Method and system for diagnosing partial discharge of switch cabinet

Abstract

The invention discloses a switch cabinet partial discharge diagnosis method and system, and the method comprises the steps: constructing a phase interval sequence and an amplitude interval sequence, constructing a two-dimensional array composed of a phase index and an amplitude index, setting the elements in the two-dimensional array as zero, and constructing a diagnosis model; traversing the matrix of the diagnosis model, summing the discharge times in the atlas data in each unit interval, and updating corresponding elements of the diagnosis model to obtain a given mapping diagnosis model; setting phase interval ranges, amplitude interval ranges and fault conditions corresponding to various faults of the switch cabinet, counting the total discharge times corresponding to the various faults according to a given mapping diagnosis model, and comparing according to the fault conditions to obtain corresponding fault types; calculating a corresponding fault probability according to the percentage of the total discharge frequency corresponding to each fault in the sum of the total discharge frequency of all faults; the partial discharge diagnosis efficiency and precision of the switch cabinet can be greatly improved.

Description

Technical Field

[0001] The present invention relates to a partial discharge diagnosis method and system, and particularly to a partial discharge diagnosis method and system for switchgear, belonging to the technical field of power equipment condition assessment. Background Art

[0002] As a key equipment in the power system, switchgear undertakes the core functions of power distribution and circuit protection. The internal insulating media (such as epoxy resin, silicone rubber, etc.) are affected by electrothermal stress, mechanical vibration and environmental humidity for a long time, and are prone to form partial discharge phenomena under the action of high-voltage electric fields. Although the instantaneous energy of partial discharge is only in the order of μJ, continuous discharge will trigger chain reactions such as carbonization of insulating materials and expansion of air gaps, ultimately leading to major accidents such as phase-to-phase short circuit or equipment explosion.

[0003] Traditional partial discharge detection methods mainly include electrical method, ultrasonic method and optical method, etc. Although these methods can detect partial discharge phenomena, they have significant limitations in diagnostic accuracy. For example, the electrical method is easily affected by external electromagnetic interference, resulting in inaccurate detection results; the ultrasonic method requires precise positioning of the discharge source, with complex operation and large positioning errors; although the optical method has high accuracy, the equipment cost is expensive and the operation environment requirements are strict. In addition, on-site detection usually relies on the experience and intuitive judgment of operators, making it difficult to ensure the consistency and accuracy of diagnostic results.

[0004] With the increasing complexity of the power system and the improvement of the reliability requirements for switchgear, there is an urgent need for a more accurate and intelligent partial discharge diagnosis method. In recent years, the development of computer technology and artificial intelligence technology has provided new ideas for partial discharge fault diagnosis. By extracting the characteristics and pattern recognition of partial discharge signals, higher-precision fault diagnosis and prediction can be achieved. However, the diagnostic efficiency of artificial intelligence technology is low, and the complexity and diversity of partial discharge signals make it a great challenge to construct an efficient diagnostic model. Summary of the Invention

[0005] Object of the Invention: The object of the present invention is to provide a partial discharge diagnosis method and system for switchgear that can improve the diagnostic accuracy of partial discharge in switchgear.

[0006] Technical Solution: A partial discharge diagnosis method for switchgear according to the present invention includes:

[0007] Construct a phase interval sequence and an amplitude interval sequence, and construct a two-dimensional array composed of a phase index and an amplitude index, set all elements in the two-dimensional array to zero, and construct a diagnostic model;

[0008] Traverse the matrix of the diagnostic model, sum the number of discharge times in the spectrum data within each unit interval, and update the corresponding elements of the diagnostic model to obtain a given mapping diagnostic model; the spectrum data is the partial discharge PRPD spectrum data or the partial discharge original waveform data of the switch cabinet.

[0009] Set the phase interval range, amplitude interval range, and fault conditions corresponding to various faults of the switch cabinet. According to the given mapping diagnostic model, count the total number of discharge times corresponding to various faults, and obtain the corresponding fault types by comparing the fault conditions; the various faults include metal protrusion faults, internal air gap faults, surface contamination discharge faults, floating metal body discharge faults, insulation aging delamination faults, and poor contact discharge faults.

[0010] Calculate the corresponding fault probability according to the percentage of the total number of discharge times corresponding to various faults in the total sum of the total number of discharge times of all occurring faults.

[0011] Furthermore, the phase interval sequence is represented by the following formula:

[0012]

[0013] where P is the phase interval sequence, p i is the i-th element corresponding to the phase interval sequence, i is the element serial number of the phase interval sequence, n p is the number of elements in the phase interval sequence, l p is the phase interval step size;

[0014] The amplitude interval sequence is represented by the following formula:

[0015]

[0016] where M is the amplitude interval sequence, m j is the j-th element corresponding to the amplitude interval sequence, j is the element serial number of the amplitude interval sequence, n m is the number of elements in the amplitude interval sequence, l m is the amplitude interval step size, m s is the lower limit of the amplitude interval sequence, m e is the upper limit of the amplitude interval sequence;

[0017] The diagnostic model is represented by the following formula:

[0018]

[0019] where D is a two-dimensional array, d i,j is the corresponding element in the two-dimensional array.

