Method and device for diagnosing switch cabinet faults

Abstract

The present invention relates to a method and device for switch cabinet fault diagnosis, wherein the method comprises obtaining a real-time characteristic curve of a monitored component in the switch cabinet, the real-time characteristic curve has m sampling points, the monitored component corresponds to a reference characteristic curve, the reference characteristic curve is obtained when the monitored component is in a normal working state, and the reference characteristic curve has n sampling points, and is characterized in that the method further comprises: obtaining a first expected value of the real-time characteristic curve, the reference characteristic curve corresponds to a second expected value; based on the first expected value and the second expected value, determining the Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve; and determining whether the switch cabinet has a fault according to the Pearson correlation coefficient.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and in particular to a method and device for diagnosing faults in a switch cabinet. Background Art

[0002] Switchgear equipment is a device that opens and closes, controls and protects electricity in the power system, and its normal operation must be guaranteed. In the prior art, some factories adopt online monitoring, that is, real-time monitoring of a component in the switchgear to detect the fault of the component in time. Therefore, how to analyze the data obtained during online monitoring and detect faults in time is an urgent problem to be solved. Summary of the invention

[0003] In view of this, the present invention proposes a method for fault diagnosis of a switch cabinet, comprising obtaining a real-time characteristic curve of a monitored component in the switch cabinet, wherein the real-time characteristic curve has m sampling points, and the monitored component corresponds to a reference characteristic curve, wherein the reference characteristic curve is obtained when the monitored component is in a normal working state, and the reference characteristic curve has n sampling points. The method further comprises:

[0004] Acquire a first expected value of the real-time characteristic curve, wherein the reference characteristic curve corresponds to a second expected value;

[0005] determining a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value;

[0006] Whether the switch cabinet fails is determined according to the Pearson correlation coefficient.

[0007] According to the method as described above, optionally, obtaining the first expected value of the real-time characteristic curve includes:

[0008] The first expected value E(C) of the real-time characteristic curve is obtained according to the following formula:

[0009] Wherein C(i) represents the value of the i-th sampling point of the real-time characteristic curve;

[0010] The second expected value E(R) corresponding to the reference characteristic curve is obtained by the following formula:

[0011] Wherein R(j) represents the value of the j-th sampling point of the reference characteristic curve.

[0012] According to the method as described above, optionally, determining the Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value includes:

[0013] The Pearson correlation coefficient p between the real-time characteristic curve and the reference characteristic curve is determined according to the following formula:

[0014]

[0015] Wherein, M is the smaller of the number of sampling points of the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the real-time characteristic curve, and R(q) represents the value of the qth sampling point of the reference characteristic curve;

[0016] Determining whether the switch cabinet fails according to the Pearson correlation coefficient includes:

[0017] If the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet fails.

[0018] According to the method as described above, optionally, before determining whether the switch cabinet fails according to the Pearson correlation coefficient, the method further includes:

[0019] The Pearson correlation coefficient p is corrected according to the following formula:

[0020] If m>n, p×n / m is taken as the corrected p;

[0021] If n>m, p×m / n is taken as the corrected p.

[0022] According to the method as described above, optionally, before determining the Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve, the method further includes:

[0023] The real-time characteristic curve is filtered according to the following operations:

[0024] The first sampling point and the mth sampling point of the real-time mechanical characteristic curve are retained; the first sampling point of the real-time mechanical characteristic curve is used as the initial first reference point; the value of f is assigned to 1; the absolute value of the difference between the i+fth sampling point and the first reference point in the real-time mechanical characteristic curve is obtained as the first absolute value, wherein the i-th sampling point represents the first reference point and the value of f is 1; according to the first absolute value, it is determined whether to retain the i+fth sampling point and the i+f-1th sampling point; if the determination result is yes, the i+fth sampling point is used as the updated first reference point, and the operation of assigning the value of f to 1 is returned to execute, until the absolute value of the difference between the m-1th sampling point and the first reference point is obtained as the first absolute value and according to the first absolute value, it is determined whether to retain the m-1th sampling point and the m-2th sampling point; the curve formed by all the retained sampling points is used as the filtered real-time mechanical characteristic curve;

[0025] The reference characteristic curve is filtered according to the following operations:

[0026] The first sampling point and the nth sampling point of the reference characteristic curve are retained; the first sampling point of the reference characteristic curve is used as the initial second reference point; the value of s is assigned to 1; the absolute value of the difference between the j+sth sampling point and the second reference point in the reference characteristic curve is obtained as the second absolute value, wherein the jth sampling point represents the second reference point; whether to retain the j+sth sampling point and the j+s-1th sampling point is determined according to the second absolute value; if the determination result is yes, the j+sth sampling point is used as the updated second reference point, and the operation of assigning the value of s to 1 is returned to execute, until the first absolute value of the difference between the n-1th sampling point and the first reference point is obtained and whether to retain the n-1th sampling point and the n-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered reference mechanical characteristic curve;

[0027] Correspondingly, C(q) represents the value of the qth sampling point of the real-time characteristic curve after filtering, and R(q) represents the value of the qth sampling point of the reference characteristic curve after filtering.

[0028] According to the method described above, optionally, determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value specifically includes:

[0029] Determine whether the absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the i+fth sampling point and the i+f-1th sampling point;

[0030] Determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value includes:

[0031] It is determined whether the second absolute value corresponding to the j+sth sampling point is greater than or equal to a filtering threshold; if the determination result is yes, the j+sth sampling point and the j+s-1th sampling point are retained.

