A method and system for monitoring generator stator corona degradation based on partial discharge

Abstract

This application proposes a method and system for monitoring the corona degradation of a generator stator based on partial discharge. The method includes: acquiring a multi-fault superimposed global partial discharge pulse (PRPD) map of the generator stator at various times within a preset time period, and marking multiple corona discharge local spectrum regions in the multi-fault superimposed global PRPD map; acquiring the number of discharges at each pulse amplitude and pulse phase within positive partial discharge pulses and the number of discharges at each pulse amplitude and pulse phase within negative partial discharge pulses at various times within the preset time period; determining the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude within each corona discharge local spectrum region at various times within the preset time period; and determining whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude. The technical solution proposed in this application can accurately and effectively monitor the corona state of partial discharge in the original generator insulation.

Description

Technical Field

[0001] This application relates to the field of intelligent power plant generator insulation condition monitoring technology, and in particular to a generator stator corona degradation monitoring method and system based on partial discharge. Background Technology

[0002] Large generators are core components of power plants, and according to literature statistics, stator insulation faults account for over 40% of outages. To predict insulation status in advance and avoid unplanned outages, partial discharge monitoring systems are installed on the generator stator windings. These systems continuously monitor changes in partial discharge amplitude characteristics to determine the insulation status and conduct planned maintenance and repairs to restore insulation performance. However, in engineering applications, the stator insulation of large generators is a distributed system, with multiple types of faults of varying risks overlapping. For overall partial discharge detection of phase windings, the model diagram is a global model, and the discharge amplitude only represents the fault with the largest discharge volume. This could be due to external interference or metal tip discharge, not necessarily a high-risk fault in the insulation system. Higher-risk internal insulation discharges, corona discharges, and slot discharges often only appear locally in the model diagram due to propagation attenuation and have smaller amplitudes. Therefore, existing monitoring systems for partial discharge cannot effectively monitor the development of insulation degradation based on their comprehensive amplitude characteristics. In some cases, insulation faults can cause outages without any abnormal response from the monitoring system, resulting in online monitoring failures. The corona problem in the stator of large air-cooled generators and the deterioration of the anti-corona insulation performance are prominent stator insulation problems in large hydro generators in recent years. It is necessary to study the partial discharge characteristics of the corona problem and carry out targeted continuous monitoring. Summary of the Invention

[0003] This application provides a generator stator corona degradation monitoring method and system based on partial discharge, so as to at least solve the technical problem that the prior art cannot effectively monitor the development of insulation corona degradation.

[0004] The first aspect of this application proposes a method for monitoring stator corona degradation in a generator based on partial discharge, the method comprising:

[0005] Obtain the multi-fault superimposed global PRPD map of the generator stator at each moment within a preset time period, and mark multiple corona discharge local map regions in the multi-fault superimposed global PRPD map;

[0006] Based on the global PRPD map of multiple faults superimposed on the generator stator at each moment within a preset time period, the amplitude and discharge quantity of each pulse under each pulse phase in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse under each pulse phase in the negative polarity partial discharge pulse are obtained at each moment within the preset time period.

[0007] The discharge pulse duty cycle, discharge pulse number, and discharge pulse amplitude are determined based on the pulse amplitude and discharge quantity under each pulse phase of the positive polarity partial discharge pulse and the discharge quantity under each pulse phase of the negative polarity partial discharge pulse at each moment within the preset time period.

[0008] The corona performance of the generator stator is determined based on the duty cycle, number of discharge pulses, and amplitude of the discharge pulses in each local corona discharge spectrum region at each moment within the preset time period.

[0009] Preferably, marking multiple corona discharge local spectrum regions in the multi-fault superimposed global PRPD spectrum includes:

[0010] Obtain the range of each phase angle when the generator stator discharges;

[0011] Based on the phase angle ranges, multiple corona discharge local spectrum regions are marked in the multi-fault superposition global PRPD spectrum at each time point within the preset time period.

[0012] Furthermore, determining the discharge pulse duty cycle, discharge pulse quantity, and discharge pulse amplitude within each corona discharge local spectrum region at each moment within the preset time period based on the discharge quantity at each pulse amplitude and pulse phase of the positive polarity partial discharge pulse at each moment, and the discharge quantity at each pulse amplitude and pulse phase of the negative polarity partial discharge pulse at each moment within the preset time period, includes:

[0013] A three-dimensional array of each moment in the preset time period is constructed based on the amplitude and discharge quantity of each pulse phase in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase in the negative polarity partial discharge pulse.

[0014] Based on the three-dimensional array of each moment within the preset time period, determine the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period.

[0015] Furthermore, the construction of a three-dimensional array of each moment within the preset time period based on the amplitude and discharge quantity of each pulse phase within the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase within the negative polarity partial discharge pulse at each moment within the preset time period includes:

[0016] The amplitude values ​​of each pulse in the negative polarity partial discharge pulse at the i-th moment are sequentially numbered from zero to the amplitude values ​​of each pulse in the positive polarity partial discharge pulse, and each pulse amplitude number is used as the y-coordinate.

[0017] The pulse phases within the positive polarity partial discharge pulse and the pulse phases within the negative polarity partial discharge pulse at the i-th time are numbered sequentially from zero, and each pulse phase is used as the x-coordinate;

[0018] The amplitude and discharge quantity of each pulse under each pulse phase in the positive polarity partial discharge pulse at the i-th moment, and the amplitude and discharge quantity of each pulse under each pulse phase in the negative polarity partial discharge pulse, are respectively used as their corresponding pulse amplitude and pulse phase z coordinates.

[0019] Construct a three-dimensional array for the i-th time step based on the y-coordinate, x-coordinate, and z-coordinate of the i-th time step;

[0020] Where i belongs to I, and I is the total number of moments within the preset time period.

