CN111024566B - Frequency domain analysis-based mechanical wear degree calibration method and system - Google Patents
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Abstract
The invention discloses a mechanical wear degree calibration method and system based on frequency domain analysis, and relates to the field of oil abrasive particle monitoring. The method mainly comprises the following steps: firstly, acquiring voltage signals output by a sensor under different abrasive particle concentrations through a signal acquisition card; then removing the direct current component of the acquired voltage signal, carrying out Fourier change on the voltage signal after the direct current component is removed, and converting the time domain signal into a frequency domain signal; then, the frequency domain signals are arranged in a descending order according to the magnitude of the amplitude from large to small, and the q-order gravity center frequency of the ordered frequency domain signals is calculated; and finally, obtaining the abrasive particle concentration and q-order gravity center frequency linearity through linear fitting, and calibrating the mechanical wear degree through the q-order gravity center frequency. The method can effectively reflect the change of the abrasive particle concentration in the oil liquid, so that the method can be used for calibrating the degree of mechanical wear. In addition, the method does not need an additional filter and a noise reduction step, and simplifies the signal processing step.
Description
Technical Field
The invention belongs to the field of oil abrasive particle monitoring, and particularly relates to a mechanical wear degree calibration method based on frequency domain analysis.
Background
Modern technology develops very rapidly, mechanical equipment is more and more precise, and the requirement on workpiece precision is higher. Therefore, the operation condition and the wear condition of the equipment can be better detected under the condition that the mechanical equipment is not disassembled, and the important problem in the mechanical industry is solved. The abrasive particles in the lubricating oil contain a large amount of effective information about abrasion, so that the abrasion condition of mechanical equipment can be effectively detected by detecting the lubricating oil in the machine. The basic principle of the electromagnetic abrasive particle detection sensor is the faraday electromagnetic induction principle. Utilize current drive, the sensor can produce a high-intensity magnetic field, when the grit passes through this magnetic field, can arouse the change of magnetic flux to produce an induced electromotive force, can realize the detection of grit through gathering induced electromotive force. The electromagnetic type abrasive particle detection can convert abrasive particle signals into voltage signals, and the acquired signals are analyzed to obtain the abrasion condition of mechanical equipment, so that catastrophic damage can be effectively avoided or unnecessary maintenance of the equipment in normal operation can be reduced.
At present, abrasive particle signals are mostly processed in a mode of noise reduction and abrasive particle extraction or a mode of setting a threshold value and abrasive particle separation, and the like, so that the method is simple in operation and clear in physical significance. However, the method is difficult to separate weak abrasive grain signals from background noise, and has high requirements on signal to noise ratio. And the time domain signal is converted into a frequency domain through Fourier change, and a periodic signal in background noise is converted into a spectral line, so that noise reduction is facilitated. Therefore, a novel mechanical wear calibration method based on frequency domain analysis is provided. The change of the abrasive particle concentration in the oil can be effectively detected, and an additional filter and a noise reduction step are not needed.
Disclosure of Invention
The present invention is directed to solving the above problems of the prior art. The mechanical wear degree calibration method based on frequency domain analysis is used for monitoring the concentration and the particle size distribution of abrasive particles in a lubricating oil way on line and effectively judging the health state of equipment. The technical scheme of the invention is as follows:
a mechanical wear degree calibration method based on frequency domain analysis comprises the following steps:
s1, when oil containing abrasive particles passes through the electromagnetic abrasive particle detection sensor, acquiring a voltage signal output by the electromagnetic abrasive particle detection sensor by using a signal acquisition card to obtain a sampling signal x (n) with the length of n points;
s2, removing the DC component of the collected sampling signal x (n);
s3, carrying out fast Fourier transform on the sampling signal of which the direct-current component is removed in the step S2 to obtain a frequency domain signal;
s4, sorting the frequency domain signals in a descending order according to the magnitude of the amplitude;
s5, calculating the q-order barycentric frequency of the sequenced frequency domain signals;
and S6, sampling signals for multiple times at the same concentration, calculating q-order barycentric frequency of the signals respectively, obtaining a q-order barycentric frequency sequence f (n), calculating a harmonic mean of the q-order barycentric frequency sequence f (n), performing linear fitting to obtain the linearity of the q-order barycentric frequency and the abrasive particle concentration, and calibrating the wear degree of mechanical equipment through the q-order barycentric frequency.