[0032] According to the method as described above, optionally, it also includes:

[0033] If the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is no, then after updating the value of f to f+1, returning to execute the operation of obtaining the first absolute value of the difference between the i+fth sampling point in the real-time mechanical characteristic curve and the first reference point;

[0034] If the result of determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value is no, then after updating the value of s to s+1, the operation of obtaining the absolute value of the difference between the j+sth sampling point in the reference characteristic curve and the second reference point as the second absolute value is returned.

[0035] The present invention also provides a switch cabinet fault diagnosis device, the device comprising:

[0036] A first acquisition unit, used to acquire a real-time characteristic curve of a monitored component in the switch cabinet, the real-time characteristic curve having m sampling points, the monitored component corresponding to a reference characteristic curve, the reference characteristic curve being acquired when the monitored component is in a normal working state, the reference characteristic curve having n sampling points;

[0037] Also includes:

[0038] A second acquisition unit, used for acquiring a first expected value of the real-time characteristic curve, wherein the reference characteristic curve corresponds to a second expected value;

[0039] a first determining unit, configured to determine a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value;

[0040] A second determination unit is used to determine whether the switch cabinet fails according to the Pearson correlation coefficient.

[0041] According to the above device, optionally, the second acquiring unit is specifically used for:

[0042] The first expected value E(C) of the real-time characteristic curve is obtained according to the following formula:

[0043] Wherein C(i) represents the value of the i-th sampling point of the real-time characteristic curve;

[0044] The second expected value E(R) corresponding to the reference characteristic curve is obtained by the following formula:

[0045] Wherein R(j) represents the value of the j-th sampling point of the reference characteristic curve.

[0046] According to the above device, optionally, the first determining unit is specifically configured to:

[0047] The Pearson correlation coefficient p between the real-time characteristic curve and the reference characteristic curve is determined according to the following formula:

[0048]

[0049] Wherein, M is the smaller of the number of sampling points of the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the real-time characteristic curve, and R(q) represents the value of the qth sampling point of the reference characteristic curve;

[0050] The second determining unit is specifically configured to:

[0051] If the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet fails.

[0052] According to the device as described above, optionally, it further comprises a correction unit, wherein the correction unit is used to:

[0053] The Pearson correlation coefficient p is corrected according to the following formula:

[0054] If m>n, p×n / m is taken as the corrected p;

[0055] If n>m, p×m / n is taken as the corrected p.

[0056] According to the device as described above, optionally, it further comprises a filtering unit, wherein the filtering unit is used for:

[0057] The real-time characteristic curve is filtered according to the following operations:

[0058] The first sampling point and the mth sampling point of the real-time mechanical characteristic curve are retained; the first sampling point of the real-time mechanical characteristic curve is used as the initial first reference point; the value of f is assigned to 1; the absolute value of the difference between the i+fth sampling point and the first reference point in the real-time mechanical characteristic curve is obtained as the first absolute value, wherein the i-th sampling point represents the first reference point and the value of f is 1; according to the first absolute value, it is determined whether to retain the i+fth sampling point and the i+f-1th sampling point; if the determination result is yes, the i+fth sampling point is used as the updated first reference point, and the operation of assigning the value of f to 1 is returned to execute, until the absolute value of the difference between the m-1th sampling point and the first reference point is obtained as the first absolute value and according to the first absolute value, it is determined whether to retain the m-1th sampling point and the m-2th sampling point; the curve formed by all the retained sampling points is used as the filtered real-time mechanical characteristic curve;

[0059] The reference characteristic curve is filtered according to the following operations:

[0060] The first sampling point and the nth sampling point of the reference characteristic curve are retained; the first sampling point of the reference characteristic curve is used as the initial second reference point; the value of s is assigned to 1; the absolute value of the difference between the j+sth sampling point and the second reference point in the reference characteristic curve is obtained as the second absolute value, wherein the jth sampling point represents the second reference point; whether to retain the j+sth sampling point and the j+s-1th sampling point is determined according to the second absolute value; if the determination result is yes, the j+sth sampling point is used as the updated second reference point, and the operation of assigning the value of s to 1 is returned to execute, until the first absolute value of the difference between the n-1th sampling point and the first reference point is obtained and whether to retain the n-1th sampling point and the n-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered reference mechanical characteristic curve;

[0061] Correspondingly, C(q) represents the value of the qth sampling point of the real-time characteristic curve after filtering, and R(q) represents the value of the qth sampling point of the reference characteristic curve after filtering.

[0062] According to the device as described above, optionally, when the filtering unit determines whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value, it is specifically used to: determine whether the absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the i+fth sampling point and the i+f-1th sampling point;

[0063] When determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value, the filtering unit is specifically configured to: determine whether the second absolute value corresponding to the j+sth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the j+sth sampling point and the j+s-1th sampling point.

[0064] According to the device as described above, optionally, the filtering unit is also used for:

[0065] If the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is no, then after updating the value of f to f+1, returning to execute the operation of obtaining the first absolute value of the difference between the i+fth sampling point in the real-time mechanical characteristic curve and the first reference point;

[0066] If the result of determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value is no, then after updating the value of s to s+1, the operation of obtaining the absolute value of the difference between the j+sth sampling point in the reference characteristic curve and the second reference point as the second absolute value is returned.

[0067] The present invention also provides a switch cabinet fault diagnosis device, wherein the switch cabinet includes a plurality of monitored components, and the device includes:

[0068] at least one memory for storing instructions;

[0069] At least one processor is configured to execute the switch cabinet fault diagnosis method according to any one of the above items according to the instructions stored in the memory.

[0070] The present invention further provides a readable storage medium, wherein the readable storage medium stores machine-readable instructions. When the machine-readable instructions are executed by a machine, the machine executes the method for diagnosing a switch cabinet fault according to any one of the above items.