[0021] Furthermore, determining the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude within each corona discharge local spectrum region at each moment within the preset time period based on the three-dimensional array at each moment within the preset time period includes:

[0022] Based on the three-dimensional array of each moment within the preset time period, determine the horizontal and vertical coordinates of the lower left corner and the horizontal and vertical coordinates of the upper right corner of each corona discharge local map region at each moment within the preset time period.

[0023] The first coordinates of the lower left and upper right corners of each corona discharge local map region at each moment within the preset time period are determined based on the horizontal and vertical coordinates of the lower left and upper right corners of each corona discharge local map region at each moment within the preset time period.

[0024] Obtain the number of discharges in each corona discharge local spectrum region at each time point within the preset time period;

[0025] The discharge pulse duty cycle and the number of discharge pulses within the corona discharge local spectrum region are determined based on the number of discharges within the region, the first coordinate of the lower left corner, and the first coordinate of the upper right corner of the corona discharge local spectrum region.

[0026] The discharge pulse amplitude within the corona discharge local spectrum region is determined based on the first coordinates of the lower left corner and the upper right corner of the local spectrum region.

[0027] Furthermore, determining the first coordinates of the lower left and upper right corners of each corona discharge local spectrum region at each moment within the preset time period based on the horizontal and vertical coordinates of the lower left and upper right corners of each corona discharge local spectrum region at each moment within the preset time period includes:

[0028] Divide the horizontal coordinate of the lower left corner by the preset granularity to obtain the horizontal coordinate of the first coordinate of the lower left corner, and use the vertical coordinate of the lower left corner as the vertical coordinate of the first coordinate of the lower left corner;

[0029] Divide the x-coordinate of the upper right corner by a preset granularity to obtain the x-coordinate of the first coordinate of the upper right corner, and use the y-coordinate of the upper right corner as the y-coordinate of the first coordinate of the upper right corner.

[0030] Furthermore, the formula for calculating the duty cycle of the discharge pulse within the corona discharge local spectrum region is as follows:

[0031] K s =H / ((x2-x1+1)*(y2-y1+1))

[0032] In the formula, K s Let be the duty cycle of the discharge pulse in the s-th corona discharge local spectrum region, H be the number of discharges in the s-th corona discharge local spectrum region, x1 be the abscissa of the first coordinate of the lower left corner, y1 be the ordinate of the first coordinate of the lower left corner, x2 be the abscissa of the first coordinate of the upper right corner, and y2 be the ordinate of the first coordinate of the upper right corner.

[0033] The formula for calculating the number of discharge pulses within the corona discharge local spectrum region is as follows:

[0034]

[0035] In the formula, NQN s Let be the number of discharge pulses within the s-th local corona discharge pattern region. NQNX s Let z be the number of discharges;

[0036] The formula for calculating the discharge pulse amplitude within the local corona discharge spectrum region is as follows:

[0037]

[0038] In the formula, QM s Let R be the amplitude of the discharge pulse in the s-th corona discharge local spectrum region, where R is the upper limit of the range and F is the number of panes for the amplitude.

[0039] Furthermore, determining whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period includes:

[0040] Based on the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude within each corona discharge local spectrum region at each moment within the preset time period, a continuous sample feature series for the preset time period is constructed.

[0041] A trend curve is plotted based on the continuous sample feature series of the preset time period, and the corona performance of the generator stator is determined based on the trend curve.

[0042] A second aspect of this application provides a generator stator corona degradation monitoring system based on partial discharge, comprising:

[0043] The first acquisition module is used to acquire the multi-fault superimposed global PRPD map of the generator stator at each moment within a preset time period, and mark multiple corona discharge local map regions in the multi-fault superimposed global PRPD map.

[0044] The second acquisition module is used to acquire the number of discharges under each pulse amplitude and each pulse phase in the positive polarity partial discharge pulse and the number of discharges under each pulse amplitude and each pulse phase in the negative polarity partial discharge pulse based on the multi-fault superimposed global PRPD map of the generator stator at each moment within the preset time period.

[0045] The first determining module is used to determine the discharge pulse duty cycle, discharge pulse number, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period based on the discharge quantity under each pulse amplitude and pulse phase of the positive polarity partial discharge pulse at each moment within the preset time period, and the discharge quantity under each pulse amplitude and pulse phase of the negative polarity partial discharge pulse.

[0046] The second determining module is used to determine whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period.

[0047] A third aspect of this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the method described in the first aspect.

[0048] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0049] This application proposes a method and system for monitoring corona degradation of a generator stator based on partial discharge. The method includes: acquiring a multi-fault superimposed global partial discharge pulse (PRPD) map of the generator stator at various times within a preset time period, and marking multiple corona discharge local spectrum regions in the PRPD map; based on the PRPD map of the generator stator at various times within the preset time period, acquiring the number of discharges at each pulse amplitude and phase of the positive polarity partial discharge pulse, and the number of discharges at each pulse phase of the negative polarity partial discharge pulse at various times within the preset time period. The amplitude and discharge quantity under each pulse phase are used to determine the discharge pulse duty cycle, discharge pulse quantity, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period, based on the discharge pulse amplitude and discharge quantity under each pulse phase of the positive polarity partial discharge pulse and the negative polarity partial discharge pulse at each moment within the preset time period. Based on the discharge pulse duty cycle, discharge pulse quantity, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period, it is determined whether the corona performance of the generator stator has deteriorated. The technical solution proposed in this application can accurately and effectively monitor the corona state of partial discharge in the original generator insulation.

[0050] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0051] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0052] Figure 1 This is a flowchart of a generator stator corona degradation monitoring method based on partial discharge, according to an embodiment of this application.

