CN110926798A - Method and device for judging on-off state of electromagnetic valve - Google Patents
Method and device for judging on-off state of electromagnetic valve Download PDFInfo
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Abstract
The invention provides a method and a device for judging the on-off state of an electromagnetic valve, wherein the on-off state of the electromagnetic valve is judged by detecting a weak impact signal generated when the electromagnetic valve is closed and combining non-contact magnetic flux leakage measurement; when the impact signal is detected and extracted and the magnetic leakage digital signal is higher than the threshold value, the electromagnetic valve switch is judged to be in a closed state, and when the magnetic leakage digital signal is lower than the threshold value, the electromagnetic valve switch is judged to be in an open state; therefore, the method combining the impact signal extraction and the magnetic flux leakage measurement based on the wavelet transformation not only overcomes the difficulty in detecting the vibration signal in a strong noise environment, but also solves the problem that the existing detection method is easy to misjudge, and is beneficial to improving the reliability of the control of the electromagnetic valve in the spacecraft and industrial equipment.
Description
Technical Field
The invention belongs to the technical field of signal detection, and particularly relates to a method and a device for judging the on-off state of an electromagnetic valve.
Background
The electromagnetic valve is an important control part, is applied to various aerospace craft and various industrial equipment, the reliability and the performance of the electromagnetic valve determine the success or failure and the performance level of an engine, and is very important in engines started for many times, particularly in attitude control engines. Although the methods have engineering application, the methods have some defects, for example, in the conventional vibration detection, the state of the electromagnetic valve is judged by the peak value of a vibration signal output by a vibration sensor, when two electromagnetic valves are close to each other, the formed vibration is easily captured by the adjacent vibration sensor and is difficult to distinguish, and in addition, because the environment where the electromagnetic valves are located is often accompanied by strong noise interference, a weak vibration signal is often submerged by noise, and the detection error of the working state of the electromagnetic valve is easily caused. The current type detection needs to be additionally connected with equipment in a control loop in series, but when the electromagnetic valve has a clamping fault, the coil still has current, so that the working state of the electromagnetic valve is misjudged. Since the leakage magnetic flux of the solenoid valve is generated by the coil current, the leakage magnetic flux detection and the current detection may also cause erroneous determination of the operating state.
Disclosure of Invention
In order to solve the problems, the invention provides the method and the device for judging the on-off state of the electromagnetic valve, which not only overcome the difficulty in detecting the vibration signal in a strong noise environment, but also solve the problem that the conventional detection method is easy to generate misjudgment, and are beneficial to improving the reliability of the control of the electromagnetic valve in spacecrafts and industrial equipment.
A method for judging the on-off state of an electromagnetic valve comprises the following steps:
s1: collecting a magnetic flux leakage analog signal and a vibration analog signal of the electromagnetic valve;
s2: respectively converting the magnetic flux leakage analog signal and the vibration analog signal into a magnetic flux leakage digital signal and a vibration digital signal;
s3: extracting an impact signal from the vibration digital signal based on a wavelet transform method;
s4: and judging whether the electromagnetic valve is closed or not according to whether the peak value of the impact signal and the magnetic leakage digital signal are simultaneously larger than a preset threshold value or not.
Further, the method for extracting the impact signal comprises the following steps:
S31: selecting Morlet wavelet as mother wavelet of wavelet transform, and optimizing center frequency and bandwidth of Morlet wavelet to obtain optimal center frequency f of Morlet waveletocAnd an optimum bandwidth fob；
S32: setting the value range [ f ] of the analysis frequency f1,f2,…,fm]Analysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)iI is 1,2, …, m, and m is at least 2; for each scale factor aiUsing a frequency based on the optimum center frequency focAnd an optimum bandwidth fobPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
wherein, Δ t is a preset sampling time interval;
s33: calculating kurtosis value K of the wavelet coefficient corresponding to each scale factor, and enabling the kurtosis value K to be larger than a preset threshold value KthrhdThe wavelet coefficient corresponding to the scale factor is used as a wavelet coefficient to be selected;
s34: denoising the wavelet coefficient to be selected by using a soft threshold denoising method;
s35: and performing inverse wavelet transform on the denoised wavelet coefficient to obtain an impact signal.
