CN109946597B - Tap switch operation state evaluation method based on electromechanical signals - Google Patents
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Abstract
The invention discloses a tap changer (OLTC) operation state evaluation method based on electromechanical signals. As an important device in a transformer, an on-load tap changer (OLTC) has a great significance for the operation of the transformer and the whole power system. Firstly, acquiring and extracting original signals including current signals and vibration signals; secondly, carrying out envelope analysis on the current signal, carrying out singularity and wavelet packet analysis on the vibration signal, and extracting characteristic quantities, namely operation duration, impact current, Delta current, singularity index and wavelet packet energy entropy; and finally, evaluating the mechanical operation state of the tap changer by adopting a fuzzy clustering algorithm (FCM) based on the characteristic quantity.
Description
Technical Field
The invention provides a tap changer operation state evaluation method based on electromechanical signals, belongs to the technical field of power equipment, and particularly relates to a tap changer mechanical state evaluation method.
Background
With the increase of the power load and the expansion of the power supply range of the power grid, the voltage regulation of the system is more and more frequent, so that the fault rate of an on-load tap changer (OLTC) is continuously increased. Mechanical faults such as switch sliding, transmission mechanism faults, and contact faults are major faults of the OLTC. These mechanical faults affect the normal operation of the tap changer body and the power transformer, and in severe cases, cause system breakdown. Therefore, the assessment of the mechanical state of the tap changer is of great significance to guarantee the safe, stable and reliable operation of the power transformer and the system.
The traditional detection method for the mechanical operation state of the tap changer mainly judges whether the tap changer can safely and normally operate or not by testing the contact resistance, the transition resistance and the switching time of the tap changer through power failure, the workload is large, the detection environmental requirement is strict, and the tap changer needs to be operated in a power failure mode. There is no effective means for managing daily operations, especially for online operating conditions. One feasible method is to monitor vibration signals and current signals of a driving motor in the switching process of the tap changer, and extract important index quantity from the vibration signals and the current signals when the tap changer is in normal operation, abnormal operation and fault states, wherein the vibration signals and the current signals have rich related information, and the vibration signals and the current signals have important significance for reducing the faults of the tap changer and ensuring the normal operation of the tap changer.
When the operation mechanism fails to work, the operation time of the tap changer in the switching process is prolonged; when the motor is abnormally started, the amplitude of the impact current can be changed; the difference value of the minimum value and the maximum value of the current in a steady state, namely the Delta value reflects the lubrication problem of the tap switch and abnormal mechanical wear; when the tap changer breaks down in the switching process, the wave crest of the vibration signal is reflected to change, and the singularity can reflect the change; wear of the tap changer contacts changes the high and low frequency signal content of the vibration signal. The invention therefore extracts these 5 characteristic parameters of the tap changer signal for evaluating the operating state of the tap changer mechanism.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the tap changer operation state evaluation method based on the electromechanical signals, which can effectively judge the mechanical operation state of the tap changer.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a tap changer operation state evaluation method based on electromechanical signals is characterized by comprising the following steps:
(1) collecting vibration signals and driving current signals of the tap switch through an acceleration sensor and a current clamp;
(2) carrying out envelope analysis on the acquired driving current signal, and extracting operation duration, impact current and Delta current, wherein the Delta current is the difference between the minimum current and the maximum current when the driving current signal is in a steady state;
(3) performing wavelet transformation and wavelet packet analysis on the collected vibration signals of the tap switch, and extracting an anisotropy index and a wavelet packet energy entropy;
(4) and evaluating the mechanical operation state of the tap switch by adopting an FCM clustering algorithm based on the characteristic quantity, namely the characteristic quantity consisting of the operation duration, the impact current, the Delta current, the singularity index and the wavelet packet energy entropy.
The invention further preferably comprises the following technical scheme:
in step (1), the vibration signals and the driving current signals of the tap changer are collected to comprise normal signals and fault signals.
In the step (2), the operation time length, the impact current and the Delta current of the collected driving current signal are extracted, and the operation time length, the impact current and the Delta current comprise the following contents:
2.1, solving each peak point of the collected driving current signal, and then connecting each peak point to obtain an envelope line of the driving current signal;
2.2 extracting the operation duration, the impact current and the Delta current of the current signal according to the envelope curve of the current signal;
wherein the operation time length is the total time between the current start and the current end; the impact current is the maximum current when the motor is started; delta current is the difference between the minimum and maximum current values at steady state.
