Excitation signal harmonic filtering method and system of residual stress measuring instrument

Abstract

The invention discloses an excitation signal harmonic filtering method and system for a residual stress measuring instrument, and belongs to the technical field of signal processing. The excitation signal read from a magnetic anisotropy residual stress measuring instrument is decomposed to obtain a multi-layer IMF function of the excitation signal, and IMF components containing harmonic components in each layer of IMF components are determined; obtaining the Fourier spectrum of the IMF component containing the harmonic wave, and determining the data length and the sampling frequency of the IMF component containing the harmonic wave; according to the data length and the sampling frequency, the frequency resolution of IMF components containing harmonic waves is determined; the harmonic frequency to be eliminated and the frequency resolution are determined according to the actual situation, the frequency spectrum index corresponding to the harmonic frequency to be eliminated is obtained, the frequency spectrum value of the position of the frequency spectrum index is set to be zero, and the IMF component after harmonic filtering is obtained through inverse Fourier transform. According to the method, harmonic components in the excitation signal can be effectively filtered out, and the accuracy of a measurement result is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of signal processing, and more specifically to a method and system for filtering harmonics of an excitation signal of a residual stress measuring instrument. Background Art

[0002] For magnetic measuring instruments, applying excitation signals of different frequencies to the object to be tested will result in different magnetization parameters (such as residual magnetism, coercive force, etc.) of the object to be tested, which will cause the instrument to deviate from the detection signal, thus affecting the accuracy of the test results. Therefore, ensuring the singleness of the excitation signal frequency is very critical to ensure the accuracy of the test results.

[0003] However, in practical applications, due to the uneven quality of signal generators in magnetic measuring instruments, the presence of nonlinear elements in the circuit and deficiencies in circuit design, the excitation signal is often accompanied by harmonic components. However, the presence of these harmonics will cause the frequency spectrum of the excitation signal to become complex, which will significantly interfere with the accurate identification of the detection signal. Therefore, filtering out the harmonic signal has become an urgent task.

[0004] At present, commonly used filtering technologies include adjustable filters and wavelet transforms. However, adjustable filters are not an ideal choice due to their limited adjustment range, large internal space occupied by the instrument, high power consumption, and increased instrument costs. On the other hand, although the wavelet transform method has a high application frequency in signal processing, its processing results are greatly affected by the selection of wavelet basis and window function, resulting in a certain degree of uncertainty and low universality of the processing results.

[0005] In summary, the existing harmonic filtering technology cannot provide the instrument probe with excitation signals of different frequency values ​​in a timely and fast manner according to the needs of on-site detection due to the uncertainty and instability of the processing results, which affects the accuracy of the measurement results. Summary of the invention

[0006] In response to the problems existing in the above-mentioned fields, the present invention proposes a method and system for filtering harmonics of the excitation signal of a residual stress measuring instrument, which can reduce the uncertainty and instability caused by methods such as adjustable filters and wavelet transforms, thereby improving the accuracy and reliability of the measurement results.

[0007] In order to solve the above technical problems, the present invention discloses a method for filtering harmonics of an excitation signal of a residual stress measuring instrument, comprising the following steps:

[0008] Decompose the excitation signal of the magnetic anisotropic residual stress measuring instrument to obtain the multi-layer IMF function of the excitation signal;

[0009] According to the multi-layer IMF function of the excitation signal, the IMF components containing harmonic components in each layer of IMF components are determined;

[0010] Obtain the Fourier spectrum of the IMF component containing harmonics, determine the data length and sampling frequency of the IMF component containing harmonics; determine the frequency resolution of the IMF component containing harmonics according to the data length and sampling frequency; determine the harmonic frequency and frequency resolution to be eliminated according to actual conditions, obtain the spectrum index corresponding to the harmonic frequency to be eliminated, and set the spectrum value at the spectrum index position to zero, and obtain the IMF component after filtering out the harmonics through inverse Fourier transform.

