CN113219053B - Sensitivity matrix ultrasonic inversion method for integrity parameters of coating surface interface - Google Patents
Sensitivity matrix ultrasonic inversion method for integrity parameters of coating surface interface Download PDFInfo
- Publication number
- CN113219053B CN113219053B CN202110429231.4A CN202110429231A CN113219053B CN 113219053 B CN113219053 B CN 113219053B CN 202110429231 A CN202110429231 A CN 202110429231A CN 113219053 B CN113219053 B CN 113219053B
- Authority
- CN
- China
- Prior art keywords
- ultrasonic
- parameter
- coating surface
- sensitivity matrix
- surface interface
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
- G01N29/4409—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison
- G01N29/4418—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison with a model, e.g. best-fit, regression analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/02—Indexing codes associated with the analysed material
- G01N2291/023—Solids
- G01N2291/0237—Thin materials, e.g. paper, membranes, thin films
Landscapes
- Physics & Mathematics (AREA)
- Biochemistry (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Acoustics & Sound (AREA)
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
A sensitivity matrix ultrasonic inversion method of coating surface interface integrity parameters belongs to the technical field of nondestructive testing. The method aims at the requirements of multi-parameter high-precision detection of surface interface integrity such as coating defects, geometry, structure and performance, model regularization, data regularization and sensitivity matrix analysis are combined based on a propagation mechanism of ultrasonic waves in a coating multi-interface structure, and a material-oriented characteristic detection signal regularization strategy is provided. The model regularization adopts analysis, numerical simulation and machine learning to realize the theoretical modeling of the ultrasonic response signals. Data regularization functionally associates ultrasonic detection signals with a theoretical model. The sensitivity matrix analysis converts an ill-posed nonlinear inverse problem into a well-defined linear inverse problem, and a coating surface interface integrity multi-parameter ultrasonic inversion method based on the sensitivity matrix is developed. The detection method overcomes the defects of the traditional trial and error method, and can promote the qualitative, semi-quantitative to accurate quantitative jump of the nondestructive detection technology.
Description
Technical Field
The invention relates to a sensitivity matrix ultrasonic inversion method of coating surface interface integrity parameters, belonging to the technical field of ultrasonic nondestructive testing of materials.
Background
The thermal barrier, sealing, wave absorbing and other functional coatings can obviously improve the comprehensive performances of heat insulation, sealing, stealth and the like of the parts, and have wide application in the field of aviation. Parameters such as thickness, surface interface morphology, organization structure, sound velocity, density and elastic modulus of an aviation functional coating (hereinafter referred to as a coating) are key indexes for controlling surface interface integrity of parts. The coating has the geometrical and material coupling characteristics of anisotropy, non-homogeneity, ultrathin multi-interface and the like, so that the signal response mechanism of ultrasonic detection is complex, quantitative description is difficult, signal acquisition and analysis are limited, and the ultrasonic detection technology based on the traditional trial-and-error method is difficult to be suitable for the requirement of simultaneous quantitative and nondestructive characterization of multiple unknown parameters of the coating. The research on the nondestructive testing principle of the integrity parameters of the coating surface interface and the application technology thereof has important significance for exerting excellent comprehensive performance.
