Shock absorber bearing raceway hardness measuring method and device based on electromagnetic induction signal

Abstract

The invention relates to the technical field of electromagnetic induction bearing raceway hardness measurement, in particular to a shock absorber bearing raceway hardness measurement method and device based on an electromagnetic induction signal. Determining an optimized penalty coefficient according to the difference between the current damper bearing voltage signal and each historical damper bearing voltage signal on the corresponding penalty coefficient and the difference between the voltage signals, and denoising the current damper bearing voltage signal; and the hardness of the current shock absorber bearing raceway is measured. According to the method, the de-noising quality is improved by dynamically optimizing the penalty coefficient, and the accuracy and reliability of hardness measurement of the bearing raceway of the shock absorber are improved.

Description

Technical Field

[0001] This application relates to the field of electromagnetic induction bearing raceway hardness measurement technology, specifically to a method and equipment for measuring the raceway hardness of shock absorber bearings based on electromagnetic induction signals. Background Technology

[0002] Traditional automotive shock absorber bearing raceway hardness testing relies on destructive methods such as Rockwell or Vickers, which are inefficient, time-consuming, and unable to achieve full inspection. In contrast, inductive hardness testing technology, based on the principle of electromagnetic induction, can achieve non-destructive and efficient batch full inspection of bearing raceways. This technology places the bearing raceway in an alternating magnetic field; differences in hardness alter the electromagnetic induction state of the coil, generating a weak voltage signal that can be analyzed. By amplifying and analyzing this voltage signal, the raceway hardness can be accurately determined, providing a fast and reliable solution for quality control on the production line.

[0003] However, in practical applications, the voltage signal collected by the electromagnetic induction coil inevitably becomes mixed with various noises, such as power frequency interference, mechanical vibration, and environmental electromagnetic noise. These noises can severely weaken or even obscure the effective information related to hardness, leading to signal distortion. Secondly, the inherent multi-component and non-stationary characteristics of the induction signal make it difficult to directly analyze using traditional methods. Therefore, if the unprocessed raw voltage signal is used directly for hardness analysis, significant errors will inevitably be introduced, severely affecting the accuracy and reliability of the hardness measurement of the shock absorber bearing raceway. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and equipment for measuring the raceway hardness of shock absorber bearings based on electromagnetic induction signals. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals. This method includes the following steps: Obtain the voltage signal of each shock absorber bearing as it passes through the electromagnetic induction coil; Modal decomposition is performed on the voltage signal of each shock absorber bearing. By analyzing the disorder of each modal component, the distribution difference of the voltage signal of each shock absorber bearing is determined. By analyzing the correlation between each modal component and all other modal components in the voltage signal of each shock absorber bearing and the difference in center frequency, the correlation of the voltage signal of each shock absorber bearing is determined. Combined with the distribution difference, the modal aliasing of the voltage signal of each shock absorber bearing is determined. Based on the comprehensive difference between all amplitudes of the voltage signal before and after denoising for each shock absorber bearing, as well as the disorder of each modal component in the voltage signal and the modal aliasing, the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition is determined; by comparing the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals at the corresponding penalty coefficient and the difference between the voltage signals, and combining the signal denoising degree, the optimized penalty coefficient of the current shock absorber bearing voltage signal is determined, and the current shock absorber bearing voltage signal is denoised; The hardness of the raceway of the current shock absorber bearing is measured based on the noise-reduced voltage signal of the current shock absorber bearing.

[0005] Preferably, the method for determining the distribution difference of the voltage signal of each shock absorber bearing is as follows: Calculate the sum of the differences between the envelope entropy of all modal components and the maximum envelope entropy of all modal components in the voltage signal of each shock absorber bearing. Multiply the sum by the maximum envelope entropy as the distribution difference of the voltage signal of each shock absorber bearing.

[0006] Preferably, the method for determining the correlation of the voltage signals of each shock absorber bearing is as follows: For each damper bearing voltage signal, the normalized value of the center frequency difference between each modal component and the other modal components is recorded as the frequency difference value between each modal component and the other modal components. The correlation coefficient between each modal component and the other modal components is divided by the frequency difference value, and the result is used as the correlation characteristic value between each modal component and the other modal components. The maximum value among the correlation eigenvalues ​​between each modal component and all other modal components is obtained. The mean of the maximum correlation eigenvalues ​​of all modal components in each shock absorber bearing voltage signal is taken as the correlation of each shock absorber bearing voltage signal.

[0007] Preferably, the modal aliasing degree of each shock absorber bearing voltage signal is the ratio of the correlation normalized value to the distribution difference normalized value of each shock absorber bearing voltage signal.

[0008] Preferably, the expression for the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition is: In the formula, This represents the signal denoising degree of the shock absorber bearing voltage signal i under the penalty coefficient in the corresponding mode decomposition; This represents the overall difference between all amplitudes of the shock absorber bearing voltage signal i before and after noise reduction; This represents the maximum value of the envelope entropy of all modal components in the shock absorber bearing voltage signal i; This represents the modal aliasing degree of the shock absorber bearing voltage signal i.

