CN112781709A - Method for analyzing early failure and extracting characteristics of equipment vibration signal under variable speed working condition - Google Patents
Method for analyzing early failure and extracting characteristics of equipment vibration signal under variable speed working condition Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 claims abstract description 12
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- G—PHYSICS
- G01—MEASURING; TESTING
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- G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a method for analyzing early failure and extracting characteristics of equipment vibration signals under the working condition of variable speed, which comprises the steps of synchronously acquiring the equipment vibration signals and rotating speed pulse signals at high speed, carrying out envelope extraction on high-frequency vibration signals, identifying the pulse edge time scale of the rotating speed pulse signals, carrying out instantaneous rotating frequency estimation, calculating an angle domain sampling time sequence, carrying out digital tracking anti-aliasing filtering on the vibration envelope signals, carrying out order ratio tracking sampling on original vibration envelope signals, and carrying out FFT analysis on the ratio envelope signals. The problems of early fault signal analysis and fault feature extraction of equipment such as a bearing, a gear box and the like under the working condition of variable rotating speed are effectively solved, and the signal analysis precision and the fault diagnosis accuracy are improved.
Description
Technical Field
The invention belongs to the technical field of equipment fault analysis, and particularly relates to the field of state monitoring, predictive maintenance and fault diagnosis of rotary equipment in a production field in the nuclear power industry.
Background
The vibration signals of the equipment such as a rolling bearing, a gear box and the like have the characteristics of time-varying property, strong noise and complex frequency components, and the frequency spectrum not only contains the characteristic frequencies of the gear box components (a sun gear, a planet gear, a gear ring and the like) and the bearing components (an inner ring, an outer ring, a rolling body and the like), but also contains the meshing frequency of each gear pair and the vibration coupling information of power input and load equipment.
The early defects of the gear box and the bearing component can generate weak periodic impulse signals, the anti-interference capability of the impulse signals is weak, the stability is not high, the impulse signals are often covered under background signals and noises, signal modulation can be formed, and the impulse signals are not easy to extract and identify. In the twentieth century and the seventies, technicians provide a resonance demodulation method, high-frequency band-pass filtering is carried out on collected vibration signals, signal envelopes are extracted by using Hilbert transform, fast Fourier transform is carried out on the envelope signals, the impact cycle frequency of an impact pulse signal is obtained through calculation, and fault characteristics are identified by combining structures of a bearing and a gearbox component so as to determine whether the bearing and the gearbox have faults or not and which fault type belongs.
The resonance demodulation technology well solves the problems of state monitoring and fault diagnosis of the gear box and the bearing equipment under the operating condition of constant rotating speed, and is widely applied to the industrial field. However, the industrial field device has complex operation conditions, often encounters unsteady-state environments such as variable rotating speed and variable working conditions, the application effect of the traditional resonance demodulation technology is poor, and a new vibration signal analysis technology needs to be adopted to solve the problems of state monitoring and fault diagnosis of the bearing and gearbox devices under the variable speed working conditions.
Disclosure of Invention
The invention provides a method for analyzing and extracting early failure of equipment vibration signals under a variable speed working condition, which solves the problems of state monitoring and failure diagnosis under the variable speed working condition of industrial field bearings and gear box equipment, and comprises the following steps:
step 1) synchronously acquiring a vibration signal and a rotating speed pulse signal of equipment at a high speed, and synchronously acquiring one path of rotating speed pulse signal and a plurality of paths of vibration signals of rotating equipment by an ADC (analog-to-digital converter) module by adopting a higher sampling frequency;
step 2) extracting envelope of the high-frequency vibration signal, performing band-pass filtering on the high-frequency vibration signal by adopting a digital band-pass filter, removing low-frequency and high-frequency background signals with large vibration amplitude, and extracting a signal envelope waveform by applying a resonance demodulation technology to the vibration signal obtained after band-pass filtering;
step 3) identifying the time scale of the pulse edge of the rotating speed pulse signal, carrying out threshold detection on the rotating speed pulse signal, and accurately identifying and recording the arrival time t0, t1 and t2 … tN of the rising edge or the falling edge of the key phase pulse signal according to the set key phase pulse threshold;