The nondestructive detection of materials is a typical inverse problem, and as the aviation functional coating often has the characteristics of multiple interfaces, heterogeneity, elastic anisotropy and the like, the ultrasonic detection problem has multiple unknown parameters, nonlinearity and inadequacy, and the multi-parameter inversion has obvious advantages and flexibility in solving the detection problem and has attracted wide attention. According to different matrix or function representation modes for constructing an ultrasonic propagation theoretical model, the inverse problem solving is mainly divided into the following steps: a regularization method oriented to a matrix equation and a random optimization method oriented to a function. The regularization method is to approximate the solution of the original problem by the solution of a family of fitness problems that are "adjacent" to the original fitness problem. Methods including Tikhonov regularization, iterative regularization, singular value decomposition, etc. have been developed to obtain unique, stable solutions to the inverse problem. Such as Bustillo et al, construct a transmission matrix for ultrasound waves in a thin layer structure byl 1And the norm constrains the solving process, reduces the complexity of the inversion solution, and finally realizes the simultaneous inversion of the thickness and the sound velocity when the echo aliasing of the aluminum thin layer interface reaches 65%. Aiming at the complex ultrasonic detection problem of multivariable and nonlinear, a theoretical model is difficult to be analyzed by a matrix equation, and is constructed by means of a hidden function form, and a random optimization method is a main mode for solving the inverse problem. For example, Schneider et al adopts laser ultrasonic technology to excite surface wave frequency dispersion curvec(f) The ZrO spraying of the plasma is realized by combining a least square function optimization method2The elastic modulus of the coating is inverted. The result shows that the inversion elastic modulus is 11.2 GPa-46 GPa, which is far smaller than 241 GPa of a compact block, and indicates that the inversion uncertainty of the elastic modulus caused by the preset values of the density of the coating and the matrix, the Poisson ratio and the thickness of the coating is +/-12.5%. Ma et al propose an inversion technique for simultaneously representing roughness, sound velocity and thickness of an interface in a coating by adopting an ultrasonic full time domain signal phase spectrum, and realize the purpose by adopting a phase spectrum function and combining a cross-correlation optimization methodThe roughness of the inner interface of the coating, the sound velocity and the thickness are inverted at the same time, the relative error between the inversion result and the true value is less than 10.9%, and meanwhile, the fact that the correlation between the phase spectrum function and the coating density is weak, the density is difficult to invert accurately is pointed out, and other methods are required to be adopted for independent determination in advance.
The method constructs theoretical models of parameters such as thickness, roughness, sound velocity, density, attenuation coefficient and/or elastic modulus of the thin-layer structure acted by ultrasonic waves, and solves a plurality of unknown parameters through a simultaneous matrix equation or a function formula of experimental data and the theoretical models. However, the correlation difference and the nonlinearity degree between the theoretical model and the surface interface integrity parameter can cause the inversion solution to be non-unique and unstable, and the mismatching of the degree of freedom of the theoretical model and the unknown parameter to be solved can further increase the discomfort of the inverse problem. Theoretical models constructed in the work of Bustillo, Schneider, Ma and the like all need to preset partial unknown table interface integrity parameters according to experience to improve uniqueness and stability of an inversion solution, have certain trial and error performance and blindness, and the inversion process may fall into a local optimal solution.
Disclosure of Invention
The invention aims to provide a sensitivity matrix ultrasonic inversion method of coating surface interface integrity parameters, which overcomes the problem that the traditional experience-based trial and error method solves the problem that the coating ultrasonic detection problem is often nonlinear, not unique and not suitable, develops a material-oriented characteristic detection signal regularization strategy by combining model regularization, data regularization and sensitivity matrix analysis, converts the non-linear inverse problem which is not suitable into a linear inverse problem, provides a coating surface interface integrity multi-parameter ultrasonic detection inversion method based on a sensitivity matrix, has high quantitative accuracy and wider application range, can be popularized and applied to other nondestructive detection technologies, and has greater economic benefit.
