nondestructive testing method for blade test piece of aero-engine based on terahertz technology
阅读说明：本技术 一种基于太赫兹技术的航空发动机叶片试件无损检测方法 (nondestructive testing method for blade test piece of aero-engine based on terahertz technology ) 是由 张留洋 陈雪峰 徐亚飞 翟智 孙瑜 于 2019-07-31 设计创作，主要内容包括：本公开揭示了一种基于太赫兹技术的航空发动机叶片试件无损检测方法,包括：利用太赫兹信号对样品进行无损检测,获得太赫兹原始检测信号；对太赫兹原始检测信号进行傅里叶变换、频域解卷积和小波处理获得高信噪比的特征信号；对高信噪比的特征信号通过傅里叶变换获得频域功率谱,对所述频域功率谱进行扩展获得样品成像；对所述提高成像对比度后的样品成像中陶瓷层厚度和缺陷进行定量表征。本公开还提供了一种基于太赫兹技术的航空发动机叶片试件无损检测装置。本公开能够克服传统无损检测方式检测精度低、检测范围有限、漏检误检的问题,实现热障涂层表面、界面、内部裂纹缺陷及陶瓷层厚度的高精度定量检测。(The invention discloses a nondestructive testing method for an aero-engine blade test piece based on a terahertz technology, which comprises the following steps: carrying out nondestructive detection on the sample by utilizing the terahertz signal to obtain a terahertz original detection signal; carrying out Fourier transform, frequency domain deconvolution and wavelet processing on the terahertz original detection signal to obtain a characteristic signal with a high signal-to-noise ratio; carrying out Fourier transform on the characteristic signal with high signal-to-noise ratio to obtain a frequency domain power spectrum, and expanding the frequency domain power spectrum to obtain sample imaging; and quantitatively characterizing the thickness and the defects of the ceramic layer in the sample image after the imaging contrast is improved. The utility model also provides an aeroengine blade test piece nondestructive test device based on terahertz technique. The method can overcome the problems of low detection precision, limited detection range and missed detection and false detection in the traditional nondestructive detection mode, and realizes high-precision quantitative detection of the surface, interface and internal crack defects of the thermal barrier coating and the thickness of the ceramic layer.)
1. a nondestructive testing method for an aero-engine blade test piece based on a terahertz technology comprises the following steps:
S100: carrying out nondestructive detection on a sample by utilizing a terahertz original signal i (t) through point-by-point scanning to obtain a terahertz echo detection signal r (t) with a low signal-to-noise ratio;
S200: carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample, and carrying out frequency domain deconvolution and stationary wavelet denoising processing on the frequency domain information of the sample to obtain a characteristic signal h' (t) with the high signal-to-noise ratio;
s300: obtaining a frequency domain power spectrum E by Fourier transform on the characteristic signal h' (t) with high signal-to-noise ratio, expanding the frequency domain power spectrum E to obtain sample imaging, and processing the sample imaging by utilizing a-6 dB rule to improve imaging contrast;
s400: and quantitatively characterizing the thickness and the defects of the ceramic layer in the sample image after the imaging contrast is improved according to the standard sample.
2. the method according to claim 1, wherein said step S200 comprises the following steps:
s201: carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample;
S202: filtering the frequency domain information of the sample by using a frequency domain deconvolution method and selecting a Hanning window function to obtain a terahertz pulse response signal h (t) of the sample;
S203: carrying out 4-level wavelet decomposition on the terahertz impulse response signal h (t) of the sample to obtain wavelet coefficients;
S204: and comparing the wavelet coefficient with a wavelet coefficient threshold, eliminating the wavelet coefficient smaller than the wavelet coefficient threshold, and reconstructing the wavelet coefficient larger than the wavelet coefficient threshold to obtain a sample characteristic signal h' (t) with a high signal-to-noise ratio.
3. The method according to claim 2, wherein in step S204, when the absolute value of the wavelet coefficient is smaller than the wavelet coefficient threshold, the wavelet coefficient is regarded as a noise signal; when the absolute value of the wavelet coefficient is greater than the wavelet coefficient threshold, the wavelet coefficient is considered as a significant feature signal.