In the step (3), further performing wavelet packet analysis on the collected vibration signal of the tap switch, and extracting a singularity index and a wavelet packet energy entropy, wherein the specific contents are as follows:
3.1, performing wavelet transformation on the acquired vibration signals, and judging the positions of singular points and singular indexes according to the transmissibility of mode maximum values on all scales of the wavelet transformation;
3.2 wavelet packet j layer decomposition is carried out on the collected vibration signals of the tap switch to obtain 2jCalculating energy value of node corresponding to each frequency band, and calculating the first 2j2 energy and 2jThe ratio t of/2 energy sums.
The 8 frequency bands are 0-3.125 kHz, 3.125-6.25 kHz, 6.25-9.375 kHz, 9.375-12.5 kHz, 12.5-15.625 kHz, 15.625-18.75 kHz, 18.75-21.875 kHz, 21.875-25 kHz respectively.
In 3.1, the singularity index is calculated approximately as follows;
and i is the number of layers of the vibration signal of the tap changer which is decomposed by wavelet analysis, the vibration signal is decomposed by the wavelet i layers to obtain k frequency bands, wherein k is i +1, and the modulus maximum value on the frequency band k is MkThe sequence of modulus maxima corresponding to each layer is formed as MkGet the singularity index:
αi＝log2Mk-log2Mk-1 (1)
calculating the singular index alpha on the i decomposition layers according to the formula (1)iAveraging the singularity indexes on all decomposition layers to obtain a singularity index alpha after wavelet transformation of the collected vibration signal; .
In 3.1, the tap changer vibration signal is wavelet decomposed using the db10 wavelet basis.
The mechanical operation state of the tap changer can be fully embodied by performing 6-layer wavelet decomposition on the tap changer vibration signal by adopting a db10 wavelet base of the Daubechies wavelet series.
And (3) selecting a db10 wavelet base of a Daubechies wavelet series to perform wavelet packet j-layer decomposition on the acquired tap switch vibration signals.
And j is 3, namely db10 wavelet basis is selected to carry out 3-layer wavelet packet transformation on the collected tap switch vibration signals to obtain 238 frequency bands.
Calculating the energy entropy E of the ith frequency band of the 3 rd layer after wavelet packet decomposition according to the following formula3(i) (ii) a W (3, i) is a signal of each node of the third layer after 3 layers of wavelet packet decomposition; then
In the formula: w (3, i) is the signal energy of each node in the third layer after 3 layers of wavelet packet decomposition, xikRepresents a signal E3(i) A kth scatter value in the i-band; wherein, i is 1,2,…, 8; k is 1,2, …, N, N is signal xikTotal length of (d);
the ratio of the high frequency to low frequency energy entropy is:
t＝(E3(1)+E3(2)+E3(3)+E3(4))/(E3(5)+E3(6)+E3(7)+E3(8)) (3)
wherein E is3(1)、E3(2)、E3(3)、E3(4) The energy entropy of the first 4 frequency bands after the 3 rd layer after wavelet packet decomposition; e3(5)、E3(6)、E3(7)、E3(8) The energy entropy of the last 4 frequency bands after the 3 rd layer after wavelet packet decomposition.
In the step (4), the characteristic quantities obtained in the steps (2) and (3), namely the operation duration, the impact current, the Delta current, the singularity index and the wavelet packet energy entropy, are used as sample data, the FCM clustering algorithm is adopted to calculate the membership degree of the sample data, and the mechanical operation state of the tap changer is evaluated according to the membership degree interval.