[0011] Preferably, the determining of the data length and sampling frequency of the IMF component containing harmonics specifically includes:

[0012] Perform Fourier transform on the IMF components containing harmonics, calculate the Fourier spectrum of the IMF components containing harmonics through the fast Fourier transform algorithm, and determine the data length and sampling frequency f s ;

[0013] The IMF component containing harmonics is obtained as x[n], n=0, 1, ..., N-1, where N is the data length;

[0014] X[k]=FFT(x[n]) calculated by the Fast Fourier Transform algorithm, k=0,1,…,N-1;

[0015] The result X[k] of the fast Fourier transform algorithm is a complex number whose magnitude represents the intensity of the frequency component and whose phase represents the phase of the frequency component.

[0016] Preferably, obtaining the spectrum index corresponding to the harmonic frequency to be eliminated comprises the following steps:

[0017] According to the data length and sampling frequency, the frequency resolution is calculated as:

[0018]

[0019] In actual situation, the mth harmonic frequency to be eliminated is determined to be f h =m×f0, where f0 is the fundamental frequency;

[0020] Determine the mth harmonic frequency to be eliminated according to the frequency resolution and actual situation, and calculate the spectrum index corresponding to the harmonic frequency to be eliminated as:

[0021]

[0022] Preferably, obtaining the IMF component after filtering out harmonics by inverse Fourier transform comprises the following steps:

[0023] Take X[kh ]=0, when the harmonic frequency does not exactly correspond to an index, the spectrum index k needs to be h The spectrum value of the position is set to zero, and the processed spectrum X[k] is obtained;

[0024] Perform inverse fast Fourier transform on the processed spectrum X[k], convert the processed spectrum X[k] back to the time domain, and obtain the IMF component after filtering out harmonics:

[0025] y[n]=IFFT(X[k]).

[0026] Preferably, the method further comprises reconstructing the signal of the IMF component after filtering out the harmonics and other IMF components not containing harmonic components to obtain the excitation signal after eliminating the harmonics.

[0027] Preferably, the multi-layer IMF function for obtaining the excitation signal comprises the following steps:

[0028] Collect the excitation signal x(t) of the magnetic anisotropy residual stress measuring instrument;

[0029] Identify all local maximum and local minimum points of the excitation signal x(t);

[0030] All local maximum and minimum points are fitted by cubic spline interpolation to obtain the upper envelope e max (t) and the lower envelope e min (t);

[0031] Calculate the average of the upper and lower envelopes:

[0032]

[0033] Subtract the average of the upper and lower envelopes from the excitation signal x(t) to obtain the signal h(t):

[0034] h(t)=x(t)-m(t)

[0035] The excitation signal x(t) is decomposed into multiple IMF components using the empirical mode decomposition method;

[0036] Each IMF component satisfies two conditions: first, in the entire data segment, the number of extreme points and the number of zero crossing points must be equal or differ by at most one; second, at any point, the average value of the envelope defined by the local maximum point and the local minimum point is zero;

[0037] Determine whether the signal h(t) satisfies the IMF component condition. If it does not, take h(t) as a new signal and repeat the above steps until a signal that satisfies the IMF component condition is obtained, which is recorded as C.i (t), C i (t) is the i-th IMF component;

[0038] Subtract the resulting IMF component from the excitation signal to obtain a residual signal r(t) = x(t) - C i (t);

[0039] Update the new signal h(t) through the residual signal r(t), and continue the above decomposition process. Stop the decomposition when the residual signal is a monotonic function.

[0040] The excitation signal x(t) is expressed as the sum of multiple IMF components and a residual component:

[0041]

[0042] Where n is the number of IMF components, r n (t) is the trend term;

[0043] Discard trend items.