[0071] According to the present invention, whether a switch cabinet fails is determined by the Pearson correlation coefficient, the health status of the switch cabinet can be accurately judged, and the online monitoring and diagnosis of the switch cabinet are more precise and rapid. It can be applied to a variety of monitored components and has strong applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the above and other features and advantages of the present invention will be more apparent to those skilled in the art. In the accompanying drawings:

[0073] Figure 1 The figure is a flow chart of a method for diagnosing switch cabinet faults according to an embodiment of the present invention.

[0074] Figure 2 The figure is a flow chart of a method for diagnosing switch cabinet faults according to another embodiment of the present invention.

[0075] Figure 3A The figure is a schematic diagram of the structure of a switch cabinet fault diagnosis device according to an embodiment of the present invention.

[0076] Figure 3B FIG. 4 is a schematic diagram of the structure of a switch cabinet fault diagnosis device according to another embodiment of the present invention.

[0077] Figure 4 The figure is a schematic diagram of the structure of a switch cabinet fault diagnosis device according to another embodiment of the present invention. DETAILED DESCRIPTION

[0078] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail with reference to the following embodiments.

[0079] In the present invention, it is necessary to obtain the real-time mechanical characteristic curve of the monitored component. For example, in the process of the trolley in the switch cabinet moving from the experimental position to the working position, its voltage value can be measured in real time by the sensor, and the curve composed of the multiple voltage values ​​can be used as the real-time mechanical characteristic curve; the monitored component can also be the drive shaft in the switch cabinet, and specifically the current value corresponding to the drive shaft moving from the closing position to the opening position can be monitored, and the curve composed of the multiple current values ​​can be used as the real-time mechanical characteristic curve. That is, the curve composed of the corresponding multiple sampling points in one operation of the monitored component is used as the real-time mechanical characteristic curve. The monitored component also corresponds to a preset reference mechanical characteristic curve, which is the mechanical characteristic curve of the monitored component when it is working normally.

[0080] Embodiment 1

[0081] This embodiment provides a method for diagnosing a switch cabinet fault. The method can be executed by a switch cabinet fault diagnosis device, and the device can be integrated in a relay protection device.

[0082] like Figure 1 FIG. 1 is a flow chart of a method for diagnosing a switch cabinet fault according to this embodiment. The method includes:

[0083] Step 101: obtain a real-time characteristic curve of a monitored component in a switch cabinet, where the real-time characteristic curve has m sampling points.

[0084] The monitored components can be set according to actual needs, such as the switch cabinet trolley, control shaft, ground knife, energy storage motor, opening and closing coil, etc., which will not be elaborated here. The real-time mechanical characteristic curve refers to the curve corresponding to the movement of the monitored component, which can be obtained by recording. Characteristics are, for example, current, voltage or vibration. The real-time mechanical characteristic curve is a curve composed of multiple sampling points, and the curve can be a curve of a complete action. For example, the trolley moves from one position to another, and the control shaft rotates from one position to another, which are all complete actions.

[0085] In addition, the monitored component has a preset reference mechanical characteristic curve. The reference mechanical characteristic curve is obtained when the monitored component is in normal working state, and the characteristics of the reference mechanical characteristic curve are consistent with the real-time mechanical characteristic curve, such as current, voltage or vibration. The reference mechanical characteristic curve is composed of multiple sampling points, such as a curve of a complete action, such as a trolley moving from one position to another, and a control shaft rotating from one position to another, which are all complete actions.

[0086] The horizontal axis of each curve may be time, and the vertical axis may be a characteristic value. The difference between the sampling points is the characteristic difference, such as the voltage difference or the current difference.

[0087] The reference characteristic curve and the real-time mechanical characteristic curve of this embodiment can be the curves remaining after removing the startup phase from the recording. Since the data of the startup phase has little effect on determining whether the switch cabinet has a fault, it can be removed to reduce the amount of data processing.

[0088] Step 102: obtaining a first expected value of the real-time characteristic curve, and the reference characteristic curve corresponds to a second expected value.

[0089] For example, the first expected value of the real-time characteristic curve can be obtained according to the following formula:

[0090] Where C(i) represents the value of the i-th sampling point of the real-time characteristic curve.

[0091] The expected value of the reference characteristic curve of this embodiment can also be obtained according to the following formula:

[0092] Where R(j) represents the value of the jth sampling point of the reference characteristic curve.

[0093] In this embodiment, the expected value of the reference characteristic curve can be obtained in advance and used when needed, that is, the expected value of the reference characteristic curve can be calculated and stored before step 101 .

[0094] Step 103: Determine a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value.

[0095] The Pearson correlation coefficient is a value between -1 and 1. Optionally, the Pearson correlation coefficient p of this embodiment can be determined according to the following formula:

[0096]

[0097] Where M is the smaller of the number of sampling points in the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the real-time characteristic curve, and R(w) represents the value of the qth sampling point of the reference characteristic curve. The value here should of course be understood as the value of the characteristic, not the sampling time.

[0098] Optionally, the reference characteristic curve and the real-time characteristic curve used in determining the Pearson correlation coefficient may be curves processed according to the original data, for example, the original reference characteristic curve is filtered after being obtained, and the filtered reference characteristic curve is the reference characteristic curve used in this step. Filtering the reference characteristic curve and the real-time characteristic curve can reduce the amount of data calculation.

[0099] It should be noted that the sampling points of the reference characteristic curve and the sampling points of the real-time characteristic curve used in step 102 are sampling points of original data, for example, the sampling points remaining after removing the startup phase data after recording.

[0100] Step 104: Determine whether the switch cabinet fails based on the Pearson correlation coefficient.