[0053] Figure 2 This is a multi-fault overlay global PRPD map provided according to one embodiment of this application;

[0054] Figure 3 This is a first schematic diagram of a local corona discharge pattern region according to an embodiment of this application;

[0055] Figure 4 This is a second schematic diagram of a corona discharge local spectrum region provided according to an embodiment of this application;

[0056] Figure 5 A B2-QM trend chart provided according to one embodiment of this application;

[0057] Figure 6A B2-K trend chart provided according to one embodiment of this application;

[0058] Figure 7 This is a structural diagram of a generator stator corona degradation monitoring system based on partial discharge, according to an embodiment of this application. Detailed Implementation

[0059] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0060] This application proposes a method and system for monitoring corona degradation of a generator stator based on partial discharge. The method includes: acquiring a multi-fault superimposed global partial discharge pulse (PRPD) map of the generator stator at various times within a preset time period, and marking multiple corona discharge local spectrum regions in the PRPD map; based on the PRPD map of the generator stator at various times within the preset time period, acquiring the number of discharges at each pulse amplitude and phase of the positive partial discharge pulse and the number of discharges at each pulse of the negative partial discharge pulse at various times within the preset time period. The amplitude and discharge quantity under each pulse phase are used to determine the discharge pulse duty cycle, discharge pulse quantity, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period, based on the discharge pulse amplitude and discharge quantity under each pulse phase of the positive polarity partial discharge pulse and the negative polarity partial discharge pulse at each moment within the preset time period. Based on the discharge pulse duty cycle, discharge pulse quantity, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period, it is determined whether the corona performance of the generator stator has deteriorated. The technical solution proposed in this application can accurately and effectively monitor the corona state of partial discharge in the original generator insulation.

[0061] The following description, with reference to the accompanying drawings, illustrates a generator stator corona degradation monitoring method and system based on partial discharge, according to an embodiment of this application.

[0062] Example 1

[0063] Figure 1 This is a flowchart illustrating a generator stator corona degradation monitoring method based on partial discharge, according to an embodiment of this application. Figure 1 As shown, the method includes:

[0064] Step 1: Obtain the multi-fault superimposed global PRPD map of the generator stator at each moment within a preset time period, and mark multiple corona discharge local map regions in the multi-fault superimposed global PRPD map.

[0065] It should be noted that the multi-fault superimposed global PRPD map at a given moment can be as follows: Figure 2 As shown.

[0066] The original data records corresponding to the multi-fault superimposed global PRPD map are shown in Tables 1 and 2.

[0067] Table 1. Count of Positive Polarity Partial Discharge Pulses

[0068]

[0069] Table 2 Count of Negative Polarity Partial Discharge Pulses

[0070]

[0071]

[0072] It should be noted that the original data Data_d of the multi-fault superimposed global PRPD map is structured and processed by extracting the pulse record data corresponding to the map from the xlsx data table to generate a 32*100*3 3D list data Data.

[0073] 1) The data tables for storing pulse records are shown in Table 1 (positive polarity partial discharge pulse count) and Table 2 (negative polarity partial discharge pulse count). Column indices 1 to 16 in the tables represent pulse amplitude windows. The larger the value, the larger the discharge amplitude corresponding to the data in the corresponding column. Row indices 1 to 100 represent pulse phases. The larger the value, the larger the discharge phase corresponding to the data in the corresponding row. The data in the tables represent the number of discharges that occur at the current phase and amplitude, i.e., the number of discharges.

[0074] 2) Starting from the negative polarity maximum pane to 0 and then to the positive polarity maximum pane, the values ​​are represented by the y-coordinate y = [0, 1, 2... 15, 16, 17... 30, 31]. The phase from 1 to 100 is represented by the x-coordinate x = [0, 1, 2, 3... 97, 98, 99]. The discharge pulse count in the table data is represented by the z-coordinate. The 269 in the 33rd row and 1st column of Table 2 can be represented as [32, 15, 269]. The 22 in the 100th row and 1st column of Table 1 can be represented as [99, 16, 22]. The 0 in the 80th row and 16th column of Table 1 can be represented as [79, 31, 0]. And so on, all discharge pulse counts can be represented as [x, y, z] coordinates plus numerical values.

[0075] 3) Following the method in 2) above, Data is a three-dimensional array of 100*32*3:

[0076] Data = [[[x 00 ,y 00 ,z 00 ],[x 01 ,y 00 ,z 01 ],[x 02 ,y 00 ,z 02 ]......[x 98 ,y 00 ,z 02 ],[x 99 ,y

[0077] 00 ,z 99 ]] .

[0079] [[x 00 ,y 15 ,z 1500 ],[x 01 ,y 15 ,z 1501 ],[x 02 ,y 15 ,z 1502 ]......[x 98 ,y 15 ,z 198 ],[x 99 ,y 15 ,z 1599 ]] .

[0081] [[x 00 ,y 31 ,z 3100 ],[x 01 ,y 31 ,z 3101 ],[x 02 ,y 31 ,z 3102 ]......[x 98 ,y 31 ,z 3198 ],[x 99 ,y 31 ,z 3199 ]]

[0082] In this embodiment of the disclosure, marking multiple corona discharge local spectral regions in the multi-fault superimposed global PRPD map includes:

[0083] Obtain the range of each phase angle when the generator stator discharges;

[0084] Based on the phase angle ranges, multiple corona discharge local spectrum regions are marked in the multi-fault superposition global PRPD spectrum at each time point within the preset time period.