[0020] Further, when the atlas data is partial discharge PRPD atlas data, it is directly represented by a triple of phase, amplitude, and discharge times. When the atlas data is partial discharge original waveform data, the triple of phase, amplitude, and discharge time of the partial discharge original waveform data is converted into a triple of phase, amplitude, and discharge times with the discharge times equal to 1. The triple of phase, amplitude, and discharge times is expressed as:

[0021]

[0022] where T is a triple of actual values of phase, amplitude, and discharge times, X is a sequence of actual phase values, x k is the corresponding element, Y is a sequence of actual amplitude values, y k is the corresponding element, Z is a sequence of actual discharge times values, z k is the corresponding element, k is the element number, and n T is the sequence length.

[0023] Further, traverse the matrix of the diagnosis model, sum up the discharge times in the atlas data within each unit interval, and update the corresponding elements of the diagnosis model. Specifically:

[0024] Design a three-layer loop structure. First, traverse the phase sequence of the diagnosis model matrix, and extract the maximum phase threshold and the minimum phase threshold of the unit interval. The maximum phase threshold and the minimum phase threshold are expressed by the following formula:

[0025]

[0026] where MIN x is the minimum phase threshold, MAX x is the maximum phase threshold, n p is the number of intervals, and p i is the corresponding element;

[0027] Secondly, traverse the amplitude sequence of the diagnosis model matrix, and extract the maximum amplitude threshold and the minimum amplitude threshold of the unit interval. The maximum amplitude threshold and the minimum amplitude threshold are expressed by the following formula:

[0028]

[0029] where MIN y is the minimum amplitude threshold, and MAX y is the maximum amplitude threshold;

[0030] Finally, traverse the triple of actual values of phase, amplitude, and discharge times, screen the atlas data within the unit interval, sum up the discharge times within the unit interval, and update the corresponding elements of the diagnosis model;

[0031] The discrimination conditions for screening are expressed as:

[0032]

[0033] The corresponding elements of the updated diagnostic model are expressed as::

[0034] d i,j =(∑ z ) ij

[0035] where (∑ z ) ij is the sum of the number of discharges contained in all the spectrogram data within the corresponding interval.

[0036] Furthermore, for the phase interval range, amplitude interval range, and fault conditions corresponding to various faults set for the switchgear, according to the given mapping diagnostic model, the total number of discharges corresponding to various faults is counted, and the corresponding fault types are obtained by comparing the fault conditions, including:

[0037] Calculate the total number of discharges S required for comparing the fault conditions using the given mapping diagnostic model, which is expressed as:

[0038]

[0039] where S is the total number of discharges of the given mapping diagnostic model;

[0040] For the metal protrusion fault, the corresponding phase interval range is from 90° to 110°, and the corresponding amplitude interval range is from 0.7 times the interval length to 0.9 times the interval length. The screening data of the given mapping diagnostic model corresponding to the metal protrusion fault is expressed as:

[0041] D1 = [d i,j 90≤p i ≤110,0.7L≤m j ≤0.9L

[0042] where D1 is the screening data for the metal protrusion fault, p i is the i-th element of the phase interval sequence, m j is the j-th element of the amplitude interval sequence, and L is the amplitude interval length;

[0043] The comparison threshold for the metal protrusion fault is expressed as:

[0044] θ1 = max{0.05S, 0.1S1, 10max{D1}}

[0045] where θ1 is the comparison threshold for the metal protrusion fault, S1 is the sum of the screening data for the metal protrusion fault, and max{·} is the maximum operator;

[0046] If S1 > θ1, it is determined that a metal protrusion fault has occurred;

[0047] For the internal air gap fault, the corresponding phase interval range is from 150° to 180°, and the corresponding amplitude interval range is from 0.5 times the interval length to 0.7 times the interval length. The screening data of the given mapping diagnosis model corresponding to the internal air gap fault is expressed as:

[0048] D2 = [d i,j 150 ≤ p i ≤ 180, 0.5L ≤ m j ≤ 0.7L

[0049] where D2 is the screening data of the internal air gap fault;

[0050] The comparison threshold of the internal air gap fault is expressed as:

[0051] θ2 = max{0.04S, 20mean{D2}, 5var{D2}}

[0052] where θ2 is the comparison threshold of the internal air gap fault, mean{·} is the average operator, and var{·} is the variance operator;

[0053] If S2 > θ2, it is determined that an internal air gap fault has occurred; where S2 is the sum of the screening data of the internal air gap fault;

[0054] For the surface contamination discharge fault, the corresponding phase interval range is less than or equal to 30°, and the corresponding amplitude interval range is from 0.8 times the interval length to 1.0 times the interval length. The screening data of the given mapping diagnosis model corresponding to the surface contamination discharge fault is expressed as:

[0055] D3 = [d i,j 0 ≤ p i ≤ 30, 0.8L ≤ m j ≤ L

[0056] where D3 is the screening data of the surface contamination discharge fault;

[0057] The comparison threshold of the surface contamination discharge fault is expressed as:

[0058] θ3 = max{0.03S, 0.1S3, 10max{D3}}

[0059] where θ3 is the comparison threshold of the surface contamination discharge fault, and S3 is the sum of the screening data of the surface contamination discharge fault;

