the performance of the material, and finally evaluate and analyze the detected defects. The nondestructive testing technology is an important method for controlling the quality of products and ensuring the normal operation of in-service products, is also an indispensable effective tool in the industrial field, and can reflect the industrial technical level of one country-! With the high-speed development of the economic level and the scientific technology in China, the nondestructive testing technology developed at present can not only qualitatively detect materials, namely judge whether the materials are defective, but also quantitatively detect, for example, identify the position, shape, size, type and the like of the defects. For inspecting composite materials, radiation, ultrasonic inspection, and the like are mainly used. In recent years, terahertz nondestructive detection technology is paid more attention to in the field of industrial detection, and compared with X-ray detection technology, terahertz wave has very low single photon energy, high safety to human bodies and samples to be detected, and low imaging contrast caused by excessive irradiation; compared with ultrasonic detection, terahertz detection does not need a couplant, and the spatial resolution is higher. Therefore, the terahertz technology is hopeful to become a novel nondestructive testing means.
Terahertz waves are electromagnetic waves with a spectrum between microwaves and infrared rays, named in the frequency range of 0.1-10 THz, and corresponding to wavelengths between 30 μm and 3 mm. Along with the rapid development of ultrafast laser and semiconductor technology, the excitation and detection means of terahertz waves are also increasingly stable and reliable. Terahertz waves have good penetrability to most nonmetallic materials (such as glass fiber, ceramic, foam, composite materials and the like). At present, pulse terahertz time-domain spectroscopy and imaging technology thereof have become an important bridge connecting terahertz technology and nondestructive testing technology.
Terahertz time-domain spectroscopy is a typical representative technique that has been developed in the course of development of terahertz spectroscopy. The technology utilizes the interaction relation between the pulse terahertz wave and the substance to measure the phase and the amplitude of the terahertz signal at the same time, so as to realize the microstructure analysis of the tested piece, and rapidly and accurately acquire and measure the physical and chemical information. Compared with the conventional nondestructive testing technology, the terahertz time-domain spectroscopy technology has the following advantages: detecting the signal frequency bandwidth; the space-time resolution is high; the anti-interference capability is strong; the spectrum information is rich; no contact detection is required; can be monitored in real time. In conclusion, the terahertz time-domain spectroscopy technology is particularly suitable for non-contact, rapid and comprehensive nondestructive detection, and realizes thickness characterization of the composite material surface coating in the aviation field.
The genetic algorithm is a model for simulating the biological evolution process in the nature, genetic operation is carried out on the group to be optimized according to the principle of the winner and the loser, new optimized groups are continuously generated, the optimal solution meeting the requirements is sought, and the algorithm is used in image segmentation and can be used for iteratively calculating the optimal threshold value. However, since the convergence effect of the model is very dependent on the crossover rate and the mutation rate, most of the current selection of these parameters is based on experience, so that there is still a great improvement space for the algorithm.
The existing terahertz nondestructive testing technology has poor imaging effect on glass fiber composite materials, edge detail information characterization is not obvious, and practical information such as relative area and the like cannot be estimated. Because terahertz light source is invisible light, it is difficult to estimate whether the facula gathers on the sample surface during the detection, and the detector can receive the light source after the reflection completely.
Accordingly, those skilled in the art have been working to develop a reflection-type terahertz time-domain spectral tomography method based on an adaptive genetic algorithm to overcome the problems of the prior art.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present invention is to provide a reflection-type terahertz time-domain spectral tomography method based on an adaptive genetic algorithm, which adaptively adjusts the crossover probability and the variation probability according to the fitness value, improves the convergence capacity and the optimizing capacity of the model, makes the theoretical model more accurate in a manner closer to the actual one, eliminates the measurement error caused by external noise, improves the imaging resolution, and completes the tomography.