Further, the optimal center frequency focAnd an optimum bandwidth fobThe acquisition method comprises the following steps:
s311: setting the value of the analysis frequency f as [ f1,f2,…,fm]Center frequency fcHas a value range of [ P, Q]And is the bandwidth fbSetting an initial value fb0；
S312: centering frequency fcIs increased from P to Q in preset steps, wherein f is the center frequency for eachcAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (2)i(ii) a For each scale factor aiAdopt the followingFront center frequency fcAnd initial value of bandwidth fb0Performing wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
s313: calculating each center frequency f according to the formula (3) and the formula (4)cCorresponding Shannon entropy H (f)c) Entropy of Shannon H (f)c) To a minimum value Hmin(fc) The center frequency of time is used as the optimal center frequency foc；
Wherein, Wc(aiτ) as the center frequency fcCorresponding scale factor aiThe wavelet coefficients of;
s314: bandwidth fbThe value range is set as [ R, S]Then the bandwidth f is divided by a preset stepbIncreases from R to S, wherein f is for each bandwidthbAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)i(ii) a For each scale factor aiUsing a frequency based on the optimum center frequency focAnd the current bandwidth fbPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain other m wavelet coefficients;
s315: calculating each bandwidth f according to equation (5) and equation (6)bCorresponding Shannon entropy H (f)b) Entropy of Shannon H (f)b) To a minimum value Hmin(fb) Bandwidth of time as optimal bandwidth fob；
Wherein, Wb(aiτ) is the bandwidth fbCorresponding scale factor aiThe wavelet coefficients of (a).
A solenoid valve switch state judging device comprises a magnetic circuit sensor, a vibration sensor, an A/D conversion module and a processing module;
the magnetic circuit sensor is used for acquiring a magnetic flux leakage analog signal of the electromagnetic valve; the vibration sensor is used for acquiring vibration analog signals of the electromagnetic valve; the A/D conversion module is used for respectively converting the magnetic flux leakage analog signal and the vibration analog signal into a magnetic flux leakage digital signal and a vibration digital signal; the processing module extracts an impact signal from the vibration digital signal based on a wavelet transform method, and then judges whether the electromagnetic valve is closed or not according to whether the peak value of the impact signal and the magnetic flux leakage digital signal are simultaneously larger than a preset threshold value or not.
Further, the processing module extracts an impact signal from the vibration digital signal based on wavelet transform, specifically:
s31: selecting Morlet wavelet as mother wavelet of wavelet transform, and optimizing center frequency and bandwidth of Morlet wavelet to obtain optimal center frequency f of Morlet waveletocAnd an optimum bandwidth fob；
S32: setting the value range [ f ] of the analysis frequency f1,f2,…,fm]Analysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)iI is 1,2, …, m, and m is at least 2; for each scale factor aiUsing a frequency based on the optimum center frequency focAnd an optimum bandwidth fobPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
wherein, Δ t is a preset sampling time interval;
s33: calculating kurtosis value K of the wavelet coefficient corresponding to each scale factor, and enabling the kurtosis value K to be larger than a preset threshold value KthrhdThe wavelet coefficient corresponding to the scale factor is used as a wavelet coefficient to be selected;
s34: denoising the wavelet coefficient to be selected by using a soft threshold denoising method;
s35: and performing inverse wavelet transform on the denoised wavelet coefficient to obtain an impact signal.
Further, the optimal center frequency focAnd an optimum bandwidth fobThe acquisition method comprises the following steps:
s311: setting the value of the analysis frequency f as [ f1,f2,…,fm]Center frequency fcHas a value range of [ P, Q]And is the bandwidth fbSetting an initial value fb0；
S312: centering frequency fcIs increased from P to Q in preset steps, wherein f is the center frequency for eachcAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (2)i(ii) a For each scale factor aiUsing a frequency f based on the current center frequencycAnd initial value of bandwidth fb0Performing wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
s313: calculating each center frequency f according to the formula (3) and the formula (4)cCorresponding Shannon entropy H (f)c) Entropy of Shannon H (f)c) To a minimum value Hmin(fc) The center frequency of time is used as the optimal center frequency foc；
Wherein, Wc(aiτ) as the center frequency fcCorresponding scale factor aiThe wavelet coefficients of;
s314: bandwidth fbThe value range is set as [ R, S]Then the bandwidth f is divided by a preset stepbIncreases from R to S, wherein f is for each bandwidthbAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)i(ii) a For each scale factor aiUsing a frequency based on the optimum center frequency focAnd the current bandwidth fbPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain other m wavelet coefficients;
s315: calculating each bandwidth f according to equation (5) and equation (6)bCorresponding Shannon entropy H (f)b) Entropy of Shannon H (f)b) To a minimum value Hmin(fb) Bandwidth of time as optimal bandwidth fob；
Wherein, Wb(aiτ) is the bandwidth fbCorresponding scale factor aiThe wavelet coefficients of (a).