[0060] If S3 > θ3, it is determined that a surface contamination discharge fault has occurred;

[0061] The discharge fault of the suspended metal body has a corresponding phase interval range less than or equal to 360°, and a corresponding amplitude interval range less than or equal to 0.1 times the interval length. The screening data of the given mapping diagnosis model corresponding to the discharge fault of the suspended metal body is expressed as:

[0062] D4 = [d i,j 0 ≤ p i ≤ 360, 0 ≤ m j ≤ 0.1L

[0063] where D4 is the screening data of the discharge fault of the suspended metal body;

[0064] The comparison threshold of the discharge fault of the suspended metal body is expressed as:

[0065] θ4 = max{0.1S4, 200mean{D4}}

[0066] where θ4 is the comparison threshold of the discharge fault of the suspended metal body, and S4 is the sum of the screening data of the discharge fault of the suspended metal body;

[0067] If S4 > θ4, it is determined that a discharge fault of the suspended metal body has occurred;

[0068] For the insulation aging delamination fault, the corresponding phase interval range is 60° to 80°, and the corresponding amplitude interval range is 0.3 times the interval length to 0.5 times the interval length. The screening data of the given mapping diagnosis model corresponding to the insulation aging delamination fault is expressed as:

[0069] D5 = [d i,j 60 ≤ p i ≤ 80, 0.3L ≤ m j ≤ 0.5L

[0070] where D5 is the screening data of the insulation aging delamination fault;

[0071] The comparison threshold of the insulation aging delamination fault is expressed as:

[0072] θ5 = max{0.02S, 10mean{D5}}

[0073] where θ5 is the comparison threshold of the insulation aging delamination fault;

[0074] If S5 > θ5, it is determined that an insulation aging delamination fault has occurred; where S5 is the sum of the screening data of the insulation aging delamination fault;

[0075] For the poor contact discharge fault, the corresponding phase interval range is 120° to 140°, and the corresponding amplitude interval range is 0.6 times the interval length to 0.8 times the interval length. The screening data of the given mapping diagnosis model corresponding to the poor contact discharge fault is expressed as:

[0076] D6 = [d i,j 120 ≤ p i ≤ 140, 0.6L ≤ m j ≤ 0.8L

[0077] Among them, D6 is the screening data for poor contact discharge faults;

[0078] The comparison threshold for poor contact discharge faults is expressed as:

[0079] θ6 = max{0.03S, 2var{D6}}

[0080] Among them, θ6 is the comparison threshold for poor contact discharge faults;

[0081] If S6 > θ6, it can be determined that a poor contact discharge fault has occurred; among them, S6 is the sum of the screening data for poor contact discharge faults.

[0082] Furthermore, the sum of the total number of discharges for all faults that have occurred is expressed as:

[0083]

[0084] Among them, S ∑ is the sum of the number of discharge times for all faults that have occurred, and x is the corresponding fault number;

[0085] If S ∑ = 0, the diagnosis result is normal and there is no fault.

[0086] Furthermore, the corresponding fault probability is calculated based on the percentage of the total number of discharges corresponding to each type of fault in the sum of the total number of discharges for all faults that have occurred, and is expressed as:

[0087]

[0088] Among them, η x is the probability of the corresponding fault occurring.

[0089] Based on the same inventive concept, the present invention also provides a partial discharge diagnosis system for a switchgear, including:

[0090] A diagnostic model construction module for constructing a phase interval sequence and an amplitude interval sequence, constructing a two-dimensional array composed of a phase index and an amplitude index, setting all elements in the two-dimensional array to zero, and constructing a diagnostic model;

[0091] A data mapping module, configured to traverse the matrix of the diagnostic model, sum up the number of discharges in the atlas data within each unit interval, and update the corresponding elements of the diagnostic model to obtain a given mapped diagnostic model; the atlas data is the partial discharge PRPD atlas data or the partial discharge original waveform data of the switch cabinet.

[0092] A data statistics and data comparison module, configured to set the phase interval range, amplitude interval range, and fault conditions corresponding to various faults of the switch cabinet, count the total number of discharges corresponding to various faults according to the given mapped diagnostic model, and obtain the corresponding fault type by comparing according to the fault conditions; the various faults include metal protrusion faults, internal air gap faults, surface contamination discharge faults, suspended metal body discharge faults, insulation aging and delamination faults, and poor contact discharge faults.

[0093] A fault probability calculation module, configured to calculate the corresponding fault probability according to the percentage of the total number of discharges corresponding to various faults in the total sum of the total number of discharges of all occurring faults.

[0094] Based on the same inventive concept, the present invention also provides a computing device, including: one or more processors, one or more memories, and one or more programs, the programs are stored in the memory and configured to be executed by the processor, and when the programs are loaded into the processor, the steps of the switch cabinet partial discharge diagnosis method according to any one of the above are implemented.

[0095] Based on the same inventive concept, the present invention also provides a storage medium, the storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by the processor, the processor is caused to execute the steps of the switch cabinet partial discharge diagnosis method according to any one of the above.