step 4) estimating instantaneous rotation frequency, calculating the time difference between two pulses according to the time scale of the rotation speed pulse, wherein dt0 is t1-t0, dt1 is t2-t1, …, dtN-1 is tN-tN-1, and calculating the rotation speed rpm and the instantaneous rotation frequency f by a digital differentiation method;
step 5) calculating an angle domain sampling time sequence, and determining an angle domain equal angle sampling order ratio number M, namely the number of samples needing equal angle acquisition every time a rotor rotates one circle; calculating by interpolation according to the pulse edge time scale and the equal-angle sampling order of the rotating speed pulse signal to obtain an angle domain equal-angle sampling time sequence;
step 6) digital tracking anti-aliasing filtering is carried out on the vibration envelope signal, digital anti-aliasing filtering is carried out on the original vibration envelope signal extracted in the step 2), and the cut-off frequency of a filter of the digital anti-aliasing filtering is determined by the instantaneous frequency conversion obtained by calculation in the step 4) and the sampling order ratio number M in the step 5);
step 7) original vibration envelope signal order ratio tracking sampling, according to the angle domain sampling time sequence obtained by calculation in the step 5), carrying out digital resampling on the original vibration envelope signal filtered in the step 6), and obtaining angular domain equiangular vibration envelope waveform signals;
and 8) carrying out FFT analysis on the ratio envelope signals, carrying out FFT calculation on the equiangular envelope waveform signals subjected to the order tracking sampling to obtain a vibration envelope signal order spectrum, calculating fault characteristic frequency components of the bearing and the gear box by applying the envelope signal order spectrum, and finishing fault early warning and diagnosis functions by monitoring the characteristic frequencies.
Preferably, the vibration signal acquisition in step 1) is performed by a front-pass analog anti-aliasing filter, and the high-frequency noise and the unwanted high-frequency signal are filtered, and the cut-off frequency of the analog anti-aliasing filter is set to be half of the sampling frequency of the ADC module.
Preferably, the interpolation operation in the step 5) adopts a cascaded integrator comb filter as an interpolation filter, and performs M-fold interpolation operation on the rotational speed pulse to obtain a time sequence corresponding to each sample of the angular vibration signal in the angular domain and the like; for the convenience of subsequent FFT operation, M is an n power of 2, and n is more than or equal to 4.
Preferably, the digital resampling interpolation operation in step 7) adopts a Sinc interpolation algorithm.
By providing a novel vibration signal analysis method, the invention effectively solves the problems of early fault signal analysis and fault feature extraction of equipment such as a bearing, a gear box and the like under the working condition of variable rotating speed, and improves the signal analysis precision and the fault diagnosis accuracy.
Drawings
FIG. 1 is a schematic flow diagram of vibration signal analysis in accordance with the present invention;
FIG. 2 is a synchronously acquired tachometer pulse signal;
FIG. 3 is a raw vibration signal acquired synchronously;
FIG. 4 is a raw vibration signal spectrum;
FIG. 5 is a tachometer pulse edge identification result of the present invention;
FIG. 6 shows the result of the curve of the variation of the rotation speed in the present aspect;
FIG. 7 is an original vibration envelope waveform signal;
FIG. 8 is a spectrum of an original vibration signal envelope;
FIG. 9 is an angular domain equiangular sampled envelope waveform of the present invention;
fig. 10 is an equi-angularly sampled envelope ratio spectrum of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
1) The method comprises the steps of selecting an 8-channel 24-bit synchronous acquisition module ADS1278 of a TI company, carrying out high-speed synchronous acquisition on vibration signals and rotating shaft rotating speed signals of rotating equipment such as a bearing and a gear box, selecting an IEPE piezoelectric ceramic acceleration sensor as a vibration sensor, selecting an inductive proximity switch as a rotating speed sensor, setting the sampling frequency to be 256kps, carrying out anti-mixing filtering on the vibration signals by using an 8-order Chebyshev filter before the vibration signals are acquired, filtering out high-frequency noise and useless high-frequency signals, and setting the cut-off of the filter to be 12.8 kHz. The vibration signals obtained by synchronous acquisition are shown in figure 3, the rotating speed pulse signals are shown in figure 2, figure 4 is a vibration frequency spectrum obtained by directly carrying out FFT calculation on the original vibration signals, and figure 4 shows that the vibration frequency spectrum has a serious frequency spectrum leakage phenomenon, the fault characteristic frequency cannot be identified, and the method cannot be used for vibration analysis and fault diagnosis of industrial field rotating equipment.