4. the method according to claim 1, wherein the step S300 comprises the steps of:
s301: obtaining a spectral density s (f) by Fourier transform on the characteristic signal h' (t) with high signal-to-noise ratio;
s302: obtaining a spectrum power spectrum E of the characteristic signal h' (t) with the high signal-to-noise ratio according to a Pasteval theorem;
S303: expanding the frequency domain power spectrum E to obtain sample imaging;
s304: the imaging contrast is improved by processing the sample image using the-6 dB rule.
5. the method according to claim 4, wherein the spectral power spectrum E of the high SNR signature signal h' (t) is expressed as:
where f is the frequency in the frequency domain and t is the time variable in the time domain.
6. the method according to claim 4, wherein in step S304, the improving of the imaging contrast by processing the sample imaging with the-6 dB rule is: and extracting the maximum value of the gray value of each image in the sample imaging, and setting the pixel points of which the gray values are more than half of the maximum value of the gray values in each image as red.
7. The method according to claim 1, wherein in the step S400, the standard sample comprises: reference sample, ceramic layer defect-free sample, ceramic layer irregular longitudinal crack sample and ceramic layer longitudinal hole sample.
8. The method according to claim 1, wherein the step S400 comprises the steps of:
s401: determining the optical refractive index of the sample ceramic layer, and obtaining the thickness of the sample ceramic layer according to the optical refractive index of the sample ceramic layer;
S402: according to the time difference delta t of the time domain corresponding to the upper and lower interfaces of the extracted sample defect1depth information characterizing the sample defects; and characterizing the transverse dimension information of the sample defect according to the extracted edge information of the sample defect.
9. the method of claim 8, wherein in step S401, the thickness of the sample ceramic layer is:
Wherein, c represents a constant value,expressing the optical refractive index of the ceramic layer of the sample, delta t expressing the absolute value of the time difference corresponding to the maximum amplitude of the h ' (t) signal of any 5 pixels of the sample without the ceramic layer and the second maximum amplitude thereof, and tau expressing the absolute value of the time difference corresponding to the maximum amplitude of the h ' (t) signal of any 5 pixels of the sample without the ceramic layer and the maximum amplitude of the h ' (t) signal of 5 pixels corresponding to the reference sample;
In step S402, the depth information of the sample defect is:
wherein c represents a constant, Δ t1representing the time difference of the corresponding time domains of the upper and lower interfaces of the crack and the hole defect of the sample;
the transverse dimension information of the sample defects is as follows:
D＝Δx×N
where D denotes the defect lateral diameter and Δ x denotes the sampling interval.
10. The utility model provides an aeroengine blade test piece nondestructive test device based on terahertz technique, includes:
The echo detection signal acquisition module is used for carrying out nondestructive detection on the sample by utilizing the terahertz original signal i (t) through point-by-point scanning to obtain a terahertz echo detection signal r (t) with a low signal-to-noise ratio;
The characteristic signal acquisition module is used for carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample, and carrying out frequency domain deconvolution and stationary wavelet denoising processing on the frequency domain information of the sample to obtain a characteristic signal h' (t) with a high signal-to-noise ratio;
the sample imaging acquisition module is used for obtaining a frequency domain power spectrum E by Fourier transform on the characteristic signal h' (t) with the high signal-to-noise ratio, expanding the frequency domain power spectrum E to obtain sample imaging, and processing the sample imaging by utilizing a-6 dB rule to improve the imaging contrast;
And the quantitative characterization module is used for realizing the quantitative characterization of the thickness and the defects of the ceramic layer in the sample imaging after the imaging contrast is improved according to the standard sample.
Technical Field
the disclosure relates to a nondestructive testing method for an aero-engine blade, in particular to a nondestructive testing method for an aero-engine blade test piece based on a terahertz technology.
background
An aircraft engine is a highly complex and precise thermodynamic machine that directly impacts the performance, reliability, and economy of an aircraft. The aircraft engine is used as the most important power source of military equipment, is usually operated at high temperature and high pressure, has complex and harsh service environment, and is applied to flight equipment such as the aircraft engine and the like in order to improve the high temperature resistance and oxidation resistance of the aircraft engine. The thermal barrier coating is generally a three-layer structure, which comprises a ceramic layer for heat insulation, a bonding layer for transition bonding and oxidation resistance, and a substrate for bearing mechanical load from top to bottom. Because the thermal barrier coating part processing technology is complicated, the precision requirement is higher and the service environment is complicated and changeable, in the thermal barrier coating manufacturing and service process, the ceramic layer thickness inequality can exist inevitably and lead to the processing service defect, and then produce various failure modes, wherein, the most important failure mode is the spalling of ceramic layer, leads to the reason of failing to lie in: the evolution and the expansion of micro defects (such as longitudinal cracks, holes and the like) formed in the processing and service processes, the uneven thickness of the ceramic layer and the existence of the processing service defects influence the service performance of the thermal barrier coating, limit the application of the thermal barrier coating on the aeroengine and reduce the safety performance of the aeroengine.