[0009] Preferably, the expression for the optimized penalty coefficient of the current shock absorber bearing voltage signal is: In the formula, This represents the optimized penalty coefficient for the current shock absorber bearing voltage signal; This represents the preset initial penalty coefficient for the current shock absorber bearing voltage signal; This represents the normalized value of the modal aliasing degree of the current shock absorber bearing voltage signal; This represents the adjustment direction factor of the current shock absorber bearing voltage signal, which is based on the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals in terms of the corresponding penalty coefficient, the difference between the voltage signals, and the signal denoising degree. This indicates the signal noise reduction level of the current shock absorber bearing voltage signal; This represents the maximum value of the signal denoising among all historical shock absorber bearing voltage signals for which the penalty coefficient is less than the preset initial penalty coefficient of the current shock absorber bearing voltage signal.

[0010] Preferably, the expression for the adjustment direction factor of the current shock absorber bearing voltage signal is: In the formula, This indicates the adjustment direction factor of the current shock absorber bearing voltage signal; , These represent the total number of historical shock absorber bearing voltage signals with a penalty coefficient greater than the preset initial penalty coefficient of the current shock absorber bearing voltage signal, and the total number of historical shock absorber bearing voltage signals with a penalty coefficient less than the preset initial penalty coefficient of the current shock absorber bearing voltage signal, respectively. , They represent The signal noise reduction of the voltage signal of the j-th shock absorber bearing. This represents the signal denoising degree of the voltage signal of the m-th damping bearing; , These respectively represent the current shock absorber bearing voltage signal and... The reciprocal of the difference between the voltage signals of the j-th shock absorber bearing and the... The reciprocal of the difference between the bearing voltage signals of the m-th shock absorber.

[0011] Preferably, the noise reduction of the current shock absorber bearing voltage signal includes: The current shock absorber bearing voltage signal is used as the input to the mode decomposition algorithm, where the optimized penalty coefficient of the current shock absorber bearing voltage signal is used as the penalty coefficient in the current mode decomposition algorithm, and all modal components of the current shock absorber bearing voltage signal are output. Calculate the envelope entropy of all modal components, reconstruct all modal components except the one with the maximum envelope entropy, and use the reconstructed signal as the noise-reducing voltage signal of the current shock absorber bearing.

[0012] Preferably, the measurement of the hardness of the current shock absorber bearing raceway includes: The feature vector of the denoised voltage signal of the current shock absorber bearing is obtained, and the feature vector is used as the input of a pre-trained bearing raceway hardness measurement model to output the hardness of the current shock absorber bearing raceway. Secondly, embodiments of this application also provide a shock absorber bearing raceway hardness measurement device based on electromagnetic induction signals, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described shock absorber bearing raceway hardness measurement methods based on electromagnetic induction signals.

[0013] This application has at least the following beneficial effects: This application first comprehensively evaluates modal aliasing and over-decomposition by constructing a correlation between the distribution difference characterizing the purity of signal separation and the degree of information redundancy, and then combining the two into a modal aliasing degree to accurately assess the decomposition quality under the current penalty coefficient, ultimately providing optimal decomposition parameters for high-precision hardness detection. Furthermore, this application constructs a signal denoising degree that comprehensively evaluates denoising quality, determines the optimal adjustment direction by analyzing historical data, and dynamically adjusts the penalty coefficient based on the current signal decomposition quality and historical experience, ensuring the stability and optimality of the denoising effect. Finally, this application extracts the feature vector of the high-quality denoised voltage signal and inputs it into a hardness measurement model pre-trained with a large amount of sample data, thereby achieving accurate and automated mapping from the processed electrical signal to the bearing raceway hardness, improving the accuracy and reliability of shock absorber bearing raceway hardness measurement. This invention uses the variational mode decomposition (VMD) algorithm to decompose the acquired electrical signal, adaptively separating the signal into multiple intrinsic mode function (IMF) components. The signal purity of modal components is evaluated by calculating the envelope entropy of each modal component: modes with lower envelope entropy values ​​contain more regular and useful information, while modes with higher envelope entropy values ​​contain noise components. Based on the distributional differences of envelope entropy, this invention quantifies the separation effect of modal components, ensuring that useful signals are retained in low-entropy modes, thereby reducing the loss of useful information while denoising.