2) And carrying out digital envelope extraction on the high-frequency vibration after synchronous acquisition by applying a resonance demodulation technology. Firstly, spectral kurtosis analysis is carried out on high-frequency vibration signals, the central frequency and the bandwidth of a band-pass filter before resonance demodulation are determined according to the spectral kurtosis calculation result, then band-pass filtering is carried out on the original high-frequency vibration signals, weak periodic impulse signals related to equipment faults in the original vibration signals are extracted, Hilbert transformation is carried out on the vibration signals after the band-pass filtering, and envelope waveforms of the periodic impulse vibration signals are extracted. The original vibration envelope waveform extracted in the step is shown in figure 7, the original vibration envelope spectrum is shown in figure 8, and the fault characteristic frequency cannot be identified due to the fact that a serious spectrum leakage site exists.
3) According to the voltage amplitude range of the rotating speed pulse signal, a pulse threshold value is artificially set, threshold detection is carried out on the rotating speed pulse signal, and the accurate reaching time sequence of the rising edge or the falling edge of the rotating speed pulse signal is identified [ t0, t1, t2, …, tN ]. Time scale of the resulting pulse rising edge is identified figure 5.
4) The time scale sequence [ t0, t1, t2, …, tN ] of the rising edge or the falling edge identified in the step 3) calculates the time difference between the rising edge or the falling edge of two pulses, dt 0-t 1-t0, dt 1-t 2-t1, …, dtN-1-tN-1, and the instantaneous rotating speed rpm of the rotating shaft of the equipment and the corresponding instantaneous rotating frequency f are calculated by using a digital differentiation technology. Fig. 6 shows the results of the speed variation using the digital integration technique.
5) According to the type of monitoring equipment and the requirement of vibration fault diagnosis and analysis, selecting the equal-angle sampling order number M of a vibration signal angle domain, namely the number of samples which need to be collected at equal angles every time a rotor rotates a circle, for example, taking M as 128. And (3) obtaining a time sequence corresponding to the angular domain equiangular sampling samples by interpolation resampling calculation according to the time scale sequence of the rising edge or the falling edge of the pulse of the rotating speed pulse signal and the equiangular sampling order number M. And (3) performing interpolation operation by selecting a Cascade integration Comb filter (Cascade Integrator Comb) as an interpolation filter, and performing M-time interpolation operation on the rotational speed pulse to obtain a time sequence corresponding to each sample of the angular vibration signal with equal angles in the angular domain. For the convenience of the subsequent FFT operation, M is the power n of 2, and n is 4, 5, 6, 7, 8, etc. The cascade integrator comb filter (CIC filter) has the characteristics of simple structure and high operation speed, and is suitable for real-time operation of signal interpolation.
6) And (3) adopting a Kaiser window FIR low-pass filter as an anti-aliasing filter, carrying out digital anti-aliasing filtering on the original vibration envelope signal extracted in the step 2), and determining the cut-off frequency of the filter by calculating the instantaneous frequency conversion in the step 4) and the sampling order ratio M in the step 5). The digital tracking anti-aliasing filtering aims to remove frequency components except the order tracking frequency in the envelope signal and prevent the frequency aliasing phenomenon in the subsequent interpolation resampling;
7) the original vibration envelope signal order ratio tracks the samples. According to the angle domain sampling time sequence obtained by calculation in the step 5), carrying out digital resampling on the original vibration envelope signal filtered in the step 6) to obtain angular domain equiangular vibration envelope signals, wherein a Sinc interpolation algorithm is adopted in the digital resampling interpolation operation. Fig. 9 is an angular domain equiangular sampling envelope waveform calculated by the method of the present invention.
8) And FFT analysis is carried out on the order envelope signal. FFT calculation is carried out on equiangular envelope waveform signals sampled by the order tracking to obtain a vibration envelope signal order spectrum, the envelope signal order spectrum is used for realizing the calculation of fault characteristic frequency components (such as inner ring characteristic frequency BPFI) of the bearing and the gear box, and the fault early warning and diagnosis functions are completed by monitoring the characteristic frequencies. FIG. 10 is a vibration signal envelope order ratio frequency spectrum calculated by the method of the present invention, wherein an order ratio spectral line (3.75 order and its frequency multiplication harmonic) corresponds to a bearing fault outer ring characteristic frequency BPFO. Therefore, the vibration signal analysis method under the variable-speed working condition provided by the invention can accurately identify the fault characteristic frequency of equipment such as a bearing, a gear box and the like, and help technicians to realize early fault early warning and diagnosis analysis.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is intended to include such modifications and variations. The foregoing examples or embodiments are merely illustrative of the present invention, which may be embodied in other specific forms or in other specific forms without departing from the spirit or essential characteristics thereof. The described embodiments are, therefore, to be considered in all respects as illustrative and not restrictive. The scope of the invention should be indicated by the appended claims, and any changes that are equivalent to the intent and scope of the claims should be construed to be included therein.