Aiming at the problems of uneven coating thickness of the existing thermal barrier coating ceramic and complexity and diversity of defects, the traditional nondestructive detection means such as ultrasonic detection, X-ray detection, magnetic powder detection and the like has the advantages of single detection mode, low detection precision and reliability, easy defect omission and false detection, and difficulty in meeting the service requirement of the aeroengine on the defect detection precision under the complex working condition.
the terahertz technology is gradually applied to the field of nondestructive testing as a novel technology, can be used for spectrum testing of most nonpolar substances due to good transient property and strong penetrability of terahertz waves, has good time resolution, and can realize the acquisition of thickness and defect information of a sample by detecting terahertz spectrum which is reflected or transmitted from a sample interface and carries amplitude and phase information of the sample. At present, the terahertz detection technology is widely applied to nondestructive detection of ceramic matrix composite materials and other composite materials.
therefore, the novel nondestructive testing technology, namely the terahertz spectrum technology, is provided, the high-precision positioning quantitative detection of the thickness of the thermal barrier coating ceramic layer and the defects of internal cracks and holes is realized, and the method has important significance for the high-precision processing of the thermal barrier coating and the reliability evaluation of the component with the thermal barrier coating.
Disclosure of Invention
Aiming at the problems of low detection precision and low imaging resolution of the thickness and the internal defects of the ceramic layer of the thermal barrier coating in the prior art, the invention aims to provide a terahertz technology-based nondestructive detection method for an aircraft engine blade test piece, which combines signal processing and image processing methods such as wavelet transformation and the like to realize high-precision detection of the thickness and the internal tiny defects of the ceramic layer of the thermal barrier coating.
To achieve the above object, the technical solution of the present disclosure is described as follows:
A nondestructive testing method for an aero-engine blade test piece based on a terahertz technology comprises the following steps:
s100: carrying out nondestructive detection on a sample by utilizing a terahertz original signal i (t) through point-by-point scanning to obtain a terahertz echo detection signal r (t) with a low signal-to-noise ratio;
s200: carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample, and carrying out frequency domain deconvolution and stationary wavelet denoising processing on the frequency domain information of the sample to obtain a characteristic signal h' (t) with the high signal-to-noise ratio;
s300: obtaining a frequency domain power spectrum E by Fourier transform on the characteristic signal h' (t) with high signal-to-noise ratio, expanding the frequency domain power spectrum E to obtain sample imaging, and processing the sample imaging by utilizing a-6 dB rule to improve imaging contrast;
S400: and quantitatively characterizing the thickness and the defects of the ceramic layer in the sample image after the imaging contrast is improved according to the standard sample.
Preferably, the step S200 includes the steps of:
S201: carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample;
S202: filtering the frequency domain information of the sample by using a frequency domain deconvolution method and selecting a Hanning window function to obtain a terahertz pulse response signal h (t) of the sample;
s203: carrying out 4-level wavelet decomposition on the terahertz impulse response signal h (t) of the sample to obtain wavelet coefficients;
S204: and comparing the wavelet coefficient with a wavelet coefficient threshold, eliminating the wavelet coefficient smaller than the wavelet coefficient threshold, and reconstructing the wavelet coefficient larger than the wavelet coefficient threshold to obtain a sample characteristic signal h' (t) with a high signal-to-noise ratio.
Preferably, in step S204, when the absolute value of the wavelet coefficient is smaller than the wavelet coefficient threshold, the wavelet coefficient is regarded as a noise signal; when the absolute value of the wavelet coefficient is greater than the wavelet coefficient threshold, the wavelet coefficient is considered as a significant feature signal.
Preferably, the step S300 includes the steps of:
s301: obtaining a spectral density s (f) by Fourier transform on the characteristic signal h' (t) with high signal-to-noise ratio;
s302: obtaining a spectrum power spectrum E of the characteristic signal h' (t) with the high signal-to-noise ratio according to a Pasteval theorem;
S303: expanding the frequency domain power spectrum E to obtain sample imaging;
S304: the imaging contrast is improved by processing the sample image using the-6 dB rule.
