A correction processing method for vibration measurement data of vibration sensor

Abstract

The present invention provides a correction processing method for vibration measurement data of a vibration sensor, including an interpolation calibration method and an actual calculation full-frequency domain data correction processing method. The steps of the interpolation calibration method are as follows: the working bandwidth Fw of the probe is divided into n sub-bandwidths, and each sub-bandwidth is = Fw / nHz, and a fixed-frequency output with a fixed amplitude is generated on the vibration table in turn at intervals, the acceleration data of the probe is collected, and the effective value Ai in the time domain is calculated, and compared with the standard value Abi of the vibration table output, the calibration coefficient Fx[i]=Abi / Ai of the frequency point is obtained. Through the correction processing method of this scheme, the accuracy of the medium and high frequency data of the vibration probe can be greatly improved, and then the accuracy of the overall vibration data of the vibration probe can be improved. The corrected three-axis data can be within 5% within the range of 5kHz, which is significantly improved, the amount of correction data is small, the processing is simple, and it can be applied on mainstream single-chip microcomputers. The parameters are flexible to adjust, and the specific points that need to be calibrated can be flexibly adjusted according to actual needs.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of methods for improving the accuracy of vibration monitoring data of a vibration sensor, and in particular to a correction processing method for vibration measurement data of a vibration sensor. Background Art

[0002] MEMS accelerometers have the characteristics of small size and low power consumption. They can significantly reduce the power consumption, volume and system cost of vibration probes when used in rotating equipment monitoring systems. However, the frequency range of most MEMS accelerometer chips that guarantee linearity is very low and cannot be used for high-frequency tests in industrial sites. The performance of some chips is slightly better, with acceptable accuracy below 1kHz, but at 3-5kHz, the measured amplitude will be greatly attenuated. In the intermediate stage, the measured data may be amplified or reduced by a certain proportion (some chips amplify by more than 20% and attenuate by more than 50%). The three-axis amplitude-frequency characteristics of three-axis MEMS chips are also very different, and a unified processing method is needed. See Figure 3 shown.

[0003] Based on the above, it can be seen that the amplitude-frequency response characteristics of existing MEMS chips (accelerometers) are poor, and high-frequency data attenuation is obvious. If its data is used directly, various time domain and frequency domain measurement results will have obvious deviations from standard equipment, making it difficult to apply to the field of industrial monitoring. Summary of the invention

[0004] The present invention mainly provides a correction processing method for vibration measurement data of a vibration sensor, which is used to solve the technical problems raised in the above-mentioned background technology.

[0005] The technical solution adopted by the present invention to solve the above technical problems is:

[0006] A correction processing method for vibration measurement data of a vibration sensor includes an interpolation calibration method and an actual calculation full-frequency domain data correction processing method. The steps of the interpolation calibration method are as follows:

[0007] S1: Divide the working bandwidth Fw of the probe into n sub-bandwidths, and the bandwidth of each sub-bandwidth is = Fw / nHz, which generates fixed-frequency outputs of fixed amplitude on the vibration table at intervals.

[0008] S2: Collect the acceleration data of the probe and calculate the effective value Ai in the time domain.

[0009] S3: Compared with the standard value Abi of the vibration table output, the calibration coefficient Fx[i]=Abi / Ai of the frequency point is obtained, and a total of n+1 correction coefficients Fx[n+1] are obtained.

[0010] The steps of actually calculating the full-frequency domain data correction processing method are:

[0011] S1: Continuously collect m points of raw data at the working sampling frequency and record the total collection time T.

[0012] S2: Perform Fourier transform FFT on the collected data to obtain the original data of each frequency point in the frequency domain.

[0013] S3: Use 1 / T as the actual frequency interval of the spectrum line and as the basis for calculating the frequency of each spectrum line.

[0014] S4: For each spectral line k, first calculate the actual frequency f[k] of the spectral line, determine the sub-frequency band that the spectral line falls into, and then use the frequency domain correction coefficients at the two endpoints of the frequency band to perform linear interpolation to find the correction coefficient Fx[k] at f[k], and multiply the amplitude of the spectral line by Fx[k] to obtain the accurate amplitude of the spectral line.

[0015] S5: Correct all spectral lines in turn. After the correction of this axis data is completed, correct all three axis data in turn. Perform inverse Fourier transform IFFT on the corrected frequency domain data to obtain accurate time domain data. Then use the calibrated time domain data for subsequent related processing.