In the step (4), the following contents are specifically included:
4.1 sample data T is the feature value obtained in steps (2) and (3) { T ═ T1,T2,…,TnAnd establishing a fuzzy membership matrix A ═ a of the sample dataij]c×nAnd the clustering center C ═ C1,c2,…,cn]TFCM is expressed as:
in the formula: c is the number of clustering centers; n is the number of samples, and n is 5; m is a fuzzy weighting index; dijAnd aijAre respectively a sample point TjTo the center of the cluster ciThe Euclidean distance and the membership degree;
determining values of c and m, and initializing A and iteration times l; wherein c is 3, and m, l is a value built in the fcm function in matlab;
4.2 calculating a clustering center C according to the matrix A;
4.3 according to the following formula, according to the clustering center ciUpdating a membership matrix A;
4.4 for a given discrimination accuracy ε>0, if Al+1-AlIf | | is less than or equal to epsilon, stopping iteration, otherwise, setting l to l +1, and returning to the step 4.2 until a given judgment precision condition is met;
and 4.5, evaluating the mechanical operation state of the tap changer by utilizing the membership degree meeting the judgment precision requirement obtained by the step 4.4.
If the membership degree is in the period of 0,0.5), indicating that the tap changer is in a fault state;
if the membership degree is in the period of [0.5,0.9), indicating that the tap changer is in an abnormal state, and stopping to check at a proper time;
if the degree of membership is during 0.9,1, it indicates that the tap changer is in a normal state.
The invention achieves the following beneficial effects:
1. the invention analyzes and processes the vibration signal and the current signal of the tap switch, the extracted characteristic quantity can effectively reflect various mechanical states of the tap switch, the method is simple and easy to implement, and the algorithm is simple;
2. because the vibration signal and the current signal can be collected when the tap changer operates, the invention provides technical support for on-line operation monitoring of the tap changer;
3. the tap changer mechanical operation state is evaluated by adopting a fuzzy clustering algorithm, and the normal operation state and the fault degree of the tap changer can be accurately reflected.
Drawings
Fig. 1 is a flow chart of a tap changer operating condition evaluation method based on electromechanical signals in accordance with the present invention;
fig. 2 is a characteristic parameter explanatory diagram.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following embodiments are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, the invention discloses a tap changer operation state evaluation method based on electromechanical signals, which comprises the following steps:
step 1: acquiring a vibration signal and a driving current signal of the tap switch through an acceleration sensor and a current clamp;
the collected vibration signals and current signals comprise normal signals and fault signals.
In a preferred embodiment of the present invention, 32 sets of data (i.e., 16 sets of current signals, 12 sets of fault data, 4 sets of normal data, and 16 sets of vibration signals, 12 sets of fault data, 4 sets of normal data) are collected together.
Step 2: and carrying out envelope analysis on the acquired current signals, and extracting the operation duration, the impact current and the Delta current.
In the preferred embodiment of the present invention, the envelope analysis is performed on the collected current signal, and the extraction of the operating duration, the inrush current, and the Delta current includes the following contents:
2.1, calculating a peak point of the current signal, and then connecting the peak point to obtain an envelope curve of the current signal, namely envelope analysis.
And 2.2, extracting the operation time length, the impact current and the Delta current of the current signal according to the envelope curve of the current signal.
The meaning of the parameters of the operation duration, the impact current and the Delta current is shown in FIG. 2, namely, the operation duration is the total time between the beginning and the end of the current; the impact current is the maximum current when the motor is started; delta current is the difference between the minimum and maximum current values at steady state. The rejection caused by the failure of the tap changer operating mechanism can be found through the operating duration; the impact current can find abnormal faults of the motor starting; tap changer lubrication problems as well as abnormal mechanical wear can be found by Delta current. Therefore, by extracting these characteristic quantities of the tap changer, the mechanical operating state of the tap changer can be found efficiently.
And step 3: carrying out wavelet packet analysis on the collected vibration signals, and extracting a singularity index and a wavelet packet energy entropy;
in a preferred embodiment of the present invention, step 3 specifically includes the following:
3.1 wavelet transform is carried out on the vibration signal, the position of a singular point and a singular index are judged according to the transmissibility of the mode maximum value on each scale of the wavelet transform, and the singular index can be approximately calculated as follows.
And i is the number of layers of the vibration signal of the tap changer which is decomposed by wavelet analysis, the vibration signal is decomposed by the wavelet i layers to obtain k frequency bands, wherein k is i +1, and the modulus maximum value on the frequency band k is MkThe sequence of modulus maxima corresponding to each layer is formed as MkGet the singularity index:
αi＝log2Mk-log2Mk-1 (1)
calculating alpha values on i decomposition layers according to the formula (1), and then taking an average value;
according to multiple calculation and analysis, the vibration signal of the tap changer is decomposed by 6 layers by adopting db10 wavelet base, so that the mechanical operation state of the tap changer can be fully reflected.