[0101] For example, if the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet has a fault; if the Pearson correlation coefficient is greater than the preset threshold, it is determined that the switch cabinet has not a fault. The preset threshold of this embodiment can be adjusted according to the number of sampling points of the real-time characteristic curve. If the number is large, such as tens of thousands, the value of the preset threshold is set relatively low, such as 0.5; if the number of sampling points is small, such as dozens, the value of the preset threshold is set relatively high, such as 0.8. This is because the more the number of sampling points, the greater the error rate, so adjusting the preset threshold according to the total number of sampling points can make the fault diagnosis result more accurate.

[0102] Optionally, before determining whether the switch cabinet fails based on the Pearson correlation coefficient, the Pearson correlation coefficient p is corrected, for example, by the following formula:

[0103] If m>n, p×n / m is taken as the corrected p;

[0104] If n>m, p×m / n is taken as the corrected p.

[0105] By correcting the Pearson correlation coefficient using the above formula, the error caused by the difference in the number of original sampling points of the two curves can be minimized.

[0106] According to the present invention, whether a switch cabinet fails is determined by the Pearson correlation coefficient, the health status of the switch cabinet can be accurately judged, and the online monitoring and diagnosis of the switch cabinet are more precise and rapid. It can be applied to a variety of monitored components and has strong applicability.

[0107] Embodiment 2

[0108] This embodiment further supplements the switch cabinet fault diagnosis method of the first embodiment.

[0109] like Figure 2 , which is a flow chart of the switch cabinet fault diagnosis method according to this embodiment.

[0110] Step 201: obtain a real-time characteristic curve of a monitored component in the switch cabinet, where the real-time characteristic curve has m sampling points.

[0111] This step is the same as step 101 and will not be described again here.

[0112] Step 202: Obtain a first expected value of the real-time characteristic curve, and the reference characteristic curve corresponds to a second expected value.

[0113] This step is consistent with step 102 and will not be described again here.

[0114] Step 203: filter the real-time characteristic curve according to the following operations:

[0115] a0: retain the first sampling point and the mth sampling point of the real-time mechanical characteristic curve;

[0116] a1: take the first sampling point of the real-time mechanical characteristic curve as the initial first reference point;

[0117] a2: Assign the value of f to 1;

[0118] a3: obtaining the absolute value of the difference between the i+fth sampling point in the real-time mechanical characteristic curve and the first reference point as the first absolute value, wherein the i-th sampling point represents the first reference point;

[0119] a4: determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value;

[0120] a5: If the result of the determination is yes, the i+fth sampling point is used as the updated first reference point, and the operation of a2 is returned until the absolute value of the difference between the m-1th sampling point and the first reference point is obtained as the first absolute value and it is determined whether to retain the m-1th sampling point and the m-2th sampling point according to the first absolute value;

[0121] a6: The curve formed by all the retained sampling points is used as the filtered real-time mechanical characteristic curve.

[0122] In this embodiment, the first sampling point and the mth sampling point are first retained in order to make the duration of the real-time mechanical characteristic curve consistent with the duration of the reference mechanical characteristic curve, so as to avoid the situation where the contours of the two curves are inconsistent due to the removal of the first sampling point or the mth sampling point, thereby causing errors in the monitoring results. In other words, regardless of the subsequent determination results, the first sampling point and the last sampling point should be retained. According to the time of acquisition, the earliest acquired sampling point is used as the first reference point. In the case where the first sampling point is used as the first reference point, the absolute value between the difference between the second sampling point and the first sampling point is first obtained. Since the sampling point itself is a value representing a characteristic, such as current, voltage, amplitude difference, etc., the difference between the sampling points is the current difference, voltage difference or amplitude difference, etc.

[0123] In this embodiment, the assignment operation of step a2 is regarded as an initial value of f. If step a2 is not triggered again, the value of f changes according to the subsequent operation. If step a2 is triggered again, the value of f is still assigned to 1. The purpose of the assignment of f is to enable the value of f in step a3 to have a specific value.

[0124] In this embodiment, it can be determined whether the first absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and the initial value of f is 1. If the determination result is yes, the i+fth sampling point and the i+f-1th sampling point are retained. If the determination result is no, the i+fth sampling point is not retained. The filtering threshold is preset and can be set according to actual needs, for example, according to the voltage level. It can be understood that if the i+f-1th sampling point has been retained, it does not need to be retained again. The i+fth sampling point and the previous sampling point are retained to make the contour of the curve as consistent as possible with the shape of the original curve. Not retaining here means not performing the retention operation, which does not mean that the i+fth sampling point will be discarded, and it may be retained later. This step can retain feature data on the basis of reducing data.

[0125] Currently, the first sampling point is used as the first reference point. If the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is yes, then the second sampling point is used as the first reference point and the operation of step 104 is performed. If the determination result is still yes, then the third sampling point is used as the first reference point and the operation of step 104 is performed; if the determination result becomes no, the first absolute value of the difference between the fifth sampling point and the third sampling point currently used as the first reference point can be obtained, and it is determined whether to retain the fifth sampling point according to the first absolute value. If the determination result is yes, then the fifth sampling point is updated as the first reference point in the next step.

[0126] This is done until the absolute value between the second to last sampling point and the first reference point is obtained and whether to retain the second to last sampling point and the third to last sampling point is determined according to the absolute value. That is, the operation can be stopped after determining whether to retain the second to last sampling point and the third to last sampling point, because the last point must be retained.

