In-service material performance detection system based on indentation method

Abstract

The invention relates to the field of material mechanical property testing, and provides an in-service material property detection system based on an indentation method, comprising: an excitation module for applying a composite dynamic excitation load to a pressure head when the spherical pressure head is pressed into a to-be-detected material; the signal acquisition module is used for synchronously acquiring a dynamic load signal and a dynamic displacement signal in the pressing-in process of the pressing head; the data processing module is used for calculating an instantaneous phase difference according to the dynamic load signal and the dynamic displacement signal, constructing an evolution curve of the instantaneous phase difference along with the change of the pressure depth, and extracting a first characteristic depth, a second characteristic depth and a phase hardening index from the evolution curve; and the performance resolving module is used for calculating the elastic modulus and the yield strength of the to-be-tested material according to the first characteristic depth, the second characteristic depth, the phase hardening index and the mapping relation model. According to the method, the plastic hardening constitutive relation of the material does not need to be preset, rapid and micro-damage detection of the tensile property of the material can be achieved through single-time micron-order pressing-in, and the method is particularly suitable for field evaluation of in-service equipment.

Description

Technical Field

[0001] This invention relates to the field of material mechanical property testing technology, and in particular to an in-service material performance testing system based on indentation method. Background Technology

[0002] In fields such as petrochemicals, power, and aerospace, a large number of in-service equipment operate in harsh environments for extended periods, leading to degradation of their material properties. Therefore, accurately assessing their mechanical properties is crucial for ensuring safe operation. However, traditional testing methods such as uniaxial tensile testing require destructive sampling, which cannot meet the needs of in-service testing.

[0003] Existing technologies also provide some methods for testing the performance of in-service materials. For example, the ball indentation test method, including Chinese patent application CN114935516A, typically obtains data points by performing multiple loading and unloading cycles on the same location of the material under test. Then, given the known plastic hardening constitutive relationship of the material (such as power-law hardening or linear hardening), a corresponding equation is selected for fitting to obtain the stress-strain curve and strength. However, in actual engineering, the hardening behavior of materials is usually unpredictable. Selecting different constitutive equations can lead to significant differences in results, and multiple indentation cycles can easily cause damage and accumulation effects, affecting the stability of the elastic modulus calculation and the acquisition of yield stage information. Chinese patent application CN112945775A provides a method for identifying tensile property parameters of metallic materials based on indentation contours. This method identifies material parameters based on the contour morphology after indentation unloading, combined with finite element simulation and Bayesian inversion. However, while this method avoids the shortcomings of loading and unloading curve measurement, it relies heavily on a large pre-calculated simulation database and complex statistical inversion calculations. The process is cumbersome, computationally expensive, and difficult to achieve rapid on-site detection. Furthermore, the probabilistic output results are not intuitive enough for engineering applications. Summary of the Invention

[0004] The present invention aims to solve at least one of the problems existing in the prior art and provide an in-service material performance testing system based on indentation method.

[0005] This invention provides an in-service material performance testing system based on indentation method, comprising: The excitation module is used to apply a composite dynamic excitation load, including axial primary excitation and radial subharmonic excitation, to the spherical indenter during formal indentation testing, as the spherical indenter is pressed into a designated position on the surface of the material to be tested. The signal acquisition module is used to synchronously acquire dynamic load signals and dynamic displacement signals during the process of the spherical indenter pressing into a designated position on the surface of the material to be tested. The data processing module, connected to the signal acquisition module, is used to calculate the instantaneous phase difference based on the dynamic load signal and the dynamic displacement signal, construct the evolution curve of the instantaneous phase difference as a function of the indentation depth, and extract the first feature depth, the second feature depth, and the phase hardening index from the evolution curve. The performance calculation module, connected to the data processing module, is used to calculate and output the elastic modulus and yield strength of the material under test based on the first feature depth, the second feature depth, the phase hardening index, and the pre-stored mapping relationship model.

[0006] Optionally, the excitation module is specifically used to: apply an axial sine wave excitation with a frequency of f to the spherical indenter as the axial main excitation, and simultaneously apply a radial sine wave excitation with a frequency of 2f as the radial second harmonic excitation, wherein the amplitude of the radial sine wave excitation is 1 / 10 to 1 / 5 of the amplitude of the axial sine wave excitation.

[0007] Optionally, the data processing module includes: A signal preprocessing unit is used to perform bandpass filtering on the dynamic load signal and the dynamic displacement signal; A phase calculation unit is used to perform phase demodulation on the filtered dynamic load signal and the dynamic displacement signal to calculate the instantaneous phase difference. The curve construction unit is used to associate the instantaneous phase difference with the indentation depth to generate a phase difference-depth curve, and to perform differential operations on the phase difference-depth curve to generate the corresponding first-order derivative curve and second-order derivative curve. The feature extraction unit is used to extract the first feature depth from the second derivative curve and the second feature depth from the first derivative curve.