Furthermore, the electromagnetic valve switch state judging device also comprises a magnetic circuit sensor conditioning module and a vibration sensor conditioning module;
the magnetic circuit sensor conditioning module is used for conditioning the voltage of the magnetic leakage analog signal into the sampling voltage range of the A/D conversion module; the vibration sensor conditioning module is used for conditioning the voltage of the vibration analog signal into the sampling voltage range of the A/D conversion module.
Has the advantages that:
1. the invention provides a method for judging the on-off state of an electromagnetic valve, which judges the on-off state of the electromagnetic valve by detecting a weak impact signal generated when the electromagnetic valve is closed and combining non-contact magnetic flux leakage measurement; when the impact signal is detected and extracted and the magnetic leakage digital signal is higher than the threshold value, the electromagnetic valve switch is judged to be in a closed state, and when the magnetic leakage digital signal is lower than the threshold value, the electromagnetic valve switch is judged to be in an open state;
therefore, the method combining the impact signal extraction and the magnetic flux leakage measurement based on the wavelet transformation not only overcomes the difficulty in detecting the vibration signal in a strong noise environment, but also solves the problem that the existing detection method is easy to misjudge, and is beneficial to improving the reliability of the control of the electromagnetic valve in the spacecraft and industrial equipment.
2. The invention provides a solenoid valve on-off state judging device, which judges the on-off state of a solenoid valve by detecting a weak impact signal generated when the solenoid valve is closed and combining non-contact magnetic flux leakage measurement; when the vibration sensor detects and extracts an impact signal and the non-contact magnetic leakage sensor detects that a magnetic field signal is higher than a threshold value, the electromagnetic valve switch is judged to be in a closed state, and when the non-contact magnetic leakage sensor detects that the magnetic field signal is lower than the threshold value, the electromagnetic valve switch is judged to be in an open state;
therefore, the electromagnetic valve on-off state judgment device based on wavelet transformation extracts the impact signal when the electromagnetic valve is closed and the magnetic leakage measurement of the magnetic circuit sensor from the output of the vibration sensor to comprehensively judge whether the electromagnetic valve is in the closed state, not only overcomes the difficulty in detecting the vibration signal in a strong noise environment, but also solves the problem that the existing detection method is easy to misjudge, and is beneficial to improving the reliability of the control of the electromagnetic valve in spacecrafts and industrial equipment.
Drawings
FIG. 1 is a schematic block diagram of an electromagnetic valve on-off state determination device provided by the present invention;
FIG. 2 is a logic diagram for determining the working status of the solenoid valve according to the present invention;
FIG. 3 is a schematic block diagram of a method for determining the on-off state of an electromagnetic valve according to the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
Example one
Referring to fig. 1, a schematic block diagram of an electromagnetic valve on-off state determination device according to the present embodiment is shown. A solenoid valve on-off state judging device is characterized by comprising a magnetic circuit sensor, a vibration sensor, a magnetic circuit sensor conditioning module, a vibration sensor conditioning module, an A/D conversion module and a processing module;
the magnetic circuit sensor is used for acquiring a magnetic flux leakage analog signal of the electromagnetic valve; the vibration sensor is used for acquiring vibration analog signals of the electromagnetic valve; the magnetic circuit sensor conditioning module is used for conditioning the voltage of the magnetic leakage analog signal into the sampling voltage range of the A/D conversion module; the vibration sensor conditioning module is used for conditioning the voltage of the vibration analog signal into the sampling voltage range of the A/D conversion module; the A/D conversion module is used for respectively converting the conditioned magnetic leakage analog signal and the conditioned vibration analog signal into a magnetic leakage digital signal and a vibration digital signal; the processing module extracts an impact signal from the vibration digital signal based on a wavelet transform method, and then judges whether the electromagnetic valve is closed or not according to whether the peak value of the impact signal and the magnetic flux leakage digital signal are simultaneously larger than a preset threshold value or not.