[0044] Preferably, determining the IMF components containing harmonic components in the IMF components of each layer comprises the following steps:

[0045] According to the multi-layer IMF function of the excitation signal, Hilbert transform is performed on each layer of IMF components to obtain the Hilbert transform value of each layer of IMF components, and the Hilbert transform value of each layer of IMF components is calculated to obtain the instantaneous amplitude and instantaneous frequency of each layer of IMF components;

[0046] According to the instantaneous amplitude and instantaneous frequency of each layer of IMF components, the Hilbert spectrum of each layer of IMF components is plotted; according to the Hilbert spectrum of each layer of IMF components, the IMF components containing harmonic components and the IMF components not containing harmonic components are determined.

[0047] Preferably, obtaining the instantaneous amplitude and instantaneous frequency of the IMF components of each layer specifically includes:

[0048] Perform Hilbert transform on each layer of IMF components to obtain the Hilbert transform value H[C i (t)];

[0049] Definition C i The Hilbert transform of (t) is:

[0050]

[0051] Where PV represents the Cauchy principal value integral, and τ represents the integral variable;

[0052] Through the Hilbert transform value, construct Ci The analytical signal of (t) is:

[0053]

[0054] in, represents the instantaneous amplitude, represents the instantaneous phase, Represents the instantaneous frequency.

[0055] Preferably, the determination of the IMF components containing harmonic components and the IMF components not containing harmonic components is to take time and instantaneous frequency as two dimensions, and determine the IMF components containing harmonic components and the IMF components not containing harmonic components by plotting the Hilbert spectrum of each layer of IMF components.

[0056] Preferably, it also includes an excitation signal harmonic filtering system of a residual stress measuring instrument, comprising:

[0057] A signal decomposition module is used to decompose the excitation signal of the magnetic anisotropic residual stress measuring instrument to obtain a multi-layer IMF function of the excitation signal;

[0058] A signal harmonic component determination module is used to determine the IMF components containing harmonic components in each layer of IMF components according to the multi-layer IMF function of the excitation signal;

[0059] The harmonic filtering module is used to obtain the Fourier spectrum of the IMF component containing harmonics, determine the data length and sampling frequency of the IMF component containing harmonics; determine the frequency resolution of the IMF component containing harmonics according to the data length and sampling frequency; determine the harmonic frequency and frequency resolution to be eliminated according to actual conditions, obtain the spectrum index corresponding to the harmonic frequency to be eliminated, and set the spectrum value at the spectrum index position to zero, and obtain the IMF component after filtering out the harmonics through inverse Fourier transform.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] The method for filtering harmonics of an excitation signal proposed by the present invention decomposes the read excitation signal to obtain a multi-layer IMF function, and can decompose a complex signal into a series of components called intrinsic mode functions IMF, each of which has different frequency and time scale characteristics. According to the Fourier spectrum of the IMF component containing harmonics obtained, the data length and sampling frequency of the IMF component containing harmonics are determined, the frequency resolution of the IMF component containing harmonics is determined, and the frequency and amplitude information of the signal changing with time is obtained, which overcomes some limitations of traditional time-frequency analysis methods (such as Fourier transform), can adaptively process nonlinear and non-stationary signals, more accurately reveal the time-frequency characteristics of the signal, and realize an accurate description of the time-frequency characteristics of the signal. According to the actual needs of the site, by determining the spectrum index corresponding to the harmonic frequency to be eliminated, and setting the spectrum value at the spectrum index position to zero, and then performing an inverse Fourier transform to convert the processed spectrum back to the time domain, it is ensured that the harmonics are effectively filtered out, and the IMF component after filtering out the harmonics is obtained, and the real-time dynamic adjustment of the required frequency components is also realized. Furthermore, a pure excitation signal after filtering out harmonics can be obtained through signal reconstruction, and the signal can be used for subsequent magnetic anisotropy residual stress measurement to improve the measurement accuracy and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A flow chart of a method for filtering harmonics of an excitation signal of a residual stress measuring instrument proposed by the present invention;

[0063] Figure 2 An excitation signal of a magnetic anisotropy residual stress measuring instrument provided in an embodiment of the present invention;