[0127] Optionally, if the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is no, then the value of f is updated to f+1, and then the operation of a3 is returned to be executed. This step is to increase the value of f by 1 and then assign it to f. For example, the initial value of f is 1, and the absolute value of the difference between the second sampling point and the first sampling point is initially judged. If the result of the determination according to the absolute value is no, the second sampling point and the first sampling point are not retained, and the value of f is updated to 2. Since the first sampling point has been retained, even if the judgment result of step 104 is no, the first sampling point is still retained. It should be noted that not retaining the second sampling point and the first sampling point does not mean that the two sampling points are deleted, but they are not retained at present, and may be retained later. After the determination result is no, the absolute value of the difference between the 3rd sampling point and the 1st sampling point is calculated, and whether to retain the 3rd sampling point and the 2nd sampling point is determined based on the absolute value. If the determination result is yes, the operation of taking the i+fth sampling point as the updated first reference point is performed, that is, the 3rd sampling point is taken as the updated first reference point. If the determination result is no, the value of f is updated to 3, and the absolute value of the difference between the 4th sampling point and the 1st sampling point is calculated, and whether to retain the 4th sampling point and the 3rd sampling point is determined based on the absolute value of the difference. Similarly, if it is determined that the corresponding sampling point and the previous sampling point need to be retained, the operation of taking the i+fth sampling point as the updated first reference point is performed.

[0128] Optionally, determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value specifically includes: determining whether the absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retaining the i+fth sampling point and the i+f-1th sampling point. The filtering threshold here can be set according to actual needs and will not be described in detail here.

[0129] Step 204 , filtering the reference characteristic curve according to the following operation.

[0130] The first sampling point and the nth sampling point of the reference characteristic curve are retained; the first sampling point of the reference characteristic curve is used as the initial second reference point; the value of s is set to 1; the absolute value of the difference between the j+sth sampling point and the second reference point in the reference characteristic curve is obtained as the second absolute value, wherein the jth sampling point represents the second reference point; whether to retain the j+sth sampling point and the j+s-1th sampling point is determined according to the second absolute value; if the determination result is yes, the j+sth sampling point is used as the updated second reference point, and the operation of assigning the value of s to 1 is returned to execute, until the first absolute value of the difference between the n-1th sampling point and the first reference point is obtained and whether to retain the n-1th sampling point and the n-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered reference mechanical characteristic curve.

[0131] Optionally, if the result of determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value is no, then after updating the value of s to s+1, the operation of obtaining the absolute value of the difference between the j+sth sampling point in the reference characteristic curve and the second reference point as the second absolute value is returned.

[0132] Optionally, determining whether to retain the j+s th sampling point and the j+s-1 th sampling point according to the second absolute value includes:

[0133] It is determined whether the second absolute value corresponding to the j+sth sampling point is greater than or equal to a filtering threshold. If the determination result is yes, the j+sth sampling point and the j+s-1th sampling point are retained.

[0134] The operation of this step is actually similar to step 203 and will not be repeated here.

[0135] It should be noted that there is no order between step 203 and step 204, and they can be performed simultaneously or one after the other.

[0136] Step 205 : determining a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value.

[0137] The Pearson correlation coefficient is a value between -1 and 1. Optionally, the Pearson correlation coefficient p of this embodiment can be determined according to the following formula:

[0138]

[0139] Wherein, M is the smaller of the number of sampling points in the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the filtered real-time characteristic curve, and R(q) represents the value of the qth sampling point of the filtered reference characteristic curve. Obtaining the Pearson correlation coefficient based on the filtered sampling points can filter out redundant data, further simplify the calculation complexity, and reduce memory usage.

[0140] Optionally, the original data is used to obtain the expected value, which can ensure the accuracy of the expected value, and the processed data is used to obtain the Pearson correlation coefficient, which can reduce the amount of calculation, so as to determine whether the switch cabinet is faulty in time.

[0141] Step 206: Determine whether the switch cabinet fails based on the Pearson correlation coefficient.

[0142] For example, if the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet has a fault; if the Pearson correlation coefficient is greater than the preset threshold, it is determined that the switch cabinet has not a fault. The preset threshold of this embodiment can be adjusted according to the number of sampling points of the real-time characteristic curve. If the number is large, such as tens of thousands, the value of the preset threshold is set relatively low. If the number of sampling points is small, such as dozens, the value of the preset threshold is set relatively high. This is because the more the number of sampling points, the greater the error rate.

[0143] Optionally, before determining whether the switch cabinet fails based on the Pearson correlation coefficient, the Pearson correlation coefficient p is corrected, for example, by the following formula:

[0144] If m>n, p×n / m is taken as the corrected p;

[0145] If n>m, p×m / n is taken as the corrected p.

[0146] Then, the corrected Pearson correlation coefficient is used to determine whether the switch cabinet is faulty.

[0147] According to this embodiment, when obtaining the Pearson correlation coefficient, the sampling points in the filtered fact characteristic curve and the filtered reference characteristic curve are used. This can minimize the data to be processed while obtaining accurate fault diagnosis results, thereby determining whether the switch cabinet has a fault as soon as possible.

[0148] Embodiment 3

[0149] This embodiment provides a switch cabinet fault diagnosis device, which is used to execute the method of embodiment 1. The device can be provided separately or integrated in a relay protection device.

[0150] like Figure 3A As shown, the switch cabinet fault diagnosis device of this embodiment has a first acquisition unit 301, which is used to obtain a real-time characteristic curve of a monitored component in the switch cabinet. The real-time characteristic curve has m sampling points. The monitored component corresponds to a reference characteristic curve. The reference characteristic curve is obtained when the monitored component is in normal working state, and the reference characteristic curve has n sampling points.

[0151] The switch cabinet fault diagnosis device of this embodiment further includes a second acquisition unit 302, a first determination unit 303 and a second determination unit 304. The second acquisition unit 302 is used to acquire a first expected value of the real-time characteristic curve, and the reference characteristic curve corresponds to a second expected value; the first determination unit 303 is used to determine the Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value; the second determination unit 304 is used to determine whether the switch cabinet has a fault according to the Pearson correlation coefficient.

