A signal analysis method for nondestructive testing of creep in metallic materials

Abstract

This invention discloses a signal analysis method for nondestructive testing of creep in metallic materials. The creep testing process includes: preparation of the test object and acquisition of nondestructive testing signals; projection of basis functions and calculation of parameters on the acquired test signals; comparison of the obtained parameter values ​​with a creep evaluation curve of the same material to assess the degree of creep. The basis functions and creep evaluation curve used in this process should be obtained under specified testing conditions, and the test signals of the tested object should also be obtained under these conditions. This invention patent prepares dedicated comparative test blocks for specific materials, including high-temperature aging test blocks and creep test blocks. It uses a certain amount of test data to extract test parameters and form a set of basis functions, ensuring the specificity of the test parameters to the material and creep structure, improving test sensitivity, reducing the dispersion of test results, and ensuring the repeatability of test results.

Description

Technical Field

[0001] This invention relates to the field of industrial nondestructive testing, specifically a signal analysis method for creep nondestructive testing of metallic materials. Background Technology

[0002] Metallic materials undergo slow deformation under high-temperature, low-stress service conditions, a process known as creep. Creep can cause sudden fractures in high-temperature metallic structures and is a major cause of failure in metal structures in the petrochemical and power industries. Accurately estimating the creep state and creep life of high-temperature service metal structures remains a challenging problem in the field.

[0003] Changes in microstructure are a direct method for characterizing the creep state of metallic materials. Microstructural characteristics of materials, such as grain boundary movement, dislocation morphology and density, void distribution and density, creep void density, passivation of strengthening phases, and growth of weakening phases, all change significantly with the degree of creep. These characteristics can be used to evaluate the creep state of materials, analyze the mechanisms of creep failure, and estimate creep lifetime.

[0004] Creep life assessment methods based on microstructure can be broadly classified into two categories: one uses creep void characteristics as the evaluation standard, and the other uses precipitate characteristics. Since creep voids are a prominent feature of creep damage in metallic materials, there is considerable research on creep void-based life assessment methods, using evaluation parameters such as void area percentage, comprehensive void characteristics, lattice consistency, and void density. For the other type of method, because different materials exhibit different creep precipitates and growth mechanisms, it is difficult to find a universal characterization method for creep life assessment using precipitates. Therefore, most of these assessments are non-quantitative. A representative study is the precipitate growth model established by You Fa Yin et al. for P91 steel. This model, combined with a creep mechanics model, has preliminarily achieved the prediction of creep life for P91 steel. In addition, Le Graverend Jean-Briac et al. proposed a creep evaluation parameter that comprehensively considers creep voids and precipitates. They used this parameter to evaluate the creep life of single-crystal nickel-based superalloys and obtained good consistency. This evaluation method that integrates different microstructure characteristics is a development direction for microstructure creep life evaluation.

[0005] Currently, the main methods for observing and analyzing the creep structure of materials include optical microscopy, transmission electron microscopy, scanning electron microscopy, X-ray energy dispersive spectroscopy, laser confocal scanning microscopy, electron backscattering scanning spectroscopy, neutron scattering, replica microscopy, and atomic force microscopy. Among these, only replica microscopy and atomic force microscopy can be used for in-service testing, while the other methods have high requirements for the samples and can currently only be used under laboratory conditions.

[0006] Metamorphic imaging is a widely used creep evaluation technique. Its advantages include in-situ, direct observation of creep development and high detection accuracy (capable of observing creep cavities as small as 0.5 μm). Furthermore, due to the thin metallographic corrosion layer, it is often considered a non-destructive testing method. However, metamorphic imaging also has some limitations. Because it can only sample from the surface, the measurement of creep cavities (volume defects) often has some error, especially at weld locations (where surface cavities are almost non-existent). In addition, metamorphic imaging requires highly skilled personnel and operators. Improper operation during metallographic preparation can lead to the enlargement or reduction of creep cavities, and the interpretation of metallographic images can vary from person to person. Therefore, improving the accuracy of metamorphic imaging requires further refinement in personnel training and the development of operating procedures. Atomic force microscopy can also achieve in-situ metallographic extraction of the target. Both atomic force microscopy and replica techniques have the drawback of only being able to extract the metallographic state of the surface. In addition, due to the small area to be detected in a single test and the cost, it is difficult for both techniques to achieve 100% coverage of the target.