[0008] Optionally, the feature extraction unit is specifically used to perform the following operations: Identify the point on the second derivative curve where the absolute value of the second derivative first exceeds a first preset threshold, and use the indentation depth corresponding to that point as the first feature depth; Identify the first local maximum point on the first derivative curve, and use the indentation depth corresponding to that point as the second feature depth.

[0009] Optionally, the feature extraction unit is further configured to: extract features within the indentation depth range. Within the curve, the first derivative is integrated, and the integral result is defined as the phase hardening exponent; where M is a constant greater than 1. This indicates the depth of the second feature.

[0010] Optionally, the mapping model is used to characterize the functional relationship between the yield strength and the second characteristic depth, the phase hardening index, and the elastic modulus.

[0011] Optionally, the in-service material performance testing system based on indentation method further includes: The control module, connected to the excitation module and the signal acquisition module respectively, is used to perform the following pre-scanning steps before the formal indentation test: controlling the spherical indenter to perform reciprocating micro-motion with an amplitude within a preset range, acquiring response signals during the reciprocating micro-motion of the spherical indenter, and adjusting the frequency of the composite dynamic excitation load based on the response signals.

[0012] Optionally, the control module is further configured to: calculate the surface uniformity index of the material under test based on the response signal acquired in the pre-scanning step, and when the uniformity index is greater than a second preset threshold, select multiple different location points in the test area of ​​the material under test as the designated location points respectively.

[0013] Optionally, the in-service material performance testing system based on indentation method further includes: The evaluation module is used to calculate a comprehensive confidence score based on the discrete values ​​of yield strength obtained by different methods in the same detection process, and the energy value of the environmental vibration signal at the excitation frequency.

[0014] Optionally, the in-service material performance testing system based on indentation method further includes: The self-learning module is used to update the parameters in the mapping relationship model based on the deviation between the performance test results of the standard material and the actual values ​​of the corresponding performance of the standard material after obtaining the performance test results of the standard material using the indentation-based in-service material performance testing system, or to update the parameters in the evaluation module used to calculate the comprehensive confidence score when the indentation-based in-service material performance testing system further includes an evaluation module for calculating the comprehensive confidence score.

[0015] Compared with the prior art, the present invention has the following advantages: By simultaneously applying composite dynamic excitation loads, including axial and radial loads, during the pressing process and analyzing the evolution characteristics of the instantaneous phase difference between the dynamic load signal and the dynamic displacement signal, the early elastoplastic deformation behavior of the material is directly decoupled. This invention automatically extracts characteristic parameters with clear physical meaning from the phase difference evolution curve, representing key nodes that deviate from linear elasticity, undergo microscopic plastic yielding, and exhibit subsequent hardening trends. This eliminates the dependence on preset specific hardening constitutive equations, making the identification process of material properties more direct and universal, and helping to reduce systematic errors introduced by improper model selection. By establishing an explicit mapping model from characteristic parameters to material properties, the complex inverse mechanical problem is transformed into a forward calculation problem based on calibration data. The performance calculation module only needs to perform simple algebraic operations on the real-time extracted characteristic parameters and the pre-stored model coefficients to directly output the yield strength and elastic modulus. This avoids the iterative optimization or complex probabilistic inversion process required in the prior art, improves the calculation efficiency and determinism, and makes rapid and real-time field testing possible. The calculation process is stable and the results are intuitive. Furthermore, this invention integrates pre-scan adaptive frequency optimization, surface condition judgment, confidence scoring, and self-learning functions. Among these, pre-scan adaptive frequency optimization helps improve signal quality and test consistency; surface condition judgment can trigger multi-point measurement strategies to address situations where materials are locally inhomogeneous; confidence scoring provides users with a quantitative reference for the reliability of test results; and the self-learning function can fine-tune model parameters through periodic calibration to maintain the long-term measurement accuracy and stability of the system. These auxiliary functions together improve the applicability and reliability of the system in real-world complex industrial environments. Attached Figure Description

[0016] One or more embodiments are illustrated by way of example with the corresponding pictures in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0017] Figure 1 A schematic diagram of the formal indentation testing workflow and module interaction of an in-service material performance testing system based on indentation method provided for one embodiment of the present invention; Figure 2 A schematic diagram of data processing and feature extraction provided for another embodiment of the present invention; Figure 3 An optimized detection flowchart of the control module provided for another embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the various embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details are presented in the various embodiments of the present invention to facilitate a better understanding of the invention. However, the technical solutions claimed in the present invention can be implemented even without these technical details and with various variations and modifications based on the following embodiments. The division of the various embodiments below is for ease of description and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined with and referenced by each other without contradiction.

[0019] One embodiment of the present invention provides an in-service material performance testing system based on indentation method, including an excitation module, a signal acquisition module, a data processing module, and a performance calculation module. This system can obtain the elastic modulus and other properties of in-service materials through a single micrometer-level indentation process. With yield strength The tensile property parameters, including those mentioned above.