The working principle of the solenoid valve on-off state determination device provided by the embodiment is described as follows:
after the electromagnetic valve is electrified, the valve core of the electromagnetic valve moves, after the valve core is completely attracted, the magnetic field of the valve wall is saturated, a large amount of magnetic lines of force overflow, and the magnetic circuit sensor at the moment can output an analog signal with a certain numerical value. The vibration sensor is arranged on a plane which is closer to the electromagnetic valve, a weak impact signal can be generated when the electromagnetic valve is closed, the weak impact signal is often submerged in strong noise and other vibration signals, the weak impact signal needs to be extracted, and the analog signal output by the vibration sensor contains the information of the weak impact signal. The analog signal output by the magnetic circuit sensor and the analog signal output by the vibration sensor are conditioned to reach the A/D sampling range, the magnetic leakage analog signal of the magnetic circuit sensor and the vibration analog signal of the vibration sensor are converted into digital signals by the A/D module, the magnetic leakage digital signal and the vibration digital signal are sent to a processor for processing, and finally the judgment result of the electromagnetic valve is given by an electromagnetic valve working state judgment algorithm of the processor.
Referring to fig. 2, which is a logic diagram for determining the working state of the solenoid valve provided in this embodiment, first, the threshold of the impact signal is determined, and whether the peak value of the extracted impact signal is greater than the set threshold is determined; then judging the leakage magnetic signal, and judging whether the detected leakage magnetic signal is larger than a set threshold value; and finally, comprehensively judging by combining the impact signal and the magnetic leakage signal, wherein when the peak value of the impact signal is greater than a set threshold and the magnetic leakage signal is also greater than the set threshold, the electromagnetic valve is in a closed state, and when the magnetic leakage signal is less than the set threshold, the electromagnetic valve is in an open state no matter what the state of the impact signal is.
Further, the extracting, by the processing module, the impact signal from the vibration digital signal based on the wavelet transform specifically includes:
s31: selecting Morlet wavelet as mother wavelet of wavelet transform, and optimizing center frequency and bandwidth of Morlet wavelet to obtain optimal center frequency f of Morlet waveletocAnd an optimum bandwidth fob。
Optionally, in this embodiment, the parameters of the Morlet wavelet are optimized by using an optimization method based on the minimum shannon entropy criterion to obtain the optimal central frequency f of the waveletocSum bandwidth fobFirst, the principle of application thereof will be described.
And evaluating the wavelet function and optimizing wavelet parameters by using the sparsity of data, wherein when the sparsity of the wavelet coefficient is strongest, the corresponding mother wavelet parameter is optimal. The shannon entropy is an index for measuring sparsity, and the calculation formula is as follows:
wherein f is a parameter to be optimized, m is the number of the wavelet transformation scale factors a and is at least 2. In practical applications, the scale factor is usually a set of continuous values ai(i ═ 1, …, m). p is a radical ofiIs a function of the parameter f to be optimized, is a distribution sequence obtained by wavelet coefficient calculation under each scale, and has the calculation formula:
wherein, W (a)iτ) is the scale aiWavelet coefficient of lower, then piSatisfy the requirement of
Given center frequency f for each groupcSum bandwidth fbThere is a corresponding Shannon entropy H (f), so that Shannon entropy and center frequency f can be obtainedcSum bandwidth fbThe two-dimensional mapping relationship of (1). For a signal with a sampling time interval delta t, the signal analysis frequency f (namely the central frequency corresponding to the mother wavelet after the mother wavelet is subjected to scale expansion) and the central frequency f of the mother waveletcAnd the scale factor a, the following relationship exists:
wherein each scale factor a is shifted with τ to obtain a set of wavelet coefficients. It follows that the optimum center frequency focAnd an optimum bandwidth fobThe acquisition method specifically comprises the following steps:
s311: setting the value of the analysis frequency f as [ f according to the frequency range of the signal1,f2,…,fm]Center frequency fcHas a value range of [ P, Q]And is the bandwidth fbSetting an initial value fb0；
Note that the initial value f of the bandwidth is setb0Is a large value, the purpose being to make each frequency window non-overlappingIn part, at an optimum center frequency fcWhen the frequency of the entropy change is within the range of fcIt is related.