3.2 wavelet packet j layer decomposition is carried out on the collected vibration signals of the tap switch to obtain 2jCalculating energy value of node corresponding to each frequency band, and calculating the first 2j2 energy and 2jThe ratio t of/2 energy sums.
In the embodiment of the invention, the decomposition of the wavelet packet is to decompose the signal into a high frequency range and a low frequency range by using a high filter and a low filter, and the frequency band of the signal is decomposed by more layers. The invention selects db10 wavelet of Daubechies wavelet series to perform 3-layer wavelet packet transformation on the collected vibration signal, so as to obtain 8 frequency bands and improve the time-frequency resolution of the signal.
In the preferred embodiment of the present application, the 8 frequency bands are 0-3.125 kHz, 3.125-6.25 kHz, 6.25-9.375 kHz, 9.375-12.5 kHz, 12.5-15.625 kHz, 15.625-18.75 kHz, 18.75-21.875 kHz, 21.875-25 kHz, respectively.
The wavelet packet decomposition result expressed according to the energy mode is called a wavelet packet-energy spectrum, and because the time drift of a vibration impact event can be caused when the mechanical fault occurs to the tap changer, and the change of some wave peak values in a time domain waveform can also be caused, the proportion of energy of each frequency band to the total energy can be broken along with the change of the state of the tap changer. That is, the proportion of the energy of each frequency band can reflect the fault information of the tap changer. Let E3(i) To correspond to node energy, where E3(i) The energy entropy of the ith frequency band of the layer 3 after wavelet packet decomposition is obtained. W (3, i) is a signal of each node of the third layer after 3 layers of wavelet packet decomposition; then
In the formula: x is the number ofikRepresents a signal E3(i) A kth scatter value in the i-band; wherein, i is 1,2, …, 8; k is 1,2, …, N. N is a signal xikThe total length of (c).
The ratio of the high frequency to low frequency energy entropy is:
t＝(E3(1)+E3(2)+E3(3)+E3(4))/(E3(5)+E3(6)+E3(7)+E3(8)) (3)
wherein E is3(1)、E3(2)、E3(3)、E3(4) The energy entropy of the first 4 frequency bands after the 3 rd layer after wavelet packet decomposition; e3(5)、E3(6)、E3(7)、E3(8) The energy entropy of the last 4 frequency bands after the 3 rd layer after wavelet packet decomposition.
And 4, step 4: evaluating the mechanical operation state of the tap changer by adopting an FCM clustering algorithm based on the characteristic quantity (namely the characteristic quantity consisting of operation duration, impact current, Delta current, a singularity index and wavelet packet energy entropy);
and (3) forming characteristic quantities for estimating the mechanical running state of the tap changer by the 5 parameters (namely the operation duration, the impact current, the Delta current, the singularity index and the energy entropy) obtained in the steps (2) and (3), wherein the characteristic quantities obtained by the method are a 16 x 5 matrix.
The FCM clustering algorithm comprises the following steps:
4.1 using the feature value obtained in step (2) as sample data T ═ T1,T2,…,TnAnd establishing a fuzzy membership matrix A ═ a of sample dataij]c×nAnd the clustering center C ═ C1,c2,…,cn]TFCM is expressed as:
in the formula: c is the number of clustering centers; n is the number of samples; m is a fuzzy weighting index; dijAnd aijAre respectively a sample point TjTo the center of the cluster ciThe Euclidean distance and the membership degree;
determining values of c and m, initializing A and iteration times l, wherein c is 3, and the value of m is a built-in value of the fcm function in matlab;
in a preferred embodiment of the present application, the number of samples n is 5.
4.2 calculating a clustering center C according to the matrix A;
4.3 clustering center ciUpdating a membership matrix A;
4.4 for a given discrimination accuracy ε>0, empirical value 0.1, if Al+1-AlIf | | is less than or equal to epsilon, stopping iteration, otherwise, setting l to l +1, and returning to the step 4.2 until a given judgment precision condition is met;
and 4.5, evaluating the mechanical operation state of the tap changer by utilizing the membership degree meeting the judgment precision requirement obtained by the step 4.4.