[0085] It should be noted that, based on the aforementioned global spectrum structuring, local corona discharge spectrum regions are determined, such as... Figure 3 Regions A1, A2, B1, and B2. Phase angle θ in region A1. x1 =0,θ x2 =64, Phase angle θ in region A2 x1 =324,θ x2 =360, Phase angle θ in region B1 x1 =144,θ x2 =180, Phase angle θ in region B2 x1 =180,θ x2 =244; the remaining areas represent other types of faults and were not selected to avoid affecting the analysis of the corona problem's development trend. Among them, corona fault is a known typical generator insulation fault. Statistical analysis of experimental data revealed a strong correlation between the number and position of the dots in the above four selected areas when a corona fault occurs, while other areas showed weak correlation or no correlation. The above areas were determined by the phase start and end points, and then represented using three-dimensional data. Figure 3 In the diagram, the vertical axis represents the number of panes. The lower half has 16 panes, numbered 0-15, and the upper half has 16 panes, numbered 16-31, for a total of 32 panes. This corresponds to the number 32 in the three-dimensional array Data. The array row numbers are 0-31, meaning that the panes correspond to the array rows.

[0086] In actual testing, different range units (mV) are selected to represent the discharge amplitude, i.e., the height of the dots in the diagram. Different range selections mean that each pane represents a different discharge magnitude, and the dots in the diagram represent different discharge amplitudes. For example, if the range R is selected as 10-170 [mV], then R=170, the lower half (0-15 panes) corresponds to -170 to 0 mV, and the upper half (16-31 panes) corresponds to 0 to +170 mV. If the range is increased to 20-340, then the lower half (0-15 panes) corresponds to -340 to 0 mV, and the upper half (16-31 panes) corresponds to 0 to +340 mV. That is, while the number of panes remains constant, the represented amplitude changes with the range selection, thus adapting to the needs of partial discharge measurement for different severity levels of faults in the field.

[0087] Step 2: Based on the global PRPD map of multiple faults superimposed at each moment within a preset time period, obtain the amplitude and discharge quantity of each pulse under each pulse phase of the positive polarity partial discharge pulse, and the amplitude and discharge quantity of each pulse under each pulse phase of the negative polarity partial discharge pulse at each moment within the preset time period.

[0088] It should be noted that the discharge quantity is the same as the data in Table 1 and Table 2.

[0089] Step 3: Determine the discharge pulse duty cycle, discharge pulse number, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period based on the pulse amplitude and discharge quantity under each pulse phase of the positive polarity partial discharge pulse at each moment, and the discharge quantity under each pulse phase of the negative polarity partial discharge pulse.

[0090] In this embodiment of the disclosure, step 3 specifically includes:

[0091] 3.1 Construct a three-dimensional array of each moment in the preset time period based on the amplitude and discharge quantity of each pulse phase in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase in the negative polarity partial discharge pulse at each moment in the preset time period.

[0092] 3.1 includes:

[0093] The amplitude values ​​of each pulse in the negative polarity partial discharge pulse at the i-th moment are sequentially numbered from zero to the amplitude values ​​of each pulse in the positive polarity partial discharge pulse, and each pulse amplitude number is used as the y-coordinate.

[0094] The pulse phases within the positive polarity partial discharge pulse and the pulse phases within the negative polarity partial discharge pulse at the i-th time are numbered sequentially from zero, and each pulse phase is used as the x-coordinate;

[0095] The amplitude and discharge quantity of each pulse under each pulse phase in the positive polarity partial discharge pulse at the i-th moment, and the amplitude and discharge quantity of each pulse under each pulse phase in the negative polarity partial discharge pulse, are respectively used as their corresponding pulse amplitude and pulse phase z coordinates.

[0096] Construct a three-dimensional array for the i-th time step based on the y-coordinate, x-coordinate, and z-coordinate of the i-th time step;

[0097] Where i belongs to I, and I is the total number of moments within the preset time period.

[0098] For example, the three-dimensional array can be the 100*32*3 three-dimensional array Data constructed in 1) above.

[0099] 3.2 Determine the discharge pulse duty cycle, discharge pulse number, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period based on the three-dimensional array of each moment within the preset time period.

[0100] 3.2 includes:

[0101] 3.2.1 Based on the three-dimensional array of each moment within the preset time period, determine the horizontal and vertical coordinates of the lower left corner and the horizontal and vertical coordinates of the upper right corner of each corona discharge local spectrum region at each moment within the preset time period;

[0102] 3.2.2 Determine the first coordinates of the lower left corner and the first coordinates of the upper right corner of each corona discharge local spectrum region at each moment within the preset time period based on the horizontal and vertical coordinates of the lower left corner and the horizontal and vertical coordinates of the upper right corner of each corona discharge local spectrum region at each moment within the preset time period.

[0103] Wherein, 3.2.2 includes:

[0104] Divide the horizontal coordinate of the lower left corner by the preset granularity to obtain the horizontal coordinate of the first coordinate of the lower left corner, and use the vertical coordinate of the lower left corner as the vertical coordinate of the first coordinate of the lower left corner;

[0105] Divide the x-coordinate of the upper right corner by a preset granularity to obtain the x-coordinate of the first coordinate of the upper right corner, and use the y-coordinate of the upper right corner as the y-coordinate of the first coordinate of the upper right corner.

[0106] In the 100*32*3 three-dimensional array Data, the granularity is equal to

[0107] Example,

[0108] A1: x1=0 / (360 / 100)=0, y1=0; x2=64 / (360 / 100)=18, y2=15;

[0109] A2: x1=324 / (360 / 100)=90, y1=0; x2=360 / (360 / 100)=100, y2=15;

[0110] B1: x1=144 / (360 / 100)=40, y1=16; x2=180 / (360 / 100)=50, y2=31;

[0111] B1: x1=180 / (360 / 100)=50, y1=16; x2=244 / (360 / 100)=68, y2=31;

[0112] Here, 360 represents the 360-degree phase of a sine wave. The partial discharge pulse phase analysis (PRPD) map is carried out under a sine wave phase. 100 is 100 in the 100*32*3 three-dimensional array Data, which represents the granularity of the detection record, i.e., 360 / 100 = 3.6 degrees, that is, data is recorded once every 3.6 degrees of phase.