[0016] Preferably, the specific method for collecting the acceleration data of the probe and calculating the time domain effective value Ai is:

[0017] Starting from a certain vibration frequency f1 (for example, 200 Hz), calibrate the acceleration at each frequency point at a certain frequency interval (for example, 200 Hz) to fn (for example, 5000 Hz): calculate the effective value A[i].

[0018] Preferably, in the method for calculating the effective value Ai in the time domain, F0 is specially processed, and the 50 Hz point can be taken for calibration to replace the vibration coefficient of 0 Hz (the vibration table cannot output, and the calibration point offset has a slight effect on the low frequency, but it can be ignored).

[0019] Preferably, for a spectral line k, the method for calculating the actual frequency f[k] of the spectral line is:

[0020] The frequency of the kth spectral line is: k*(1 / T)=k / T; (k: 0-N / 2-1).

[0021] Preferably, the specific method for obtaining the correction coefficient Fx[k] at f[k] is:

[0022] The frequency of the kth spectral line is divided by the frequency calibration interval (for example, 200Hz) to obtain the correction index Ck = k / T / , where Ck is a floating point number, and its integer part is Cz, which represents the index of the first correction coefficient used for the calculation of the spectral line. Cz+1 is the index of the second correction coefficient used for the calculation of the spectral line. The decimal part of Ck is Cx, and the correction coefficient of the kth spectral line is calculated as follows:

[0023] Fx[k]=(Fx[Cz+1]- Fx[Cz]) Cx+Fx[Cz].

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows: through the correction processing method of this scheme, the accuracy of the medium and high frequency data of the vibration probe can be greatly improved, thereby improving the accuracy of the overall vibration data of the vibration probe. When applied to a certain sampling rate of the kx224-1053 chip, before correction, the 1400Hz data of the X and Y axes began to exceed 5%, and from 1800Hz to 3200Hz, the data was 10-20% larger, and the data decreased at higher frequencies; the original data of the Z axis was more than 50% smaller at 5kHz. The corrected three-axis data can be within 5% within the range of 5kHz, which is a significant improvement. The amount of corrected data is small and the processing is simple. It can be applied on mainstream single-chip microcomputers, and the parameters can be adjusted flexibly. The specific points that need to be calibrated can be flexibly adjusted according to actual needs.

[0025] The present invention will be explained in detail below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the X-axis calibration process of the present invention;

[0027] Figure 2 It is a schematic diagram of the correction process of all spectral lines in the X-axis frequency domain of the present invention;

[0028] Figure 3 This is the amplitude-frequency response curve of a MEMS chip. DETAILED DESCRIPTION

[0029] To facilitate understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings, but the present invention can be implemented in different forms and is not limited to the embodiments described in the text. On the contrary, these embodiments are provided to make the content disclosed in the present invention more thorough and comprehensive.

[0030] It should be noted that when an element is referred to as being "fixed on" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used in this article are for illustrative purposes only.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly connected by technicians in the technical field to which the present invention belongs. The terminology used in the specification of the present invention is for the purpose of describing specific embodiments and is not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0032] Please refer to the attached Figure 1-3 A correction processing method for vibration measurement data of a vibration sensor includes an interpolation calibration method and an actual calculation full-frequency domain data correction processing method. The steps of the interpolation calibration method are:

[0033] S1: Divide the working bandwidth Fw of the probe into n sub-bandwidths, and the bandwidth of each sub-bandwidth is = Fw / nHz, which generates fixed-frequency outputs of fixed amplitude on the vibration table at intervals.

[0034] S2: Collect the acceleration data of the probe and calculate the effective value Ai in the time domain.

[0035] S3: Compared with the standard value Abi of the vibration table output, the calibration coefficient Fx[i]=Abi / Ai of the frequency point is obtained, and a total of n+1 correction coefficients Fx[n+1] are obtained.

[0036] The actual steps of calculating the full-frequency domain data correction processing method are:

[0037] S1: Continuously collect m points of raw data at the working sampling frequency and record the total collection time T.

[0038] S2: Perform Fourier transform FFT on the collected data to obtain the original data of each frequency point in the frequency domain.

[0039] S3: Use 1 / T as the actual frequency interval of the spectrum line and as the basis for calculating the frequency of each spectrum line.

[0040] S4: For each spectral line k, first calculate the actual frequency f[k] of the spectral line, determine the sub-frequency band that the spectral line falls into, and then use the frequency domain correction coefficients at the two endpoints of the frequency band to perform linear interpolation to find the correction coefficient Fx[k] at f[k], and multiply the amplitude of the spectral line by Fx[k] to obtain the accurate amplitude of the spectral line.