[0064] Figure 3 The result of performing EMD decomposition on the excitation signal provided by the embodiment of the present invention;

[0065] Figure 4 The Hilbert spectrum of each layer of IMF components provided by the embodiment of the present invention;

[0066] Figure 5 The embodiment of the present invention provides an excitation signal with harmonic components filtered out. DETAILED DESCRIPTION

[0067] The following will be combined with the attached embodiment of the present invention Figure 1-Figure 5 , the technical solutions in the embodiments of the present invention are clearly and completely described. It should be understood that the terms described in the present invention are only used to describe specific implementation methods and are not used to limit the present invention.

[0068] In order to accurately obtain the excitation signal with a single frequency component, and to provide the instrument probe with excitation signals with different single frequency values ​​in a timely and fast manner according to the needs of on-site detection, such as Figure 1 As shown, the present invention proposes a method for filtering harmonics of an excitation signal of a residual stress measuring instrument.

[0069] The method aims to reduce the uncertainty and instability of the processing results caused by the selection of filters, wavelet bases and window functions by designing a more stable and universal filtering method, thereby improving the accuracy and reliability of the measurement results. According to the specific needs of the magnetic anisotropic residual stress measuring instrument, the harmonic components in the excitation signal are effectively filtered out to ensure the authenticity and accuracy of the measurement signal. The overall performance of the measuring instrument is improved, so that it has a wider application prospect in the field of magnetic measurement and provides more accurate measurement methods for related industries.

[0070] The method specifically comprises the following steps:

[0071] S1: Signal acquisition and preprocessing

[0072] A high-performance sensor is used to collect or read the excitation signal x(t) of the magnetic anisotropy residual stress measuring instrument.

[0073] S2: Empirical Mode Decomposition (EMD)

[0074] EMD is an adaptive data processing method, which is particularly suitable for the analysis of nonlinear and non-stationary signals. Its basic idea is to decompose complex signals into a series of components called intrinsic mode functions (IMFs), each of which has different frequency and time scale characteristics and meets certain conditions.

[0075] Use EMD to decompose the excitation signal x(t) into multiple IMF components, including:

[0076] Identify all local maximum and local minimum points of the excitation signal x(t);

[0077] All local maximum and minimum points are fitted by cubic spline interpolation to obtain the upper envelope e max (t) and the lower envelope e min (t);

[0078] Calculate the average of the upper and lower envelopes:

[0079]

[0080] Subtract the average of the upper and lower envelopes from the excitation signal x(t) to obtain the signal h(t):

[0081] h(t)=x(t)-m(t)

[0082] Each IMF component must meet two conditions: first, in the entire data segment, the number of extreme points and the number of zero-crossing points must be equal or differ by at most one; second, at any point, the average value of the envelope defined by the local maximum point and the local minimum point is zero. These conditions ensure that the IMF component has the characteristics of a local, single frequency component, and can better reflect the local characteristics and change laws of the signal.

[0083] Determine whether the signal h(t) satisfies the IMF component condition. If it does not, take h(t) as a new signal and repeat the above steps until a signal that satisfies the IMF component condition is obtained, which is recorded as C. i (t), C i (t) is the i-th IMF component;

[0084] Subtract the resulting IMF component from the excitation signal to obtain a residual signal r(t) = x(t) - C i (t);

[0085] Take the remaining signal as the new signal and continue the above decomposition process. Stop the decomposition when the remaining signal is a monotonic function.

[0086] Through such a decomposition process, the excitation signal x(t) is expressed as the sum of multiple IMF components and a residual component:

[0087]

[0088] Where n is the number of IMF components, r n (t) is the trend term, which is discarded.

[0089] The excitation signal x(t) is decomposed, and the complex excitation signal is decomposed into a series of IMF components with different frequencies and time scales.