[0152] Optionally, the second acquiring unit 302 of this embodiment is specifically configured to:

[0153] The first expected value E(C) of the real-time characteristic curve is obtained according to the following formula:

[0154] Where C(i) represents the value of the i-th sampling point of the real-time characteristic curve;

[0155] The second expected value E(R) corresponding to the reference characteristic curve is obtained by the following formula:

[0156] Where R(j) represents the value of the jth sampling point of the reference characteristic curve.

[0157] Optionally, the first determining unit 303 of this embodiment is specifically configured to:

[0158] The Pearson correlation coefficient p between the real-time characteristic curve and the reference characteristic curve is determined according to the following formula:

[0159]

[0160] Wherein, M is the smaller of the number of sampling points in the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the real-time characteristic curve, and R(q) represents the value of the qth sampling point of the reference characteristic curve;

[0161] The second determining unit 304 is specifically configured to:

[0162] If the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet is faulty.

[0163] Alternatively, if Figure 3B As shown, the switch cabinet fault diagnosis device of this embodiment further includes a correction unit 305, and the correction unit 305 is used to:

[0164] The Pearson correlation coefficient p is corrected according to the following formula:

[0165] If m>n, p×n / m is taken as the corrected p;

[0166] If n>m, p×m / n is taken as the corrected p.

[0167] The working methods of each unit in this embodiment are the same as those in the previous embodiment and will not be described again here.

[0168] According to the present invention, whether a switch cabinet fails is determined by the Pearson correlation coefficient, the health status of the switch cabinet can be accurately judged, and the online monitoring and diagnosis of the switch cabinet are more precise and rapid. It can be applied to a variety of monitored components and has strong applicability.

[0169] Embodiment 4

[0170] This embodiment further supplements the switch cabinet fault diagnosis device of the third embodiment.

[0171] like Figure 4 As shown, the switch cabinet fault diagnosis device of this embodiment further includes a filtering unit 401, and the filtering unit 401 is specifically used to filter the real-time characteristic curve according to the following operations: Figure 4 Although the correction unit 305 is not shown in the figure, the correction unit 305 may be included.

[0172] The 1st sampling point and the mth sampling point of the real-time mechanical characteristic curve are retained; the 1st sampling point of the real-time mechanical characteristic curve is used as the initial first reference point; the value of f is assigned to 1; the absolute value of the difference between the i+fth sampling point and the first reference point in the real-time mechanical characteristic curve is obtained as the first absolute value, wherein the i-th sampling point represents the first reference point and the value of f is 1; whether to retain the i+fth sampling point and the i+f-1th sampling point is determined according to the first absolute value; if the determination result is yes, the i+fth sampling point is used as the updated first reference point, and the operation of assigning the value of f to 1 is returned to execute, until the absolute value of the difference between the m-1th sampling point and the first reference point is obtained as the first absolute value and whether to retain the m-1th sampling point and the m-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered real-time mechanical characteristic curve;

[0173] The reference characteristic curve is filtered as follows:

[0174] The first sampling point and the nth sampling point of the reference characteristic curve are retained; the first sampling point of the reference characteristic curve is used as the initial second reference point; the value of s is assigned to 1; the absolute value of the difference between the j+sth sampling point and the second reference point in the reference characteristic curve is obtained as the second absolute value, wherein the jth sampling point represents the second reference point; whether to retain the j+sth sampling point and the j+s-1th sampling point is determined according to the second absolute value; if the determination result is yes, the j+sth sampling point is used as the updated second reference point, and the operation of assigning the value of s to 1 is returned to execute, until the first absolute value of the difference between the n-1th sampling point and the first reference point is obtained and whether to retain the n-1th sampling point and the n-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered reference mechanical characteristic curve;

[0175] Correspondingly, C(q) represents the value of the qth sampling point of the filtered real-time characteristic curve, and R(q) represents the value of the qth sampling point of the filtered reference characteristic curve.

[0176] Optionally, when determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value, the filtering unit 401 is specifically configured to: determine whether the absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the i+fth sampling point and the i+f-1th sampling point;

[0177] When determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value, the filtering unit 401 is specifically used to: determine whether the second absolute value corresponding to the j+sth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the j+sth sampling point and the j+s-1th sampling point.

[0178] Optionally, the filtering unit 401 is further used for:

[0179] If the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is no, then after updating the value of f to f+1, return to execute the operation of obtaining the first absolute value of the difference between the i+fth sampling point and the first reference point in the real-time mechanical characteristic curve;

[0180] If the result of determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value is no, then after updating the value of s to s+1, the operation of obtaining the absolute value of the difference between the j+sth sampling point in the reference characteristic curve and the second reference point as the second absolute value is returned.

[0181] According to this embodiment, when obtaining the Pearson correlation coefficient, the sampling points in the filtered fact characteristic curve and the filtered reference characteristic curve are used. This can minimize the data to be processed while obtaining accurate fault diagnosis results, thereby determining whether the switch cabinet has a fault as soon as possible.

[0182] The present invention also provides a device for switch cabinet fault diagnosis, wherein the switch equipment includes a plurality of monitored components, and the device includes at least one memory and at least one processor. The memory is used to store instructions. The processor is used to execute the switch cabinet fault diagnosis method described in any of the above embodiments according to the instructions stored in the memory.

[0183] An embodiment of the present invention further provides a readable storage medium in which machine-readable instructions are stored, and when the machine-readable instructions are executed by a machine, the machine executes the switch cabinet fault diagnosis method described in any of the above embodiments.