[0113] y1 is the y-coordinate of the bottom left corner of region A1, represented by y00 in the 100*32*3 three-dimensional array Data, which is the bottom left corner y-coordinate of the red box A1. (The y-coordinate ranges from 0 to 31.) Figure 3 From bottom to top: 0-15 16-31 (lower half 0-15, upper half 16-31);

[0114] In the 3D array Data of 100*32*3, y15 represents the ordinate value of the upper right corner of region A1, which is the ordinate of the upper right corner of the red box A1, 15.

[0115] Follow this method Figure 3 The start and end coordinates of regions A1, A2, B1, and B2,4 are recorded in the dictionary regions; taking region A1 as an example, in the value corresponding to the A1 key, [0,0] represents the coordinates of the lower left corner of region A1, and [18,15] represents the coordinates of the upper right corner of region A1.

[0116] 3.2.3 Obtain the number of discharges in each corona discharge local spectrum region at each time point within the preset time period;

[0117] 3.2.4 Determine the discharge pulse duty cycle and the number of discharge pulses within the corona discharge local spectrum region based on the number of discharges within the region, the first coordinate of the lower left corner, and the first coordinate of the upper right corner of the corona discharge local spectrum region.

[0118] The formula for calculating the duty cycle of the discharge pulse within the local corona discharge spectrum region is as follows:

[0119] K s =H / ((x2-x1+1)*(y2-y1+1))

[0120] In the formula, K s Let be the duty cycle of the discharge pulse in the s-th corona discharge local spectrum region, H be the number of discharges in the s-th corona discharge local spectrum region, x1 be the abscissa of the first coordinate of the lower left corner, y1 be the ordinate of the first coordinate of the lower left corner, x2 be the abscissa of the first coordinate of the upper right corner, and y2 be the ordinate of the first coordinate of the upper right corner.

[0121] The formula for calculating the number of discharge pulses within the corona discharge local spectrum region is as follows:

[0122]

[0123] In the formula, NQN s Let be the number of discharge pulses within the s-th local corona discharge pattern region. NQNX s Let z be the number of discharges;

[0124] 3.2.5 Determine the discharge pulse amplitude within the corona discharge local spectrum region based on the first coordinates of the lower left corner and the upper right corner of the corona discharge local spectrum region.

[0125] The formula for calculating the discharge pulse amplitude within the local corona discharge spectrum region is as follows:

[0126]

[0127] In the formula, QM s Let R be the discharge pulse amplitude within the s-th corona discharge local spectrum region, and F be the upper limit of the range and the number of panes for the amplitude. Figure 3 In this case, F equals 32. It should be noted that R is the upper limit of the sample test range, such as R: 10-170 [mV], then R = 170.

[0128] Step 4: Determine whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period.

[0129] In this embodiment of the disclosure, step 4 specifically includes:

[0130] 4.1: Construct a series of continuous sample features for the preset time period based on the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period;

[0131] It should be noted that the continuous sample feature series of the preset time period is X = [X1, X2, ..., X...]. n-1 ,X n ], where n is the total duration within the preset time period, and X is the sample X at time t within the preset time period. n The calculation formula is as follows:

[0132] X n =[[K A1,n NQN A1,n QM A1,n ],

[0133] [K A2,n NQN A2,n QM A2,n ],

[0134] [K B1,n NQN B1,n QM B1,n ],

[0135] [K B2,n NQN B2,n QM B2,n ]]

[0136] In the formula, K A1,n Let NQN be the number of discharge pulses in the local corona discharge spectrum region of A1 at time n. A1,n Let QM be the number of discharge pulses in the local corona discharge spectrum region of A1 at time n. A1,n Let be the amplitude of the discharge pulse in the local spectrum region of A1 corona discharge at time n.

[0137] 4.2: Draw a trend curve based on the continuous sample feature series of the preset time period, and determine whether the corona performance of the generator stator has deteriorated based on the trend curve.

[0138] It should be noted that by selecting sample time periods from the continuous sample feature series X, and plotting the trend curves of the areas and features to be monitored, a trend graph is obtained. The trend graph shows that the insulation and anti-corona performance has been continuously deteriorating during many years of continuous operation.

[0139] In this embodiment, the A1, A2, B1, and B2 partitions can be adjusted in size and position using the coordinate parameters of the corresponding key values ​​in the `regions` dictionary to meet the monitoring needs of different faults. The feature vector uses x... i = [Ki, NQNi, QMi], i = A1, A2, B1, B2. Trend monitoring can monitor 1 feature or 3 features simultaneously.

[0140] The generator stator corona degradation monitoring method based on partial discharge, as described above, is explained in detail below with examples:

[0141] 1. Obtain the original data of the partial discharge samples, as shown in Table 3;

[0142] Table 3

[0143]

[0144] The data in Table 3 is a 3D list data of 100*32*3. Taking 7569.xl sx as an example sample, the processed data is as follows. The other samples are processed in the same way.

[0145] Data =

[0146] [[[0,0,0],[1,0,0],......[98,0,0],[99,0,0]],

[0147] [[0,1,0],[1,1,0],......[98,1,0],[99,1,0]],

[0148] [[0,2,1],[1,2,0],......[98,2,1],[99,2,0]], ......

[0150] [[0,3,0],[1,3,0],......[98,3,0],[99,3,0]],

[0151] [[0,30,0],[1,30,0],.......[98,30,0],[99,30,0]],

[0152] [[0,31,0],[1,31,0],.......[98,31,0],[99,31,0]]]

[0153] 2. In the global spectral structured data, determine the local spectral regions of corona discharge, such as... Figure 4 Regions A1, A2, B1, and B2. Phase angle θ in region A1. x1 =0,θ x2 =64, Phase angle θ in region A2 x1 =324,θ x2 =360, Phase angle θ in region B1 x1 =144,θ x2 =180, Phase angle θ in region B2 x1 =180,θ x2 =244, region selection as follows Figure 4 The diagram is shown in the figure frame.