[0090] S3: Hilbert-Huang Transform (HHT) analysis

[0091] HHT is a time-frequency analysis method, which mainly consists of two parts: empirical mode decomposition (EMD) and Hilbert transform (HT). It can overcome some limitations of traditional time-frequency analysis methods (such as Fourier transform), can adaptively process nonlinear and non-stationary signals, and more accurately reveal the time-frequency characteristics of signals.

[0092] The Hilbert transform processes each IMF component to obtain its analytical signal, and then obtains the instantaneous frequency and instantaneous amplitude.

[0093] Specifically, according to the multi-layer IMF function, Hilbert transform is performed on the IMF components of each layer to obtain the Hilbert transform values ​​of the IMF components of each layer; according to the Hilbert transform values ​​of the IMF components of each layer, the instantaneous amplitude and instantaneous frequency of the IMF components of each layer are calculated.

[0094] Perform Hilbert transform on each layer of IMF components to obtain the Hilbert transform value H[C i (t)].

[0095] Definition C i The Hilbert transform of (t) is:

[0096]

[0097] Where PV represents the Cauchy principal value integral and τ represents the integral variable.

[0098] Through the Hilbert transform value, construct C i The analytical signal of (t) is:

[0099]

[0100] in, represents the instantaneous amplitude, represents the instantaneous phase, Represents the instantaneous frequency.

[0101] In this way, the frequency and amplitude information of the signal changing with time can be obtained, thus achieving an accurate description of the time-frequency characteristics of the signal.

[0102] Taking time and instantaneous frequency as two dimensions and using color to represent instantaneous amplitude, the Hilbert spectrum of each layer of IMF components is plotted; based on the Hilbert spectrum of each layer of IMF components, the IMF components containing harmonic components and the IMF components not containing harmonic components are determined.

[0103] S4: Direct zeroing method to eliminate harmonics

[0104] Perform Fourier transform FFT on the IMF component containing harmonics to obtain the corresponding Fourier spectrum; based on the corresponding Fourier spectrum, determine the spectrum index corresponding to the harmonic frequency to be eliminated, and set the spectrum value at the spectrum index position to zero, and obtain the IMF component after filtering out the harmonics through inverse Fourier transform.

[0105] 1) Perform Fourier transform on the IMF components containing harmonics to determine the data length and sampling frequency:

[0106] Assume that the IMF component containing harmonics is x[n], n=0,1,…,N-1, where N is the number of data points;

[0107] Determine the sampling frequency f s ;

[0108] Use the fast Fourier transform algorithm to calculate X[k]=FFT(x[n]), k=0,1,…,N-1;

[0109] When X[k] is a complex number, its amplitude represents the intensity of the sampling frequency component, and its phase represents the phase of the sampling frequency component.

[0110] 2) Determine the spectrum index corresponding to the harmonic frequency to be eliminated

[0111] Calculate the frequency resolution:

[0112]

[0113] Determine the mth harmonic frequency f to be eliminated according to the actual situation h =m×f0, f0 is the fundamental frequency;

[0114] Calculate the spectrum index:

[0115]

[0116] Among them, k h is the spectrum index corresponding to the mth harmonic frequency to be eliminated.

[0117] 3) Set the spectrum value corresponding to the harmonic frequency to zero

[0118] Let X[k h ]=0, when the harmonic frequency does not exactly correspond to an index, the spectrum index k needs to be h The spectrum value of the position is set to zero to obtain the processed spectrum X[k] to ensure that the harmonics are effectively eliminated.

[0119] 4) Perform inverse Fourier transform

[0120] Perform inverse fast Fourier transform on the processed spectrum X[k], convert the processed spectrum X[k] back to the time domain, and obtain the IMF component after filtering out harmonics:

[0121] y[n]=IFFT(X[k])

[0122] S5: Reconstruct the IMF components after filtering out harmonics and the IMF without harmonic components to obtain a pure excitation signal after eliminating harmonics. This signal can be used for subsequent magnetic anisotropic residual stress measurement to improve the measurement accuracy and reliability.