[0096] Advantageous effects: Compared with the prior art, the present invention constructs a phase interval sequence and an amplitude interval sequence, initializes the diagnostic model, and traverses and updates the diagnostic model according to the partial discharge PRPD atlas data or the partial discharge original waveform data. By setting the phase, amplitude interval range, and fault conditions corresponding to various faults, the total number of discharges corresponding to various faults is counted, and the corresponding fault type is obtained by comparing according to the fault conditions, so as to realize the diagnosis of six types of faults including metal protrusion faults, internal air gap faults, surface contamination discharge faults, suspended metal body discharge faults, insulation aging and delamination faults, and poor contact discharge faults. Finally, according to the statistical values of the total number of discharges corresponding to various faults, the corresponding fault occurrence probability is calculated. It can not only greatly improve the efficiency and accuracy of switch cabinet partial discharge diagnosis, but also has important practical value and broad application prospects for promoting the development of power system monitoring technology and improving the safety and reliability of power grid operation. Description of the Drawings

[0097] Figure 1 It is the flowchart of the method of the embodiment of the present invention;

[0098] Figure 2 It is the data mapping flowchart of the embodiment of the present invention. Specific embodiments

[0099] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application.

[0100] As shown in the Figure 1 accompanying drawings, the partial discharge diagnosis method of the switchgear cabinet in this embodiment includes:

[0101] Step 1, construct a phase interval sequence and an amplitude interval sequence, and construct a two-dimensional array composed of a phase index and an amplitude index, set all elements in the two-dimensional array to zero, and construct a diagnosis model;

[0102] Step 2, traverse the matrix of the diagnosis model, sum the number of discharges in the pattern data within each unit interval, and update the corresponding elements of the diagnosis model to obtain a given mapping diagnosis model; the pattern data is the partial discharge PRPD pattern data or the partial discharge original waveform data of the switchgear cabinet;

[0103] Step 3, set the phase interval range, amplitude interval range and fault conditions corresponding to various faults of the switchgear cabinet, count the total number of discharges corresponding to various faults according to the given mapping diagnosis model, and obtain the corresponding fault types by comparing according to the fault conditions; the various faults include metal protrusion faults, internal air gap faults, surface contamination discharge faults, suspended metal body discharge faults, insulation aging and delamination faults, and poor contact discharge faults;

[0104] Step 4, calculate the corresponding fault probability according to the percentage of the total number of discharges corresponding to various faults in the total sum of the total number of discharges of all occurring faults.

[0105] Specifically, in Step 1, construct a phase interval sequence and an amplitude interval sequence according to the design requirements, and construct a two-dimensional array composed of two indexes of phase and amplitude, and set all elements therein to zero to construct a diagnosis model.

[0106] The phase interval is generally from 0° to 360°, and the step size is freely selected according to the design requirements, then the phase interval sequence can be expressed as:

[0107]

[0108] where P is the phase interval sequence, p i is the i-th element corresponding to the phase interval sequence, i is the element serial number of the phase interval sequence, n pis the number of elements in the phase interval sequence, l p is the phase interval step size;

[0109] The upper limit, lower limit, and step size of the amplitude interval sequence are all selected according to the design requirements. Then, the amplitude interval sequence can be expressed as:

[0110]

[0111] where M is the amplitude interval sequence, m j is the j-th element corresponding to the amplitude interval sequence, j is the element serial number of the amplitude interval sequence, n m is the number of elements in the amplitude interval sequence, l m is the amplitude interval step size, m s is the lower limit of the amplitude interval sequence, m e is the upper limit of the amplitude interval sequence;

[0112] The diagnostic model can be expressed as:

[0113]

[0114] where D is a two-dimensional array, d i,j is the corresponding element in the two-dimensional array.

[0115] In step 2, according to the partial discharge PRPD pattern data or the partial discharge original waveform data, traverse the diagnostic model matrix, sum the number of discharges in the pattern data within each unit interval, and update the corresponding elements of the diagnostic model.

[0116] The partial discharge PRPD pattern data is a triple of phase, amplitude, and number of discharges. The partial discharge original waveform data is a triple of phase, amplitude, and discharge time, which can be converted into a triple of phase, amplitude, and number of discharges equal to 1. The triple of phase, amplitude, and number of discharges can be expressed as:

[0117]

[0118] where T is a triple of actual values of phase, amplitude, and number of discharges, X is the actual value sequence of phase, x k is the corresponding element, Y is the actual value sequence of amplitude, y k is the corresponding element, Z is the actual value sequence of number of discharges, z k is the corresponding element, k is the element serial number, n T is the sequence length.

[0119] As Figure 2 shown, the data mapping is a three-layer loop structure. First, traverse the phase sequence of the diagnostic model matrix, and extract the maximum phase threshold and the minimum phase threshold of the unit interval. The maximum and minimum phase thresholds can be expressed as:

[0120]

[0121] Among them, MIN x is the minimum phase threshold, MAX x is the maximum phase threshold, n p is the number of intervals, p i is the corresponding element;

[0122] Secondly, traverse the amplitude sequence of the diagnostic model matrix, and also extract the maximum amplitude threshold and minimum amplitude threshold of the unit interval. The maximum and minimum amplitude thresholds can be expressed as:

[0123]

[0124] Among them, MIN y is the minimum amplitude threshold, MAX y is the maximum amplitude threshold.