[0020] The excitation module is used to apply a composite dynamic excitation load, including axial primary excitation and radial subharmonic excitation, to the spherical indenter during formal indentation testing, as the spherical indenter is pressed into a designated location on the surface of the material under test, in order to stimulate the dynamic mechanical response of the material.

[0021] The signal acquisition module is used to synchronously acquire dynamic load signals and dynamic displacement signals during the process of the spherical indenter pressing into a specified position on the surface of the material under test, so as to provide synchronous raw data for subsequent phase analysis.

[0022] The data processing module is connected to the signal acquisition module and is used to calculate the instantaneous phase difference based on the dynamic load signal and the dynamic displacement signal, construct an evolution curve of the instantaneous phase difference as a function of indentation depth, and extract the first characteristic depth to characterize the elastic-plastic transition state of the material based on the differential characteristics of the evolution curve. Second feature depth And the phase hardening index I.

[0023] The performance calculation module is connected to the data processing module and is used to calculate based on the first feature depth. Second feature depth The performance calculation module uses the phase hardening index I and a pre-stored mapping model to calculate and output the elastic modulus and yield strength of the material under test. In other words, the performance calculation module is used to calculate the first feature depth... Second feature depth Using the phase hardening index I as input, combined with a pre-stored mapping model that characterizes the quantitative relationship between material performance parameters and characteristic parameters, the elastic modulus and yield strength of the material under test are directly calculated and output.

[0024] Specifically, the in-service material performance testing system based on indentation method provided in this embodiment may also include a control module. The control module is connected to both the excitation module and the signal acquisition module, and is used to perform the following pre-scanning steps before conducting the formal indentation test: controlling the spherical indenter to perform reciprocating micro-motions with amplitude within a preset range; acquiring response signals during the reciprocating micro-motions of the spherical indenter; and adjusting the frequency of the composite dynamic excitation load based on the response signals. By utilizing the control module to perform the pre-scanning steps before conducting the formal indentation test, adaptive frequency optimization can be achieved, which helps improve signal quality and test consistency.

[0025] The control module is also used to: calculate the surface uniformity index of the material under test based on the response signal acquired in the pre-scanning step, and determine the surface uniformity index when it exceeds a second preset threshold. In this case, multiple different locations are selected within the test area of ​​the material to be tested as designated locations to address local non-uniformity of the material and improve the reliability of the results.

[0026] The in-service material performance testing system based on the indentation method provided in this embodiment may further include an evaluation module. The evaluation module is used to calculate a comprehensive confidence score based on the discrete values ​​of the yield strength determined using different methods during the same testing process, and the energy value of the environmental vibration signal at the excitation frequency. By setting up the evaluation module, the reliability of the test results obtained by the indentation method-based in-service material performance testing system can be evaluated, thereby providing users with a quantitative reference for the reliability of the test results.

[0027] The in-service material performance testing system based on the indentation method provided in this embodiment may further include a self-learning module. The self-learning module is used to update the parameters in the mapping relationship model or the parameters used in the evaluation module to calculate the comprehensive confidence score, based on the deviation between the performance test results and the actual values ​​of the corresponding performance of the standard material after obtaining the performance test results using the indentation method-based in-service material performance testing system. By setting the self-learning module to update the relevant parameters, each corresponding parameter can be fine-tuned periodically to maintain the long-term measurement accuracy and stability of the system.

[0028] The in-service material performance testing system based on indentation method provided in this embodiment can be physically integrated into a portable testing probe and a connected control and analysis box. The portable testing probe may internally include a piezoelectric actuator, an excitation module, a signal acquisition module, and a control module. The control and analysis box may internally include a data processing module, a performance calculation module, an evaluation module, and a self-learning module. The piezoelectric actuator is used to drive the spherical indenter to press into a designated location on the surface of the material under test.

[0029] Figure 1This embodiment illustrates the formal indentation testing workflow and module interactions of the indentation-based in-service material performance testing system. The following section combines... Figure 1 This paper introduces the formal indentation testing workflow of the in-service material performance testing system based on the indentation method provided in this embodiment.

[0030] Combined Figure 1 The formal indentation test workflow of the in-service material performance testing system based on indentation method provided in this embodiment includes the following steps: The formal indentation test process is initiated; the excitation module uses a piezoelectric actuator to drive a spherical indenter to press into a designated location on the surface of the material under test, while simultaneously applying a composite dynamic excitation load containing axial primary excitation and radial subharmonic excitation to the spherical indenter; the signal acquisition module synchronously acquires and records the dynamic load signal and dynamic displacement signal throughout the entire process of the spherical indenter pressing into the designated location on the surface of the material under test; then, the data processing module processes the dynamic load signal and dynamic displacement signal, calculates the instantaneous phase difference, constructs its evolution curve as a function of indentation depth (i.e., indentation depth), and extracts the first characteristic depth from the evolution curve. Second feature depth and phase hardening index The feature parameters are included; subsequently, the performance calculation module uses the extracted feature parameters and the pre-stored mapping relationship model to calculate the elastic modulus of the material under test. and yield strength And output it.