[0007] The use of non-destructive testing (NDT) techniques in creep life assessment is primarily due to the need for in-service or in-situ testing of high-temperature equipment, requiring high coverage. Furthermore, current major creep testing methods (replication techniques) can only detect surface damage, resulting in significant errors in detecting volumetric creep defects. Therefore, theoretically, NDT methods capable of achieving 100% coverage and volumetric detection have been extensively researched. However, no NDT method for creep assessment of metallic materials has yet been successfully applied in industrial practice. Most NDT-based creep life assessment methods are currently still in the laboratory stage, or even in the principle exploration stage.

[0008] Based on the detection energy used, non-destructive testing (NDT) techniques applied to creep detection of metallic materials can be broadly categorized into ultrasonic testing (using mechanical waves), electromagnetic testing (using electromagnetic waves), potentiometric testing (using direct current or alternating current), and radiation testing (X-rays, neutron beams, electron beams, positron beams, etc.). These also include combined methods such as electromagnetic-acoustic techniques and eddy current techniques; strain detection methods, including external dimensional measurement, digital imaging-related strain measurement, and infrared imaging strain estimation; and methods for detecting micro-damage are also typically included in the NDT category, such as hardness measurement and the aforementioned replication techniques. All of the above methods are active detection methods. NDT also includes passive detection methods, among which acoustic emission detection has recently been explored for creep monitoring. Furthermore, there are exploratory studies, such as electrochemical methods and hydrogen release methods.

[0009] Studies have shown that active nondestructive testing methods are more sensitive for creep detection of metallic materials.

[0010] Among these methods, electromagnetic testing methods (including remanence testing, magnetic coercivity testing, Barkhausen method, eddy current technology, magnetoacoustic emission technology, etc.) are considered the most sensitive to changes in the microstructure and composition of materials. The main limitation of these methods in creep detection is that the results are easily affected by non-creep factors (such as work hardening, compositional segregation, residual stress, etc.); due to the skin effect, these methods are more sensitive to near-surface creep but lack the ability to detect bulk defects.

[0011] Acoustic testing methods are the most studied methods. Acoustic parameters commonly used to characterize creep damage in metallic materials include sound attenuation coefficient, sound velocity, noise analysis, nonlinear coefficient, acoustic-ultrasonic parameters, and acoustic birefringence coefficient. The accuracy of these ultrasonic parameters has been verified in creep testing experiments on different materials, but due to various limitations, they cannot yet be applied to in-service testing.

[0012] The above non-destructive testing methods used for creep detection of metallic materials typically employ conventional parameters to describe creep, which are the same as those used for detecting macroscopic defects or other types of damage. However, due to the significant differences in creep structures among different metallic materials and the minute scale of these structures, the aforementioned parameters lack specificity and are easily affected by other factors. Consequently, the test results exhibit large dispersion and poor repeatability. Summary of the Invention

[0013] The purpose of this invention is to provide a signal analysis method for nondestructive testing of creep in metallic materials, so as to solve the problems mentioned in the background art.

[0014] To achieve the above objectives, the present invention provides the following technical solution:

[0015] A signal analysis method for nondestructive testing of creep in metallic materials is disclosed. The creep testing process includes, in sequence: preparation of the test object and acquisition of nondestructive testing signals; projection of basis functions and calculation of parameters onto the acquired test signals; comparison of the obtained parameter values ​​with a creep evaluation curve of the same material to assess the degree of creep. The basis functions and creep evaluation curve used in this process should be obtained under specified testing conditions, and the test signals of the test object should also be obtained under these conditions. The signal analysis method used in the above process is as follows:

[0016] Step (1): For the target material, a certain number of comparative test blocks are made, and high-temperature aging test and creep test are performed on them under the same detection system and detection conditions to form a non-destructive testing signal set. The signal set is then analyzed in the time domain and decomposed using statistical analysis methods to form a basis function set, which is then transformed into an orthogonal basis function set.

[0017] Step (2): Using the orthogonal basis functions and orthogonal basis function vectors as the sensitive parameter projection basis, calculate the parameter values;

[0018] Step (3): Perform sensitivity analysis on all obtained parameter values ​​for creep detection of metallic materials, determine the creep detection parameters for the target material, establish the correspondence between parameter values ​​and creep state, and form the creep evaluation curve of the target material.