In order to achieve the above purpose, the invention provides a reflection-type terahertz time-domain spectral tomography method based on an adaptive genetic algorithm, which comprises the following steps:
step 1, a three-dimensional displacement motion platform fixed under a terahertz time-domain spectroscopy imaging system is adopted to place a multi-layer composite material coating sample with defects to be detected, and the z-direction position of the multi-layer composite material coating sample is adjusted through a visible light signal placed in the terahertz time-domain spectroscopy imaging system, so that light spots are focused on the surface of the multi-layer composite material coating sample;
step 2, setting control parameters of the three-dimensional displacement motion platform system according to the defect positions and the sizes of the pre-acquired multilayer composite material coating samples, so that the three-dimensional displacement motion platform moves according to a pre-designed path to ensure that the terahertz time-domain spectrum imaging system can completely scan all defect information on the multilayer composite material coating samples;
step 3, performing time domain peak tomography on a terahertz time domain waveform chart acquired by the terahertz time domain spectrum imaging system in the moving process of the multilayer composite material coating sample, finding a slice position where a defect is located according to a defect reflection peak on the time domain waveform, and observing a slice imaging result;
step 4, establishing a self-adaptive genetic algorithm model, and ensuring that the terahertz time-domain spectrum imaging system has better optimizing capability and convergence capability through a self-adaptive adjustment mechanism of cross probability and variation probability in the design model, so as to calculate threshold parameters most suitable for defect image segmentation and segment images;
and 5, denoising the segmented defect image by using a morphological corrosion expansion algorithm, wherein the finally obtained image is used as a tomography result of the multilayer composite material coating sample.
Further, the terahertz time-domain spectroscopy imaging system in step 1 further includes a normal incidence reflection type visible light path for adjusting the position of the multilayer composite material coating sample so that terahertz waves are focused on the surface of the multilayer composite material coating sample.
Further, the terahertz time-domain spectroscopy imaging system in step 2 includes:
a femtosecond laser for generating high-frequency pulse laser;
the beam splitter is used for receiving the high-frequency pulse light and dividing the high-frequency pulse light into pump light and detection light;
the delay line is used for ensuring that the optical path length of the pump light is consistent with that of the detection light;
a terahertz transmitter for receiving the pump light and generating terahertz waves;
and the terahertz wave detector is used for receiving the terahertz waves reflected after focusing on the surface of the multilayer composite material coating sample.
Further, the adaptive genetic algorithm in step 4 aims to achieve trade-off between searching and randomness in different ways, and adaptively adjusts the crossover probability p according to the fitness value c Probability of variation p m Is the value of (1):
wherein f max Is the maximum fitness value of the population, f avg Is the average fitness value of each generation of population, f' is the larger fitness value of two individuals with intersection, f is the fitness value of the individual to be mutated, k 1 、k 2 、k 3 、k 4 Is an adjustment coefficient between (0, 1), p 0 Is the default mutation rate.
The invention has the beneficial effects that:
(1) The terahertz time-domain spectrum imaging system also comprises a vertical incidence reflection type visible light path which is used for adjusting the position of the multilayer composite material coating sample so that terahertz waves are focused on the surface of the coating sample.
(2) The invention creatively adopts the combination of the self-adaptive genetic algorithm model and the terahertz time-domain spectrum imaging technology, avoids the iterative computation from entering a local optimal solution by self-adaptively adjusting the cross probability and the genetic probability, more accurately computes the image threshold suitable for segmentation, evaluates the computation result by the fitness value, and can furthest improve the image segmentation precision while ensuring the image processing time.
(3) The method is simple and convenient to actually operate, and the detection cost is low.
The conception, specific structure, and technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, features, and effects of the present invention.
Drawings
FIG. 1 is a flow chart of method steps of a preferred embodiment of the present invention;
FIG. 2 is a terahertz time-domain peak-to-peak imaging diagram of a sample of a preferred embodiment of the invention;
FIG. 3 is a specific flow chart of an adaptive genetic algorithm according to a preferred embodiment of the present invention;
FIG. 4 is a graph showing the image segmentation effect of a sample according to a preferred embodiment of the present invention through an adaptive genetic algorithm.
Detailed Description
The following description of the preferred embodiments of the present invention refers to the accompanying drawings, which make the technical contents thereof more clear and easier to understand. The present invention may be embodied in many different forms of embodiments and the scope of the present invention is not limited to only the embodiments described herein.