[0041] S5: Correct all spectral lines in turn. After the correction of this axis data is completed, correct all three axis data in turn. Perform inverse Fourier transform IFFT on the corrected frequency domain data to obtain accurate time domain data. Then use the calibrated time domain data for subsequent related processing.

[0042] The specific method for collecting the acceleration data of the probe and calculating the effective value Ai in the time domain is:

[0043] Starting from a certain vibration frequency f1 (for example, 200 Hz), calibrate the acceleration at each frequency point at a certain frequency interval (for example, 200 Hz) to fn (for example, 5000 Hz): calculate the effective value A[i].

[0044] In the method of calculating the effective value Ai in the time domain, F0 is specially processed, and the 50Hz point can be taken for calibration to replace the vibration coefficient of 0Hz (the vibration table cannot output, and the calibration point offset has a slight effect on the low frequency, but it can be ignored).

[0045] For spectral line k, the method to calculate the actual frequency f[k] of the spectral line is:

[0046] The frequency of the kth spectral line is: k*(1 / T)=k / T; (k: 0-N / 2-1).

[0047] The specific method to obtain the correction coefficient Fx[k] at f[k] is:

[0048] The frequency of the kth spectral line is divided by the frequency calibration interval (for example, 200Hz) to obtain the correction index Ck = k / T / , where Ck is a floating point number, and its integer part is Cz, which represents the index of the first correction coefficient used for the calculation of the spectral line. Cz+1 is the index of the second correction coefficient used for the calculation of the spectral line. The decimal part of Ck is Cx, and the correction coefficient of the kth spectral line is calculated as follows:

[0049] Fx[k]=(Fx[Cz+1]- Fx[Cz]) Cx+Fx[Cz].

[0050] The specific operation mode of the present invention is as follows:

[0051] Calibration method:

[0052] Place the vibration probe or chip on a standard vibration table, which generates a fixed-amplitude acceleration vibration value (such as 2g), and the vibration frequency is output according to the test point requirements.

[0053] The probe collects a fixed number (e.g. 4096) of acceleration data at a fixed acquisition frequency (e.g. 12800 Hz) each time, and calculates the corresponding acceleration effective value;

[0054] Divide the acquisition frequency by 2.56 to get the analysis frequency of this acquisition frequency (for example, 5000Hz). According to the analysis frequency and the number of calibration points (for example, 25+1=26), determine the calibration frequency interval (5000 / 25=200Hz).

[0055] Determine the number of calibration points required based on actual needs (balance between accuracy and calibration efficiency, memory usage, etc.);

[0056] Starting from a certain vibration frequency f1 (for example, 200Hz), calibrate the acceleration at each frequency point from a certain frequency interval (for example, 200Hz) to fn (for example, 5000Hz): calculate the effective value A[i], compare it with the vibration output standard value Ab[i] of the vibration table, and obtain the frequency domain correction coefficient Fx[i] = Ab[i] / A[i] for each frequency point.

[0057] Among them, F0 is specially processed, and the 50Hz point can be used for calibration to replace the vibration coefficient of 0Hz (the vibration table cannot output, and the calibration point offset has a slight effect on the low frequency, but it can be ignored).

[0058] A total of n+1 calibration coefficients are obtained.

[0059] Perform the above steps to calibrate the three axes in sequence.

[0060] Correction method during actual measurement:

[0061] Continuously collect N points of raw data at the working sampling frequency, and record the total collection time T. This time needs to be accurately measured, because the acquisition frequency of MEMS chips often has a large error, even up to about 5%, and accurate measured data is needed to accurately perform post-correction in the frequency domain.

[0062] Perform N (4096) point real Fourier transform FFT on the collected data to obtain the original data of each frequency point in the frequency domain and obtain N / 2 frequency domain spectrum lines.

[0063] The actual accurate spectrum interval is the reciprocal of the total sampling time T (in seconds), that is: 1 / T.

[0064] The frequency of the kth spectral line is: k*(1 / T)=k / T; (k: 0-N / 2-1).

[0065] The amplitude correction method for the kth spectral line is as follows:

[0066] Divide the frequency of the kth spectral line by the frequency calibration interval (e.g. 200Hz) to get the correction index Ck = k / T / , where Ck is a floating point number, and its integer part is Cz, which represents the index of the first correction coefficient used for the calculation of the spectral line, and Cz+1 is the index of the second correction coefficient used for the calculation of the spectral line. The decimal part of Ck is Cx.

[0067] For example, if the spectral line frequency is 2500Hz, then Ck=12.5, Cz=12, Cz+1=13, that is, the 12th and 13th correction coefficients are used for interpolation calculation.