Further, the step S2 of removing the dc component of the acquired sampling signal x (n) specifically includes:
selecting the average M of the voltage signals x (n) as a direct current component, and subtracting the average M from each value of the voltage signals x (n) to obtain the voltage signals X (n) with the direct current offset removed.
Further, in step S3, the signal x (n) from which the dc offset has been removed is subjected to fast fourier transform to obtain a frequency signal
Further, the step S4 performs descending order on the frequency domain signals according to the magnitude of the amplitude from large to small; arranging the spectral lines with higher amplitude at low frequency and the spectral lines with lower amplitude at high frequency, and calculating the q-order barycentric frequency of the ordered frequency domain signals P (n)
Further, the step S6 calculates harmonic averages H (m) of q-order barycentric frequency sequences at different concentrations,
and obtaining the linearity k of the abrasive grain concentration and the q-order barycentric frequency by using a least square method
A mechanical wear degree calibration system based on frequency domain analysis comprises:
a sampling module: when oil containing abrasive particles passes through the electromagnetic abrasive particle detection sensor, acquiring a voltage signal output by the electromagnetic abrasive particle detection sensor by using a signal acquisition card to obtain a sampling signal x (n) with the length of n points;
a preprocessing module: the device is used for removing the direct current component of the sampling signal x (n) and performing fast Fourier transform to obtain a frequency domain signal; sorting the frequency domain signals in a descending order according to the magnitude of the amplitude from large to small;
a calculation module: the device is used for calculating the q-order barycentric frequency of the sequenced frequency domain signals; sampling signals for multiple times at the same concentration, respectively calculating q-order barycentric frequency of the signals, obtaining a q-order barycentric frequency sequence f (n), and calculating a harmonic mean of the q-order barycentric frequency sequence f (n);
a fitting module: the method is used for obtaining the linearity of q-order gravity center frequency and abrasive particle concentration by adopting linear fitting, and calibrating the abrasion degree of mechanical equipment by the q-order gravity center frequency.
The invention has the following advantages and beneficial effects:
(1) the abrasive particle signal is often contaminated by noise, and especially when the signal-to-noise ratio is low, the threshold value set based on the time domain thresholding method is often not related to the abrasive particle signal. The invention does not need to set a threshold value, so that the accuracy is higher.
(2) The time domain thresholding method requires filtering processing, and various parameters are required to be set for filtering. The denoising effect of the wavelet threshold filtering algorithm has a great relationship with the selection of wavelet basis and decomposition layer number, so the denoising effect is not stable and reliable enough. And when the signal-to-noise ratio of the abrasive particle signal is too low, the wavelet denoising effect is very poor. The filter noise reduction method needs to set parameters such as cut-off frequency, and in addition, the filter has the defects of nonlinear phase, limit cycle effect and the like, which can affect the original signal. The invention avoids the filtering step, greatly simplifies the signal processing process and reduces the operation amount.
(3) According to the invention, the q-order gravity center frequency of the sequenced frequency spectrum is calculated, the weights of the abrasive particle signals and the background noise are changed, the influence of noise on the abrasive particle signals can be effectively reduced, meanwhile, the abrasive particle signals are enhanced, and the signal-to-noise ratio is effectively improved.
Drawings
FIG. 1 is a schematic time domain diagram and a partial enlarged view of an original signal according to a preferred embodiment of the present invention:
fig. 2 is a frequency domain diagram of an original time domain signal after fourier transform:
fig. 3 is a frequency domain diagram of the original time domain signal after fourier transform and partial amplification:
FIG. 4 is a plot of the frequency domain after descending order:
FIG. 5 is a graph showing the linearity between the second order center of gravity frequency and the abrasive particle concentration;
fig. 6 is a flowchart of a mechanical wear degree calibration method based on frequency domain analysis according to a preferred embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail and clearly with reference to the accompanying drawings. The described embodiments are only some of the embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
as shown in fig. 6, the specific process of the present invention is as follows:
and S1, when the oil containing the abrasive particles passes through the electromagnetic abrasive particle detection sensor, the sensor outputs an induced voltage signal in real time. Acquiring the output voltage signal by using a signal acquisition card to obtain a sampling signal x (n) with the length of n points:
x(n)＝{x1,x2,...,xn-1,xn}
where n is fs × t, n is the number of sampling points, fs is the sampling frequency, and t is the sampling time.