[0031] Subsequently, the in-service material performance testing system based on the indentation method can also evaluate the reliability of the test results through the evaluation module, and provide a corresponding comprehensive confidence score. The in-service material performance testing system based on the indentation method can also use a self-learning module to self-calibrate the model parameters in the system using the performance test results of standard materials.

[0032] In particular, before starting the formal indentation test process, the in-service material performance testing system based on the indentation method can also perform a pre-scanning step through the control module to optimize the test parameters and select a specified location point on the surface of the material to be tested by evaluating the surface condition of the material to be tested.

[0033] The functions of each module in the in-service material performance testing system based on indentation method provided in this embodiment will be described in detail below.

[0034] The excitation module can generate a composite dynamic excitation load that includes axial primary excitation and radial secondary harmonic excitation.

[0035] The excitation module is specifically used to: apply an axial sinusoidal wave excitation with a frequency of f to the spherical indenter as the axial main excitation, and simultaneously apply a radial sinusoidal wave excitation with a frequency of 2f as the radial subharmonic excitation. The amplitude of the radial sinusoidal wave excitation is 1 / 10 to 1 / 5 of the amplitude of the axial sinusoidal wave excitation. This configuration can enhance the detection sensitivity of the early nonlinear behavior of the material through subharmonic coupling.

[0036] Specifically, when implementing the axial main excitation, a frequency of [frequency value missing] can be generated by the first signal source. A sinusoidal voltage signal is used as the axial main excitation. After amplification, this signal drives the piezoelectric ceramic stack located along the main axis of the spherical indenter, causing the spherical indenter to produce micro-amplitude reciprocating vibrations along its axis. The displacement amplitude is... It can be controlled at 20nm.

[0037] When implementing radial subharmonic excitation, a frequency of [frequency value missing] can be generated by a second signal source. The sinusoidal voltage signal is used as the radial subharmonic excitation, and its amplitude is set to 0.125 times the amplitude of the first signal source. After being amplified, this signal drives a set of radially arranged piezoelectric ceramic sheets, causing the spherical indenter to produce a micro-amplitude vibration perpendicular to the axis.

[0038] When applying a composite dynamic excitation load containing axial principal excitation and radial subharmonic excitation to a spherical indenter, the two excitations, namely the axial principal excitation and the radial subharmonic excitation, are pressed into the surface of the material under test at designated points until a preset maximum indentation depth is reached. It is applied continuously and synchronously throughout the entire process.

[0039] The signal acquisition module can simultaneously acquire dynamic load signals and dynamic displacement signals.

[0040] Specifically, when acquiring dynamic load signals, a high-resonance-frequency miniature dynamic force sensor can be used to measure the axial dynamic force experienced by the spherical indenter at a designated point on the surface of the material under test. As a dynamic load signal, the sampling frequency can be set to t represents time.

[0041] When acquiring dynamic displacement signals, a high-precision capacitive displacement sensor can be used to measure the axial dynamic displacement of the spherical indenter relative to the probe frame. As a dynamic displacement signal, the sampling frequency can also be set to... .

[0042] The control module generates a synchronization trigger signal to ensure that data acquisition from the force sensor and displacement sensor starts strictly simultaneously, thus ensuring... and Synchronization and recording. Simultaneously, the signal acquisition module records... and The corresponding total indentation depth of the spherical indenter .

[0043] The data processing module can receive raw signals. , and The algorithm processes and outputs the feature parameters, namely the first feature depth. Second feature depth and phase hardening index .

[0044] The data processing module may include a signal preprocessing unit, a phase calculation unit, a curve construction unit, and a feature extraction unit. The following section will combine these components... Figure 2 The data processing and feature extraction process of the data processing module is explained.

[0045] The signal preprocessing unit is used to perform bandpass filtering on the dynamic load signal and the dynamic displacement signal to separate the steady-state response signal component caused by the composite dynamic excitation load.

[0046] Specifically, the signal preprocessing unit performs signal preprocessing operations. For example, the signal preprocessing unit uses synchronously acquired dynamic load signals... and dynamic displacement signal For input, the passband can be used. A finite-length unit impulse response bandpass filter, respectively for and Perform digital filtering and output the filtered signal. and ,in, This is the filtered dynamic load signal. This is the filtered dynamic displacement signal.

[0047] The phase calculation unit is used to demodulate the phase of the filtered dynamic load signal and the dynamic displacement signal, and calculate the instantaneous phase difference between the dynamic load signal and the dynamic displacement signal.

[0048] Specifically, the phase calculation unit calculates... Lagging behind instantaneous phase difference First, a first reference signal is generated. Second reference signal ,in, , .

[0049] for Calculate the first load phase reference signal Second load phase reference signal ,in, , .Will and With a cutoff frequency of The low-pass filter is obtained. Corresponding in-phase components and orthogonal components Then the load phase for .