S312: centering frequency fcBy a predetermined step size epsiloncIncrease from P to Q, wherein f is for each center frequencycAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (2)i(ii) a For each scale factor aiUsing a frequency f based on the current center frequencycAnd initial value of bandwidth fb0Performing wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
s313: calculating each center frequency f according to the formula (3) and the formula (4)cCorresponding Shannon entropy H (f)c) Entropy of Shannon H (f)c) To a minimum value Hmin(fc) The center frequency of time is used as the optimal center frequency foc；
Wherein, Wc(aiτ) as the center frequency fcCorresponding scale factor aiThe wavelet coefficients of;
s314: bandwidth fbThe value range is set as [ R, S]Then the bandwidth f is divided by a preset stepbIncreases from R to S, wherein f is for each bandwidthbAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)i(ii) a For each scale factor aiUsing a frequency based on the optimum center frequency focAnd the current bandwidth fbThe Morlet wavelet carries out wavelet transformation on the vibration digital signal to obtain another mWavelet coefficients;
s315: calculating each bandwidth f according to equation (5) and equation (6)bCorresponding Shannon entropy H (f)b) Entropy of Shannon H (f)b) To a minimum value Hmin(fb) Bandwidth of time as optimal bandwidth fob；
Wherein, Wb(aiτ) is the bandwidth fbCorresponding scale factor aiThe wavelet coefficients of (a).
S32: setting the value range [ f ] of the analysis frequency f1,f2,…,fm]Analysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)iI is 1,2, …, m; for each scale factor aiUsing a frequency based on the optimum center frequency focAnd an optimum bandwidth fobPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
wherein, Δ t is a preset sampling time interval, and the formula of the wavelet transform is as follows:
wherein x (t) represents a vibration digital signal, W (a)iτ) is the wavelet coefficient, is the conjugate, τ is the time-shift factor, and τ is from Δ t to m Δ t.
S33: each time of calculationA kurtosis value K of the wavelet coefficient corresponding to one scale factor is larger than a preset threshold value KthrhdThe wavelet coefficient corresponding to the scale factor of (a) is taken as the wavelet coefficient to be selected.
That is, the kurtosis value K of the wavelet coefficient at each scale is calculated, wherein the kurtosis K can be calculated by formula (7), and a relation curve of the kurtosis and the scale can be obtained. Setting a threshold value KthrhdThe kurtosis value K is calculated by m wavelet coefficients under a certain scale factoraiIf the wavelet coefficients exceed the threshold, the m wavelet coefficients under the scale factors are considered to mainly comprise the impact signals in the signals, and therefore the wavelet coefficients under the scale factors are screened out to carry out the next impact signal reconstruction.
Wherein x is a wavelet coefficient under a certain scale factor,
is the average of m wavelet coefficients at a certain scale factor,
is that
Is calculated from the expected value of (c).
S34: and denoising the wavelet coefficient to be selected by using a soft threshold denoising method.
It should be noted that, the soft threshold denoising method is used to remove gaussian noise remaining in a certain frequency band after wavelet transform, and its formula is shown in formula (8):
where W is the wavelet coefficient at a scale factor and T is the threshold. T is calculated from the following formula
Wherein, N is the number of sampling points,
is an estimate of the variance of the wavelet coefficients at a scale factor,
by
And calculating, wherein the MAD represents the absolute median difference of the wavelet coefficients.
S35: and performing inverse wavelet transform on the denoised wavelet coefficient to obtain an impact signal.
Note that, the denoised wavelet coefficients are subjected to inverse wavelet transform by equation (10) to reconstruct the impulse signal.
Wherein the content of the first and second substances,
is a tolerance condition proposed for Ψ (t).
Example two
Based on the above embodiments, the present embodiment provides a method for determining an on-off state of an electromagnetic valve. Referring to fig. 3, the schematic block diagram of a method for determining the on-off state of an electromagnetic valve according to this embodiment is shown. A method for judging the on-off state of an electromagnetic valve comprises the following steps:
s1: and collecting a magnetic flux leakage analog signal and a vibration analog signal of the electromagnetic valve.
S2: and respectively converting the magnetic flux leakage analog signal and the vibration analog signal into a magnetic flux leakage digital signal and a vibration digital signal.