[0123] The present invention also proposes an excitation signal harmonic filtering system for a residual stress measuring instrument, comprising:

[0124] A signal decomposition module is used to decompose the excitation signal of the magnetic anisotropic residual stress measuring instrument to obtain a multi-layer IMF function of the excitation signal;

[0125] A signal harmonic component determination module is used to determine the IMF components containing harmonic components in each layer of IMF components according to the multi-layer IMF function of the excitation signal;

[0126] The harmonic filtering module is used to obtain the Fourier spectrum of the IMF component containing harmonics, determine the data length and sampling frequency of the IMF component containing harmonics; determine the frequency resolution of the IMF component containing harmonics according to the data length and sampling frequency; determine the harmonic frequency and frequency resolution to be eliminated according to actual conditions, obtain the spectrum index corresponding to the harmonic frequency to be eliminated, and set the spectrum value at the spectrum index position to zero, and obtain the IMF component after filtering out the harmonics through inverse Fourier transform.

[0127] The harmonic filtering method of the excitation signal of the residual stress measuring instrument proposed in the present invention decomposes the read excitation signal to obtain a multi-layer IMF function, which can decompose the complex signal into a series of components called intrinsic mode functions IMF, each of which has different frequency and time scale characteristics. According to the Fourier spectrum of the IMF component containing harmonics obtained, the data length and sampling frequency of the IMF component containing harmonics are determined, and the frequency resolution of the IMF component containing harmonics is determined to obtain the frequency and amplitude information of the signal changing with time, which overcomes some limitations of traditional time-frequency analysis methods (such as Fourier transform), can adaptively process nonlinear and non-stationary signals, more accurately reveal the time-frequency characteristics of the signal, and achieve accurate description of the time-frequency characteristics of the signal. By determining the spectrum index corresponding to the harmonic frequency to be eliminated, and setting the spectrum value at the spectrum index position to zero, and then performing inverse Fourier transform to convert the processed spectrum back to the time domain, to ensure that the harmonics are effectively filtered out, the IMF component after filtering out the harmonics is obtained, and through further signal reconstruction, a pure excitation signal after filtering out the harmonics can be obtained. This signal can be used for subsequent magnetic anisotropy residual stress measurement to improve the measurement accuracy and reliability. According to the actual needs of the site, the IMF function containing the corresponding frequency components is retained to achieve harmonic filtering, and the real-time dynamic adjustment of the required frequency components is also achieved.

[0128] The method for filtering harmonics of the excitation signal of the residual stress measuring instrument proposed in the present invention has the following advantages:

[0129] 1. By accurately filtering out the harmonic interference in the excitation signal, the measurement error is effectively reduced, making the measurement results of magnetic anisotropic residual stress more accurate and reliable, providing more valuable data support for material performance evaluation and engineering structure analysis.

[0130] 2. The present invention integrates a variety of advanced technologies and can flexibly adjust the harmonic filtering strategy according to different measurement scenarios and requirements. Whether facing complex signal environments or diverse measurement tasks, it can achieve the best harmonic filtering effect, greatly improving the applicability and versatility of the method.

[0131] 3. In the process of filtering out harmonics, attention is paid to the protection of the fundamental wave and useful components of the excitation signal, minimizing the impact on signal integrity. This ensures the sensitivity and stability of the measurement system, so that the measurement results can truly reflect the magnetic anisotropic residual stress state of the material.

[0132] 4. The adaptive characteristics of EMD and HHT technologies enable the method of the present invention to adaptively process excitation signals of various types and characteristics without having a deep understanding of the specific characteristics of the signal in advance. Whether it is the change of signal frequency or the complexity of harmonic components, the method can effectively cope with it and has strong practical application value and reliability.

[0133] Example

[0134] In order to verify the feasibility of the method proposed in the present invention, the excitation signal harmonic reconstruction method of the residual stress measuring instrument proposed in the present invention is verified through the following examples.