Claims (4)
1. The method for analyzing the early failure and extracting the characteristics of the equipment vibration signals under the variable speed working condition is characterized by comprising the following steps of:
step 1) synchronously acquiring a vibration signal and a rotating speed pulse signal of equipment at a high speed, and synchronously acquiring one path of rotating speed pulse signal and a plurality of paths of vibration signals of rotating equipment by an ADC (analog-to-digital converter) module by adopting a higher sampling frequency;
step 2) extracting envelope of the high-frequency vibration signal, performing band-pass filtering on the high-frequency vibration signal by adopting a digital band-pass filter, removing low-frequency and high-frequency background signals with large vibration amplitude, and extracting a signal envelope waveform by applying a resonance demodulation technology to the vibration signal obtained after band-pass filtering;
step 3) identifying the time scale of the pulse edge of the rotating speed pulse signal, carrying out threshold detection on the rotating speed pulse signal, and accurately identifying and recording the arrival time t0, t1 and t2 … tN of the rising edge or the falling edge of the key phase pulse signal according to the set key phase pulse threshold;
step 4) estimating instantaneous rotation frequency, calculating the time difference between two pulses according to the time scale of the rotation speed pulse, wherein dt0 is t1-t0, dt1 is t2-t1, …, dtN-1 is tN-tN-1, and calculating the rotation speed rpm and the instantaneous rotation frequency f by a digital differentiation method;
step 5) calculating an angle domain sampling time sequence, and determining an angle domain equal angle sampling order ratio number M, namely the number of samples needing equal angle acquisition every time a rotor rotates one circle; calculating by interpolation according to the pulse edge time scale and the equal-angle sampling order of the rotating speed pulse signal to obtain an angle domain equal-angle sampling time sequence;
step 6) digital tracking anti-aliasing filtering is carried out on the vibration envelope signal, digital anti-aliasing filtering is carried out on the original vibration envelope signal extracted in the step 2), and the cut-off frequency of a filter of the digital anti-aliasing filtering is determined by the instantaneous frequency conversion obtained by calculation in the step 4) and the sampling order ratio number M in the step 5);
step 7) original vibration envelope signal order ratio tracking sampling, according to the angle domain sampling time sequence obtained by calculation in the step 5), carrying out digital resampling on the original vibration envelope signal filtered in the step 6), and obtaining angular domain equiangular vibration envelope waveform signals;
and 8) carrying out FFT analysis on the ratio envelope signals, carrying out FFT calculation on the equiangular envelope waveform signals subjected to the order tracking sampling to obtain a vibration envelope signal order spectrum, calculating fault characteristic frequency components of the bearing and the gear box by applying the envelope signal order spectrum, and finishing fault early warning and diagnosis functions by monitoring the characteristic frequencies.
2. The method for analyzing the early failure and extracting the features of the vibration signal of the equipment under the variable speed working condition according to claim 1, wherein the vibration signal acquisition in the step 1) is performed by a front-pass analog anti-aliasing filter for filtering high-frequency noise and useless high-frequency signals, and the cut-off frequency of the analog anti-aliasing filter is set to be half of the sampling frequency of the ADC module.
3. The method for analyzing the early failure and extracting the characteristics of the vibration signals of the equipment under the variable speed working condition according to claim 1, wherein the interpolation operation in the step 5) adopts a cascade integration comb filter as an interpolation filter, and performs M times of interpolation operation on the rotational speed pulse to obtain a time sequence corresponding to each sample of the angular domain equiangular vibration signals; for the convenience of subsequent FFT operation, M is an n power of 2, and n is more than or equal to 4.
4. The method for analyzing the early failure and extracting the characteristics of the vibration signals of the equipment under the variable speed working condition according to claim 1, wherein the digital resampling interpolation operation in the step 7) adopts a Sinc interpolation algorithm.
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