S3: and extracting the impact signal from the vibration digital signal based on a wavelet transform method.
It should be noted that the method for extracting the impact signal is the same as the method for extracting the processing module in the electromagnetic valve on-off state determination device, and therefore, this embodiment will not be described in detail.
S4: and judging whether the electromagnetic valve is closed or not according to whether the peak value of the impact signal and the magnetic leakage digital signal are simultaneously larger than a preset threshold value or not.
It should be noted that, the leakage magnetic digital signal may be filtered to remove noise, and then it is determined whether it is greater than the preset threshold. As can be seen from fig. 3, when the peak value of the impact signal is greater than the set threshold and the magnetic leakage digital signal is also greater than the set threshold, the solenoid valve is in the closed state, and when the magnetic leakage digital signal is less than the set threshold, the solenoid valve is in the open state regardless of the state of the impact signal.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it will be understood by those skilled in the art that various changes and modifications may be made herein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (7)
1. A method for judging the on-off state of an electromagnetic valve is characterized by comprising the following steps:
s1: collecting a magnetic flux leakage analog signal and a vibration analog signal of the electromagnetic valve;
s2: respectively converting the magnetic flux leakage analog signal and the vibration analog signal into a magnetic flux leakage digital signal and a vibration digital signal;
s3: extracting an impact signal from the vibration digital signal based on a wavelet transform method;
s4: and judging whether the electromagnetic valve is closed or not according to whether the peak value of the impact signal and the magnetic leakage digital signal are simultaneously larger than a preset threshold value or not.
2. The electromagnetic valve on-off state determination method according to claim 1, wherein the impact signal is extracted by a method comprising:
s31: selecting Morlet wavelet as mother wavelet of wavelet transform, and applying Morlet waveletOptimizing the central frequency and the bandwidth to obtain the optimal central frequency f of the Morlet waveletocAnd an optimum bandwidth fob；
S32: setting the value range [ f ] of the analysis frequency f1,f2,…,fm]Analysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)iI is 1,2, …, m, and m is at least 2; for each scale factor aiUsing a frequency based on the optimum center frequency focAnd an optimum bandwidth fobPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
wherein, Δ t is a preset sampling time interval;
s33: calculating kurtosis value K of the wavelet coefficient corresponding to each scale factor, and enabling the kurtosis value K to be larger than a preset threshold value KthrhdThe wavelet coefficient corresponding to the scale factor is used as a wavelet coefficient to be selected;
s34: denoising the wavelet coefficient to be selected by using a soft threshold denoising method;
s35: and performing inverse wavelet transform on the denoised wavelet coefficient to obtain an impact signal.
3. The electromagnetic valve on-off state determination method according to claim 2, characterized in that the optimum center frequency focAnd an optimum bandwidth fobThe acquisition method comprises the following steps:
s311: setting the value of the analysis frequency f as [ f1,f2,…,fm]Center frequency fcHas a value range of [ P, Q]And is the bandwidth fbSetting an initial value fb0；
S312: centering frequency fcIs increased from P to Q in preset steps, wherein f is the center frequency for eachcAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (2)i(ii) a For eachA scale factor aiUsing a frequency f based on the current center frequencycAnd initial value of bandwidth fb0Performing wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
s313: calculating each center frequency f according to the formula (3) and the formula (4)cCorresponding Shannon entropy H (f)c) Entropy of Shannon H (f)c) To a minimum value Hmin(fc) The center frequency of time is used as the optimal center frequency foc；
Wherein, Wc(aiτ) as the center frequency fcCorresponding scale factor aiThe wavelet coefficients of;
s314: bandwidth fbThe value range is set as [ R, S]Then the bandwidth f is divided by a preset stepbIncreases from R to S, wherein f is for each bandwidthbAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)i(ii) a For each scale factor aiUsing a frequency based on the optimum center frequency focAnd the current bandwidth fbPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain other m wavelet coefficients;
s315: calculating each bandwidth f according to equation (5) and equation (6)bCorresponding Shannon entropy H (f)b) Entropy of Shannon H (f)b) To a minimum value Hmin(fb) Bandwidth of time as optimal bandwidth fob；
Wherein, Wb(aiτ) is the bandwidth fbCorresponding scale factor aiThe wavelet coefficients of (a).