[0050] for Calculate separately and ,Will and With a cutoff frequency of The low-pass filter is obtained. Corresponding in-phase components and orthogonal components Then the displacement phase for .

[0051] according to Calculate instantaneous phase difference Instantaneous phase difference at all times Forming a phase difference array .

[0052] The curve construction unit is used to correlate the instantaneous phase difference with the indentation depth to generate a phase difference-depth curve, and to perform differential operations on the phase difference-depth curve to generate the corresponding first derivative curve P1 and second derivative curve P2. The first derivative curve P1 reflects the rate of phase change, and the second derivative curve P2 reflects the acceleration of phase change.

[0053] Specifically, when constructing the evolution curve, the curve building unit first converts the phase difference array... With the corresponding total indentation depth Align, and get - The curve is the phase difference-depth curve. Next, the central difference method is used to calculate... - Let P be the array of first derivatives and P' be the array of second derivatives. The curve corresponding to the first derivative array P is the first derivative curve P1, and the curve corresponding to the second derivative array P' is the second derivative curve P2. For the first derivative... point: , .

[0054] The first derivative in the array P is the first derivative of the first derivative. One element, for Instantaneous phase difference at time for Instantaneous phase difference at time for Total indentation depth at time for Total indentation depth at time The second derivative array P' is the first... One element, The first derivative in the array P is the first derivative of the first derivative. One element, The first derivative in the array P is the first derivative of the first derivative. Each element.

[0055] The feature extraction unit is used to extract the first feature depth from the second derivative curve and the second feature depth from the first derivative curve.

[0056] Specifically, the feature extraction unit is used to analyze the shape of the second derivative curve P2 and the first derivative curve P1, and extracts the first feature depth characterizing the material response as it begins to deviate from linearity from the second derivative curve P2. The second characteristic depth, representing the microscopic plastic yielding of the material, is extracted from the first derivative curve P1. .

[0057] The feature extraction unit is specifically used to perform the following operation: identify the absolute value of the second derivative curve P2. First time greater than the first preset threshold The point is used as the first feature depth for the indentation depth. Identify the first local maximum point on the first derivative curve P1, and use the indentation depth corresponding to that point as the second feature depth. .

[0058] For example, the feature extraction unit extracts... When, the first preset threshold can be... Set as From a total indentation depth of 0 Start scanning the corresponding elements in the second derivative array P' from point 1, and find the first element in the second derivative array P' that satisfies the condition. point that point The corresponding total indentation depth is at this point Total indentation depth That is, the first feature depth .

[0059] The feature extraction unit extracts... At that time, a moving average filter is applied to the first-order derivative array P to obtain the filtered first-order derivative array. The window width can be set to 5 points, starting from a total push depth of 0. Start scanning here Find the corresponding element in China satisfies and ,and The first point that point The corresponding total indentation depth is at this point Total indentation depth That is, the second feature depth is ,in, for The first in One element, for The first in One element, for The first in Each element.

[0060] The feature extraction unit is also used for: in the indentation depth range Within the curve, the first derivative curve P1 is integrated, and the result of the integration is defined as the phase hardening exponent. Where M is a constant greater than 1, This represents the second feature depth, and the purpose of this integral operation is to quantify the hardening behavior trend of the material during the initial plastic deformation stage.

[0061] Specifically, the feature extraction unit calculates the phase hardening index. At that time, it can be set The trapezoidal rule is used to calculate the first derivative array. In the interval The definite integral obtained over the given time is the corresponding phase hardening index. .

[0062] The feature extraction unit can also be used to calculate the full width at half maximum (FWHM). To enable the evaluation module to utilize the full width at half maximum (WHM) The detection results are evaluated. Specifically, the feature extraction unit calculates the full width at half maximum (FWHM). First, calculate the array of first-order derivatives. In the interval Find the peak half-width within that interval. maximum value Calculate half of the maximum value. ,Right now Next, linear interpolation is used to find the peak value, i.e., the maximum value. Find the left and right sides respectively corresponding depth and ,in, Peak value is the maximum value. The left side satisfies Total indentation depth, Peak value is the maximum value. The right side satisfies The total indentation depth is then the full width at half height. for The interpolation formula is: if at point... and Between Then the interpolation depth for , They are first derivative arrays The first in One point, They are respectively The corresponding total indentation depth.

[0063] The performance calculation module can calculate the elastic modulus and yield strength of materials based on characteristic parameters, and it has a pre-stored mapping relationship model.

[0064] Specifically, the pre-stored mapping model in the performance calculation module is used to characterize the yield strength. With the second feature depth Phase hardening index and elastic modulus The model establishes a quantitative functional relationship between the material properties and the parameters, and directly calculates the material properties by substituting the characteristic parameters into a preset function.

[0065] In calculating the elastic modulus At: In the initial stage, the total indentation depth is less than the first feature depth. In the first 10 points, the deformation of the material under test is mainly elastic deformation. This stage... - Curve inversion of elastic modulus.