[0068] The correction coefficient of the kth spectral line is calculated as follows:

[0069] Fx[k] = (Fx[Cz+1]- Fx[Cz]) Cx + Fx[Cz];

[0070] The original amplitude value A[k] of the kth spectral line is multiplied by the correction coefficient Fx[k] to obtain the corrected accurate value Az[k], that is: Az[k] = A[k]*Fx[k];

[0071] According to the above steps, each spectral line is corrected in turn to obtain accurate frequency domain data.

[0072] By performing an inverse fast Fourier transform (IFFT) on the frequency domain data, accurate acceleration time domain data can be obtained, and then the acceleration data can be used to calculate the effective value of acceleration, the kurtosis value, or further integrated to obtain derived data such as velocity and displacement.

[0073] The above corrections are performed on the XYZ axes in sequence.

[0074] If the data consistency of the acceleration chip is good, default values ​​can be set for some correction coefficients according to the test results, or only the parts with larger errors can be corrected to reduce the workload of correction.

[0075] During calibration and calculation, low and high frequencies outside the working frequency band are filtered before the above operations.

[0076] The above is an exemplary description of the present invention in combination with the accompanying drawings. It is obvious that the specific implementation of the present invention is not limited to the above-mentioned method. As long as such non-substantial improvements are made by adopting the method concept and technical solution of the present invention, or the concept and technical solution of the present invention are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. A correction processing method for vibration measurement data of a vibration sensor, comprising an interpolation calibration method and an actual calculation full-frequency domain data correction processing method, characterized in that: The steps of the interpolation calibration method are: S1: Divide the working bandwidth Fw of the probe into n sub-bandwidths, and the bandwidth of each sub-bandwidth is Δf = Fw / GHz, and generate fixed-frequency outputs with fixed amplitude on the vibration table in turn at intervals of Δf; S2: Collect the acceleration data of the probe and calculate the effective value Ai in the time domain; S3: Compare with the standard value Abi of the vibration table output to obtain the calibration coefficient Fx[i]=Abi / Ai of the frequency point, and obtain n+1 correction coefficients Fx[n+1] in total; The steps of actually calculating the full-frequency domain data correction processing method are: S1: Continuously collect m points of raw data at the working sampling frequency and record the total collection time T; S2: Perform Fourier transform FFT on the collected data to obtain the original data of each frequency point in the frequency domain; S3: 1 / T is used as the actual frequency interval of the spectrum line and as the basis for calculating the frequency of each spectrum line; S4: For each spectral line k, first calculate the actual frequency f[k] of the spectral line, determine the sub-frequency band that the spectral line falls into, and then use the frequency domain correction coefficients of the two end points of the frequency band to perform linear interpolation to find the correction coefficient Fx[k] at f[k], and multiply the amplitude of the spectral line by Fx[k] to obtain the accurate amplitude of the spectral line; S5: Correct all spectral lines in turn. After the correction of this axis data is completed, correct all three axis data in turn. Perform inverse Fourier transform IFFT on the corrected frequency domain data to obtain accurate time domain data. Then use the calibrated time domain data for subsequent related processing. The specific method to obtain the correction coefficient Fx[k] at f[k] is: The frequency of the kth spectral line is divided by the frequency calibration interval to obtain the correction index Ck=k / T / , where Ck is a floating point number, and its integer part is Cz, which represents the index of the first correction coefficient used for the calculation of the spectral line. Cz+1 is the index of the second correction coefficient used for the calculation of the spectral line. The decimal part of Ck is Cx, and the correction coefficient of the kth spectral line is calculated as follows: Fx[k]=(Fx[Cz+1]-Fx[Cz])Cx+Fx[Cz].

2. The correction processing method for vibration measurement data of a vibration sensor according to claim 1, characterized in that: The specific method for collecting the acceleration data of the probe and calculating the effective value Ai in the time domain is: Starting from a certain vibration frequency f1, at a certain frequency interval, to fn, calibrate the acceleration at each frequency point: calculate the effective value A[i].

3. The correction processing method for vibration measurement data of a vibration sensor according to claim 1, characterized in that: In the method of calculating the effective value Ai in the time domain, F0 is specially processed and the 50 Hz point is taken for calibration to replace the vibration coefficient of 0 Hz. The slight influence of the vibration table being unable to output and the calibration point offset on the low frequency is negligible.

4. The correction processing method for vibration measurement data of a vibration sensor according to claim 1, characterized in that: For spectral line k, the method to calculate the actual frequency f[k] of the spectral line is: The frequency of the kth spectral line is: k*(1 / T)=k / T; where: k: 0-N / 2-1.

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