Preferably, the expression of the spectrum power spectrum E of the characteristic signal h' (t) with high signal-to-noise ratio is:
where f is the frequency in the frequency domain and t is the time variable in the time domain.
preferably, in step S304, the step of improving the imaging contrast by processing the sample by using the-6 dB rule is to: and extracting the maximum value of the gray value of each image in the sample imaging, and setting the pixel points of which the gray values are more than half of the maximum value of the gray values in each image as red.
preferably, in step S400, the standard sample includes: reference sample, ceramic layer defect-free sample, ceramic layer irregular longitudinal crack sample and ceramic layer longitudinal hole sample.
Preferably, the step S400 includes the steps of:
s401: determining the optical refractive index of the sample ceramic layer, and obtaining the thickness of the sample ceramic layer according to the optical refractive index of the sample ceramic layer;
s402: according to the time difference delta t of the time domain corresponding to the upper and lower interfaces of the extracted sample defect1depth information characterizing the sample defects; and characterizing the transverse dimension information of the sample defect according to the extracted edge information of the sample defect.
preferably, in step S401, the thickness of the sample ceramic layer is:
wherein, c represents a constant value,Expressing the optical refractive index of the ceramic layer of the sample, delta t expressing the absolute value of the time difference corresponding to the maximum amplitude of the h ' (t) signal of any 5 pixels of the sample without the ceramic layer and the second maximum amplitude thereof, and tau expressing the absolute value of the time difference corresponding to the maximum amplitude of the h ' (t) signal of any 5 pixels of the sample without the ceramic layer and the maximum amplitude of the h ' (t) signal of 5 pixels corresponding to the reference sample;
in step S402, the depth information of the sample defect is:
wherein c represents a constant, Δ t1Representing the time difference of the corresponding time domains of the upper and lower interfaces of the crack and the hole defect of the sample;
the transverse dimension information of the sample defects is as follows:
D＝Δx×N
where D denotes the defect lateral diameter and Δ x denotes the sampling interval.
The utility model also provides an aeroengine blade test piece nondestructive test device based on terahertz technique now, include:
the echo detection signal acquisition module is used for carrying out nondestructive detection on the sample by utilizing the terahertz original signal i (t) through point-by-point scanning to obtain a terahertz echo detection signal r (t) with a low signal-to-noise ratio;
the characteristic signal acquisition module is used for carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample, and carrying out frequency domain deconvolution and stationary wavelet denoising processing on the frequency domain information of the sample to obtain a characteristic signal h' (t) with a high signal-to-noise ratio;
the sample imaging acquisition module is used for obtaining a frequency domain power spectrum E by Fourier transform on the characteristic signal h' (t) with the high signal-to-noise ratio, expanding the frequency domain power spectrum E to obtain sample imaging, and processing the sample imaging by utilizing a-6 dB rule to improve the imaging contrast;
and the quantitative characterization module is used for realizing the quantitative characterization of the thickness and the defects of the ceramic layer in the sample imaging after the imaging contrast is improved according to the standard sample.
compared with the prior art, the beneficial effect that this disclosure brought does: the method comprises the steps of detecting a sample by utilizing terahertz to obtain an echo signal carrying sample information, improving the signal-to-noise ratio and the imaging resolution of a detection signal by combining a frequency domain deconvolution, a signal processing mode of stable wavelet noise reduction, frequency domain power spectrum imaging and a-6 dB image processing mode, realizing quantitative characterization of the thickness of a coating layer and internal tiny defects of a multilayer structure, and overcoming the problem of low detection precision of the traditional nondestructive detection technology.
drawings
FIG. 1 is a flow chart of a nondestructive testing method for an aero-engine blade test piece based on terahertz technology provided by the disclosure;
Fig. 2(a) -2 (d) are schematic diagrams of sample coupons provided by the present disclosure, wherein fig. 2(a) represents a reference coupon; FIG. 2(b) shows a defect-free specimen; FIG. 2(c) shows a specimen containing irregular cracks; FIG. 2(d) shows a sample containing pores;
FIG. 3 is a schematic structural diagram of an aeroengine blade test piece nondestructive testing device based on terahertz technology provided by the present disclosure.