The technical scheme adopted by the invention for solving the technical problems is as follows: a sensitivity matrix ultrasonic inversion method of coating surface interface integrity parameters expresses an ultrasonic detection system by a mathematical function as follows:
wherein, p is the coating surface interface integrity parameter of the part, including the flaw parameter d such as crack, stratification, etc., the geometric parameter g such as thickness, roughness, curvature, etc., the microstructure parameter s such as porosity, second phase particle characteristic, etc., and the characteristic parameter c such as sound velocity, attenuation coefficient, elastic modulus, density, etc., M (p) is a coefficient matrix, which is a theoretical model describing the ultrasonic response of the material under the action of the additional ultrasonic excitation x, and includes the wave equation of the ultrasonic wave and the action mechanisms such as the scattering attenuation, frequency dispersion, etc. caused by the reflection, transmission and encountering the phase interface or the flaw; according to the action mechanism of ultrasonic waves in a multi-interface structure of the coating, model regularization, data regularization and sensitivity matrix analysis are combined, and a characteristic detection signal regularization strategy facing materials is provided. The model regularization is to analyze the result of microstructure of the material, construct the theoretical model that can accurately describe the ultrasonic response of factors such as material defect, geometry, structure, performance under the excitation x of the additional ultrasonic through analyzing, numerical simulation, machine learning, etc., also call forward to preserve the model f (d, g, s, c); the data regularization is performed by signal and image processing methods (LOperator) decouples the experimentally obtained ultrasonic output signal y into characteristic detection signals weakly correlated with the detection system response S, noise N, etcLy(Lx)-1To ensureLy(Lx)-1Weakly associated with the applied ultrasonic excitation x, the detection system S, the noise response N, | ∂ | (Ly(Lx)-1) The/∂ x | ≈ 0; the sensitivity matrix analysis is based on the forward preset model f (d, g, s, c) to identify and preferably strongly correlate the characteristic detection signal | ∂ (c) with the interface integrity parameter d, g, s, c of the table to be solvedLf(d, g, s, c)/∂p|>δThreshold valueδThe method is determined by the precision and accuracy of the whole detection system, and comprises the following specific steps:
1. model regularization: constructing a theoretical model f (d, g, s, c) which causes response when ultrasonic waves act on a coating material, accurately describing mechanisms such as reflection, scattering, frequency dispersion and the like of the ultrasonic waves in a coating structure, and constructing the theoretical model by adopting methods such as analysis, numerical simulation, machine learning and the like;
2. data regularization: the ultrasonic output signal y is subjected to signal analysis techniques such as Fourier transform, wavelet transform, normalization processing and the likeLTransform processing to obtain feature detection signalLy(Lx)-1And equivalent relation with the transformed theoretical model F (d, g, s, c), and the processing procedure is described as follows:
in the formula (I), the compound is shown in the specification,Lis an operator for processing the ultrasonic output signal, F (d, g, s, c) is F (d, g, s, c)LTransformed, processed feature detection signalLy(Lx)-1The integrity parameter p of the coating surface to be solved has non-uniform correlation with the detection system S and the noise N, the correlation of the integrity parameter p of the coating surface to be solved is larger, and the correlation of the integrity parameter p of the coating surface to be solved is smaller;
3. and (3) sensitivity matrix analysis: sensitivity matrix analysis converts a non-linear inverse problem described by an unsolvable implicit function into a linear inverse problem represented by an easily solvable sensitivity matrix, and a characteristic detection signal | ∂ (a) is identified and preferably strongly correlated with an interface integrity parameter of a table to be solved based on the sensitivity matrixLf(d, g, s, c)/∂p|>δThe suitability for solving the inverse problem is improved; detecting signals based on theoretical model F (d, g, s, c) and featuresLy(Lx)-1The method for solving the inverse problem of ultrasonic detection based on the sensitivity matrix is provided, and the partial derivatives on the two sides of the formula 2 are converted into:
whereinkDetection signal representing characteristicsLy(Lx)-1The vector dimension of (a) is,nrepresenting the number of the integrity parameters p of the interface of the table to be solved, SF-pPresetting a model for a forward directionL(p) a sensitivity matrix for the coating surface interface integrity parameter p to be solved:
4. sensitivity matrix based inversion: optimization of | ∂ by sensitivity matrix analysisLf(d, g, s, c)/∂p|>δ characteristic detection signal; then, presetting a group of initial values for the table interface integrity parameter to be solvedd j，g j，s j，c jInputting a forward default model F: (d j，g j，s j，c j) Calculating corresponding output response and calculating central sensitivity matrix S under current parametersj(ii) a Secondly, calculating the interface integrity parameter increment of the table to be solved aiming at the inversion algorithm corresponding to the underdetermined/positive determined/overdetermined sensitivity matrix
d j，
g j，
s j，
c jAnd update a new set of solutionsd j+1，g j+1，s j+1，c j+1(ii) a Finally, a new solution is adoptedd j+1，g j+1，s j+1，c j+1Recalculating the output response F (of the forward predictive model)d j+1，g j+1，s j+1，c j+1) And calculated j+1Andd j，g j+1andg j，s j+1ands j，c j+1andc jdeviation between, if any, ofAnd j = j +1, repeating the steps until all the deviations are within the allowable range, finishing the solution, and obtaining an accurate solution of multiple parameters of the integrity of the coating surface interface.