4. The electromagnetic valve switch state judging device is characterized by comprising a magnetic circuit sensor, a vibration sensor, an A/D conversion module and a processing module;
the magnetic circuit sensor is used for acquiring a magnetic flux leakage analog signal of the electromagnetic valve; the vibration sensor is used for acquiring vibration analog signals of the electromagnetic valve; the A/D conversion module is used for respectively converting the magnetic flux leakage analog signal and the vibration analog signal into a magnetic flux leakage digital signal and a vibration digital signal; the processing module extracts an impact signal from the vibration digital signal based on a wavelet transform method, and then judges whether the electromagnetic valve is closed or not according to whether the peak value of the impact signal and the magnetic flux leakage digital signal are simultaneously larger than a preset threshold value or not.
5. The electromagnetic valve switch state determination device according to claim 4, wherein the processing module extracts an impact signal from the vibration digital signal based on wavelet transform, specifically:
s31: selecting Morlet wavelet as mother wavelet of wavelet transform, and optimizing center frequency and bandwidth of Morlet wavelet to obtain optimal center frequency f of Morlet waveletocAnd an optimum bandwidth fob；
S32: setting the value range [ f ] of the analysis frequency f1,f2,…,fm]Analysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)iI is 1,2, …, m, and m is at least 2; for each scale factor aiUsing a frequency based on the optimum center frequency focAnd an optimum bandwidth fobMorlet wavelet to the number of vibrationsPerforming wavelet transformation on the word signal to obtain m wavelet coefficients;
wherein, Δ t is a preset sampling time interval;
s33: calculating kurtosis value K of the wavelet coefficient corresponding to each scale factor, and enabling the kurtosis value K to be larger than a preset threshold value KthrhdThe wavelet coefficient corresponding to the scale factor is used as a wavelet coefficient to be selected;
s34: denoising the wavelet coefficient to be selected by using a soft threshold denoising method;
s35: and performing inverse wavelet transform on the denoised wavelet coefficient to obtain an impact signal.
6. The electromagnetic valve on-off state determining device according to claim 5, wherein the optimum center frequency focAnd an optimum bandwidth fobThe acquisition method comprises the following steps:
s311: setting the value of the analysis frequency f as [ f1,f2,…,fm]Center frequency fcHas a value range of [ P, Q]And is the bandwidth fbSetting an initial value fb0；
S312: centering frequency fcIs increased from P to Q in preset steps, wherein f is the center frequency for eachcAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (2)i(ii) a For each scale factor aiUsing a frequency f based on the current center frequencycAnd initial value of bandwidth fb0Performing wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain m wavelet coefficients;
s313: calculating each center frequency f according to the formula (3) and the formula (4)cCorresponding Shannon entropy H (f)c) Entropy of Shannon H (f)c) To a minimum value Hmin(fc) The center frequency of time is used as the optimal center frequency foc；
Wherein, Wc(aiτ) as the center frequency fcCorresponding scale factor aiThe wavelet coefficients of;
s314: bandwidth fbThe value range is set as [ R, S]Then the bandwidth f is divided by a preset stepbIncreases from R to S, wherein f is for each bandwidthbAnalysis frequency f from f1Value to fmGenerating m scale factors a according to equation (1)i(ii) a For each scale factor aiUsing a frequency based on the optimum center frequency focAnd the current bandwidth fbPerforming wavelet transformation on the vibration digital signal by using the Morlet wavelet to obtain other m wavelet coefficients;
s315: calculating each bandwidth f according to equation (5) and equation (6)bCorresponding Shannon entropy H (f)b) Entropy of Shannon H (f)b) To a minimum value Hmin(fb) Bandwidth of time as optimal bandwidth fob；
Wherein, Wb(aiτ) is the bandwidth fbCorresponding scale factor aiThe wavelet coefficients of (a).
7. The electromagnetic valve on-off state determination device according to claim 4, further comprising a magnetic circuit sensor conditioning module and a vibration sensor conditioning module;
the magnetic circuit sensor conditioning module is used for conditioning the voltage of the magnetic leakage analog signal into the sampling voltage range of the A/D conversion module; the vibration sensor conditioning module is used for conditioning the voltage of the vibration analog signal into the sampling voltage range of the A/D conversion module.
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