[0125] Finally, traverse the triple of the actual values of phase, amplitude, and number of discharges, filter the atlas data within the unit interval, sum the number of discharges within the unit interval, and update the corresponding element of the diagnostic model. The discrimination condition of the unit interval can be expressed as:

[0126]

[0127] The update of the corresponding element of the diagnostic model is expressed as::

[0128] d i,j =(∑ z ) i,j

[0129] Among them, (∑ z ) i,j is the sum of the number of discharges included in all atlas data within the corresponding interval.

[0130] In step 3, set the phase, amplitude interval range and fault conditions corresponding to various faults of the switchgear, including six types of faults: metal protrusion fault, internal air gap fault, surface contamination discharge fault, suspended metal body discharge fault, insulation aging delamination fault, and poor contact discharge fault. According to the given mapping diagnostic model, count the total number of discharges corresponding to various faults, and obtain the corresponding fault type by comparing with the fault conditions.

[0131] The comparison of the fault conditions needs to use the total number of discharges of the given mapping diagnostic model, which can be expressed as:

[0132]

[0133] Among them, S is the total number of discharges of the given mapping diagnostic model.

[0134] For the metal protrusion fault, the corresponding phase interval ranges from 90° to 110°, and the corresponding amplitude interval ranges from 0.7 times the interval length to 0.9 times the interval length. Then the screening data of the given mapping diagnosis model can be expressed as:

[0135] D1 = [d i,j 90 ≤ p i ≤ 110, 0.7L ≤ m j ≤ 0.9L

[0136] where D1 is the screening data for metal protrusion faults, and L is the amplitude interval length.

[0137] The comparison threshold for the metal protrusion fault can be expressed as:

[0138] θ1 = max{0.05S, 0.1S1, 10max{D1}}

[0139] where θ1 is the comparison threshold for metal protrusion faults, S1 is the sum of the screening data for metal protrusion faults, and max{·} is the maximum operator;

[0140] If S1 > θ1, it can be determined that a metal protrusion fault has occurred.

[0141] For the internal air gap fault, the corresponding phase interval ranges from 150° to 180°, and the corresponding amplitude interval ranges from 0.5 times the interval length to 0.7 times the interval length. Then the screening data of the given mapping diagnosis model can be expressed as:

[0142] D2 = [d i,j 150 ≤ p i ≤ 180, 0.5L ≤ m j ≤ 0.7L

[0143] where D2 is the screening data for internal air gap faults;

[0144] The comparison threshold for the internal air gap fault is expressed as:

[0145] θ2 = max{0.04S, 20mean{D2}, 5var{D2}}

[0146] where θ2 is the comparison threshold for internal air gap faults, mean{·} is the average operator, and var{·} is the variance operator;

[0147] If S2 > θ2, it can be determined that an internal air gap fault has occurred.

[0148] where S2 is the sum of the screening data for internal air gap faults.

[0149] For the surface pollution discharge fault, the corresponding phase interval range is less than or equal to 30°, and the corresponding amplitude interval range is from 0.8 times the interval length to 1.0 times the interval length. Then the screening data of the given mapping diagnosis model can be expressed as:

[0150] D3 = [d i,j 0 ≤ p i ≤ 30, 0.8L ≤ m j ≤ L

[0151] where D3 is the screening data of the surface pollution discharge fault.

[0152] The comparison threshold of the surface pollution discharge fault is expressed as:

[0153] θ3 = max{0.03S, 0.1S3, 10max{D3}}

[0154] where θ3 is the comparison threshold of the surface pollution discharge fault, and S3 is the sum of the screening data of the surface pollution discharge fault;

[0155] If S3 > θ3, it can be determined that a surface pollution discharge fault has occurred.

[0156] For the suspended metal body discharge fault, the corresponding phase interval range is less than or equal to 360°, and the corresponding amplitude interval range is less than or equal to 0.1 times the interval length. Then the screening data of the given mapping diagnosis model can be expressed as:

[0157] D4 = [d i,j 0 ≤ p i ≤ 360, 0 ≤ m j ≤ 0.1L

[0158] where D4 is the screening data of the suspended metal body discharge fault;

[0159] The comparison threshold of the suspended metal body discharge fault is expressed as:

[0160] θ4 = max{0.1S4, 200mean{D4}}

[0161] where θ4 is the comparison threshold of the suspended metal body discharge fault, and S4 is the sum of the screening data of the suspended metal body discharge fault;

[0162] If S4 > θ4, it can be determined that a suspended metal body discharge fault has occurred.

[0163] For the insulation aging delamination fault, the corresponding phase interval range is from 60° to 80°, and the corresponding amplitude interval range is from 0.3 times the interval length to 0.5 times the interval length. Then the screening data of the given mapping diagnosis model can be expressed as:

[0164] D5 = [di,j 60 ≤ p i ≤ 80, 0.3L ≤ m j ≤ 0.5L

[0165] Among them, D5 is the screening data for insulation aging delamination faults;

[0166] The comparison threshold for insulation aging delamination faults is expressed as:

[0167] θ5 = max{0.02S, 10mean{D5}}

[0168] Among them, θ5 is the comparison threshold for insulation aging delamination faults;

[0169] If S5 > θ5, it can be determined that an insulation aging delamination fault has occurred.