Detailed Description
The technical solution of the present disclosure is described in detail below with reference to the accompanying drawings and embodiments.
As shown in fig. 1, a nondestructive testing method for an aircraft engine blade test piece based on a terahertz technology includes the following steps:
s100: carrying out nondestructive detection on a sample by utilizing a terahertz signal to obtain a terahertz original detection signal with a low signal-to-noise ratio;
S200: carrying out Fourier transform on the terahertz original detection signal with the low signal-to-noise ratio to obtain frequency domain information of a sample, and carrying out frequency domain deconvolution and stationary wavelet denoising on the frequency domain information of the sample to obtain a characteristic signal with the high signal-to-noise ratio;
S300: obtaining a frequency domain power spectrum by Fourier transform of the characteristic signal with high signal-to-noise ratio, expanding the frequency domain power spectrum to obtain sample imaging, and processing the sample imaging by utilizing a-6 dB rule to improve imaging contrast;
s400: and realizing the quantitative characterization of the thickness and the defects of the ceramic layer in the sample imaging after the imaging contrast is improved according to the standard sample.
The embodiment forms a complete technical scheme of the disclosure, and compared with the prior art, the embodiment adopts the terahertz time-domain spectroscopy technology to perform nondestructive detection on a sample, improves the signal-to-noise ratio and the imaging resolution of a detection signal by obtaining an echo signal carrying sample information and combining a frequency domain deconvolution, a signal processing mode of stable wavelet denoising, frequency domain power spectrum imaging and a-6 dB image processing mode, and realizes quantitative characterization of the thickness of a coating layer and internal tiny defects of a multilayer structure, thereby overcoming the problem of low detection precision in the traditional nondestructive detection technology.
in another embodiment, the step S200 includes the steps of:
s201: carrying out Fourier transform on the terahertz original detection signal with the low signal-to-noise ratio to obtain frequency domain information of the sample;
s202: filtering the frequency domain information of the sample by using a frequency domain deconvolution method and selecting a Hanning window function to obtain a terahertz pulse response signal of the sample;
s203: carrying out 4-level wavelet decomposition on the terahertz pulse response signal of the sample to obtain a wavelet coefficient;
S204: and comparing the wavelet coefficient with a wavelet coefficient threshold, eliminating the wavelet coefficient smaller than the wavelet coefficient threshold, and reconstructing the wavelet coefficient larger than the wavelet coefficient threshold to obtain a sample characteristic signal with high signal-to-noise ratio.
in another embodiment, in step S204, when the absolute value of the wavelet coefficient is smaller than the wavelet coefficient threshold, the wavelet coefficient is regarded as a noise signal; when the absolute value of the wavelet coefficient is greater than the wavelet coefficient threshold, the wavelet coefficient is considered as a significant feature signal.
in another embodiment, the step S300 includes the steps of:
S301: obtaining a spectral density s (f) by Fourier transform on the characteristic signal h' (t) with high signal-to-noise ratio;
s302: obtaining a spectrum power spectrum E of the characteristic signal h' (t) with the high signal-to-noise ratio according to a Pasteval theorem;
s303: expanding the frequency domain power spectrum E to obtain sample imaging;
s304: the imaging contrast is improved by processing the sample image using the-6 dB rule.
In another embodiment, the expression of the spectral power spectrum E of the characteristic signal h' (t) with high snr is:
Where f is the frequency in the frequency domain and t is the time variable in the time domain.
In another embodiment, in the step S304, the improving the imaging contrast by processing the sample imaging with the-6 dB rule is: and extracting the maximum value of the gray value of each image in the sample imaging, and setting the pixel points of which the gray values are more than half of the maximum value of the gray values in each image as red.
In the embodiment, the pixel points with the gray value larger than half of the maximum gray value in each image are set to be red, so that the contrast between the defect and the background can be improved, the information of the layered interface and the internal cracks and holes of the sample can be visually seen, and the subsequent quantitative characterization of the defect is facilitated.
in another embodiment, in the step S400, the standard sample includes: reference sample, ceramic layer defect-free sample, ceramic layer irregular longitudinal crack sample and ceramic layer longitudinal hole sample.
In this example, FIG. 2(a) is a reference sample, FIG. 2(b) is a defect-free ceramic layer sample, FIG. 2(c) is a sample in which the ceramic layer contains irregular longitudinal cracks, and FIG. 2(d) is a sample in which the ceramic layer contains longitudinal holes.