The invention has the advantages that: the functional coating surface interface integrity multi-parameter ultrasonic inversion method based on the sensitivity matrix combines model regularization, data regularization and sensitivity matrix analysis according to the action mechanism of ultrasonic waves in a coating multi-interface structure, and provides a material-oriented characteristic detection signal regularization strategy. The ultrasonic inversion method overcomes the problems of nonlinearity, uniqueness and unsuitability of the traditional experience-based trial and error method for solving the complex nondestructive testing problem of multiple unknown parameters, can realize multi-parameter ultrasonic quantitative detection of surface interface integrality such as coating defects, geometry, structure, performance and the like, has high quantitative accuracy and wider application range, can promote the jump of the nondestructive testing technology from traditional qualitative detection, semi-quantitative detection to accurate quantitative detection, and has greater economic benefit.
Drawings
FIG. 1 is a schematic diagram of a sensitivity matrix ultrasonic inversion method of coating surface interface integrity parameters.
Fig. 2 is a flow chart of the sensitivity matrix-based solution method of fig. 1.
FIG. 3 is a diagram of the measurement of plasma sprayed Al by water immersion ultrasonic back reflection method2O3And (4) a structural schematic diagram of the coating sound velocity.
FIG. 4 is a view of FIG. 3x 1-x 3And (3) measuring result graphs of longitudinal wave and transverse wave sound velocities of the coating under different angles of the plane.
Fig. 5 is a graph of sensitivity of longitudinal and transverse acoustic velocities to elastic constants. Wherein a is the longitudinal wave sound velocityV lSensitivity chart to elastic constant, b is transverse wave sound velocityV sSensitivity plot against elastic constant.
FIG. 6 is a graph of elastic constants based on sensitivity matrixC ijAnd (5) inverting the result graph. Wherein a is a convergence process diagram; b is a slowness map.
Detailed Description
FIGS. 1 and 2 show a schematic diagram and a flow chart of a method for ultrasonic inversion of a sensitivity matrix of coating surface interface integrity parameters. The sensitivity matrix-based functional coating surface interface integrity multi-parameter ultrasonic inversion method in the figure comprises model regularization, sensitivity matrix analysis, data regularization, sensitivity matrix-based inversion, and accurate multi-parameter solution of the functional coating surface interface integrity obtained by combining the model regularization, the data regularization, the sensitivity matrix analysis and the inversion. Plasma spraying of Al2O3The ultrasonic detection of a plurality of unknown elastic constants of the coating is taken as an example, and the application effect of the functional coating surface interface integrity multi-parameter ultrasonic inversion method based on the sensitivity matrix is illustrated. The method adopts the following measurement steps:
1. model regularization: the plasma sprayed coating has a lamellar structure, defining Al2O3The coating corresponds to the isotropic axis along the spraying directionx 3All of which comprisex 3The plane of the axis, called the anisotropic plane, being perpendicular tox 3The plane of the axis is called the isotropic plane, as in fig. 3. In the anisotropic planex 1-x 3Sound velocity and elastic constant of medium longitudinal wave and transverse waveC ijDirection of propagationθThe forward preset model in between can be resolved as:
longitudinal waves:
(5)
transverse wave:
(6)
wherein
，θIs the vector of the ultrasonic wave and the isotropic axisThe included angle between the two parts is smaller than the included angle,ρis the coating density.