[0019] As a further aspect of the present invention: the comparative test block in step (1) should be the same as the target material, the conditions of the high temperature aging test and creep test should meet the relevant standard requirements, the creep and high temperature aging test time of the test block should cover the evaluation interval, and the time points should be no less than 5, and the temperature and time conditions of the high temperature aging test should be the same as those of the creep test.

[0020] As a further aspect of the present invention: in step (1), data is collected on the prepared comparison test block using acoustic and / or acousto-optic methods. The number of data collections for a single test block is not less than 5. When using the same method to test different test blocks, the testing conditions should be kept stable.

[0021] As a further aspect of the present invention: in step (2), the collected acoustic detection signals or acousto-optic detection signals are organized into a data set, and the time-domain basis functions of the data set are extracted using the time-domain statistical analysis method and transformed into an orthogonal basis function set.

[0022] As a further embodiment of the present invention: step (3) includes 1) projecting the detection signal onto an orthogonal basis function set, 2) comparing the detection sensitivity of different basis function projection values ​​to high-temperature aging structure and creep structure, 3) selecting parameters sensitive to creep structure as sensitive parameters for creep detection of target material, 4) creating a curve showing the correspondence between parameter values ​​and creep degree, and 5) completing the selection of creep detection parameters for target material.

[0023] Application of creep detection parameters: Keep the detection system unchanged and the detection conditions basically stable, detect the object, obtain the detection signal, project the signal onto the selected basis function, calculate the projection value, compare the projection value with the evaluation curve, and evaluate the creep state of the object.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] ① This invention patent produces comparative test blocks for specific materials, including high-temperature aging test blocks and creep test blocks. It extracts test parameters using actual test data, ensuring that the test parameters are specific to the material and the creep structure, improving the test sensitivity, reducing the dispersion of the test results, and ensuring the repeatability of the test results.

[0026] ② By utilizing the signal processing method proposed in this invention, combined with a detection device that can provide stable detection conditions, it is expected to provide high-precision creep detection and evaluation of metallic materials.

[0027] ③ This invention proposes a method for extracting sensitive parameters for nondestructive testing of creep in metallic materials using time-domain statistical signal analysis. By eliminating factors affecting high-temperature aging structures, the detection sensitivity for creep structures is improved. Detailed Implementation

[0028] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0029] Example 1

[0030] A signal analysis method for nondestructive testing of creep in metallic materials is disclosed. The creep testing process includes, in sequence: preparation of the test object and acquisition of nondestructive testing signals; projection of the acquired test signals onto basis functions and calculation of parameters; comparison of the obtained parameter values ​​with the creep evaluation curve of the same material to assess the degree of creep. The basis functions and creep evaluation curve used in this process should be obtained under specified testing conditions, and the test signals of the test object should also be obtained under these conditions.

[0031] Step (1): For the target material, a certain number of comparative test blocks are made, and high-temperature aging test and creep test are performed on them under the same detection system and detection conditions to form a non-destructive testing signal set. The signal set is then analyzed in the time domain and decomposed using statistical analysis methods to form a basis function set, which is then transformed into an orthogonal basis function set.

[0032] Step (2): Using the orthogonal basis functions and orthogonal basis function vectors as the sensitive parameter projection basis, calculate the parameter values;

[0033] Step (3): Perform sensitivity analysis on all obtained parameter values ​​for creep detection of metallic materials, determine the creep detection parameters for the target material, establish the correspondence between parameter values ​​and creep state, and form the creep evaluation curve of the target material.

[0034] The comparative test block in step (1) should be the same as the target material. The conditions of the high temperature aging test and creep test should meet the relevant standard requirements. The creep and high temperature aging test time of the test block should cover the evaluation interval and there should be no less than 5 time points. The temperature and time conditions of the high temperature aging test should be the same as those of the creep test.

[0035] In step (1), data is collected from the prepared comparison test blocks using acoustic and / or acousto-optic methods. The number of data collections for a single test block is no less than 5. When using the same method to test different test blocks, the testing conditions should be kept stable.

[0036] In step (2), the collected acoustic detection signals or acousto-optic detection signals are organized into a data set. The time-domain basis functions of the data set are extracted using time-domain statistical analysis and transformed into an orthogonal basis function set.