A higher degree of membership indicates that the group of data is more correlated with the normal state of the tap changer, i.e., the tap changer is more likely to be in a normal operating state.
The criteria for assessing the degree of membership in the mechanical operating state of the tap changer are defined as follows:
if the membership degree is in the period of [00.5), indicating that the tap changer is in a fault state;
if the membership is in the period of [0.50.9), the tap changer is indicated to be in an abnormal state, namely, the tap changer can still operate, but the shutdown check is preferred;
if the degree of membership is during 0.91, it indicates that the tap changer is in a normal state.
In the preferred embodiment of the present application, the 16 x 5 component tap data are FCM clustered to obtain the evaluation results shown in table 1,
TABLE 1
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| 0.0189 | 0.0191 | 0.0158 | 0.0400 | 0.0480 | 0.0703 | 0.0074 | 0.0030 |
| 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 |
| 0.0513 | 0.0070 | 0.0046 | 0.0067 | 0.9965 | 0.9973 | 0.9867 | 0.9903 |
Table 1 shows the result of the evaluation by the FCM clustering algorithm, and it can be seen from table 1 that the membership of the last four groups of data is in the range of [0.91], and the others are in the period of [00.5 ], and it can be seen from the above evaluation that the tap changer of the first 12 groups of data is in a fault state, and should be stopped for inspection, and the tap changer of the last 4 groups of data is in a normal state. The evaluation result is consistent with the actual running state of the tap changer, so that the evaluation method can effectively evaluate the running state of the tap changer and verify the effectiveness of the invention.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.
Claims (9)
1. A tap changer operation state evaluation method based on electromechanical signals is characterized by comprising the following steps:
(1) acquiring a vibration signal and a driving current signal of the tap switch through an acceleration sensor and a current clamp;
(2) carrying out envelope analysis on the acquired driving current signal, and extracting operation duration, impact current and Delta current, wherein the Delta current is the difference between the minimum current and the maximum current when the driving current signal is in a steady state;
2.1, solving each peak point of the collected driving current signal, and then connecting each peak point to obtain an envelope line of the driving current signal;
2.2 extracting the operation duration, the impact current and the Delta current of the current signal according to the envelope curve of the current signal; wherein the operation time length is the total time between the current start and the current end; the impact current is the maximum current when the motor is started; delta current is the difference between the minimum and maximum current values in a steady state;
(3) wavelet transform and wavelet packet analysis are carried out on the collected vibration signals of the tap switch, the singularity index and the wavelet packet energy entropy are extracted, and the first 2 in the wavelet packet energy entropy is calculatedj2 energy and 2jThe ratio t of energy sum is 2, wherein j refers to the number of layers for performing wavelet packet decomposition on the acquired tap changer vibration signal by using db10 wavelet base of Daubechies wavelet series;
(4) based on characteristic quantity, namely, the characteristic quantity consists of operation duration, impact current, Delta current, singular index and top 2 of wavelet packet energy entropyj2 energy and 2jThe characteristic quantity formed by the ratio t of the/2 energy sums is calculated by adopting an FCM clustering algorithm to calculate the membership degree of the sample data, wherein the clustering is performedThe number of centers is 3;
if the membership degree is in the period of 0,0.5), indicating that the tap changer is in a fault state;
if the membership degree is in the period of [0.5,0.9), indicating that the tap changer is in an abnormal state, and stopping to check at a proper time;
if the degree of membership is during 0.9,1, it indicates that the tap changer is in a normal state.
2. The method of claim 1, wherein the method comprises the steps of:
in step (1), the vibration signals and the driving current signals of the tap changer are collected to comprise normal signals and fault signals.
3. The method of claim 1, wherein the method comprises the steps of:
in the step (3), further comprising performing wavelet packet analysis on the collected vibration signal of the tap switch, and extracting a singularity index and a ratio t of the sum of the front 2j/2 energy and the rear 2j/2 energy in the wavelet packet energy entropy, wherein the specific contents are as follows:
3.1, performing wavelet transformation on the acquired vibration signals, and judging the positions of singular points and singular indexes according to the transmissibility of mode maximum values on all scales of the wavelet transformation;
3.2 wavelet packet j layer decomposition is carried out on the collected vibration signals of the tap switch to obtain 2jCalculating energy value of node corresponding to each frequency band, and calculating the first 2j2 energy and 2jThe ratio t of/2 energy sums.