[0154] 3. Determine the regions in the map that represent the coordinates of regions A1, A2, B1, and B2, i.e., the regions formed by the first coordinates;

[0155] 4. Calculate the discharge pulse duty cycles KA1, KA2, KB1, KB2, pulse counts NQNA1, NQNA2, NQNB1, NQNB2, and pulse amplitudes QMA1, QMA2, QMB1, QMB2 in regions A1, A2, B1, and B2. Using ID7569 as an example, calculate the characteristic quantities, represented as a three-dimensional array of characteristic matrices X7569; the characteristic quantity calculation results are as follows... Figure 4 Figure A1, A2, B1, and B2 are shown in the frame.

[0156] X7569 =[[11.3,74,42.5],

[0157] [3.1,1,21.2],

[0158] [2.1,1,85],

[0159] [18.8,124,85]]

[0160] Complete the calculations for all samples in Table 3 using the process described above to obtain the continuous sample data feature series X;

[0161] 5. Select sample time periods from the continuous sample feature series X, and plot trend curves based on the regions and features to be monitored, such as... Figure 5 The B2-QM trend chart mentioned above, Figure 6 The B2-K trend chart shows that the insulation and anti-corona performance has been continuously deteriorating over many years of continuous operation.

[0162] The generator stator corona degradation monitoring method based on partial discharge provided in this embodiment mainly relies on online monitoring of insulation partial discharge. Partial discharge monitoring should detect the overall state of the stator winding insulation, including internal insulation defect discharge, internal load cycle gap discharge, corona discharge, end-phase gap discharge, and metal tip discharge at conductor connections. More than one type of fault can occur simultaneously; therefore, current online partial discharge monitoring represents the overall state of multiple superimposed faults and cannot reflect specific fault trends. This invention, based on the overall partial discharge state data, determines the corona discharge region data, recalculates and extracts features, and monitors corona discharge through data feature quantities. This solves the problems of the original generator insulation partial discharge online monitoring lacking specificity and corona state monitoring failure. Besides corona problems, it can also detect insulation defects of interest by adjusting the region coordinates.

[0163] In summary, the generator stator corona degradation monitoring method based on partial discharge proposed in this embodiment can accurately and effectively monitor the corona state of partial discharge in the original generator insulation.

[0164] Example 2

[0165] Figure 7 This is a structural diagram of a generator stator corona degradation monitoring system based on partial discharge, according to an embodiment of this application. Figure 7 As shown, the system includes:

[0166] The first acquisition module 100 is used to acquire the multi-fault superimposed global PRPD map of the generator stator at each moment within a preset time period, and mark multiple corona discharge local map regions in the multi-fault superimposed global PRPD map.

[0167] The step of marking multiple corona discharge local spectrum regions in the multi-fault superimposed global PRPD spectrum includes:

[0168] Obtain the range of each phase angle when the generator stator discharges;

[0169] Based on the phase angle ranges, multiple corona discharge local spectrum regions are marked in the multi-fault superposition global PRPD spectrum at each time point within the preset time period.

[0170] The second acquisition module 200 is used to acquire the number of discharges under each pulse amplitude and each pulse phase in the positive polarity partial discharge pulse and the number of discharges under each pulse amplitude and each pulse phase in the negative polarity partial discharge pulse based on the multi-fault superimposed global PRPD map of the generator stator at each moment within the preset time period.

[0171] The first determining module 300 is used to determine the discharge pulse duty cycle, discharge pulse number, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period based on the discharge quantity under each pulse amplitude and pulse phase of each positive polarity partial discharge pulse and the discharge quantity under each pulse phase of each negative polarity partial discharge pulse.

[0172] The second determining module 400 is used to determine whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, the number of discharge pulses, and the discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period.

[0173] In this embodiment of the disclosure, the first determining module 300 is further configured to:

[0174] A three-dimensional array of each moment in the preset time period is constructed based on the amplitude and discharge quantity of each pulse phase in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase in the negative polarity partial discharge pulse.

[0175] The step of constructing a three-dimensional array for each moment within the preset time period based on the amplitude and discharge quantity of each pulse phase within the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase within the negative polarity partial discharge pulse includes:

[0176] The amplitude values ​​of each pulse in the negative polarity partial discharge pulse at the i-th moment are sequentially numbered from zero to the amplitude values ​​of each pulse in the positive polarity partial discharge pulse, and each pulse amplitude number is used as the y-coordinate.

[0177] The pulse phases within the positive polarity partial discharge pulse and the pulse phases within the negative polarity partial discharge pulse at the i-th time are numbered sequentially from zero, and each pulse phase is used as the x-coordinate;

[0178] The amplitude and discharge quantity of each pulse under each pulse phase in the positive polarity partial discharge pulse at the i-th moment, and the amplitude and discharge quantity of each pulse under each pulse phase in the negative polarity partial discharge pulse, are respectively used as their corresponding pulse amplitude and pulse phase z coordinates.

[0179] Construct a three-dimensional array for the i-th time step based on the y-coordinate, x-coordinate, and z-coordinate of the i-th time step;

[0180] Where i belongs to I, and I is the total number of moments within the preset time period.

[0181] Based on the three-dimensional array of each moment within the preset time period, determine the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period.

[0182] The step of determining the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period based on the three-dimensional array at each moment within the preset time period includes:

[0183] Based on the three-dimensional array of each moment within the preset time period, determine the horizontal and vertical coordinates of the lower left corner and the horizontal and vertical coordinates of the upper right corner of each corona discharge local map region at each moment within the preset time period.