And S2, regarding the signals in different time periods, the direct current offset of the signals has slight difference, so that the collected signals need to be subjected to direct current removing processing. Calculating the average value of the sampling signals x (n), and subtracting the value from each value of the group of signals to obtain the voltage signal x (n) with the DC offset removed.
S3, the signal X (n) with DC offset removed is processed with fast Fourier transform to obtain frequency domain signal S (n).
S4, according to the spectrum analysis, the background noise is mainly composed of random noise and determined signals. The main components of the determination signal are current power frequency, 50Hz and harmonic thereof, as shown in figure 4. In order to eliminate the influence of background noise, the frequency domain signals s (n) obtained in step 3 are sorted from large to small according to the magnitude of the amplitude. Spectral lines with higher amplitudes are arranged at low frequencies and spectral lines with lower amplitudes are arranged at high frequencies. Then, the q-order barycentric frequency of the sorted frequency domain signal P (n) is calculated. And changing the weights of the low frequency and the high frequency by calculating the ordered q-order barycentric frequency, so that the weight of the low frequency part is reduced, and the weight of the high frequency part is increased. Meanwhile, the interference of power frequency signals is reduced, and the weight of abrasive particle signals is enhanced.
And S5, in order to eliminate the influence of errors and extreme values caused by the fact that abrasive particles randomly pass through the sensor on the result, sampling the signals for multiple times at the same concentration, calculating q-order gravity center frequencies of the signals respectively, and obtaining a q-order gravity center frequency sequence f (n).
And S6, respectively calculating harmonic averages of the q-order barycentric frequency sequences under different concentrations, and obtaining the linearity of the abrasive particle concentration and the q-order barycentric frequency by using a least square method.
The specific embodiment is as follows:
firstly, an experimental device is built, and oil liquid with abrasive particle concentration of 0ppm, 20ppm, 40ppm, 60ppm and 80ppm is configured. The excitation current was set to 0.3A and the flow rate of the peristaltic pump was set to 150 ml/min. In addition, in order to eliminate the error caused by the random passing of the abrasive particles through the sensor, 25 groups of voltage signals are respectively collected for the oil liquid with different abrasive particle concentrations. The following detailed description of the embodiments and the working principles of the present invention will be made with reference to the accompanying drawings
(1) Collecting signals:
when the oil containing the abrasive particles passes through the electromagnetic type abrasive particle detection sensor, the sensor can output an induced voltage signal in real time. And acquiring the output signal of the sensor by using a signal acquisition card. The sampling frequency is set to fs-25000, and the sampling time is set to t-240, so that a sampling signal with a length of 6000000 is acquired:
x(n)＝{x1,x2,...,xn-1,xn}
(2) removing the direct current component of the signal:
calculating the average value of the sampling signals x (n) obtained in the step 1, and then subtracting the average value from each value of the group of signals to obtain the voltage signals x (n).
(3) Carrying out Fourier transform on the acquired voltage signals:
and (3) performing Fourier transform on the voltage signal X (n) obtained in the step (2), and obtaining a frequency domain signal S (n) from the signal after the fast Fourier transform.
(4) Sorting the frequency domain signals according to the amplitude from large to small
And 4, sequencing all amplitudes of the frequency domain signal S (n) obtained in the step 4 from large to small.
(5) Calculating second order center of gravity frequency
And calculating the second-order barycentric frequency (frequency mean square) of the frequency domain signals after the descending order arrangement.