Specifically, in this embodiment, FB-PVD (electron beam physical vapor deposition) process is used to prepare samples, high temperature nickel-based alloy is used as the sample substrate, MCrAlY alloy is used as the bonding layer, the thickness is about 120 μm, and the ceramic surface layer is Y with a mass fraction of 8%2O3Partially stabilized ZrO2thickness about 400 μm, prepared sample size 10cmx10cm, 4 species in total: the first one is a double-layer structure with only a surface-smooth high-temperature nickel-based alloy substrate and a bonding layer, and the double-layer structure is used as a reference sample; the second is a thermal barrier coating three-layer structure, and the ceramic layer is a defect-free sample with the thickness of 400 mu m; the third is a three-layer structure of the thermal barrier coating, the thickness of the ceramic layer is 400 mu m, and the interior of the ceramic layer has irregular longitudinal crackspattern; the fourth is a three-layer structure of the thermal barrier coating, the thickness of the ceramic layer is still 400 mu m, longitudinal holes are arranged in the ceramic layer, the diameter of each hole is 2mm, and the depth of each hole is 80 mu m.
In another embodiment, the step S400 includes the steps of:
S401: determining the optical refractive index of the sample ceramic layer, and obtaining the thickness of the sample ceramic layer according to the optical refractive index of the sample ceramic layer;
S402: according to the time difference delta t of the time domain corresponding to the upper and lower interfaces of the extracted sample defect1depth information characterizing the sample defects; and characterizing the transverse dimension information of the sample defect according to the extracted edge information of the sample defect.
in the specific embodiment of step S401, the absolute value Δ t of the time difference between the maximum amplitude of the h ' (t) signal of any 5 pixels of the ceramic layer defect-free sample and the second maximum amplitude, and the absolute value τ of the time difference between the maximum amplitude of the h ' (t) signal of any 5 pixels of the ceramic layer defect-free sample and the maximum amplitude of the h ' (t) signal of 5 pixels of the reference sample are extracted to obtain the optical refractive index of the sample ceramic layerAnd further obtaining the thickness of the ceramic layer according to a flight time method
in the specific embodiment of step S402, because the upper and lower interfaces of the crack and hole defect of the sample may cause terahertz reflection, causing a peak value to appear on the time domain waveform of the echo signal, extracting the time difference in the time domain corresponding to the upper and lower interfaces of the crack and hole defect of the sample from the processed time domain signal h' (t), and recording the time difference as Δ t1Thereby enabling the depth information of the crack and hole defects of the sample to be characterized, i.e.Extracting the edge information of the defect from the frequency domain image by combining the image processing method, and determining the edge straightness of the defectBy the maximum pixel number N, the transverse size information D of the defect can be estimated to be delta x multiplied by N, D is the transverse diameter of the defect, and delta x is the sampling interval, so that the quantitative characterization of the ceramic layer defect can be realized.
in another embodiment, as shown in fig. 3, the present disclosure further provides a nondestructive testing apparatus for an aircraft engine blade test piece based on terahertz technology, including:
the echo detection signal acquisition module is used for carrying out nondestructive detection on the sample by utilizing the terahertz original signal i (t) through point-by-point scanning to obtain a terahertz echo detection signal r (t) with a low signal-to-noise ratio;
The characteristic signal acquisition module is used for carrying out Fourier transform on the terahertz echo detection signal r (t) with the low signal-to-noise ratio to obtain frequency domain information of a sample, and carrying out frequency domain deconvolution and stationary wavelet denoising processing on the frequency domain information of the sample to obtain a characteristic signal h' (t) with a high signal-to-noise ratio;
The sample imaging acquisition module is used for obtaining a frequency domain power spectrum E by Fourier transform on the characteristic signal h' (t) with the high signal-to-noise ratio, expanding the frequency domain power spectrum E to obtain sample imaging, and processing the sample imaging by utilizing a-6 dB rule to improve the imaging contrast;
And the quantitative characterization module is used for realizing the quantitative characterization of the thickness and the defects of the ceramic layer in the sample imaging after the imaging contrast is improved according to the standard sample.
while the embodiments of the disclosure have been described above in connection with the drawings, the disclosure is not limited to the specific embodiments and applications described above, which are intended to be illustrative, instructive, and not restrictive. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto and changes may be made without departing from the scope of the disclosure as set forth in the claims that follow.