2. Data regularization: plasma spraying of Al2O3The sound velocities of the coating in different directions are accurately measured by combining a water immersion ultrasonic back reflection method with a rotating device, and a sample is perpendicular to the samplex 1-x 3The axis of the plane was rotated at angular intervals of 0.5 deg., and an oscilloscope was used to record each angle of the ultrasonic waves in the coatingθDown, and used to calculate the coating sound velocity. The longitudinal wave sound velocity of the stainless steel substrate is 5889 m/s and is perpendicular to Al and measured by an ultrasonic transit time method2O3The longitudinal wave speed 7412 m/s and the transverse wave speed 2703 m/s in the coating direction. The substrate density measured by Archimedes drainage method was 7910 kg/m3，Al2O3The density of the coating is 3530 kg/m3. The thickness of the coating and the substrate observed by an optical microscope were 0.665 mm and 1.585 mm, respectively. FIG. 4 shows Al2O3Is coated onx 1-x 3As a result of sound velocity measurement under different angles of a plane (an anisotropic surface), longitudinal waves mainly appear between 0 and 7.5 degrees, and transverse waves mainly appear between 16 and 21 degrees.
3. And (3) sensitivity matrix analysis: and (3) converting the nonlinear and implicit function relations of the sound velocity of the longitudinal wave and the transverse wave and the elastic constant into an inverse problem represented by a linear matrix easy to solve through a sensitivity matrix according to the results of the step (1) and the step (2). The sensitivity of compressional and shear acoustic velocities to 4 unknown elastic constants can be expressed as:
first, the elastic constant is presetC 11=15 GPa、C 13=5 GPa、C 33=20 GPa、C 44=5 GPa, the longitudinal wave sound velocity and the transverse wave sound velocity at intervals of 0.5 ° between 0-7.5 ° and between 16-21 ° are calculated by inputting equation 5 and equation 6, respectively. Subsequently, a sensitivity matrix centered on the current elastic constant was calculated, and the result is shown in fig. 5. The observation shows that the longitudinal wave sound velocity calculated by the current elastic constant valueV lFor is toC 33Has the greatest sensitivity toC 11The sensitivity of (c) is minimal; velocity of transverse waveV sTo pairC 11AndC 33has greater sensitivity toC 44Has the minimum sensitivity toC 13Is sensitive in the negative direction. Due to the velocity of longitudinal wavesV lTo pairC 11、C 13AndC 44all are not very sensitive, transverse wave sound velocityV sTo pairC 44And the method is not sensitive, and a unique and stable solution of 4 unknown elastic constants is difficult to obtain simultaneously by singly adopting longitudinal wave or transverse wave sound velocity.
4. Sensitivity matrix based inversion: according to the sensitivity matrix analysis result of the step 3, selecting and usingV lAndV stogether as a feature detection signal inversion elastic constant. Fig. 6(a) shows the convergence process of the forward preset model output value and the elastic constant to be solved in the iterative process, and it can be seen that the relative errors of the inversion deviations from the first iteration to the 5 th iteration are all larger than 241%, and the relative errors from the first iteration to the 5 th iteration are all smaller than 0.1%, which indicates that the sensitivity matrix-based inversion method has the characteristic of faster convergence towards the global optimal solution. Elastic constant of inversion of 5 th iterationC 11=158.9 GPa、C 13=44.1 GPa、C 33=244.1 GPa、C 44And (4) inputting the forward preset model by the =31.6 GPa, and drawing an inverted longitudinal wave and transverse wave slowness spectrum, which is shown in figure 6 (b). Compared with the experimental result, the longitudinal wave sound velocity based on the sensitivity matrix inversionV lVelocity of transverse waveV sThe method has good consistency with the experimentally measured sound velocity, the maximum relative error is not more than 1.2 percent, and the transverse wave sound velocity in the direction vertical to the coating is 2641 m/s through inversion calculation, and the relative error with the transverse wave sound velocity 2703 m/s directly measured is-2.3 percent.