[0184] The first coordinates of the lower left and upper right corners of each corona discharge local map region at each moment within the preset time period are determined based on the horizontal and vertical coordinates of the lower left and upper right corners of each corona discharge local map region at each moment within the preset time period.

[0185] The step of determining the first coordinates of the lower left and upper right corners of each corona discharge local spectrum region at each moment within the preset time period based on the horizontal and vertical coordinates of the lower left and upper right corners of each corona discharge local spectrum region at each moment within the preset time period includes:

[0186] Divide the horizontal coordinate of the lower left corner by the preset granularity to obtain the horizontal coordinate of the first coordinate of the lower left corner, and use the vertical coordinate of the lower left corner as the vertical coordinate of the first coordinate of the lower left corner;

[0187] Divide the x-coordinate of the upper right corner by a preset granularity to obtain the x-coordinate of the first coordinate of the upper right corner, and use the y-coordinate of the upper right corner as the y-coordinate of the first coordinate of the upper right corner.

[0188] Obtain the number of discharges in each corona discharge local spectrum region at each time point within the preset time period;

[0189] The discharge pulse duty cycle and the number of discharge pulses within the corona discharge local spectrum region are determined based on the number of discharges within the region, the first coordinate of the lower left corner, and the first coordinate of the upper right corner of the corona discharge local spectrum region.

[0190] The discharge pulse amplitude within the corona discharge local spectrum region is determined based on the first coordinates of the lower left corner and the upper right corner of the local spectrum region.

[0191] The formula for calculating the duty cycle of the discharge pulse within the local corona discharge spectrum region is as follows:

[0192] K s =H / ((x2-x1+1)*(y2-y1+1))

[0193] In the formula, K s Let be the duty cycle of the discharge pulse in the s-th corona discharge local spectrum region, H be the number of discharges in the s-th corona discharge local spectrum region, x1 be the abscissa of the first coordinate of the lower left corner, y1 be the ordinate of the first coordinate of the lower left corner, x2 be the abscissa of the first coordinate of the upper right corner, and y2 be the ordinate of the first coordinate of the upper right corner.

[0194] The formula for calculating the number of discharge pulses within the corona discharge local spectrum region is as follows:

[0195]

[0196] In the formula, NQN s Let be the number of discharge pulses within the s-th local corona discharge pattern region. NQNX s Let z be the number of discharges;

[0197] The formula for calculating the discharge pulse amplitude within the local corona discharge spectrum region is as follows:

[0198]

[0199] In the formula, QM s Let R be the amplitude of the discharge pulse in the s-th corona discharge local spectrum region, where R is the upper limit of the range and F is the number of panes for the amplitude.

[0200] In this embodiment of the disclosure, the second determining module 400 is further configured to:

[0201] Based on the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude within each corona discharge local spectrum region at each moment within the preset time period, a continuous sample feature series for the preset time period is constructed.

[0202] A trend curve is plotted based on the continuous sample feature series of the preset time period, and the corona performance of the generator stator is determined based on the trend curve.

[0203] In summary, the generator stator corona degradation monitoring system based on partial discharge proposed in this embodiment can accurately and effectively monitor the corona state of partial discharge in the original generator insulation.

[0204] Example 3

[0205] To implement the above embodiments, this disclosure also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in Embodiment 1.

[0206] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0207] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0208] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for monitoring stator corona degradation in generators based on partial discharge, characterized in that, The method includes: Obtain the multi-fault superimposed global PRPD map of the generator stator at each moment within a preset time period, and mark multiple corona discharge local map regions in the multi-fault superimposed global PRPD map; Based on the global PRPD map of multiple faults superimposed on the generator stator at each moment within a preset time period, the amplitude and discharge quantity of each pulse under each pulse phase in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse under each pulse phase in the negative polarity partial discharge pulse are obtained at each moment within the preset time period. A three-dimensional array of each moment in the preset time period is constructed based on the amplitude and discharge quantity of each pulse phase in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase in the negative polarity partial discharge pulse. Based on the three-dimensional array of each moment within the preset time period, determine the horizontal and vertical coordinates of the lower left corner and the horizontal and vertical coordinates of the upper right corner of each corona discharge local map region at each moment within the preset time period. Divide the horizontal coordinate of the lower left corner by the preset granularity to obtain the horizontal coordinate of the first coordinate of the lower left corner, and use the vertical coordinate of the lower left corner as the vertical coordinate of the first coordinate of the lower left corner; Divide the x-coordinate of the upper right corner by the preset granularity to obtain the x-coordinate of the first coordinate of the upper right corner, and use the y-coordinate of the upper right corner as the y-coordinate of the first coordinate of the upper right corner; Obtain the number of discharges in each corona discharge local spectrum region at each time point within the preset time period; The discharge pulse duty cycle and the number of discharge pulses within the corona discharge local spectrum region are determined based on the number of discharges within the region, the first coordinate of the lower left corner, and the first coordinate of the upper right corner of the corona discharge local spectrum region. The discharge pulse amplitude within the corona discharge local spectrum region is determined based on the first coordinates of the lower left corner and the upper right corner of the corona discharge local spectrum region. The corona performance of the generator stator is determined based on the duty cycle, number of discharge pulses, and amplitude of the discharge pulses in the local corona discharge spectrum region at each moment within the preset time period. The formula for calculating the duty cycle of the discharge pulse within the corona discharge local spectrum region is as follows: K s =H / ((x2-x1+1) (y2-y1+1)) In the formula, K s Let be the duty cycle of the discharge pulse in the s-th corona discharge local spectrum region, H be the number of discharges in the s-th corona discharge local spectrum region, x1 be the abscissa of the first coordinate of the lower left corner, y1 be the ordinate of the first coordinate of the lower left corner, x2 be the abscissa of the first coordinate of the upper right corner, and y2 be the ordinate of the first coordinate of the upper right corner. The formula for calculating the number of discharge pulses within the corona discharge local spectrum region is as follows: In the formula, Let be the number of discharge pulses within the s-th local corona discharge pattern region. , Let z be the number of discharges; The formula for calculating the discharge pulse amplitude within the local corona discharge spectrum region is as follows: In the formula, QM s Let R be the amplitude of the discharge pulse in the s-th corona discharge local spectrum region, where R is the upper limit of the range and F is the number of panes for the amplitude.