[0037] Step (3) includes 1) projecting the detection signal onto an orthogonal basis function set, 2) comparing the detection sensitivity of different basis function projection values ​​to high-temperature aging structures and creep structures, 3) selecting parameters sensitive to creep structures as sensitive parameters for creep detection of target materials, 4) creating a curve showing the correspondence between parameter values ​​and the degree of creep, and 5) completing the selection of creep detection parameters for target materials.

[0038] Application of creep detection parameters: Keep the detection system unchanged and the detection conditions basically stable, detect the object, obtain the detection signal, project the signal onto the selected basis function, calculate the projection value, compare the projection value with the evaluation curve, and evaluate the creep state of the object.

[0039] The working principle of this invention is:

[0040] ① This invention patent produces comparative test blocks for specific materials, including high-temperature aging test blocks and creep test blocks. It extracts test parameters using actual test data, ensuring that the test parameters are specific to the material and the creep structure, improving the test sensitivity, reducing the dispersion of the test results, and ensuring the repeatability of the test results.

[0041] ② By utilizing the signal processing method proposed in this invention, combined with a detection device that can provide stable detection conditions, it is expected to provide high-precision creep detection and evaluation of metallic materials.

[0042] ③ This invention proposes a method for extracting sensitive parameters for nondestructive testing of creep in metallic materials using time-domain statistical signal analysis. By eliminating factors affecting high-temperature aging structures, the detection sensitivity for creep structures is improved.

[0043] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A signal analysis method for nondestructive testing of creep in metallic materials, characterized in that, The creep testing process includes the following steps: preparation of the test object and acquisition of non-destructive testing signals; projection of the acquired test signals using basis functions and calculation of parameters; comparison of the obtained parameter values ​​with the creep evaluation curve of the same material to assess the degree of creep; the basis functions and creep evaluation curve used in this process should be obtained under specified testing conditions, and the test signals of the test object should also be obtained under these conditions; the signal analysis methods used in the above process are as follows: Step (1): For the target material, a certain number of comparative test blocks are made, and high-temperature aging test and creep test are performed on them under the same detection system and detection conditions to form a non-destructive testing signal set. The signal set is then analyzed in the time domain and decomposed using statistical analysis methods to form a basis function set, which is then transformed into an orthogonal basis function set. Step (2): Using the orthogonal basis functions and orthogonal basis function vectors as the sensitive parameter projection basis, calculate the parameter values; Step (3): Perform sensitivity analysis on all obtained parameter values ​​for creep detection of metallic materials, determine the creep detection parameters for the target material, establish the correspondence between parameter values ​​and creep state, and form the creep evaluation curve of the target material; Step (3) includes 1) projecting the detection signal onto an orthogonal basis function set, 2) comparing the detection sensitivity of different basis function projection values ​​to high-temperature aging structures and creep structures, 3) selecting parameters sensitive to creep structures as sensitive parameters for creep detection of target materials, 4) creating a curve showing the correspondence between parameter values ​​and the degree of creep, and 5) completing the selection process for creep detection parameters of target materials.

2. The signal analysis method for nondestructive testing of creep in metallic materials according to claim 1, characterized in that, The comparative test block in step (1) should be the same as the target material. The conditions of the high temperature aging test and creep test should meet the relevant standard requirements. The high temperature aging and creep test time of the test block should cover the evaluation interval and there should be no less than 5 time points. The temperature and time conditions of the high temperature aging test should be the same as those of the creep test.

3. The signal analysis method for nondestructive testing of creep in metallic materials according to claim 1, characterized in that, In step (1), data is collected from the prepared comparison test blocks using acoustic and / or acousto-optic methods. The number of data collections for a single test block is no less than 5. When using the same method to test different test blocks, the testing conditions should be kept stable.

4. The signal analysis method for nondestructive testing of creep in metallic materials according to claim 1, characterized in that, In step (2), the collected acoustic detection signals or acousto-optic detection signals are organized into a data set. The time-domain basis functions of the data set are extracted using time-domain statistical analysis and transformed into an orthogonal basis function set.

5. An application of a creep detection parameter for metallic materials as described in any one of claims 1-4, characterized in that, Application of creep detection parameters: Keep the detection system unchanged and the detection conditions basically stable, detect the object, obtain the detection signal, project the signal onto the selected basis function, calculate the projection value, compare the projection value with the evaluation curve, and evaluate the creep state of the object.