[0170] Among them, S5 is the sum of the screening data for insulation aging delamination faults.

[0171] For the poor contact discharge fault, the corresponding phase interval range is from 120° to 140°, and the corresponding amplitude interval range is from 0.6 times the interval length to 0.8 times the interval length. Then the screening data of the given mapping diagnosis model can be expressed as:

[0172] D6 = [d i,j 120 ≤ p i ≤ 140, 0.6L ≤ m j ≤ 0.8L

[0173] Among them, D6 is the screening data for poor contact discharge faults;

[0174] The comparison threshold for poor contact discharge faults is expressed as:

[0175] θ6 = max{0.03S, 2var{D6}}

[0176] Among them, θ6 is the comparison threshold for poor contact discharge faults;

[0177] If S6 > θ6, it can be determined that a poor contact discharge fault has occurred.

[0178] Among them, S6 is the sum of the screening data for poor contact discharge faults.

[0179] In step 4, according to the statistical values of the total discharge times corresponding to various faults, the corresponding fault probability is the percentage of the total discharge times corresponding to it in the total sum of the total discharge times of various occurring faults.

[0180] For the calculation of the fault probability, first, according to the fault types obtained by comparing the above fault conditions, calculate the total sum of the discharge times of all occurring faults, which can be expressed as:

[0181]

[0182] Among them, S Σ is the total number of breakdown discharges that have occurred, and x is the corresponding breakdown number.

[0183] If S Σ = 0, then the diagnosis result is normal and there is no fault.

[0184] According to the fault type obtained by comparing with the above fault conditions, the corresponding fault occurrence probability is the percentage of the sum of the fault screening data of the fault divided by the total number of breakdown discharges that have occurred, which can be expressed as:

[0185]

[0186] Among them, η x is the corresponding fault occurrence probability.

[0187] Based on the same inventive concept, this embodiment also provides a partial discharge diagnosis system for a switchgear, including:

[0188] A diagnostic model construction module, configured to construct a phase interval sequence and an amplitude interval sequence, and construct a two-dimensional array composed of a phase index and an amplitude index, set all elements in the two-dimensional array to zero, and construct a diagnostic model;

[0189] A data mapping module, configured to traverse the matrix of the diagnostic model, sum the number of discharges in the pattern data within each unit interval, and update the corresponding elements of the diagnostic model to obtain a given mapped diagnostic model; the pattern data is the partial discharge PRPD pattern data or the partial discharge original waveform data of the switchgear;

[0190] A data statistics and data comparison module, configured to set the phase interval range, amplitude interval range, and fault conditions corresponding to various faults of the switchgear, count the total number of discharges corresponding to various faults according to the given mapped diagnostic model, and obtain the corresponding fault type according to the fault condition comparison; the various faults include metal protrusion faults, internal air gap faults, surface contamination discharge faults, suspended metal body discharge faults, insulation aging and delamination faults, and poor contact discharge faults;

[0191] A fault probability calculation module, configured to calculate the corresponding fault probability according to the percentage of the total number of discharges corresponding to various faults in the total number of breakdown discharges that have occurred.

[0192] Based on the same inventive concept, this embodiment also provides a computing device, including: one or more processors, one or more memories, and one or more programs, the programs are stored in the memory and are configured to be executed by the processor, and when the programs are loaded into the processor, the steps of the partial discharge diagnosis method for the switchgear according to any one of the above are implemented.

[0193] Based on the same inventive concept, this embodiment also provides a storage medium storing a computer program, the computer program including program instructions, and the program instructions, when executed by a processor, cause the processor to execute the steps of the switchgear partial discharge diagnosis method according to any one of the above.

[0194] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0195] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0196] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the specified functions in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0197] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0198] The above are only embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for diagnosing partial discharge in a switchgear cabinet, characterized in that, Including: Construct a phase interval sequence and an amplitude interval sequence, construct a two-dimensional array composed of a phase index and an amplitude index, set all elements in the two-dimensional array to zero, and construct a diagnostic model; Traverse the matrix of the diagnostic model, sum the number of discharges in the pattern data within each unit interval, and update the corresponding elements of the diagnostic model to obtain a given mapping diagnostic model; the pattern data is the partial discharge PRPD pattern data or the partial discharge original waveform data of the switch cabinet; Set the phase interval range, amplitude interval range, and fault conditions corresponding to various faults of the switch cabinet, count the total number of discharges corresponding to various faults according to the given mapping diagnostic model, and obtain the corresponding fault types by comparing the fault conditions; the various faults include metal protrusion faults, internal air gap faults, surface contamination discharge faults, suspended metal body discharge faults, insulation aging delamination faults, and poor contact discharge faults; Calculate the corresponding fault probability according to the percentage of the total number of discharges corresponding to various faults in the total sum of the total number of discharges of all occurring faults.