In the drawings, like structural elements are referred to by like reference numerals and components having similar structure or function are referred to by like reference numerals. The dimensions and thickness of each component shown in the drawings are arbitrarily shown, and the present invention is not limited to the dimensions and thickness of each component. The thickness of the components is exaggerated in some places in the drawings for clarity of illustration.
The invention provides a research method of a reflection type terahertz time-domain spectral tomography technology based on a self-adaptive genetic algorithm, which is based on a non-contact type reflection type terahertz time-domain spectral imaging system and a three-dimensional displacement platform which are built independently, performs two-dimensional scanning on a multi-layer composite material containing defects in the x and y directions, performs time-domain peak-to-peak imaging on terahertz time-domain signals obtained by scanning, and can enhance the maximum contrast between the defects of a sample and the background. In order to ensure that the obtained tomographic imaging can furthest retain the detail information of defects and filter irrelevant noise, the experiment selects an adaptive genetic algorithm to perform preprocessing segmentation on the obtained image, and optimizes the optimizing and convergence capacity of the model through the adaptive adjustment of the model intersection and the variation coefficient, thereby improving the preprocessing effect on the image; the method and the device for preprocessing the terahertz imaging obtained in a mode close to reality enhance the detail information of the image defect part, filter the interference noise, greatly restore the defect information in the sample, optimize the experimental effect of the terahertz imaging technology, improve the imaging resolution of the system and realize the tomography.
The invention provides a terahertz tomography method based on a self-adaptive genetic algorithm, which is shown in fig. 1 and specifically comprises the following steps:
s1, a three-dimensional displacement motion platform fixed under a reflection type terahertz time-domain spectroscopy imaging system is adopted to place a multi-layer composite material coating sample with defects to be detected, and the z-direction position of the multi-layer composite material coating sample is adjusted through a visible light signal placed in the terahertz time-domain spectroscopy imaging system, so that light spots are focused on the surface of the multi-layer composite material coating sample;
wherein, reflection-type terahertz time-domain spectral imaging system includes:
a femtosecond laser for generating high-frequency pulse laser;
the beam splitter is used for receiving the high-frequency pulse light and dividing the high-frequency pulse light into pump light and detection light;
the optical delay system realizes the point-by-point scanning of the terahertz pulse signal by changing the optical path difference of the pump light and the detection light, and extracts the time domain data of the THz wave;
a terahertz transmitter for receiving the pump light and generating terahertz waves;
and the terahertz wave detector is used for receiving the terahertz waves reflected after focusing on the surface of the multilayer composite material coating sample.
The terahertz wave pulse signal is generated after the femtosecond laser pulse emitted by the femtosecond laser acts on the photoconductive antenna, propagates in the space optical path transmission system and generates reflection on the surface of the sample, the terahertz reflection signal carrying the sample information is received by the terahertz detector, and the terahertz time-domain spectrum signal is generated after the terahertz reflection signal is sampled by the optical delay mechanism.
Step S2, setting control parameters of a three-dimensional displacement motion platform system according to the defect positions and the sizes of the pre-acquired multilayer composite material coating samples, so that the three-dimensional displacement motion platform moves according to a pre-designed path, and the terahertz time-domain spectrum imaging system can completely scan all defect information on the multilayer composite material coating samples;
because the acquired terahertz time-domain signal has obvious high-frequency noise information due to the influence of external noise, the time-domain signal needs to be subjected to smooth filtering, and the influence of the noise signal on imaging is eliminated as much as possible.
Step S3, performing time domain peak tomography on a terahertz time domain waveform diagram acquired by a terahertz time domain spectrum imaging system in the moving process of a multilayer composite material coating sample, finding the slice position of a defect according to a defect reflection peak on the time domain waveform, and observing a slice imaging result, as shown in fig. 2;
tomography uses the peak-to-peak amplitude of the time domain waveform of a sample at a specific time point as an imaging parameter. The method can be used for acquiring the internal section information of the material, and the formula is as follows:
S(x,y)＝S sample (x,y,t 0 ), t 0 ∈(t 1 ,t 2 ) (1)
in the reflection detection, t 1 、t 2 The time t is respectively the time of the terahertz signal reflected by the upper surface and the lower surface of the sample to reach the detector 0 The specific value of (3) is correspondingly adjusted according to the actual detection requirement.