[0066] First, determine the system calibration. - Calibration curve, where, - The calibration curve is used to characterize the phase difference array established through calibration. With true contact depth The corresponding relationship. The calibration method is as follows: using a spherical indenter to press into the material to be tested, with a known elastic modulus of... Quasi-static indentation tests were performed on standard specimens, and the true contact depth at each load point was calculated using the initial slope of the unloading curve combined with the Oliver-Pharr method. Simultaneously record the corresponding phase difference array Thus establishing The lookup table of data pairs as - Calibration curve.

[0067] During the formal indentation test, the query... - The calibration curve determines the shallow pressure deep section, i.e. The initial stage, i.e., the total indentation depth is less than the first feature depth. The contact depth corresponding to the phase difference of the stage .

[0068] According to Hertz's theory of elastic contact of spherical indenters, the load With contact depth The relationship is: ,in, To reduce the elastic modulus, The radius of the pressure head. Utilizing the load of the shallow pressure section. With contact depth Measured data and indenter radius The actual value is obtained by fitting the above formula using the least squares method. The reduced elastic modulus was calculated. .

[0069] Let the elastic modulus of the material of the spherical indenter be Poisson's ratio is (For example, the elastic modulus of a diamond indenter) for Poisson's ratio for And estimate the Poisson's ratio of the material to be tested. (When the material to be tested is steel, the Poisson's ratio of the material to be tested can be used.) for Calculate the elastic modulus of the material under test according to the following formula. : .

[0070] Using the known Poisson's ratio of the material to be tested The elastic modulus of the material of the spherical indenter is and Poisson's ratio is and the calculated reduced elastic modulus , then according to The calculated elastic modulus of the material under test Among them, elastic modulus The unit is GPa.

[0071] In calculating yield strength At that time, the pre-stored mapping relationship model in the performance calculation module establishes the yield strength. With feature parameters, i.e., the second feature depth Phase hardening index and elastic modulus The quantitative relationship between them is in the form of: .

[0072] in, The value represents the yield strength of the material being tested, in MPa. The elastic modulus of the test material is calculated in GPa. The converted value, in MPa, is . For the second feature depth, in units . Let be the radius of the spherical indenter, and be a known geometric parameter, in units of . ,For example . The phase hardening index is dimensionless. All of these are model coefficients, which are constants determined through calibration. The coefficient is dimensionless. and All units are .

[0073] The calibration method is as follows: Select a set of standard specimens, and their elastic modulus... and yield strength Known through standard uniaxial tensile testing. These selected standard specimens were tested using the indentation-based in-service material performance testing system provided in this embodiment, yielding multiple sets of corresponding characteristic data. To obtain multiple sets of corresponding feature data. corresponding and As the independent variable, As Simultaneously, as a dependent variable, based on The model coefficients were obtained by fitting the data using a multiple linear regression algorithm. For example, through calibration, we can obtain: , , .

[0074] During formal indentation testing, the performance calculation module will... , , Indenter radius and model coefficients Substituting into the above formula, we get The yield strength of the material under test can then be calculated. .

[0075] The control module can automate the testing process and optimize test parameters. The following section will combine... Figure 3 The optimized testing process for the control module is explained in detail.

[0076] Before conducting the formal indentation test, during the pre-scanning step, the control module can control the spherical indenter to perform reciprocating micro-motions with an amplitude within a preset range of nanometers, such as 1 nanometer to 10 nanometers. During the reciprocating micro-motions of the spherical indenter, response signals are collected, and the system response is analyzed based on the response signals. This allows for the adaptive adjustment of the frequency of the composite dynamic excitation load to optimize the test signal-to-noise ratio.

[0077] Specifically, during pre-scanning and parameter optimization, the control module first controls the spherical indenter to... amplitude, The frequency is used for axial reciprocating micro-motion. Next, the load during the pre-scan is recorded. With displacement Calculate contact stiffness ,in, This represents the load oscillation amplitude during the pre-scan. This represents the displacement oscillation amplitude during pre-scanning. The frequency of the composite dynamic excitation load is adjusted in 1Hz increments within the range of 180Hz to 220Hz. Record the system response amplitude and the frequency of the composite dynamic excitation load in the formal test. Set at the frequency point where the system response amplitude is the largest.

[0078] The control module is also used to: calculate the uniformity index U, which reflects the consistency of the surface mechanical state of the material under test, based on the response signal acquired in the pre-scanning step; and determine the surface state uniformity index of the material under test when the uniformity index U is greater than a second preset threshold. When the surface condition of the material under test is determined to be non-uniform, multiple different locations within the test area of ​​the material under test are selected as designated locations. The in-service material performance testing system based on the indentation method provided in this embodiment then sequentially performs performance tests on the material under test based on each designated location. The test results corresponding to each designated location are integrated into a regional performance report as the final test result, thereby addressing the situation of localized material non-uniformity and improving the reliability of the results. If the uniformity index U does not exceed the second preset threshold... If the surface condition of the material to be tested is uniform, the in-service material performance testing system based on the indentation method provided in this embodiment can perform single-point testing on the material to be tested.