2. The partial discharge diagnosis method for switchgear according to claim 1, wherein The phase interval sequence is represented by the following formula: Among them, P is the phase interval sequence, and p i is the i-th element corresponding to the phase interval sequence, i is the serial number of the phase interval sequence element, and n p is the number of elements in the phase interval sequence, and l p is the phase interval step size; The amplitude interval sequence is represented by the following formula: where M is the amplitude interval sequence, m j is the j-th element corresponding to the amplitude interval sequence, j is the element sequence number of the amplitude interval sequence, n m is the number of elements of the amplitude interval sequence, l m is the amplitude interval step, m s is the lower limit of the amplitude interval sequence, m e is the upper limit of the amplitude interval sequence; The diagnostic model is represented by the following formula: where D is a two-dimensional array, and d i,j is the corresponding element in the two-dimensional array.

3. The partial discharge diagnosis method for switchgear according to claim 1, characterized in that When the pattern data is the partial discharge PRPD pattern data, it is directly represented by a triple of phase, amplitude, and number of discharges. When the pattern data is the partial discharge original waveform data, the triple of phase, amplitude, and discharge time of the partial discharge original waveform data is converted into a triple of phase, amplitude, and number of discharges with the number of discharges equal to 1; the triple of phase, amplitude, and number of discharges is represented as: Among them, T is a triple of actual values of phase, amplitude, and number of discharges, X is a sequence of actual phase values, and x k is the corresponding element, Y is a sequence of actual amplitude values, and y k is the corresponding element, Z is a sequence of actual number of discharge values, and z k is the corresponding element, k is the element number, and n T is the sequence length.

4. The partial discharge diagnosis method for switchgear according to claim 3, wherein, The process of traversing the matrix of the diagnostic model, summing the number of discharges in the pattern data within each unit interval, and updating the corresponding elements of the diagnostic model to obtain a given mapping diagnostic model is specifically as follows: Design a three-layer loop structure. First, traverse the phase sequence of the diagnostic model matrix, and extract the maximum phase threshold and the minimum phase threshold of the unit interval. The maximum phase threshold and the minimum phase threshold are represented by the following formula: Among them, MIN x is the minimum phase threshold, MAX x is the maximum phase threshold, n p is the number of intervals, p i is the corresponding element; Secondly, traverse the amplitude sequence of the diagnostic model matrix, and extract the maximum amplitude threshold and the minimum amplitude threshold of the unit interval. The maximum amplitude threshold and the minimum amplitude threshold are represented by the following formula: wherein, MIN y is the minimum amplitude threshold, and MAX y is the maximum amplitude threshold; Finally, traverse the triple of actual values of phase, amplitude, and number of discharges, screen the pattern data within the unit interval, sum the number of discharges within the unit interval, and update the corresponding elements of the diagnostic model; The discrimination condition for the screening is represented as: The update of the corresponding elements of the diagnostic model is represented as:: d i,j ＝(∑ z ) i,j Among them, (∑ z ) i,j is the sum of the number of discharges included in all the spectrogram data within the corresponding interval.