2. The method as described in claim 1, characterized in that, The marking of multiple corona discharge local spectrum regions in the multi-fault superimposed global PRPD spectrum includes: Obtain the range of each phase angle when the generator stator discharges; Based on the phase angle ranges, multiple corona discharge local spectrum regions are marked in the multi-fault superposition global PRPD spectrum at each time point within the preset time period.

3. The method as described in claim 2, characterized in that, The construction of a three-dimensional array for each moment within the preset time period, based on the amplitude and discharge quantity of each pulse at each pulse phase of the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse phase of the negative polarity partial discharge pulse, includes: The amplitude values ​​of each pulse in the negative polarity partial discharge pulse at the i-th moment are sequentially numbered from zero to the amplitude values ​​of each pulse in the positive polarity partial discharge pulse, and each pulse amplitude number is used as the y-coordinate. The pulse phases within the positive polarity partial discharge pulse and the pulse phases within the negative polarity partial discharge pulse at the i-th time are numbered sequentially from zero, and each pulse phase is used as the x-coordinate; The amplitude and discharge quantity of each pulse under each pulse phase in the positive polarity partial discharge pulse at the i-th moment, and the amplitude and discharge quantity of each pulse under each pulse phase in the negative polarity partial discharge pulse, are respectively used as their corresponding pulse amplitude and pulse phase z coordinates. Construct a three-dimensional array for the i-th time step based on the y-coordinate, x-coordinate, and z-coordinate of the i-th time step; Where i belongs to I, and I is the total number of moments within the preset time period.

4. The method as described in claim 3, characterized in that, The step of determining whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period includes: A series of continuous sample features for the preset time period is constructed based on the discharge pulse duty cycle, number of discharge pulses, and discharge pulse amplitude in each corona discharge local spectrum region at each moment within the preset time period. A trend curve is plotted based on the continuous sample feature series of the preset time period, and the corona performance of the generator stator is determined based on the trend curve.

5. A generator stator corona degradation monitoring system based on partial discharge, characterized in that, The system includes: The first acquisition module is used to acquire the multi-fault superimposed global PRPD map of the generator stator at each moment within a preset time period, and mark multiple corona discharge local map regions in the multi-fault superimposed global PRPD map. The second acquisition module is used to acquire the number of discharges under each pulse amplitude and each pulse phase in the positive polarity partial discharge pulse and the number of discharges under each pulse amplitude and each pulse phase in the negative polarity partial discharge pulse based on the multi-fault superimposed global PRPD map of the generator stator at each moment within the preset time period. The first determining module is used to construct a three-dimensional array of each moment in the preset time period based on the amplitude and discharge quantity of each pulse in the positive polarity partial discharge pulse and the amplitude and discharge quantity of each pulse in the negative polarity partial discharge pulse at each moment in the preset time period. The first determining module is further configured to determine the lower left and upper right horizontal and vertical coordinates of each corona discharge local spectrum region at each moment within the preset time period based on the three-dimensional array of each moment within the preset time period. The first determining module is further configured to divide the horizontal coordinate of the lower left corner by a preset granularity to obtain the horizontal coordinate of the first coordinate of the lower left corner, and to use the vertical coordinate of the lower left corner as the vertical coordinate of the first coordinate of the lower left corner. The first determining module is further configured to divide the horizontal coordinate of the upper right corner by a preset granularity to obtain the horizontal coordinate of the first coordinate of the upper right corner, and to use the vertical coordinate of the upper right corner as the vertical coordinate of the first coordinate of the upper right corner. The first determining module is also used to obtain the number of discharges in each corona discharge local spectrum region at each time within the preset time period; The first determining module is further configured to determine the discharge pulse duty cycle and the number of discharge pulses within the corona discharge local spectrum region based on the number of discharges within the corona discharge local spectrum region and the first coordinates of the lower left corner and the upper right corner of the corona discharge local spectrum region. The first determining module is further configured to determine the discharge pulse amplitude within the corona discharge local spectrum region based on the first coordinates of the lower left corner and the upper right corner of the corona discharge local spectrum region; The second determining module is used to determine whether the corona performance of the generator stator has deteriorated based on the discharge pulse duty cycle, number of discharge pulses, and amplitude of discharge pulses in each corona discharge local spectrum region at each moment within the preset time period. The formula for calculating the duty cycle of the discharge pulse within the corona discharge local spectrum region is as follows: K s =H / ((x2-x1+1) (y2-y1+1)) In the formula, K s Let be the duty cycle of the discharge pulse in the s-th corona discharge local spectrum region, H be the number of discharges in the s-th corona discharge local spectrum region, x1 be the abscissa of the first coordinate of the lower left corner, y1 be the ordinate of the first coordinate of the lower left corner, x2 be the abscissa of the first coordinate of the upper right corner, and y2 be the ordinate of the first coordinate of the upper right corner. The formula for calculating the number of discharge pulses within the corona discharge local spectrum region is as follows: In the formula, Let be the number of discharge pulses within the s-th local corona discharge pattern region. , Let z be the number of discharges; The formula for calculating the discharge pulse amplitude within the local corona discharge spectrum region is as follows: In the formula, QM s Let R be the amplitude of the discharge pulse in the s-th corona discharge local spectrum region, where R is the upper limit of the range and F is the number of panes for the amplitude.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-4.

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