[0014] The performance of the VMD algorithm hinges on the setting of the penalty coefficient α. This invention introduces a modal aliasing index by analyzing historical electrical signal sequences. This index integrates the differences in the envelope entropy distribution of modal components and the correlation coefficients between modes. A lower modal aliasing index indicates purer modal decomposition and more thorough separation of useful signals from noise. Based on the modal aliasing index, and considering the denoising effectiveness and signal approximation of historical signals, the penalty coefficient is adaptively adjusted: when historical signals indicate that the current penalty coefficient may lead to modal aliasing, the penalty coefficient is increased to tighten the bandwidth; when historical signals indicate potential over-decomposition, the penalty coefficient is decreased to widen the bandwidth. This adaptive adjustment mechanism ensures that the VMD algorithm can optimize decomposition under different workpiece signals, improving denoising robustness while simultaneously increasing the accuracy of hardness measurement. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals, provided in one embodiment of this application. Figure 2 This is a schematic diagram of a signal denoising extraction process provided in one embodiment of this application. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended inventive purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the method and device for measuring the raceway hardness of shock absorber bearings based on electromagnetic induction signals proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] The following, in conjunction with the accompanying drawings, details the specific scheme of the method and equipment for measuring the raceway hardness of shock absorber bearings based on electromagnetic induction signals provided in this application.

[0020] Please see Figure 1The diagram illustrates a flowchart of a method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals, according to an embodiment of this application. The method includes the following steps: Step S1: Obtain the voltage signal of each shock absorber bearing as it passes through the electromagnetic induction coil.

[0021] As each shock absorber bearing is conveyed through the electromagnetic induction coil on the production line, its hardness difference causes a change in the material's magnetic permeability, which in turn alters the magnetic field in the coil. A tiny AC voltage signal related to hardness is generated at both ends of the coil. This voltage signal reflects the electromagnetic properties of the material surface. Since the induced signal is very weak, this embodiment first uses a preamplifier to pre-amplify the tiny AC voltage signal. The amplified voltage signal is then used to measure the hardness of the shock absorber bearing raceway. The sampling frequency of the voltage signal is set to f, and the sampling time covers the entire process of the workpiece passing through the coil.

[0022] It should be noted that the sampling frequency f is set manually. In this embodiment, the sampling frequency f is 100kHz. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0023] Step S2: By analyzing the mode separation quality of the signal itself and referring to the processing effect of historical signals, the optimal penalty coefficient is dynamically determined for the voltage signal of each shock absorber bearing, thereby achieving the best noise reduction.

[0024] Electromagnetic induction signals are typically multi-component, non-stationary signals, not pure waves of a single frequency. They consist of useful intrinsic modes reflecting hardness information, various noises, and irrelevant interferences such as power frequency interference and mechanical vibration. Directly using the voltage signal of an undenoised electromagnetic induction coil for hardness detection will lead to errors. Therefore, this embodiment uses a variational mode decomposition (VMD) algorithm to denoise the electrical signal of the electromagnetic induction coil. This involves analyzing the mode separation quality of the signal itself and referencing the processing effects of historical signals to dynamically determine an optimized penalty coefficient for the voltage signal of each shock absorber bearing, thereby achieving optimal denoising. The specific process is as follows: S2.1: Perform modal decomposition on the voltage signal of each shock absorber bearing. By analyzing the disorder of each modal component, determine the distribution difference of the voltage signal of each shock absorber bearing. By analyzing the correlation between each modal component and all other modal components in the voltage signal of each shock absorber bearing and the difference in center frequency, determine the correlation of the voltage signal of each shock absorber bearing. Combined with the distribution difference, determine the modal aliasing of the voltage signal of each shock absorber bearing.

[0025] In Variational Mode Decomposition (VMD) algorithms, the penalty coefficient α is a key parameter controlling the balance between modal bandwidth and reconstruction fidelity. Its value has a decisive impact on the signal denoising effect and the final hardness detection accuracy. If the penalty coefficient is too small, insufficient constraint on reconstruction error will lead to excessively wide modal bandwidths, resulting in modal aliasing and making it impossible to effectively separate different signal components. Conversely, if the penalty coefficient is too large, excessively strict bandwidth constraints will cause over-decomposition, forcibly splitting a complete useful signal into multiple distorted narrowband components. Both of these situations, whether modal aliasing or signal distortion, will severely impair the denoising quality, ultimately leading to a decrease in hardness detection accuracy.

[0026] Therefore, this embodiment performs modal decomposition on the voltage signal of each shock absorber bearing. By analyzing the disorder of each modal component, the distribution difference of the voltage signal of each shock absorber bearing is determined. By analyzing the correlation between each modal component and all other modal components in the voltage signal of each shock absorber bearing and the difference in center frequency, the correlation of the voltage signal of each shock absorber bearing is determined. Combined with the distribution difference, the modal aliasing of the voltage signal of each shock absorber bearing is determined to optimize the penalty coefficient α and achieve high-precision hardness detection. The specific process is as follows: First, in this embodiment, the voltage signal of each shock absorber bearing is used as the input of the variational mode decomposition algorithm, wherein the number of modal components is 5. In actual application, the implementer can also set the number of modal components according to the specific situation. This embodiment does not impose any special restrictions. Finally, all modal components of the voltage signal of each shock absorber bearing are output.

[0027] Variational mode decomposition algorithm is a well-known technique, and the specific process of using it to decompose voltage signals will not be elaborated here.