S4, establishing a self-adaptive genetic algorithm model, and ensuring that the system has better optimizing capability and convergence capability through designing a self-adaptive adjustment mechanism of cross probability and variation probability in the model, so as to calculate threshold parameters most suitable for image segmentation and segment images;
the specific implementation flow is shown in figure 3; in general, adaptive genetic algorithms are divided into four phases: initializing population, evaluating fitness, breeding and stopping.
Population initialization is the process of creating an initial random solution, which can be set to n random values of 0-255 as the initial value of the pixel population, i.e., n chromosome results. The fitness function is used to evaluate fitness values for each chromosome, entering the propagation process.
The propagation process is divided into three steps: selection, crossover and mutation. Selecting chromosome results which can enter next generation propagation through the evaluation result of the fitness function, wherein the chromosome results are more excellent as the fitness value is larger in general cases; after the selection of the chromosome, performing crossover operations by a random point in the chromosome, and exchanging genes after the point; after the crossover operation is completed, the chromosome enters the compilation stage. Mutation is accomplished by randomly inverting a gene in a chromosome; when the chromosome population has completed three steps of selection, crossover and mutation, they have completed the breeding operation in this generation.
The last procedure of the adaptive genetic algorithm is a termination operation, which has two termination conditions: one is to terminate the algorithm when it runs to a manually set evolutionary algebra; the other is when the optimal individuals in the population have not improved for consecutive generations or the average fitness of the population has not improved for consecutive generations.
The adaptive genetic algorithm aims at realizing trade-off between searching property and randomness in different modes and adaptively adjusting the crossing probability p according to the fitness value c Probability of variation p m When the population tends to stay in the locally optimal solution (where the population fitness is concentrated, the diversity is poor), the crossover probability p c Probability of variation p m The value of (a) increases, and when the population spreads in the solution space (i.e., population fitness spreads, diversity is higher), the crossover probability p c Probability of variation p m Is reduced by the value of (a) and finally designs a value for the cross probability p c Probability of variation p m Is a calculation formula of (2).
When the model calculates the optimal threshold, the selection of the crossover probability and the mutation probability is very important. The crossover probability p can be adaptively adjusted according to an adaptive genetic algorithm proposed by Srinivas et al c Probability of variation p m . In the present algorithm, p c And p m Self-adjusting is performed according to the following formula:
wherein f max Is the maximum fitness value of the population, f avg Is the average fitness value of each generation of population, f' is the larger fitness value of two individuals with intersection, f is the fitness value of the individual to be mutated, k 1 、k 2 、k 3 、k 4 Is the adjustment coefficient between (0, 1). According to the formula we can see that when a certain individual fitness value is equal to the maximum fitness value, p is c And p m All 0, in order to avoid entering the locally optimal solution, the invention introduces a default mutation rate p for each individual 0 As shown in formula (3):
the method is enabled to dynamically transform, so that the optimal segmentation threshold is calculated in an iterative mode, an innovative processing method is provided for terahertz imaging processing, and threshold segmentation of the acquired defect sample image can be effectively achieved.
And S5, denoising the segmented defect image by a morphological corrosion expansion algorithm, wherein the finally obtained image is used as a tomography result of a multilayer composite material coating sample, as shown in fig. 4.
According to the invention, the terahertz reflection type spectrum imaging structure is processed by utilizing the self-adaptive genetic algorithm, the system is ensured to have better optimizing capability and convergence capability by designing the self-adaptive adjustment mechanism of the cross probability and the variation probability in the model, so that the threshold parameter which is most suitable for image segmentation is calculated, the image is segmented, the detail information of the defect can be better restored, and the internal defect condition is represented. The pixel values in the image are subjected to operations such as selection, intersection, variation and the like through simulating natural genetic rules, the iterative calculation condition is evaluated through observing the fitness value, and the image threshold value most suitable for segmentation is found. The method improves the characterization effect of terahertz on the internal defects of the glass fiber composite material, improves imaging detail information, enriches the content of terahertz nondestructive testing through characterization of parameters such as relative area and the like, and improves the practicability of the terahertz nondestructive testing technology.