By adopting the technical scheme, the problems of nonlinearity, uniqueness and unsuitability of the traditional ultrasonic detection of the integrity parameters of the coating surface interface are solved. According to the method, model regularization, data regularization and sensitivity matrix analysis are combined according to the action mechanism of ultrasonic waves in a multi-interface structure of the coating, a material-oriented feature detection signal regularization strategy is provided, the non-linear inverse problem which is not stable and difficult to solve is converted into the linear inverse problem which is stable and easy to solve, the uniqueness and the stability of an inversion solution are improved according to the high-sensitivity relation of feature detection signals to surface interface integrity parameters, and the ultrasonic detection inversion method of the surface interface integrity parameters of the coating based on the sensitivity matrix is developed. The novel ultrasonic detection method provides a new solution idea and way for the complex nondestructive detection problem of multiple unknown parameters which is difficult to solve by the traditional experience-based trial and error method, and can promote the traditional qualitative, semi-quantitative and accurate quantitative jump of the nondestructive detection technology.
Claims (1)
1. A sensitivity matrix ultrasonic inversion method of coating surface interface integrity parameters is characterized in that an ultrasonic detection system is expressed by a mathematical function as follows:
wherein, p is the integrity parameter of the coating surface interface, including defect parameter d, geometric parameter g, microstructure parameter s and characteristic parameter c, M (p) is a coefficient matrix, which is a theoretical model for describing the ultrasonic response of the defect parameter d, the geometric parameter g, the microstructure parameter s and the characteristic parameter c under the action of the additional ultrasonic excitation x, including the wave equation of the ultrasonic wave and the scattering attenuation and dispersion mechanism caused by the reflection and transmission when the ultrasonic wave meets the phase interface or the defect, and y is the ultrasonic output signal obtained by the ultrasonic experiment;
according to the action mechanism of ultrasonic waves in the coating surface interface structure, the integrity parameters of the coating surface interface are inverted by adopting the following steps:
a. model regularization: constructing a theoretical model f (d, g, s, c) capable of accurately describing the ultrasonic response of a defect parameter d, a geometric parameter g, a microstructure parameter s and a characteristic parameter c of a material under the additional ultrasonic excitation x by analyzing, numerical simulation and machine learning for the analysis result of the microstructure of the material;
b. data regularization: to ultrasonic output signaly is carried outLTransform processing to obtain feature detection signalLy(Lx)-1Equivalence with the transformed theoretical model F (d, g, s, c):
in the formula (I), the compound is shown in the specification,Lis an operator for processing ultrasonic output signals by adopting an image processing method, Fourier transform, wavelet transform and normalization processing signal analysis technology, and F (d, g, s, c) is F (d, g, s, c)LTransformed, processed feature detection signalLy(Lx)-1Strongly related to the integrity parameter p of the coating surface to be solved, weakly related to the applied ultrasonic excitation x, the detection system S and the noise N, | ∂ [ (Ly(Lx)-1)/∂x|≈0；
c. And (3) sensitivity matrix analysis: detecting signals based on the transformed theoretical model F (d, g, s, c) and featuresLy(Lx)-1The partial derivatives at two sides of the formula (2) are solved to construct a sensitivity matrix:
wherein the content of the first and second substances,kdetecting a signal for a featureLy(Lx)-1The vector dimension of (a) is,nfor the number of coating surface integrity parameters p to be determined, SF-pFor transformed theoretical modelL(p) a sensitivity matrix for the coating surface interface integrity parameter p to be solved:
| ∂ (based on the sensitivity matrix identification and preferably strongly correlated with the coating surface interface integrity parameter p to be determined | (Lf(d, g, s, c)/∂p|>δIs detected by the characteristic of the light source,δthe threshold value is determined by the precision and accuracy of the whole detection system;