4. The method of claim 3, wherein the step switch operating condition evaluation method based on electromechanical signals comprises:
in 3.1, the singularity index is calculated approximately as follows;
and i is set as the number of layers of the tap switch vibration signal decomposed by wavelet analysis, and k vibration signals are obtained after the vibration signal is decomposed by the wavelet i layerFrequency band, where k is i +1, the modulo maximum at frequency band k is MkThe sequence of modulus maxima corresponding to each layer is formed as MkGet the singularity index:
αi＝log2Mk-log2Mk-1 (1)
calculating the singular index alpha on the i decomposition layers according to the formula (1)iAnd averaging the singular indexes on all the decomposition layers to obtain the singular index alpha after the wavelet transformation of the acquired vibration signal.
5. The method of claim 4, wherein the step switch operating condition evaluation method based on electromechanical signals comprises:
the mechanical operation state of the tap changer can be fully embodied by performing 6-layer wavelet decomposition on the tap changer vibration signal by adopting a db10 wavelet base of the Daubechies wavelet series.
6. The method of claim 1, wherein the method comprises the steps of:
and j is 3, namely db10 wavelet basis is selected to carry out 3-layer wavelet packet transformation on the collected tap switch vibration signals to obtain 238 frequency bands.
7. The method of claim 6, wherein the step switch operating condition evaluation method based on electromechanical signals comprises:
calculating the energy entropy E of the ith frequency band of the 3 rd layer after wavelet packet decomposition according to the following formula3(i) (ii) a W (3, i) is a signal of each node of the third layer after 3 layers of wavelet packet decomposition; then
In the formula: w (3, i) is the signal energy of each node in the third layer after 3 layers of wavelet packet decomposition, xikRepresents a signal E3(i) A kth scatter value in the i-band; wherein, i is 1,2, …, 8; k is 12, …, N, N being the signal xikTotal length of (d);
the ratio of the high frequency to low frequency energy entropy is:
t＝(E3(1)+E3(2)+E3(3)+E3(4))/(E3(5)+E3(6)+E3(7)+E3(8)) (3)
wherein E is3(1)、E3(2)、E3(3)、E3(4) The energy entropy of the first 4 frequency bands after the 3 rd layer after wavelet packet decomposition; e3(5)、E3(6)、E3(7)、E3(8) The energy entropy of the last 4 frequency bands after the 3 rd layer after wavelet packet decomposition.
8. The method of claim 7, wherein the step switch operating condition evaluation method based on electromechanical signals comprises:
in the step (4), the following contents are specifically included:
4.1 sample data T is the feature value obtained in steps (2) and (3) { T ═ T1,T2,…,TnAnd establishing a fuzzy membership matrix A ═ a of sample dataij]c×nAnd the clustering center C ═ C1,c2,…,cn]TFCM is expressed as:
in the formula: c is the number of clustering centers; n is the number of samples, and n is 5; m is a fuzzy weighting index; dijAnd aijAre respectively a sample point TjTo the center of the cluster ciThe Euclidean distance and the membership degree;
determining values of c and m, and initializing A and iteration times l;
4.2 calculating a clustering center C according to the matrix A;
4.3 according to the following formula, according to the clustering center ciUpdating a membership matrix A;
4.4 for a given discrimination accuracy ε>0, if Al+1-AlIf | | is less than or equal to epsilon, stopping iteration, otherwise, setting l to l +1, and returning to the step 4.2 until a given judgment precision condition is met;
and 4.5, evaluating the mechanical operation state of the tap changer by utilizing the membership degree meeting the judgment precision requirement obtained by the step 4.4.
9. The method of claim 8, wherein the step switch operating condition evaluation based on electromechanical signals comprises:
in 4.1, the fuzzy weighting index m and the iteration number l are selected as the built-in values of the fcm function in matlab.
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| CN111474410B (en) * | 2020-04-07 | 2022-09-09 | 宁波市重强电器有限公司 | Detection method of electric connector |
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