[0184] The readable medium stores machine-readable instructions, which, when executed by the processor, cause the processor to execute any of the aforementioned methods. Specifically, a system or device equipped with a readable storage medium may be provided, on which a software program code implementing the functions of any of the above-mentioned embodiments is stored, and a computer or processor of the system or device reads and executes the machine-readable instructions stored in the readable storage medium.

[0185] In this case, the program code itself read from the machine-readable medium can realize the function of any one of the above-mentioned embodiments, and thus the machine-readable code and the machine-readable storage medium storing the machine-readable code constitute a part of the present invention.

[0186] Examples of readable storage media include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer or a cloud via a communication network.

[0187] Those skilled in the art should understand that the various embodiments disclosed above can be modified and altered in various ways without departing from the essence of the invention. Therefore, the protection scope of the present invention should be defined by the appended claims.

[0188] It should be noted that not all steps and units in the above-mentioned processes and system structure diagrams are necessary, and some steps or units can be ignored according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The device structure described in the above-mentioned embodiments can be a physical structure or a logical structure, that is, some units may be implemented by the same physical entity, or some units may be implemented by multiple physical entities, or some components in multiple independent devices may be implemented together.

[0189] In the above embodiments, the hardware unit can be realized by mechanical means or electrical means. For example, a hardware unit or a processor can include permanent dedicated circuits or logic (such as special processors, FPGA or ASIC) to complete the corresponding operation. The hardware unit or the processor can also include programmable logic or circuits (such as general-purpose processors or other programmable processors), which can be temporarily set by software to complete the corresponding operation. Concrete implementation (mechanical means or dedicated permanent circuits or temporarily set circuits) can be determined based on cost and time considerations.

[0190] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for diagnosing faults in a switch cabinet, comprising obtaining a real-time characteristic curve of a monitored component in the switch cabinet, wherein the real-time characteristic curve has m sampling points, and the monitored component corresponds to a reference characteristic curve, wherein the reference characteristic curve is obtained when the monitored component is in a normal working state, and the reference characteristic curve has n sampling points, wherein: The method further comprises: Acquire a first expected value of the real-time characteristic curve, wherein the reference characteristic curve corresponds to a second expected value; determining a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value; Determining whether the switch cabinet fails according to the Pearson correlation coefficient, and obtaining a first expected value of the real-time characteristic curve includes: The first expected value E(C) of the real-time characteristic curve is obtained according to the following formula: Wherein C(i) represents the value of the i-th sampling point of the real-time characteristic curve; The second expected value E(R) corresponding to the reference characteristic curve is obtained by the following formula: Wherein R(j) represents the value of the j-th sampling point of the reference characteristic curve; Determining a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value includes: The Pearson correlation coefficient p between the real-time characteristic curve and the reference characteristic curve is determined according to the following formula: Wherein, M is the smaller of the number of sampling points of the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the real-time characteristic curve, and R(q) represents the value of the qth sampling point of the reference characteristic curve; Determining whether the switch cabinet fails according to the Pearson correlation coefficient includes: If the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet has a fault; Before determining whether the switch cabinet fails according to the Pearson correlation coefficient, the method further includes: The Pearson correlation coefficient p is corrected according to the following formula: If m>n, p×n / m is taken as the corrected p; If n>m, p×m / n is taken as the corrected p.

2. The method according to claim 1, characterized in that Before determining the Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve, the method further comprises: The real-time characteristic curve is filtered according to the following operations: The 1st sampling point and the mth sampling point of the real-time characteristic curve are retained; the 1st sampling point of the real-time characteristic curve is used as the initial first reference point; the value of f is assigned to 1; the absolute value of the difference between the i+fth sampling point and the first reference point in the real-time characteristic curve is obtained as the first absolute value, wherein the i-th sampling point represents the first reference point and the value of f is 1; according to the first absolute value, it is determined whether to retain the i+fth sampling point and the i+f-1th sampling point; if the determination result is yes, the i+fth sampling point is used as the updated first reference point, and the operation of assigning the value of f to 1 is returned to execute, until the absolute value of the difference between the m-1th sampling point and the first reference point is obtained as the first absolute value and according to the first absolute value, it is determined whether to retain the m-1th sampling point and the m-2th sampling point; the curve formed by all the retained sampling points is used as the filtered real-time characteristic curve; The reference characteristic curve is filtered according to the following operations: The first sampling point and the nth sampling point of the reference characteristic curve are retained; the first sampling point of the reference characteristic curve is used as the initial second reference point; the value of s is assigned to 1; the absolute value of the difference between the j+sth sampling point and the second reference point in the reference characteristic curve is obtained as the second absolute value, wherein the jth sampling point represents the second reference point; whether to retain the j+sth sampling point and the j+s-1th sampling point is determined according to the second absolute value; if the determination result is yes, the j+sth sampling point is used as the updated second reference point, and the operation of assigning the value of s to 1 is returned to execute, until the first absolute value of the difference between the n-1th sampling point and the first reference point is obtained and whether to retain the n-1th sampling point and the n-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered reference mechanical characteristic curve; Correspondingly, C(q) represents the value of the qth sampling point of the real-time characteristic curve after filtering, and R(q) represents the value of the qth sampling point of the reference characteristic curve after filtering.

3. The method according to claim 2, characterized in that Determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value specifically includes: Determine whether the absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the i+fth sampling point and the i+f-1th sampling point; Determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value includes: It is determined whether the second absolute value corresponding to the j+sth sampling point is greater than or equal to a filtering threshold; if the determination result is yes, the j+sth sampling point and the j+s-1th sampling point are retained.

4. The method according to claim 2, characterized in that: Also includes: If the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is no, then after updating the value of f to f+1, returning to execute the operation of obtaining the first absolute value of the difference between the i+fth sampling point in the real-time characteristic curve and the first reference point; If the result of determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value is no, then after updating the value of s to s+1, the operation of obtaining the absolute value of the difference between the j+sth sampling point in the reference characteristic curve and the second reference point as the second absolute value is returned.