d. sensitivity matrix based inversion: according to the characteristic detection signal which is determined in the step c and is strongly related to the integrity parameter p of the coating surface interface to be solved, presetting a group of initial values for the integrity parameter p of the coating surface interface to be solvedd j，g j，s j，c jInputting the transformed theoretical model F: (d j，g j，s j，c j) Calculating corresponding output response and calculating the central sensitivity matrix S under the current parametersj(ii) a Then, aiming at the inversion algorithm corresponding to the underdetermined/positive determined/overdetermined sensitivity matrix, calculating the increment of the integrity parameter of the coating surface interface to be solved
d j，
g j，
s j，
c jAnd update a new set of solutionsd j+1，g j+1，s j+1，c j+1(ii) a Finally, a new solution is adoptedd j+1，g j+1，s j+1，c j+1Recalculating the output response F (of the transformed theoretical model)d j+1，g j+1，s j+1，c j+1) And calculated j+1Andd j，g j+1andg j，s j+1ands j，c j+1andc jif the deviation is not in the allowable range, j = j +1, repeating the above steps until all the deviations are allowableWithin the range, the solution is finished, and an accurate solution of the coating surface interface integrity parameter is obtained.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110429231.4A CN113219053B (en) | 2021-04-21 | 2021-04-21 | Sensitivity matrix ultrasonic inversion method for integrity parameters of coating surface interface |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110429231.4A CN113219053B (en) | 2021-04-21 | 2021-04-21 | Sensitivity matrix ultrasonic inversion method for integrity parameters of coating surface interface |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113219053A CN113219053A (en) | 2021-08-06 |
| CN113219053B true CN113219053B (en) | 2022-05-13 |
Family
ID=77088171
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110429231.4A Active CN113219053B (en) | 2021-04-21 | 2021-04-21 | Sensitivity matrix ultrasonic inversion method for integrity parameters of coating surface interface |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113219053B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114018698B (en) * | 2021-10-20 | 2024-03-15 | 北京卫星制造厂有限公司 | Method for measuring and calculating intrinsic strength of composite material by using controllable processing damage |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPWO2011158711A1 (en) * | 2010-06-14 | 2013-08-19 | 新日鐵住金株式会社 | Defect determination device |
| CN103292753A (en) * | 2013-05-29 | 2013-09-11 | 大连理工大学 | Method of measuring thickness of thermal barrier coating by ultrasonic water-immersion focusing technology |
| CN105527648A (en) * | 2014-09-30 | 2016-04-27 | 中国石油化工股份有限公司 | Calculation method and system of sensitivity matrix for anisotropy parameter inversion |
| CN106017372A (en) * | 2016-05-04 | 2016-10-12 | 大连理工大学 | Ultrasonic non-destructive abrasion-resistant coating thickness and elastic modulus measuring method |
| CN107357980A (en) * | 2017-06-29 | 2017-11-17 | 中山大学 | A kind of damnification recognition method of axial functionally gradient beam |
| CN108286952A (en) * | 2017-12-13 | 2018-07-17 | 大连理工大学 | A kind of coating layer thickness, density and longitudinal wave velocity ultrasonic inversion method simultaneously |
| CN112083068A (en) * | 2020-09-10 | 2020-12-15 | 大连理工大学 | Ultrasonic nondestructive characterization method for non-uniform medium tissue uniformity |
| CN112362745A (en) * | 2020-11-02 | 2021-02-12 | 大连理工大学 | Ultrasonic measurement and inversion method for elastic constant of uniform substrate coating layer |
-
2021
- 2021-04-21 CN CN202110429231.4A patent/CN113219053B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPWO2011158711A1 (en) * | 2010-06-14 | 2013-08-19 | 新日鐵住金株式会社 | Defect determination device |
| CN103292753A (en) * | 2013-05-29 | 2013-09-11 | 大连理工大学 | Method of measuring thickness of thermal barrier coating by ultrasonic water-immersion focusing technology |
| CN105527648A (en) * | 2014-09-30 | 2016-04-27 | 中国石油化工股份有限公司 | Calculation method and system of sensitivity matrix for anisotropy parameter inversion |
| CN106017372A (en) * | 2016-05-04 | 2016-10-12 | 大连理工大学 | Ultrasonic non-destructive abrasion-resistant coating thickness and elastic modulus measuring method |