5. The partial discharge diagnosis method for switchgear according to claim 1, wherein The process of setting the phase interval range, amplitude interval range, and fault conditions corresponding to various faults of the switch cabinet, counting the total number of discharges corresponding to various faults according to the given mapping diagnostic model, and obtaining the corresponding fault types by comparing the fault conditions includes: Calculate the total number of discharges S of the given mapping diagnostic model required for comparing the fault conditions, which is represented as: where S is the total number of discharges of the given mapping diagnostic model; The metal protrusion fault has a corresponding phase interval range of 90° to 110° and a corresponding amplitude interval range of 0.7 times the interval length to 0.9 times the interval length. The screening data of the given mapping diagnosis model corresponding to the metal protrusion fault is expressed as: D1 = [d i,j 90 ≤ p i ≤ 110, 0.7L ≤ m j ≤ 0.9L Among them, D1 is the metal protrusion fault screening data, p i is the i-th element of the phase interval sequence, m j is the j-th element of the amplitude interval sequence, and L is the amplitude interval length; The comparison threshold of the metal protrusion fault is expressed as: θ1 = max{0.05S, 0.1S1, 10max{D1}} Where θ1 is the comparison threshold of the metal protrusion fault, S1 is the sum of the screening data of the metal protrusion fault, and max{·} is the maximum value operator; If S1 > θ1, it is determined that a metal protrusion fault has occurred; The internal air gap fault has a corresponding phase interval range of 150° to 180° and a corresponding amplitude interval range of 0.5 times the interval length to 0.7 times the interval length. The screening data of the given mapping diagnosis model corresponding to the internal air gap fault is expressed as: D2 = [d i,j 150 ≤ p i ≤ 180, 0.5L ≤ m j ≤ 0.7L Where D2 is the screening data of the internal air gap fault; The comparison threshold of the internal air gap fault is expressed as: θ2 = max{0.04S, 20mean{D2}, 5var{D2}} Where θ2 is the comparison threshold of the internal air gap fault, mean{·} is the average value operator, and var{·} is the variance operator; If S2 > θ2, it is determined that an internal air gap fault has occurred; where S2 is the sum of the screening data of the internal air gap fault; The surface contamination discharge fault has a corresponding phase interval range of less than or equal to 30° and a corresponding amplitude interval range of 0.8 times the interval length to 1.0 times the interval length. The screening data of the given mapping diagnosis model corresponding to the surface contamination discharge fault is expressed as: D3 = [d i,j 0 ≤ p i ≤ 30, 0.8L ≤ m j ≤ L Where D3 is the screening data of the surface contamination discharge fault; The comparison threshold of the surface contamination discharge fault is expressed as: θ3 = max{0.03S, 0.1S3, 10max{D3}} Where θ3 is the comparison threshold of the surface contamination discharge fault, and S3 is the sum of the screening data of the surface contamination discharge fault; If S3 > θ3, it is determined that a surface contamination discharge fault has occurred; The floating metal body discharge fault has a corresponding phase interval range of less than or equal to 360° and a corresponding amplitude interval range of less than or equal to 0.1 times the interval length. The screening data of the given mapping diagnosis model corresponding to the floating metal body discharge fault is expressed as: D4 = [d i,j 0 ≤ p i ≤ 360, 0 ≤ m j ≤ 0.1L Where D4 is the screening data of the floating metal body discharge fault; The comparison threshold of the floating metal body discharge fault is expressed as: θ4 = max{0.1S4, 200mean{D4}} Where θ4 is the comparison threshold of the floating metal body discharge fault, and S4 is the sum of the screening data of the floating metal body discharge fault; If S4 > θ4, it is determined that a floating metal body discharge fault has occurred; The insulation aging delamination fault has a corresponding phase interval range of 60° to 80° and a corresponding amplitude interval range of 0.3 times the interval length to 0.5 times the interval length. The screening data of the given mapping diagnosis model corresponding to the insulation aging delamination fault is expressed as: D5 = [d i,j where 60 ≤ p i ≤ 80, 0.3L ≤ m j ≤ 0.5L Where D5 is the screening data of the insulation aging delamination fault; The comparison threshold of the insulation aging delamination fault is expressed as: θ5 = max{0.02S, 10mean{D5}} Where, θ5 is the comparison threshold for insulation aging delamination faults; If S5 > θ5, it is determined that an insulation aging delamination fault has occurred; where, S5 is the total sum of insulation aging delamination fault screening data; For the poor contact discharge fault, the corresponding phase interval range is from 120° to 140°, and the corresponding amplitude interval range is from 0.6 times the interval length to 0.8 times the interval length. The screening data of the given mapping diagnosis model corresponding to the poor contact discharge fault is expressed as: D6 = [d i,j 120 ≤ p i ≤ 140, 0.6L ≤ m j ≤ 0.8L Where, D6 is the screening data of the poor contact discharge fault; The comparison threshold for the poor contact discharge fault is expressed as: θ6 = max{0.03S, 2var{D6}} Where, θ6 is the comparison threshold for the poor contact discharge fault; If S6 > θ6, it can be determined that a poor contact discharge fault has occurred; where, S6 is the total sum of poor contact discharge fault screening data.

6. The method for diagnosing partial discharge in a switchgear cabinet according to claim 1, wherein The total sum of the total discharge times of all faults that occurred is expressed as: Among them, S ∑ is the total number of all fault discharges, and x is the corresponding fault number; If S ∑ = 0, the diagnosis result is normal and there is no fault.

7. The partial discharge diagnosis method of the switchgear according to claim 6, characterized in that The corresponding fault probability is calculated according to the percentage of the total discharge times corresponding to each type of fault in the total sum of the total discharge times of all faults that occurred, and is expressed as: Among them, η x is the corresponding probability of fault occurrence.

8. A partial discharge diagnosis system for a switchgear, characterized in that, Including: A diagnosis model construction module, configured to construct a phase interval sequence and an amplitude interval sequence, and construct a two-dimensional array composed of a phase index and an amplitude index, set all elements in the two-dimensional array to zero, and construct a diagnosis model; A data mapping module, configured to traverse the matrix of the diagnosis model, sum the discharge times in the pattern data within each unit interval, and update the corresponding elements of the diagnosis model to obtain a given mapping diagnosis model; the pattern data is the partial discharge PRPD pattern data or the partial discharge original waveform data of the switch cabinet; A data statistics and data comparison module, configured to set the phase interval range, amplitude interval range and fault conditions corresponding to various faults of the switch cabinet, count the total discharge times corresponding to various faults according to the given mapping diagnosis model, and obtain the corresponding fault types by comparing according to the fault conditions; the various faults include metal protrusion faults, internal air gap faults, surface contamination discharge faults, suspended metal body discharge faults, insulation aging delamination faults and poor contact discharge faults; A fault probability calculation module, configured to calculate the corresponding fault probability according to the percentage of the total discharge times corresponding to each type of fault in the total sum of the total discharge times of all faults that occurred.

9. A computing device, characterized in that, Including: One or more processors, one or more memories, and one or more programs, the programs are stored in the memory and are configured to be executed by the processor, and when the programs are loaded into the processor, the steps of the switch cabinet partial discharge diagnosis method according to any one of claims 1 to 7 are implemented.

10. A storage medium, characterized in that, The storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by the processor, the processor is caused to execute the steps of the switch cabinet partial discharge diagnosis method according to any one of claims 1 to 7.

Images