[0028] Furthermore, this embodiment analyzes the disorder of each modal component to determine the distribution difference of the voltage signal of each shock absorber bearing. Specifically: In this embodiment, the sum of the differences between the envelope entropy of all modal components and the maximum envelope entropy of all modal components in the voltage signal of each shock absorber bearing is calculated, and the product of the sum and the maximum envelope entropy is used as the distribution difference degree of each shock absorber bearing voltage signal.

[0029] It should be noted that there are many methods to measure the differences between data. In this embodiment, the absolute difference between the envelope entropy of all modal components and the maximum envelope entropy of all modal components is taken as the difference between the envelope entropy of all modal components and the maximum envelope entropy of all modal components. In practical applications, as other implementation methods, implementers may also use other methods such as the square or ratio of the difference to measure the differences between data, depending on the specific circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between data.

[0030] It should be noted that, unless otherwise specified, all methods in this embodiment that involve measuring differences between data use the method of calculating absolute differences.

[0031] The method for calculating the envelope entropy is a well-known technique, and its specific calculation process will not be elaborated here.

[0032] Based on the distribution difference of the voltage signal of each shock absorber bearing, it can be understood that the distribution difference is used to characterize the distinction between noise components and useful signal components in terms of entropy value. It reflects whether the variational mode decomposition algorithm has successfully divided high-entropy noise and low-entropy useful signal into different modes under the current penalty coefficient. If the difference between the envelope entropy of all modal components in the current shock absorber bearing voltage signal and the maximum envelope entropy of all modal components is larger, it indicates that the purity of the modal components is greater than that of the dirtiest mode, indicating that the signal components can be effectively distinguished, which is beneficial for noise reduction. At the same time, if the maximum envelope entropy itself is larger, it directly increases the calculation basis of the distribution difference, which means that there is a noise modal component with very low purity, indicating that the noise has been successfully isolated. Conversely, if the difference between the envelope entropy of all modal components and the maximum envelope entropy in the current shock absorber bearing voltage signal is generally small, it indicates that the purity of each mode is similar and the boundaries are blurred. This suggests that noise is mixed with the useful signal and cannot be effectively distinguished, which is not conducive to noise reduction. At the same time, if the maximum envelope entropy itself is also small, it may mean that the voltage signal itself is very clean, or that noise has seriously contaminated all modes, making it impossible to effectively identify independent noise components. This also reflects the failure of the decomposition effect.

[0033] Furthermore, this embodiment determines the correlation of the voltage signal of each shock absorber bearing by analyzing the correlation between each modal component and all other modal components in the voltage signal of each shock absorber bearing, as well as the difference in center frequency. Specifically: In this embodiment, for each damper bearing voltage signal, the normalized value of the center frequency difference between each modal component and the other modal components is recorded as the frequency difference value between each modal component and the other modal components. The correlation coefficient between each modal component and the other modal components is divided by the frequency difference value, and the result is used as the correlation characteristic value between each modal component and the other modal components. The maximum value among the correlation eigenvalues ​​between each modal component and all other modal components is obtained. The mean of the maximum correlation eigenvalues ​​of all modal components in each shock absorber bearing voltage signal is taken as the correlation of each shock absorber bearing voltage signal.

[0034] It should be noted that there are many methods for calculating the correlation coefficient between signals. In this embodiment, the Pearson correlation coefficient between each modal component and the other modal components is used as the correlation coefficient between each modal component and the other modal components. In practical applications, as other implementation methods, implementers may also use Spearman correlation coefficient or Kendall rank correlation coefficient or other correlation coefficient calculation methods according to specific circumstances. This embodiment does not impose any special restrictions on the selection of correlation coefficient calculation methods.

[0035] The calculation method for the Pearson correlation coefficient is a well-known technique, and its specific calculation process will not be elaborated here.

[0036] Based on the correlation of each shock absorber bearing voltage signal, it can be understood that the correlation is used to characterize the average level of information redundancy between each modal component, reflecting whether the variational mode decomposition algorithm has incorrectly split a physical signal component that should be complete into multiple highly similar modal components. If the correlation coefficient between the current modal component and the other modal components is larger and the difference in center frequency is smaller, the correlation of the corresponding shock absorber bearing voltage signal is larger, indicating that there are a large number of modes with overlapping information in the variational mode decomposition result, that is, serious over-decomposition has occurred, which will destroy the integrity of the voltage signal. Conversely, if the correlation coefficient between the current modal component and the other modal components is generally small and the center frequency difference is large, then the correlation of the corresponding shock absorber bearing voltage signal is smaller, indicating that the modal components obtained by variational mode decomposition are independent of each other and each represents a different physical meaning. This indicates that the decomposition quality is high and the integrity of the voltage signal is well maintained.