(6) Calculating a harmonic mean:
in order to eliminate the influence of errors and poles caused by the random passing of abrasive particles through the sensor on the result, 25 times of sampling signals are carried out at the same concentration, the frequency mean square of the signals is respectively calculated, and a frequency mean square sequence FC is obtained2(n) of (a). The harmonic mean of the frequency mean square sequence at each abrasive grain concentration was then calculated.
(7) Linear fitting to obtain linearity between frequency mean square and abrasive particle concentration
And obtaining the linearity between the abrasive grain concentration and the frequency mean square through a least square method. The mean square of the frequencies for the concentrations 0ppm, 20ppm, 40ppm, 60ppm and 80ppm were fitted linearly, resulting in a linearity of 0.99.
The above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (6)
1. A mechanical wear degree calibration method based on frequency domain analysis is characterized by comprising the following steps:
s1, when oil containing abrasive particles passes through the electromagnetic abrasive particle detection sensor, acquiring a voltage signal output by the electromagnetic abrasive particle detection sensor by using a signal acquisition card to obtain a sampling signal x (n) with the length of n points;
s2, removing the DC component of the collected sampling signal x (n);
s3, carrying out fast Fourier transform on the sampling signal of which the direct-current component is removed in the step S2 to obtain a frequency domain signal;
s4, sorting the frequency domain signals in descending order according to the magnitude of the amplitude;
s5, calculating the q-order barycentric frequency of the sorted frequency domain signals;
and S6, sampling signals for multiple times under the same abrasive particle concentration, respectively calculating q-order center of gravity frequency of the signals to obtain a q-order center of gravity frequency sequence f (n), calculating harmonic mean of the q-order center of gravity frequency sequence f (n), performing linear fitting to obtain linearity of the q-order center of gravity frequency and the abrasive particle concentration, and calibrating the wear degree of mechanical equipment through the q-order center of gravity frequency.
2. The method for calibrating mechanical wear degree based on frequency domain analysis according to claim 1, wherein the step S2 of removing the dc component of the collected sampling signal x (n) specifically comprises:
the average number M of the sampling signals x (n) is selected as the DC component, and the average number M is subtracted from each value of the sampling signals x (n) to obtain the voltage signal X (n) with the DC offset removed.
3. The method for calibrating mechanical wear degree based on frequency domain analysis of claim 2, wherein in step S3, the signal x (n) with dc offset removed is subjected to fast fourier transform to obtain a frequency signal
4. The method for calibrating mechanical wear degree based on frequency domain analysis according to claim 3, wherein the step S4 is to sort the frequency domain signals in descending order according to the magnitude of the amplitude; arranging the spectral lines with higher amplitude at low frequency and the spectral lines with lower amplitude at high frequency, then calculating the q-order barycentric frequency of the ordered frequency domain signals P (n),
5. The method for calibrating mechanical wear degree based on frequency domain analysis of claim 4, wherein said step S6 is performed to calculate harmonic mean series H (m) of q-order barycentric frequency series under different concentrations respectively
And the linearity of the abrasive grain concentration and the q-order barycentric frequency is obtained by using a least square method,
6. A mechanical wear degree calibration system based on frequency domain analysis is characterized by comprising:
a sampling module: when oil containing abrasive particles passes through the electromagnetic abrasive particle detection sensor, acquiring a voltage signal output by the electromagnetic abrasive particle detection sensor by using a signal acquisition card to obtain a sampling signal x (n) with the length of n points;
a preprocessing module: the device is used for removing the direct current component of the sampling signal x (n) and performing fast Fourier transform to obtain a frequency domain signal; sorting the frequency domain signals in a descending order according to the magnitude of the amplitude from large to small;
a calculation module: the device is used for calculating the q-order barycentric frequency of the sequenced frequency domain signals; sampling signals for multiple times at the same concentration, respectively calculating q-order barycentric frequency of the signals, obtaining a q-order barycentric frequency sequence f (n), and calculating a harmonic mean of the q-order barycentric frequency sequence f (n);
a fitting module: the method is used for obtaining the linearity of q-order gravity center frequency and abrasive particle concentration by adopting linear fitting, and calibrating the abrasion degree of mechanical equipment by the q-order gravity center frequency.
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