[0079] Specifically, when performing surface uniformity judgment and multi-point detection, the control module bases its detection on the contact stiffness of multiple cycles during the pre-scan. The value of the coefficient of variation of contact stiffness is used as a uniformity index U. , For contact stiffness standard deviation For contact stiffness The average value, set a second preset threshold. for .like If the surface of the material being tested is found to be non-uniform, then the test can be performed with the current specified location as the center and a radius of... N points (e.g., 4 points) are selected at equal intervals on the circumference. The in-service material performance testing system based on indentation method is used to perform a complete formal indentation test procedure at these N points in sequence. Finally, the arithmetic mean of the test results of these N points is taken as the report value, which is the final test result.

[0080] The evaluation module can quantitatively assess the reliability of a single test result and output a comprehensive confidence score. Specifically, the evaluation module is used to determine discrete values ​​of yield strength based on different methods, such as different algorithms or feature paths, obtained during the same detection process. And the energy value of the synchronously acquired environmental vibration signal at the excitation frequency. The overall confidence score is calculated using a preset weighted scoring function. This is used to quantify the reliability of the test results.

[0081] The evaluation module calculates discrete values. At that time, two independent internal algorithm paths are used to calculate the yield strength. The first path uses a pre-stored mapping model to establish the yield strength. With the second feature depth Phase hardening index and elastic modulus The quantitative relationship between them is The calculated output yield strength is The second path utilizes The curve is the array of first derivatives. Features: Calculates the array of first derivatives In the interval Half-height and full width inside Specifically, it can be calculated by the feature extraction unit in the data processing module, and then obtained through the formula. Another estimate for calculating yield strength ,in, and These are empirical coefficients obtained through a similar calibration process. Given the radius of the spherical indenter, The elastic modulus of the test material, expressed in GPa, calculated by the performance calculation module. The converted value. Next, according to... The discrete values ​​can then be calculated. discrete values The unit is MPa.

[0082] The evaluation module calculates the energy value. At the same time, environmental vibration signals during the detection process can be collected using an accelerometer. Environmental vibration signals Extracting its value after performing a Fast Fourier Transform (FFT) Spectral amplitude at Define energy value for ,unit .

[0083] Obtain discrete values and energy value Then, based on the preset weighted scoring function The overall confidence score can then be calculated. ,in, and These are all weighting coefficients, which can be determined by analyzing historical test data.

[0084] For example, in determining the weighting coefficients and First, the in-service material performance testing system based on indentation method provided in this embodiment is used to collect multiple sets of test data on known performance standard specimens under controlled ideal conditions. Each set of test data contains discrete values. and energy value and actual relative error ,in, The yield strength of a standard specimen with known properties obtained by the indentation-based in-service material performance testing system provided in this embodiment is given. This represents the actual value of the yield strength of a standard specimen with known performance. For the target value, the least squares method is used for fitting. and A set of example results are as follows: , Overall confidence score The value range is from 0 to 100.

[0085] The self-learning module can use standard sample test data to iteratively optimize the parameters of the in-service material performance testing system based on the indentation method provided in this embodiment.

[0086] Specifically, the self-learning module is used to update the parameters in the mapping relationship model by using the in-service material performance testing system based on the indentation method provided in this embodiment to test the standard material with known performance and obtain the performance test results of the standard material. Based on the deviation between the performance test results output by the performance calculation module and the known actual values ​​of the corresponding performance of the standard material, the self-learning module updates the parameters in the evaluation module used to calculate the comprehensive confidence score Q, so as to achieve long-term calibration and performance maintenance of the system.

[0087] The self-learning module is triggered when the in-service material performance testing system based on indentation method provided in this embodiment uses a certified yield strength of... The self-learning module is activated when the standard test block is periodically calibrated.

[0088] The learning process of the self-learning module is as follows: After completing the formal indentation test using the in-service material performance testing system based on the indentation method provided in this embodiment, the measured values ​​are obtained. That is, the yield strength of a known performance standard specimen and the current set of model coefficients obtained through the indentation-based in-service material performance testing system provided in this embodiment. .according to Calculate model error If the model error The absolute value is greater than the preset threshold, such as If so, the parameter adjustment process of the mapping relationship model will be initiated.

[0089] When adjusting the parameters of the mapping relationship model, gradient descent is used to minimize the loss function. The goal is to achieve this. Based on the model formula... The partial derivatives of the loss function with respect to the model coefficients are determined as follows: , , .

[0090] Set learning rate The model coefficient update formula is: , , .

[0091] in, The model coefficients before the update are respectively , The updated model coefficients are respectively The iteration termination condition is The change is less than the preset change threshold, such as Or it can reach the maximum number of iterations, such as 1000.

[0092] Meanwhile, the self-learning module can also refit the evaluation module used to calculate the comprehensive confidence score based on recent historical data. Weighting coefficients and The updated parameters include model coefficients. and weighting coefficients and It can be applied to subsequent testing.