[0135] The excitation signal of the magnetic anisotropy residual stress measuring instrument read in this embodiment is as follows: Figure 2 As shown, the excitation signal is decomposed by EMD to obtain 7 IMF components and a trend term, as shown in Figure 3 As shown. Plot the Hilbert spectrum of each layer of IMF components, as Figure 4 As shown, the Hilbert spectra of the seven IMF components correspond to Figure 4 As shown in Figures (a) to (g).

[0136] Depend on Figure 4 As can be seen in Figure (a), the harmonic component 300Hz is clearly visible in the Hilbert spectrum of the IMF1 component.

[0137] The IMF1 component is processed by direct zeroing method to eliminate the harmonic component. Then the signal is reconstructed to obtain a new excitation signal such as Figure 5 shown.

[0138] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0139] In addition, unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as commonly understood by those skilled in the art to which the present invention belongs. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods related to the documents. In the event of any conflict with any incorporated document, the content of this specification shall prevail.

Claims

1. A method for filtering harmonics of an excitation signal of a residual stress measuring instrument, characterized in that: The following steps are involved: Decompose the excitation signal of the magnetic anisotropic residual stress measuring instrument to obtain the multi-layer IMF function of the excitation signal; According to the multi-layer IMF function of the excitation signal, the IMF components containing harmonic components in each layer of IMF components are determined; Acquire the Fourier spectrum of the IMF component containing harmonics, determine the data length and sampling frequency of the IMF component containing harmonics; determine the frequency resolution of the IMF component containing harmonics according to the data length and the sampling frequency; The harmonic frequency and frequency resolution to be eliminated are determined according to the actual situation, the spectrum index corresponding to the harmonic frequency to be eliminated is obtained, and the spectrum value at the spectrum index position is set to zero. The IMF component after filtering out the harmonics is obtained through inverse Fourier transform.

2. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 1, characterized in that: The data length and sampling frequency of the IMF component containing harmonics specifically include: Perform Fourier transform on the IMF components containing harmonics, calculate the Fourier spectrum of the IMF components containing harmonics through the fast Fourier transform algorithm, and determine the data length and sampling frequency f s ; The IMF component containing harmonics is obtained as x[n], n=0, 1, ..., N-1, where N is the data length; X[k]=FFT(x[n]) calculated by the Fast Fourier Transform algorithm, k=0,1,…,N-1; The result X[k] of the fast Fourier transform algorithm is a complex number whose magnitude represents the intensity of the frequency component and whose phase represents the phase of the frequency component.

3. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 2, characterized in that: The step of obtaining the spectrum index corresponding to the harmonic frequency to be eliminated comprises the following steps: According to the data length and sampling frequency, the frequency resolution is calculated as: In actual situation, the mth harmonic frequency to be eliminated is determined to be f h =m×f0, where f0 is the fundamental frequency; Determine the mth harmonic frequency to be eliminated according to the frequency resolution and actual situation, and calculate the spectrum index corresponding to the harmonic frequency to be eliminated as:

4. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 3, characterized in that: The method of obtaining the IMF component after filtering out harmonics by inverse Fourier transform comprises the following steps: Take X[k h ]=0, when the harmonic frequency does not exactly correspond to an index, the spectrum index k needs to be h The spectrum value of the position is set to zero, and the processed spectrum X[k] is obtained; Perform inverse fast Fourier transform on the processed spectrum X[k], convert the processed spectrum X[k] back to the time domain, and obtain the IMF component after filtering out harmonics: y[n]=IFFT(X[k]).

5. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 4, characterized in that: The method also includes reconstructing the signal of the IMF component after filtering out the harmonics and other IMF components that do not contain harmonic components to obtain the excitation signal after eliminating the harmonics.