[0037] Furthermore, this embodiment determines the modal aliasing degree of each shock absorber bearing voltage signal based on the correlation of each shock absorber bearing voltage signal and in combination with the distribution difference degree. Specifically: In this embodiment, the ratio of the correlation normalization value to the distribution difference normalization value of each shock absorber bearing voltage signal is used as the modal aliasing degree of each shock absorber bearing voltage signal.

[0038] Based on the modal aliasing degree of each shock absorber bearing voltage signal, it can be understood that the modal aliasing degree is used to characterize the combined severity of the two undesirable phenomena of modal aliasing and over-decomposition, reflecting the degree of impurity or distortion of the signal decomposition under the current penalty coefficient. If the correlation of the current shock absorber bearing voltage signal is greater and the distribution difference is smaller, it indicates that the current shock absorber bearing voltage signal is more likely to be over-decomposed, and the modal aliasing problem is more serious. Therefore, the greater the corresponding modal aliasing degree, the more the current shock absorber bearing voltage signal is over-decomposed under the corresponding penalty coefficient. Conversely, if the correlation of the current shock absorber bearing voltage signal is smaller and the distribution difference is greater, it indicates that the modal components of the current shock absorber bearing voltage signal are both independent and clearly defined. The problems of over-decomposition and mode aliasing are not significant. Therefore, the smaller the corresponding mode aliasing, the higher the decomposition quality of the current shock absorber bearing voltage signal under the corresponding penalty coefficient, the higher the purity of the voltage signal, and the lower the degree of distortion.

[0039] Thus, this embodiment comprehensively evaluates modal aliasing and excessive decomposition, that is, by constructing the correlation between the distribution difference of the characterizing signal separation purity and the characterizing information redundancy, and then combining the two into modal aliasing degree, to accurately evaluate the decomposition quality under the current penalty coefficient, and finally provide the optimal decomposition parameters for high-precision hardness detection.

[0040] S2.2: Based on the comprehensive difference between all amplitudes of the voltage signal before and after denoising for each shock absorber bearing, as well as the disorder of each modal component in the voltage signal and the modal aliasing degree, determine the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition; by comparing the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals at the corresponding penalty coefficient and the difference between the voltage signals, and combining the signal denoising degree, determine the optimized penalty coefficient of the current shock absorber bearing voltage signal, and denoise the current shock absorber bearing voltage signal.

[0041] After obtaining the modal aliasing degree of the current signal, this embodiment determines the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition based on the comprehensive difference between all amplitudes before and after denoising of the voltage signal of each shock absorber bearing, as well as the disorder degree of each modal component in the voltage signal and the modal aliasing degree. By comparing the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals at the corresponding penalty coefficient and the difference between the voltage signals, and combining the signal denoising degree, the optimized penalty coefficient of the current shock absorber bearing voltage signal is determined, and the current shock absorber bearing voltage signal is denoised. The specific process is as follows: First, this embodiment determines the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition based on the comprehensive difference between all amplitudes before and after denoising of the voltage signal of each shock absorber bearing, as well as the disorder degree of each modal component in the voltage signal and the mode aliasing degree. Specifically: As one implementation method, in this embodiment, the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition is... The expression is: In the formula, This represents the overall difference between all amplitudes of the shock absorber bearing voltage signal i before and after noise reduction; This represents the maximum value of the envelope entropy of all modal components in the shock absorber bearing voltage signal i; This represents the modal aliasing degree of the shock absorber bearing voltage signal i.

[0042] Preferably, the schematic diagram of the signal denoising extraction process provided in this embodiment is as follows: Figure 2 As shown.

[0043] It should be noted that in this embodiment, the sum of the absolute differences between all corresponding amplitudes of the shock absorber bearing voltage signal i before and after denoising is taken as the comprehensive difference between all amplitudes of the shock absorber bearing voltage signal i before and after denoising.

[0044] Based on the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition, it can be understood that the signal denoising degree is used to characterize the quality of denoising processing of the voltage signal under a specific penalty coefficient. If the comprehensive difference between all amplitudes of the shock absorber bearing voltage signal i before and after denoising is greater, it indicates that the denoising has a greater impact on the original voltage signal. At the same time, if the maximum value of the envelope entropy of all modal components in the shock absorber bearing voltage signal i is greater, and the modal aliasing degree of the shock absorber bearing voltage signal i is smaller, it reflects that the high-entropy noise modal components have been successfully separated. In this case, the greater the comprehensive difference, the more effective the denoising is, and therefore, the greater the corresponding signal denoising degree. Conversely, if the overall difference between all amplitudes of the shock absorber bearing voltage signal i before and after denoising is smaller, it indicates that the denoising has a limited impact on the original voltage signal. At the same time, if its maximum envelope entropy is smaller and the mode aliasing is greater, it reflects that the high-entropy noise mode has not been effectively separated and the decomposition process itself has serious problems. In this case, even if there is a difference, it may be due to signal distortion rather than effective denoising. Therefore, the corresponding signal denoising degree is smaller.