[0093] Those skilled in the art will understand that the above embodiments are specific implementations of the present invention, and in practical applications, various changes can be made in form and detail without departing from the spirit and scope of the present invention.

Claims

1. A performance testing system for in-service materials based on indentation method, characterized in that, include: The excitation module is used to apply a composite dynamic excitation load, including axial primary excitation and radial subharmonic excitation, to the spherical indenter during formal indentation testing, as the spherical indenter is pressed into a designated position on the surface of the material to be tested. The signal acquisition module is used to synchronously acquire dynamic load signals and dynamic displacement signals during the process of the spherical indenter pressing into a designated position on the surface of the material to be tested. The data processing module, connected to the signal acquisition module, is used to calculate the instantaneous phase difference based on the dynamic load signal and the dynamic displacement signal, construct the evolution curve of the instantaneous phase difference as a function of the indentation depth, and extract the first feature depth, the second feature depth, and the phase hardening index from the evolution curve. The performance calculation module, connected to the data processing module, is used to calculate and output the elastic modulus and yield strength of the material under test based on the first feature depth, the second feature depth, the phase hardening index, and the pre-stored mapping relationship model.

2. The in-service material performance testing system based on indentation method according to claim 1, characterized in that, The excitation module is specifically used to: apply an axial sinusoidal wave excitation with a frequency of f to the spherical indenter as the axial main excitation, and simultaneously apply a radial sinusoidal wave excitation with a frequency of 2f as the radial second harmonic excitation, wherein the amplitude of the radial sinusoidal wave excitation is 1 / 10 to 1 / 5 of the amplitude of the axial sinusoidal wave excitation.

3. The in-service material performance testing system based on indentation method according to claim 1, characterized in that, The data processing module includes: A signal preprocessing unit is used to perform bandpass filtering on the dynamic load signal and the dynamic displacement signal; A phase calculation unit is used to perform phase demodulation on the filtered dynamic load signal and the dynamic displacement signal to calculate the instantaneous phase difference. The curve construction unit is used to associate the instantaneous phase difference with the indentation depth to generate a phase difference-depth curve, and to perform differential operations on the phase difference-depth curve to generate the corresponding first-order derivative curve and second-order derivative curve. The feature extraction unit is used to extract the first feature depth from the second derivative curve and the second feature depth from the first derivative curve.

4. The in-service material performance testing system based on indentation method according to claim 3, characterized in that, The feature extraction unit is specifically used to perform the following operations: Identify the point on the second derivative curve where the absolute value of the second derivative first exceeds a first preset threshold, and use the indentation depth corresponding to that point as the first feature depth; Identify the first local maximum point on the first derivative curve, and use the indentation depth corresponding to that point as the second feature depth.

5. The in-service material performance testing system based on indentation method according to claim 3, characterized in that, The feature extraction unit is also used for: in the indentation depth range Within the curve, the first derivative is integrated, and the integral result is defined as the phase hardening exponent; where M is a constant greater than 1. This indicates the depth of the second feature.

6. The in-service material performance testing system based on indentation method according to claim 1, characterized in that, The mapping model is used to characterize the functional relationship between the yield strength and the second characteristic depth, the phase hardening index, and the elastic modulus.

7. The in-service material performance testing system based on indentation method according to claim 1, characterized in that, The in-service material performance testing system based on indentation method also includes: The control module, connected to the excitation module and the signal acquisition module respectively, is used to perform the following pre-scanning steps before the formal indentation test: controlling the spherical indenter to perform reciprocating micro-motion with an amplitude within a preset range, acquiring response signals during the reciprocating micro-motion of the spherical indenter, and adjusting the frequency of the composite dynamic excitation load based on the response signals.

8. The in-service material performance testing system based on indentation method according to claim 7, characterized in that, The control module is further configured to: calculate the surface uniformity index of the material under test based on the response signal acquired in the pre-scanning step, and when the uniformity index is greater than a second preset threshold, select multiple different location points in the test area of ​​the material under test as the designated location points.

9. The in-service material performance testing system based on indentation method according to claim 1, characterized in that, The in-service material performance testing system based on indentation method also includes: The evaluation module is used to calculate a comprehensive confidence score based on the discrete values ​​of yield strength obtained by different methods in the same detection process, and the energy value of the environmental vibration signal at the excitation frequency.

10. The in-service material performance testing system based on indentation method according to claim 1 or 9, characterized in that, The in-service material performance testing system based on indentation method also includes: The self-learning module is used to update the parameters in the mapping relationship model based on the deviation between the performance test results of the standard material and the actual values ​​of the corresponding performance of the standard material after obtaining the performance test results of the standard material using the indentation-based in-service material performance testing system, or to update the parameters in the evaluation module used to calculate the comprehensive confidence score when the indentation-based in-service material performance testing system further includes an evaluation module for calculating the comprehensive confidence score.

Images