5. A switch cabinet fault diagnosis device, the device comprising: A first acquisition unit, used to acquire a real-time characteristic curve of a monitored component in the switch cabinet, the real-time characteristic curve having m sampling points, the monitored component corresponding to a reference characteristic curve, the reference characteristic curve being acquired when the monitored component is in a normal working state, the reference characteristic curve having n sampling points; It is characterized by further comprising: A second acquisition unit, used for acquiring a first expected value of the real-time characteristic curve, wherein the reference characteristic curve corresponds to a second expected value; a first determining unit, configured to determine a Pearson correlation coefficient between the real-time characteristic curve and the reference characteristic curve based on the first expected value and the second expected value; a second determining unit, configured to determine whether the switch cabinet fails according to the Pearson correlation coefficient; and the second obtaining unit is specifically configured to: The first expected value E(C) of the real-time characteristic curve is obtained according to the following formula: Wherein C(i) represents the value of the i-th sampling point of the real-time characteristic curve; The second expected value E(R) corresponding to the reference characteristic curve is obtained by the following formula: Wherein R(j) represents the value of the j-th sampling point of the reference characteristic curve; the first determining unit is specifically used for: The Pearson correlation coefficient p between the real-time characteristic curve and the reference characteristic curve is determined according to the following formula: Wherein, M is the smaller of the number of sampling points of the real-time characteristic curve and the number of sampling points in the reference characteristic curve, C(q) represents the value of the qth sampling point of the real-time characteristic curve, and R(q) represents the value of the qth sampling point of the reference characteristic curve; The second determining unit is specifically configured to: If the Pearson correlation coefficient is less than or equal to a preset threshold, it is determined that the switch cabinet has a fault; the device also includes a correction unit, which is used to: The Pearson correlation coefficient p is corrected according to the following formula: If m>n, p×n / m is taken as the corrected p; If n>m, p×m / n is taken as the corrected p.

6. The device according to claim 5, characterized in that Also included is a filter unit, the filter unit is used for: The real-time characteristic curve is filtered according to the following operations: The 1st sampling point and the mth sampling point of the real-time characteristic curve are retained; the 1st sampling point of the real-time characteristic curve is used as the initial first reference point; the value of f is assigned to 1; the absolute value of the difference between the i+fth sampling point and the first reference point in the real-time characteristic curve is obtained as the first absolute value, wherein the i-th sampling point represents the first reference point and the value of f is 1; according to the first absolute value, it is determined whether to retain the i+fth sampling point and the i+f-1th sampling point; if the determination result is yes, the i+fth sampling point is used as the updated first reference point, and the operation of assigning the value of f to 1 is returned to execute, until the absolute value of the difference between the m-1th sampling point and the first reference point is obtained as the first absolute value and according to the first absolute value, it is determined whether to retain the m-1th sampling point and the m-2th sampling point; the curve formed by all the retained sampling points is used as the filtered real-time characteristic curve; The reference characteristic curve is filtered according to the following operations: The first sampling point and the nth sampling point of the reference characteristic curve are retained; the first sampling point of the reference characteristic curve is used as the initial second reference point; the value of s is assigned to 1; the absolute value of the difference between the j+sth sampling point and the second reference point in the reference characteristic curve is obtained as the second absolute value, wherein the jth sampling point represents the second reference point; whether to retain the j+sth sampling point and the j+s-1th sampling point is determined according to the second absolute value; if the determination result is yes, the j+sth sampling point is used as the updated second reference point, and the operation of assigning the value of s to 1 is returned to execute, until the first absolute value of the difference between the n-1th sampling point and the first reference point is obtained and whether to retain the n-1th sampling point and the n-2th sampling point is determined according to the first absolute value; the curve formed by all the retained sampling points is used as the filtered reference mechanical characteristic curve; Correspondingly, C(q) represents the value of the qth sampling point of the real-time characteristic curve after filtering, and R(q) represents the value of the qth sampling point of the reference characteristic curve after filtering.

7. The device according to claim 6, characterized in that The filtering unit, when determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value, is specifically used to: determine whether the absolute value corresponding to the i+fth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the i+fth sampling point and the i+f-1th sampling point; When determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value, the filtering unit is specifically configured to: determine whether the second absolute value corresponding to the j+sth sampling point is greater than or equal to a filtering threshold, and if the determination result is yes, retain the j+sth sampling point and the j+s-1th sampling point.

8. The device according to claim 6, characterized in that The filtering unit is also used for: If the result of determining whether to retain the i+fth sampling point and the i+f-1th sampling point according to the first absolute value is no, then after updating the value of f to f+1, returning to execute the operation of obtaining the first absolute value of the difference between the i+fth sampling point in the real-time characteristic curve and the first reference point; If the result of determining whether to retain the j+sth sampling point and the j+s-1th sampling point according to the second absolute value is no, then after updating the value of s to s+1, the operation of obtaining the absolute value of the difference between the j+sth sampling point in the reference characteristic curve and the second reference point as the second absolute value is returned.

9. A device for diagnosing faults in a switch cabinet, the switch cabinet comprising a plurality of monitored components, characterized in that: The device comprises: at least one memory for storing instructions; At least one processor, configured to execute the switch cabinet fault diagnosis method according to any one of claims 1 to 4 according to the instructions stored in the memory.

10. A readable storage medium, characterized in that: The readable storage medium stores machine-readable instructions. When the machine-readable instructions are executed by a machine, the machine executes the method for diagnosing a switch cabinet fault according to any one of claims 1 to 4.

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