The invention designs a visible light source device consistent with the optical paths of the terahertz transmitting probe and the terahertz receiving probe, simulates the optical path of the terahertz light source and is convenient for focusing light spots. The visible light source is consistent with the terahertz light wave optical path and the optical path. The accuracy and precision of terahertz detection are improved, the operation of an experimenter is facilitated, and the practicability of the terahertz nondestructive detection technology is improved.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention without requiring creative effort by one of ordinary skill in the art. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (4)
1. The reflection-type terahertz time-domain spectral tomography method based on the adaptive genetic algorithm is characterized by comprising the following steps of:
step 1, a three-dimensional displacement motion platform fixed under a terahertz time-domain spectroscopy imaging system is adopted to place a multi-layer composite material coating sample with defects to be detected, and the z-direction position of the multi-layer composite material coating sample is adjusted through a visible light signal placed in the terahertz time-domain spectroscopy imaging system, so that light spots are focused on the surface of the multi-layer composite material coating sample;
step 2, setting control parameters of the three-dimensional displacement motion platform system according to the defect positions and the sizes of the pre-acquired multilayer composite material coating samples, so that the three-dimensional displacement motion platform moves according to a pre-designed path to ensure that the terahertz time-domain spectrum imaging system can completely scan all defect information on the multilayer composite material coating samples;
step 3, performing time domain peak tomography on a terahertz time domain waveform chart acquired by the terahertz time domain spectrum imaging system in the moving process of the multilayer composite material coating sample, finding a slice position where a defect is located according to a defect reflection peak on the time domain waveform, and observing a slice imaging result;
step 4, establishing a self-adaptive genetic algorithm model, and ensuring that the terahertz time-domain spectrum imaging system has better optimizing capability and convergence capability through a self-adaptive adjustment mechanism of cross probability and variation probability in the design model, so as to calculate threshold parameters most suitable for defect image segmentation and segment images;
and 5, denoising the segmented defect image by using a morphological corrosion expansion algorithm, wherein the finally obtained image is used as a tomography result of the multilayer composite material coating sample.
2. The adaptive genetic algorithm-based reflection terahertz time-domain spectroscopy imaging method as set forth in claim 1, wherein the terahertz time-domain spectroscopy imaging system in step 1 further includes a normal incidence reflection type visible light path for adjusting the position of the multilayer composite material coating sample so that terahertz waves are focused on the surface of the multilayer composite material coating sample.
3. The adaptive genetic algorithm-based reflection terahertz time-domain spectroscopy imaging method as set forth in claim 1, wherein the terahertz time-domain spectroscopy imaging system in step 2 includes:
a femtosecond laser for generating high-frequency pulse laser;
the beam splitter is used for receiving the high-frequency pulse light and dividing the high-frequency pulse light into pump light and detection light;
the delay line is used for ensuring that the optical path length of the pump light is consistent with that of the detection light;
a terahertz transmitter for receiving the pump light and generating terahertz waves;
and the terahertz wave detector is used for receiving the terahertz waves reflected after focusing on the surface of the multilayer composite material coating sample.
4. The adaptive genetic algorithm-based reflection terahertz time-domain spectroscopy imaging method as set forth in claim 1, wherein the adaptive genetic algorithm in step 4 aims to achieve trade-off between searching and randomness in different ways, and adaptively adjusts the crossover probability p according to fitness values c Probability of variation p m Is the value of (1):
wherein f max Is the maximum fitness value of the population, f avg Is the average fitness value of each generation of population, f' is the larger fitness value of two individuals with intersection, f is the fitness value of the individual to be mutated, k 1 、k 2 、k 3 、k 4 Is an adjustment coefficient between (0, 1), p 0 Is the default mutation rate.
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