[0045] Furthermore, this embodiment compares the differences in corresponding penalty coefficients between the current shock absorber bearing voltage signal and historical shock absorber bearing voltage signals, as well as the differences between the voltage signals, and combines this with the signal denoising degree to determine the optimized penalty coefficient for the current shock absorber bearing voltage signal, thereby denoising the current shock absorber bearing voltage signal. Specifically: As one implementation method, in this embodiment, the optimized penalty coefficient of the current shock absorber bearing voltage signal is... The expression is: In the formula, This represents the preset initial penalty coefficient for the current shock absorber bearing voltage signal; This represents the normalized value of the modal aliasing degree of the current shock absorber bearing voltage signal; This represents the adjustment direction factor of the current shock absorber bearing voltage signal, which is based on the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals in terms of the corresponding penalty coefficient, the difference between the voltage signals, and the signal denoising degree. This indicates the signal noise reduction level of the current shock absorber bearing voltage signal; This represents the maximum value of the signal denoising among all historical shock absorber bearing voltage signals for which the penalty coefficient is less than the preset initial penalty coefficient of the current shock absorber bearing voltage signal.

[0046] The method for determining the adjustment direction factor is as follows: As one implementation method, in this embodiment, the adjustment direction factor of the current shock absorber bearing voltage signal The expression is: In the formula, , These represent the total number of historical shock absorber bearing voltage signals with a penalty coefficient greater than the preset initial penalty coefficient of the current shock absorber bearing voltage signal, and the total number of historical shock absorber bearing voltage signals with a penalty coefficient less than the preset initial penalty coefficient of the current shock absorber bearing voltage signal, respectively. , They represent The signal noise reduction of the voltage signal of the j-th shock absorber bearing. This represents the signal denoising degree of the voltage signal of the m-th damping bearing; , These respectively represent the current shock absorber bearing voltage signal and... The reciprocal of the difference between the voltage signals of the j-th shock absorber bearing and the... The reciprocal of the difference between the bearing voltage signals of the m-th shock absorber.

[0047] It should be noted that there are many methods for measuring the differences between signals. In this embodiment, the current shock absorber bearing voltage signal is compared with... The DTW distance between the j-th shock absorber bearing voltage signal and the current shock absorber bearing voltage signal is used as the distance between the current shock absorber bearing voltage signal and the current shock absorber bearing voltage signal. The difference between the voltage signals of the j-th shock absorber bearing and the current shock absorber bearing voltage signal is compared with... The DTW distance between the m-th shock absorber bearing voltage signals is used as the current shock absorber bearing voltage signal and its corresponding distance. The difference between the voltage signals of the m-th shock absorber bearing can be addressed in practical applications. As another implementation method, the implementer may also use other methods such as Euclidean distance or Mahalanobis distance to measure the difference between signals, depending on the specific circumstances. This embodiment does not impose any special restrictions.

[0048] It should be noted that the preset initial penalty coefficient is set manually. In this embodiment, the preset initial penalty coefficient is 2000. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0049] The method for calculating the DTW distance is a well-known technique, and its specific calculation process will not be elaborated here.

[0050] Based on the adjustment direction factor, it can be understood that the adjustment direction factor is used to characterize whether the benefit of increasing the penalty coefficient for the current shock absorber bearing voltage signal is greater than the benefit of decreasing the penalty coefficient, reflecting the optimal adjustment direction pointed to by historical data. The adjustment direction factor is affected by the difference between two weighted averages: one is the effect of weighted average denoising of historical shock absorber bearing voltage signals with a penalty coefficient greater than that corresponding to the current shock absorber bearing voltage signal, and the other is the effect of weighted average denoising of historical shock absorber bearing voltage signals with a penalty coefficient smaller than that corresponding to the current shock absorber bearing voltage signal. If the former is significantly greater than the latter, i.e. Greater than This indicates that for historical shock absorber bearing voltage signals similar to the current shock absorber bearing voltage signal, using a larger penalty coefficient is more effective. Therefore, the adjustment direction factor is greater than 0, reflecting that the penalty coefficient should be increased. Conversely, if the latter is significantly larger than the former, that is... Greater than This indicates that for historical signals similar to the current shock absorber bearing voltage signal, using a smaller penalty coefficient is more effective. Therefore, the adjustment direction factor is less than 0, reflecting that the penalty coefficient should be reduced. If the two are almost the same, the adjustment direction factor approaches 0, reflecting that the current penalty coefficient is already in a better range and no adjustment is needed.

[0051] Furthermore, based on the optimized penalty coefficient, it can be understood that the optimized penalty coefficient is used to characterize the penalty coefficient determined to achieve the best noise reduction effect after comprehensively considering the current decomposition quality of the shock absorber bearing voltage signal and historical best practices. The calculation of the optimized penalty coefficient is jointly affected by the current penalty coefficient, the adjustment direction factor, and the modal aliasing degree. When the adjustment direction factor of the current shock absorber bearing voltage signal is greater than 0, the optimized penalty coefficient will be multiplied by the preset initial penalty coefficient. If the modal aliasing degree H of the current shock absorber bearing voltage signal is larger, it indicates that the decomposition quality of the current shock absorber bearing voltage signal is worse, and the adjustment range is also larger. When the adjustment direction factor of the current shock absorber bearing voltage signal is less than 0, the optimization penalty coefficient will be multiplied by H based on the preset initial penalty coefficient. If H is larger, that is, H is closer to 1, the adjusted optimization penalty coefficient is closer to the preset initial penalty coefficient. This reflects that when it is necessary to reduce the penalty coefficient, if the current aliasing degree is already high, the adjustment will be more cautious to avoid overcorrection. Conversely, when the adjustment direction factor is greater than 0, if the modal aliasing degree H of the current shock absorber bearing voltage signal is smaller, it indicates that the current decomposition quality is good, and only a small optimization is needed. Therefore, the smaller the adjustment range, the closer the optimization penalty coefficient is to the preset initial penalty coefficient. When the adjustment direction factor is less than 0, if H is smaller, that is, H is closer to 0, the adjusted optimization penalty coefficient will be much smaller than the preset initial penalty coefficient. This reflects that when it is necessary to reduce the penalty coefficient and the current decomposition quality is good, a larger adjustment can be made more decisively to quickly reach a better state.

[0052] Furthermore, this embodiment denoises the current shock absorber bearing voltage signal based on an optimized penalty coefficient. Specifically: In this embodiment, the current shock absorber bearing voltage signal is used as the input of the variational mode decomposition algorithm, wherein the optimized penalty coefficient of the current shock absorber bearing voltage signal is used as the penalty coefficient in the current variational mode decomposition algorithm, and all modal components of the current shock absorber bearing voltage signal are output. Calculate the envelope entropy of all modal components, reconstruct all modal components except the one with the maximum envelope entropy, and use the reconstructed signal as the noise-reducing voltage signal of the current shock absorber bearing.

[0053] Thus, this embodiment constructs a signal denoising degree that comprehensively evaluates denoising quality, determines the optimal adjustment direction by analyzing historical data, and dynamically adjusts the penalty coefficient by combining the current signal decomposition quality with historical experience, thereby ensuring the stability and optimality of the denoising effect.

[0054] Step S3: Based on the noise-reducing voltage signal of the current shock absorber bearing, measure the hardness of the raceway of the current shock absorber bearing.

[0055] Based on the denoised voltage signal obtained in step S2, the hardness of the raceway of the shock absorber bearing is measured, specifically: In this embodiment, the feature vector of the denoised voltage signal of the current shock absorber bearing is obtained, and the feature vector is used as the input of the pre-trained bearing raceway hardness measurement model to output the hardness of the current shock absorber bearing raceway.

[0056] Among them, the feature vector of the denoised voltage signal is a vector composed of the peak value, valley value, effective value of the signal, peak factor, main resonant frequency and spectral centroid of the denoised voltage signal.

[0057] It should be noted that the method for obtaining the pre-trained bearing raceway hardness measurement model is as follows: Voltage signals from K shock absorber bearings with known standard hardness are collected. Feature vectors of all voltage signals are extracted. The feature vectors of all voltage signals and the standard hardness are used as inputs to a support vector machine (SVM). The SVM is trained to establish a mapping model from "feature vectors" to "standard hardness". The trained model is used as the bearing raceway hardness measurement model. In this embodiment, K is set to 1000. In actual applications, as other implementation methods, implementers can set it according to specific circumstances.

[0058] The training process of support vector machines is a well-known technique and will not be described in detail here.

[0059] Thus, this embodiment extracts the feature vector of a high-quality denoised voltage signal and inputs it into a hardness measurement model pre-trained with a large amount of sample data, thereby achieving a precise and automated mapping from the processed electrical signal to the bearing raceway hardness, improving the accuracy and reliability of shock absorber bearing raceway hardness measurement.

[0060] Based on the same inventive concept as the above methods, this application also provides a shock absorber bearing raceway hardness measuring device based on electromagnetic induction signals, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described shock absorber bearing raceway hardness measuring methods based on electromagnetic induction signals.

[0061] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0062] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0063] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for measuring the raceway hardness of shock absorber bearings based on electromagnetic induction signals, characterized in that, The method includes the following steps: Obtain the voltage signal of each shock absorber bearing as it passes through the electromagnetic induction coil; Modal decomposition is performed on the voltage signal of each shock absorber bearing. By analyzing the disorder of each modal component, the distribution difference of the voltage signal of each shock absorber bearing is determined. By analyzing the correlation between each modal component and all other modal components in the voltage signal of each shock absorber bearing and the difference in center frequency, the correlation of the voltage signal of each shock absorber bearing is determined. Combined with the distribution difference, the modal aliasing of the voltage signal of each shock absorber bearing is determined. Based on the comprehensive difference between all amplitudes of the voltage signal before and after denoising for each shock absorber bearing, as well as the disorder of each modal component in the voltage signal and the modal aliasing, the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition is determined; by comparing the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals at the corresponding penalty coefficient and the difference between the voltage signals, and combining the signal denoising degree, the optimized penalty coefficient of the current shock absorber bearing voltage signal is determined, and the current shock absorber bearing voltage signal is denoised; The hardness of the raceway of the current shock absorber bearing is measured based on the noise-reduced voltage signal of the current shock absorber bearing.

2. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The method for determining the distribution difference of the voltage signal of each shock absorber bearing is as follows: Calculate the sum of the differences between the envelope entropy of all modal components and the maximum envelope entropy of all modal components in the voltage signal of each shock absorber bearing. Multiply the sum by the maximum envelope entropy as the distribution difference of the voltage signal of each shock absorber bearing.

3. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The method for determining the correlation of the voltage signals of each shock absorber bearing is as follows: For each damper bearing voltage signal, the normalized value of the center frequency difference between each modal component and the other modal components is recorded as the frequency difference value between each modal component and the other modal components. The correlation coefficient between each modal component and the other modal components is divided by the frequency difference value, and the result is used as the correlation characteristic value between each modal component and the other modal components. The maximum value among the correlation eigenvalues ​​between each modal component and all other modal components is obtained. The mean of the maximum correlation eigenvalues ​​of all modal components in each shock absorber bearing voltage signal is taken as the correlation of each shock absorber bearing voltage signal.

4. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The modal aliasing degree of each shock absorber bearing voltage signal is the ratio of the correlation normalized value to the distribution difference normalized value of each shock absorber bearing voltage signal.

5. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The expression for the signal denoising degree of each shock absorber bearing voltage signal under the penalty coefficient in the corresponding mode decomposition is as follows: In the formula, This represents the signal denoising degree of the shock absorber bearing voltage signal i under the penalty coefficient in the corresponding mode decomposition; This represents the overall difference between all amplitudes of the shock absorber bearing voltage signal i before and after noise reduction; This represents the maximum value of the envelope entropy of all modal components in the shock absorber bearing voltage signal i; This represents the modal aliasing degree of the shock absorber bearing voltage signal i.

6. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The expression for the optimized penalty coefficient of the current shock absorber bearing voltage signal is as follows: In the formula, This represents the optimized penalty coefficient for the current shock absorber bearing voltage signal; This represents the preset initial penalty coefficient for the current shock absorber bearing voltage signal; This represents the normalized value of the modal aliasing degree of the current shock absorber bearing voltage signal; This represents the adjustment direction factor of the current shock absorber bearing voltage signal, which is based on the difference between the current shock absorber bearing voltage signal and the historical shock absorber bearing voltage signals in terms of the corresponding penalty coefficient, the difference between the voltage signals, and the signal denoising degree. This indicates the signal noise reduction level of the current shock absorber bearing voltage signal; This represents the maximum value of the signal denoising among all historical shock absorber bearing voltage signals for which the penalty coefficient is less than the preset initial penalty coefficient of the current shock absorber bearing voltage signal.

7. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 6, characterized in that, The expression for the adjustment direction factor of the current shock absorber bearing voltage signal is: In the formula, This indicates the adjustment direction factor of the current shock absorber bearing voltage signal; , These represent the total number of historical shock absorber bearing voltage signals with a penalty coefficient greater than the preset initial penalty coefficient of the current shock absorber bearing voltage signal, and the total number of historical shock absorber bearing voltage signals with a penalty coefficient less than the preset initial penalty coefficient of the current shock absorber bearing voltage signal, respectively. , They represent The signal noise reduction of the voltage signal of the j-th shock absorber bearing. This represents the signal denoising degree of the voltage signal of the m-th damping bearing; , These respectively represent the current shock absorber bearing voltage signal and... The reciprocal of the difference between the voltage signals of the j-th shock absorber bearing and the... The reciprocal of the difference between the bearing voltage signals of the m-th shock absorber.

8. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The noise reduction of the current shock absorber bearing voltage signal includes: The current shock absorber bearing voltage signal is used as the input to the mode decomposition algorithm, where the optimized penalty coefficient of the current shock absorber bearing voltage signal is used as the penalty coefficient in the current mode decomposition algorithm, and all modal components of the current shock absorber bearing voltage signal are output. Calculate the envelope entropy of all modal components, reconstruct all modal components except the one with the maximum envelope entropy, and use the reconstructed signal as the noise-reducing voltage signal of the current shock absorber bearing.

9. The method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in claim 1, characterized in that, The measurement of the hardness of the current shock absorber bearing raceway includes: Obtain the feature vector of the denoised voltage signal of the current shock absorber bearing, use the feature vector as input to the pre-trained bearing raceway hardness measurement model, and output the hardness of the current shock absorber bearing raceway.

10. A device for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for measuring the raceway hardness of a shock absorber bearing based on electromagnetic induction signals as described in any one of claims 1-9.

Images