6. The method for removing harmonics from the excitation signal of a residual stress measuring instrument according to claim 1, characterized in that: The multi-layer IMF function for obtaining the excitation signal comprises the following steps: Collect the excitation signal x(t) of the magnetic anisotropy residual stress measuring instrument; Identify all local maximum and local minimum points of the excitation signal x(t); All local maximum and minimum points are fitted by cubic spline interpolation to obtain the upper envelope e max (t) and the lower envelope e min (t); Calculate the average of the upper and lower envelopes: Subtract the average of the upper and lower envelopes from the excitation signal x(t) to obtain the signal h(t): h(t)=x(t)-m(t) The excitation signal x(t) is decomposed into multiple IMF components using the empirical mode decomposition method; Each IMF component satisfies two conditions: first, in the entire data segment, the number of extreme points and the number of zero crossing points must be equal or differ by at most one; second, at any point, the average value of the envelope defined by the local maximum point and the local minimum point is zero; Determine whether the signal h(t) satisfies the IMF component condition. If it does not, take h(t) as a new signal and repeat the above steps until a signal that satisfies the IMF component condition is obtained, which is recorded as C. i (t), C i (t) is the i-th IMF component; Subtract the resulting IMF component from the excitation signal to obtain a residual signal r(t) = x(t) - C i (t); Update the new signal h(t) through the residual signal r(t), and continue the above decomposition process. Stop the decomposition when the residual signal is a monotonic function. The excitation signal x(t) is expressed as the sum of multiple IMF components and a residual component: Where n is the number of IMF components, r n (t) is the trend term; Discard trend items.

7. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 6, characterized in that: The step of determining the IMF components containing harmonic components in the IMF components of each layer comprises the following steps: According to the multi-layer IMF function of the excitation signal, Hilbert transform is performed on each layer of IMF components to obtain the Hilbert transform value of each layer of IMF components, and the Hilbert transform value of each layer of IMF components is calculated to obtain the instantaneous amplitude and instantaneous frequency of each layer of IMF components; According to the instantaneous amplitude and instantaneous frequency of each layer of IMF components, the Hilbert spectrum of each layer of IMF components is plotted; according to the Hilbert spectrum of each layer of IMF components, the IMF components containing harmonic components and the IMF components not containing harmonic components are determined.

8. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 7, characterized in that: The instantaneous amplitude and instantaneous frequency of the IMF components of each layer are obtained, specifically including: Perform Hilbert transform on each layer of IMF components to obtain the Hilbert transform value H[C i (t)]; Definition C i The Hilbert transform of (t) is: Where PV represents the Cauchy principal value integral, and τ represents the integral variable; Through the Hilbert transform value, construct C i The analytical signal of (t) is: in, represents the instantaneous amplitude, represents the instantaneous phase, Represents the instantaneous frequency.

9. The method for removing harmonics from the excitation signal of the residual stress measuring instrument according to claim 8, characterized in that: The method of determining the IMF components containing harmonic components and the IMF components not containing harmonic components is to use time and instantaneous frequency as two dimensions, and determine the IMF components containing harmonic components and the IMF components not containing harmonic components by drawing the Hilbert spectrum of each layer of IMF components.

10. An excitation signal harmonic filtering system for a residual stress measuring instrument, characterized in that: include: A signal decomposition module is used to decompose the excitation signal of the magnetic anisotropic residual stress measuring instrument to obtain a multi-layer IMF function of the excitation signal; A signal harmonic component determination module is used to determine the IMF components containing harmonic components in each layer of IMF components according to the multi-layer IMF function of the excitation signal; The harmonic filtering module is used to obtain the Fourier spectrum of the IMF component containing harmonics, determine the data length and sampling frequency of the IMF component containing harmonics; and determine the frequency resolution of the IMF component containing harmonics according to the data length and sampling frequency; The harmonic frequency and frequency resolution to be eliminated are determined according to the actual situation, the spectrum index corresponding to the harmonic frequency to be eliminated is obtained, and the spectrum value at the spectrum index position is set to zero. The IMF component after filtering out the harmonics is obtained through inverse Fourier transform.

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