| CN107357980A (en) * | 2017-06-29 | 2017-11-17 | 中山大学 | A kind of damnification recognition method of axial functionally gradient beam |
| CN108286952A (en) * | 2017-12-13 | 2018-07-17 | 大连理工大学 | A kind of coating layer thickness, density and longitudinal wave velocity ultrasonic inversion method simultaneously |
| CN112083068A (en) * | 2020-09-10 | 2020-12-15 | 大连理工大学 | Ultrasonic nondestructive characterization method for non-uniform medium tissue uniformity |
| CN112362745A (en) * | 2020-11-02 | 2021-02-12 | 大连理工大学 | Ultrasonic measurement and inversion method for elastic constant of uniform substrate coating layer |
Non-Patent Citations (3)
| Title |
|---|
| Identification of the Velocity,Thickness, and Interfacial Roughness of Coating Using Full Time-Domain URCPS: Cross-Correlation-Based Inverse Problem;Zhiyuan Ma et al.;《ASME J Nondestructive Evaluation》;20190122;第2卷(第1期);第011008-1页-第011008-10页 * |
| Quantitative characterization of the interfacial roughness and thickness of inhomogeneous coatings based on ultrasonic reflection coefficient phase spectrum;Zhiyuan Ma et al.;《NDT ＆ E International》;20181105;第102卷;16-25 * |
| 基于声压反射系数相位谱的涂层密度和纵波声速双参数反演;高剑英等;《无损检测》;20181030;第40卷(第10期);39-44 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113219053A (en) | 2021-08-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Castaings et al. | The generation, propagation, and detection of Lamb waves in plates using air‐coupled ultrasonic transducers | |
| Zhao et al. | Simultaneous determination of the coating thickness and its longitudinal velocity by ultrasonic nondestructive method | |
| CN104034287B (en) | A kind of elastic anisotropy metallic matrix thermal barrier coating thickness ultrasonic measurement method | |
| Habibpour-Ledari et al. | Three dimensional characterization of defects by ultrasonic time-of-flight diffraction (ToFD) technique | |
| Salinas et al. | Localization algorithm for acoustic emission | |
| Chen et al. | Simultaneously measuring thickness, density, velocity and attenuation of thin layers using V (z, t) data from time-resolved acoustic microscopy | |
| CN113219053B (en) | Sensitivity matrix ultrasonic inversion method for integrity parameters of coating surface interface | |
| Lakestani et al. | Application of ultrasonic Rayleigh waves to thickness measurement of metallic coatings | |
| Masmoudi et al. | Three-dimensional hybrid model for predicting air-coupled generation of guided waves in composite material plates | |
| Ouabi et al. | A fastslam approach integrating beamforming maps for ultrasound-based robotic inspection of metal structures | |
| Deng et al. | Uniaxial stress identification of steel components based on one dimensional-CNN and ultrasonic method | |
| Song et al. | Higher-order spatial correlation coefficients of ultrasonic backscattering signals using partial cross-correlation analysis | |
| Ponschab et al. | Simulation-based characterization of mechanical parameters and thickness of homogeneous plates using guided waves | |
| Kim et al. | Modeling ultrasonic pulse-echo signals from a flat-bottom hole in immersion testing using a multi-Gaussian beam | |
| Prosser | Applications of advanced waveform-based ae techniques for testing composite materials | |
| Korkh et al. | Detection of subsurface microflaws using the high-frequency acoustic microscopy method | |
| Zhang et al. | The identification of accurate and computationally efficient arrival time pick-up method for acoustic tomography | |
| Ma et al. | Thickness determination of dual-layer coatings based on ultrasonic spectral filtering | |
| Santos et al. | Ultrasound interferometry for the evaluation of thickness and adhesion of thin layers | |
| Ma et al. | Inverse identification of geometric and acoustic parameters of inhomogeneous coatings through URCAS-based least-squares coupled cross-correlation algorithm | |
| CN112149508A (en) | Method for extracting sparse representation of weld defect echo signal features based on shear wave characteristic fusion | |
| Lin et al. | Zhiyuan Ma | |
| Xu et al. | Wave velocity measurement in the through-thickness direction of the anisotropic material plate with ultrasonic polar scan | |
| CN117029741B (en) | Method for measuring thickness, roughness and interface rigidity of coating by ultrasonic phase derivative spectrum | |
| Wen et al. | An Auto-Calibration Algorithm for Hybrid Guided Wave Tomography Based on Full Waveform Inversion |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |