Intelligent positioning method and device for ultrahigh frequency partial discharge signal source

Abstract

The invention discloses an intelligent positioning method and device for an ultrahigh frequency partial discharge signal source, and the method comprises the steps: determining a partial discharge signal model of a measurement point pair based on the characteristic parameters of a partial discharge signal, and the measurement point pair comprises a first measurement point and a second measurement point which are adjacent in position; obtaining an energy focusing result of the partial discharge signal at the starting moment based on a partial discharge signal model; the energy focusing result represents the peak value of the partial discharge signal; and determining the reference position of the partial discharge signal source based on the energy focusing result at the starting moment. According to the method, intelligent positioning of the ultrahigh-frequency partial discharge signal source can be realized, random errors generated by manual positioning are eliminated, and a theoretical foundation is laid for realizing analysis of the partial discharge signal source and equipment operation judgment.

Description

Technical Field

[0001] The present application relates to the technical field of partial discharge detection and positioning of high-voltage electrical equipment, and in particular to an intelligent positioning method and device for a UHF partial discharge signal source. Background Art

[0002] The stable operation of gas-insulated high-voltage electrical equipment directly affects the reliability of power transmission and distribution in the power grid. Under actual operating conditions, unreliable contact of various components, surface / internal defects of different insulators, and metallic foreign matter can all lead to partial discharge inside the equipment, which seriously threatens the operational stability of high-voltage electrical equipment.

[0003] When high-voltage electrical equipment generates partial discharge, the drastically changing current pulses will excite ultra-high frequency electromagnetic signals, namely partial discharge signals (hereinafter referred to as PD signals). When conducting partial discharge analysis on electrical equipment, on the one hand, the defect type is analyzed through the statistical spectrum characteristics of the signal, and on the other hand, the PD signal is located and processed to clarify the actual location of the PD signal source. At present, the time difference positioning method is widely used to locate the PD signal source (hereinafter referred to as PD signal source). The original PD signals of different measuring points (usually two adjacent measuring points) are collected by high-speed oscilloscopes or high-speed acquisition cards. The starting time of the PD signal is currently mainly extracted manually, and the estimation of the PD signal source is realized based on the time difference of the starting time of different measuring points.

[0004] However, when conducting actual measurements of UHF PD signals on site, manual extraction results are highly random and greatly affected by the operations of on-site personnel. The use of manual starting time extraction is prone to measurement errors in the starting time of PD signals, resulting in abnormal positioning of PD signal sources and affecting the effective evaluation and defect determination of electrical equipment. Summary of the invention

[0005] The present application provides a method and device for intelligently locating a UHF partial discharge signal source, the purpose of which is to achieve intelligent locating of the partial discharge signal source.

[0006] In order to achieve the above objectives, this application provides the following technical solutions:

[0007] An intelligent positioning method for a UHF partial discharge signal source, comprising:

[0008] Determining a partial discharge signal model of a pair of measuring points based on characteristic parameters of the partial discharge signal; the pair of measuring points includes a first measuring point and a second measuring point that are adjacent in position;

[0009] Based on the local discharge signal model, obtaining an energy focusing result of the local discharge signal at a starting time; the energy focusing result represents a peak value of the local discharge signal;

[0010] Based on the energy focusing result at the starting moment, a reference position of the local discharge signal source is determined.

[0011] Optionally, based on characteristic parameters of the partial discharge signal, a partial discharge signal model of the measuring point pair is determined, including:

[0012] Obtaining characteristic parameters of a partial discharge signal; the characteristic parameters include pulse width, sampling frequency, oscillation frequency, and voltage amplitude;

[0013] Determining a first duration sequence based on the pulse width and the sampling frequency;

[0014] Determine a duration model of the partial discharge signal based on the first duration sequence in combination with the oscillation frequency and the voltage amplitude;

[0015] Obtaining the interval distance between the first measuring point and the second measuring point in the measuring point alignment;

[0016] Determining a second duration sequence corresponding to the duty cycle of the partial discharge signal based on the interval distance between the first measuring point and the second measuring point and the sampling frequency;

[0017] determining a full-time parameter based on the first duration sequence and the second duration sequence;

[0018] Based on the duration model and the full-time parameter, a partial discharge signal model of the pair of measurement points is determined.

[0019] Optionally, obtaining an energy focusing result of the local discharge signal at a starting time based on the local discharge signal model includes:

[0020] Based on the partial discharge signal model, determining envelope characteristics of the partial discharge signal;

[0021] Using a preset sum differential filter model, convolution processing is performed on the envelope feature to obtain an energy focusing result of the envelope feature;

[0022] A modulus calculation is performed on the energy focusing result to obtain the energy focusing result of the local discharge signal at the starting moment.

[0023] Optionally, determining the envelope characteristics of the partial discharge signal based on the partial discharge signal model includes:

[0024] Based on the partial discharge signal models corresponding to the first measuring point and the second measuring point, respectively, solving and obtaining an improved Hilport transform of the partial discharge signal;

[0025] Based on the improved Hilport transform and in combination with the partial discharge signal, the envelope characteristics of the partial discharge signal are obtained by solving.

[0026] Optionally, determining a reference position of a local discharge signal source based on the energy focusing result at the starting moment includes:

[0027] Based on the energy focusing result at the starting time, determining the time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal;

[0028] Based on the time delay difference, a reference position of the partial discharge signal source is determined.

[0029] Optionally, determining the time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal based on the energy focusing result at the starting time includes:

[0030] Based on the energy focusing result at the starting time, determining the signal peak positions corresponding to the first measuring point and the second measuring point respectively;

[0031] Determining the number of starting points of the partial discharge signal based on the signal peak positions corresponding to the first measuring point and the second measuring point respectively;

[0032] Based on the number of starting points, a time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal is determined.

[0033] Optionally, determining a reference position of a partial discharge signal source based on the time delay difference includes:

[0034] Based on the interval distance between the first measuring point and the second measuring point, combined with the sampling frequency of the partial discharge signal and the propagation speed of the electromagnetic wave, determining the number of interval points between the first measuring point and the second measuring point;

[0035] Determine the interval distance between the partial discharge signal source and the first measuring point based on the number of interval points, the electromagnetic wave propagation speed, and the number of starting points corresponding to the time delay difference;

[0036] A reference position of the partial discharge signal source is determined based on the interval distance between the partial discharge signal source and the first measuring point.

[0037] An intelligent positioning device for a UHF partial discharge signal source, comprising:

[0038] A model determination unit, configured to determine a partial discharge signal model of a pair of measuring points based on characteristic parameters of the partial discharge signal; the pair of measuring points comprises a first measuring point and a second measuring point that are adjacent in position;

[0039] An energy focusing unit, used for obtaining an energy focusing result of the local discharge signal at a starting time based on the local discharge signal model; the energy focusing result represents a peak value of the local discharge signal;

[0040] The position determination unit is used to determine the reference position of the partial discharge signal source based on the energy focusing result at the starting moment.

[0041] A storage medium includes a stored program, wherein the program executes the intelligent positioning method of a UHF partial discharge signal source when the program is run by a processor.

[0042] An electronic device, comprising: a processor, a memory and a bus; the processor and the memory are connected via the bus;

[0043] The memory is used to store programs, and the processor is used to run programs, wherein the program executes the intelligent positioning method of the ultra-high frequency partial discharge signal source when the processor runs it.

[0044] The technical solution provided by the present application determines the local discharge signal model of the measuring point pair based on the characteristic parameters of the local discharge signal, and the measuring point pair includes a first measuring point and a second measuring point that are adjacent in position. Based on the local discharge signal model, the energy focusing result of the local discharge signal at the starting time is obtained. The energy focusing result represents the peak value of the local discharge signal. Based on the energy focusing result at the starting time, the reference position of the local discharge signal source is determined. The present application can realize the intelligent positioning of the ultra-high frequency local discharge signal source, eliminate the random errors caused by manual positioning, and lay a theoretical foundation for realizing the analysis of the local discharge signal source and the judgment of equipment operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A schematic flow chart of an intelligent positioning method for a UHF partial discharge signal source provided in an embodiment of the present application;

[0047] Figure 2 A schematic flow chart of another method for intelligently locating a UHF partial discharge signal source provided in an embodiment of the present application;

[0048] Figure 3 A schematic flow chart of another method for intelligently locating a UHF partial discharge signal source provided in an embodiment of the present application;

[0049] Figure 4 A schematic flow chart of another method for intelligently locating a UHF partial discharge signal source provided in an embodiment of the present application;

[0050] Figure 5 A schematic flow chart of another method for intelligently locating a UHF partial discharge signal source provided in an embodiment of the present application;

[0051] Figure 6 A schematic flow chart of another method for intelligently locating a UHF partial discharge signal source provided in an embodiment of the present application;

[0052] Figure 7 A schematic diagram of the architecture of an intelligent positioning device for a UHF partial discharge signal source provided in an embodiment of the present application;

[0053] Figure 8 A schematic diagram of an experimental simulation result provided in an embodiment of the present application;

[0054] Fig. 9 Another schematic diagram of experimental simulation results provided in an embodiment of the present application;

[0055] Fig.10 Another schematic diagram of experimental simulation results provided for an embodiment of the present application. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0058] like Figure 1As shown, it is a flow chart of an intelligent positioning method for a UHF partial discharge signal source provided in an embodiment of the present application, which includes the following steps.

[0059] S101: Determine a partial discharge signal model of a pair of measuring points based on characteristic parameters of the partial discharge signal.

[0060] The measuring point pair includes a first measuring point and a second measuring point that are adjacent in position.

[0061] In some examples, characteristic parameters of the partial discharge signal include at least pulse width, sampling frequency, oscillation frequency, and voltage amplitude.

[0062] In some examples, the partial discharge signal may be analyzed and measured to obtain corresponding characteristic parameters.

[0063] It should be noted that, based on the characteristic parameters of the partial discharge signal, the partial discharge signal models corresponding to the first measuring point and the second measuring point in the measuring point pair can be determined, thereby providing a model basis for subsequent adaptive positioning of the partial discharge signal source.

[0064] Optionally, based on the characteristic parameters of the partial discharge signal, the implementation process of determining the partial discharge signal model of the measuring point pair can be found in Figure 2 The steps are shown and the corresponding explanations.

[0065] S102: Based on the partial discharge signal model, an energy focusing result of the partial discharge signal at the starting time is obtained.

[0066] The energy focusing result represents the peak value of the partial discharge signal.

[0067] Optionally, based on the local discharge signal model, the implementation process of obtaining the energy focusing result of the local discharge signal at the starting time can be found in Figure 3 The steps are shown and the corresponding explanations.

[0068] S103: Determine a reference position of the partial discharge signal source based on the energy focusing result at the start time.

[0069] Among them, after obtaining the energy focusing result at the starting moment, the time delay difference when the first measuring point and the second measuring point collect the local discharge signal can be determined based on the energy focusing result at the starting moment, and then based on the time delay difference, the reference position of the local discharge signal source can be determined.

[0070] Optionally, based on the energy focusing result at the start time, the implementation process of determining the time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal can be found in Figure 5 The steps are shown and the corresponding explanations.

[0071] Optionally, the implementation process of determining the reference position of the partial discharge signal source based on the time delay difference can be found in Figure 6 The steps are shown and the corresponding explanations.

[0072] Combination Figure 2-Figure 6 The method shown in the embodiment of the present application uses the partial discharge signal to perform envelope detection processing to obtain the envelope characteristics of the partial discharge signal, which can eliminate the influence of the pulse oscillation of the partial discharge signal. At the same time, the envelope gold foil is equivalent to the partial discharge signal for downsampling processing. In addition, the envelope characteristics are convolved by a sum differential filter to form a peak value (i.e., energy focusing) at the starting time of the partial discharge signal. The starting time of the partial discharge signal can be obtained based on the peak search, and the intelligent positioning of the partial discharge signal source can be achieved through the time delay difference corresponding to the starting time.

[0073] In some examples, the positioning effect of the embodiments of the present application is tested through simulation experiments, assuming that the simulation parameters involved in the experiment include the local discharge duration (ie, pulse width) =200ns, oscillation frequency =0.2GHz, sampling frequency =2GHz, SNR =5dB, half order of variable scale difference filter =25, the voltage amplitude of the partial discharge signal is 1, and the electromagnetic wave attenuation per meter propagation =0, the sampling value =1, the distance between the first measuring point and the second measuring point =10m, electromagnetic wave propagation speed is the speed of light, and the distance between the partial discharge signal source and the first measuring point is set to Furthermore, through simulation experiments, we can get Figure 8 , Fig. 9 as well as Fig.10 The simulation results are shown.

[0074] See also Figure 8 As shown in the simulation results, the interval distances between the first measuring point and the second measuring point and the local discharge signal source are different, and there is a time delay difference in the signals received by the two measuring points. The envelope characteristics of the local discharge signals detected by the two measuring points are also coupled with the time delay caused by the distance. The location estimation of the local discharge signal source can be achieved through the time delay difference.

[0075] See also Fig. 9 as well as Fig.10The simulation results shown in the figure show that the signal wave head can be extracted based on the peak search. The extraction result is only one point different from the previous estimation result. The error is caused by the rounding problem of the resolution unit due to the sampling rate limitation, that is, 6.667 points need to be rounded up to 67 during the simulation process. Therefore, the error is a system error, not an algorithm accuracy error (the algorithm accuracy error is the error caused by the algorithm logic problem during the operation process, such as the threshold positioning or threshold positioning method. When it is greater than a certain threshold / threshold, it is considered that the system detects the signal, but when the noise energy is greater than the threshold / threshold, it is considered that the system collects the signal. The error caused by this is the algorithm accuracy error, that is, the error caused by the algorithm logic). It is known that the distance between measuring point 1 and measuring point 2 is 10m. Based on the time delay difference of the received signal between the first measuring point and the second measuring point (that is, the time delay difference when collecting the partial discharge signal), the suspected signal source (that is, the partial discharge signal source) is located, and the distance between the abnormal signal source and measuring point 1 is solved to be 3.98m, and the measurement error is 99.5%.

[0076] The process shown in S101-S103 above can realize the intelligent positioning of the UHF partial discharge signal source, eliminate the random errors caused by manual positioning, and lay a theoretical foundation for the analysis of the partial discharge signal source and the judgment of equipment operation.

[0077] like Figure 2 As shown, it is a flow chart of another intelligent positioning method of a UHF partial discharge signal source provided in an embodiment of the present application, including the following steps.

[0078] S201: Obtain characteristic parameters of a partial discharge signal.

[0079] Among them, the characteristic parameters include pulse width , sampling frequency , Oscillation frequency , voltage amplitude .

[0080] S202: Determine a first duration sequence based on the pulse width and the sampling frequency.

[0081] Among them, based on the pulse width And the sampling frequency , determine the number of sampling points of the partial discharge signal , and use the sampling points of the partial discharge signal , solve for the first duration sequence .

[0082] In some examples, the first duration sequence The expression of can be seen in formula (1).

[0083] (1)

[0084] S203: Determine a duration model of the partial discharge signal based on the first duration sequence in combination with the oscillation frequency and the voltage amplitude.

[0085] Among them, when obtaining the first duration sequence After that, combined with the oscillation frequency And the voltage amplitude , the duration model of partial discharge signal can be established .

[0086] In some examples, the duration model The expression of can be seen in formula (2).

[0087] (2)

[0088] S204: Obtaining the interval distance between the first measuring point and the second measuring point in the measuring point alignment.

[0089] Among them, the distance between the first measuring point and the second measuring point , which can be measured on-site by technical personnel.

[0090] S205: Determine a second duration sequence corresponding to the duty cycle of the partial discharge signal based on the interval distance between the first measuring point and the second measuring point and the sampling frequency.

[0091] Among them, when obtaining the interval distance between the first measuring point and the second measuring point Then, combined with the electromagnetic wave propagation speed , the duty cycle of the partial discharge signal can be calculated , combined with the sampling frequency , the duty cycle can be determined The corresponding number of sampling points , and finally use the number of sampling points , solving for the second duration sequence .

[0092] In some examples, the second duration sequence The expression of can be seen in formula (3).

[0093] (3)

[0094] It should be noted that the propagation speed of electromagnetic waves is It is common sense in physics, using the propagation speed of electromagnetic waves , combined with the pre-assumed distance between the partial discharge signal source and the first measuring point , the time delay corresponding to the first measuring point and the second measuring point can be determined.

[0095] In some examples, the time delay corresponding to the first measurement point is , the time delay corresponding to the second measuring point is , and The expression of can be seen in formula (4).

[0096] (4)

[0097] S206: Determine a full-time parameter based on the first duration sequence and the second duration sequence.

[0098] Among them, when obtaining the first duration sequence and the second duration sequence After that, the full time parameters can be calculated .

[0099] S207: Determine a partial discharge signal model of the measurement point pair based on the duration model and the full time parameters.

[0100] Among them, based on the full time parameters And the duration model , combined with the assumed input electromagnetic wave propagation attenuation per meter , establish the partial discharge signal model of the measuring point pair .

[0101] It should be noted that the partial discharge signal model of the measuring point pair Including the partial discharge signal model corresponding to the first measuring point , and the partial discharge signal model corresponding to the second measuring point .

[0102] In some examples, the local discharge signal model corresponding to the first measuring point The expression of can be seen in formula (5). The local discharge signal model corresponding to the second measuring point is The expression of can be seen in formula (6).

[0103] (5)

[0104] (6)

[0105] Optionally, the independent variable of the partial discharge signal model includes the interval distance between the partial discharge signal source and the first measuring point, or the interval distance between the partial discharge signal source and the second measuring point.

[0106] The above process S201-S207 can establish the local discharge signal model corresponding to the first measuring point and the second measuring point respectively based on the characteristic parameters of the local discharge signal, thereby providing a model basis for the subsequent adaptive positioning of the local discharge signal source.

[0107] like Figure 3 As shown, it is a flow chart of another intelligent positioning method of a UHF partial discharge signal source provided in an embodiment of the present application, including the following steps.

[0108] S301: Determine envelope characteristics of a partial discharge signal based on a partial discharge signal model.

[0109] Wherein, based on the partial discharge signal model, envelope detection of the partial discharge signal can be implemented to obtain the envelope characteristics of the partial discharge signal.

[0110] In some examples, the envelope feature can be understood as a curve reflecting the change in the amplitude of the partial discharge signal.

[0111] Optionally, the implementation process of determining the envelope characteristics of the partial discharge signal based on the partial discharge signal model can be found in Figure 4 The steps are shown and the corresponding explanations.

[0112] S302: Using a preset sum differential filter model, perform convolution processing on the envelope feature to obtain an energy focusing result of the envelope feature.

[0113] Among them, the filter half-order of the assumed input can be used , calculate the total order of the odd-order filter , and based on the total order of the filter, determine and differentiate the filter model .

[0114] In some examples, and the difference filter model The expression of can be seen in formula (9).

[0115] (9)

[0116] It should be noted that the difference filter model is used , for the envelope characteristics Convolution processing can be performed to obtain the energy focusing result of the envelope feature. .

[0117] In some examples, the envelope feature It is a discrete partial discharge signal and can be transmitted through a continuous partial discharge signal. Transformed to get, specifically, Transformed into The process can be seen in formula (10).

[0118] (10)

[0119] In some examples, the difference filter model can be With envelope characteristics Multiply to get the energy focusing result of the envelope feature , energy focusing results The expression of can be seen in formula (11).

[0120] (11)

[0121] It should be noted that the energy focusing results Including the energy focusing result corresponding to the first measurement point , and the energy focusing result corresponding to the second measuring point .

[0122] S303: performing module value calculation on the energy focusing result to obtain the energy focusing result of the partial discharge signal at the starting moment.

[0123] Among them, the energy focusing result of obtaining the envelope characteristics Afterwards, the energy focusing results can be Perform modulus calculation to obtain the energy focusing result of the partial discharge signal at the starting time .

[0124] In some examples, the energy focusing results The process of calculating the modulus value can be seen in formula (12).

[0125] (12)

[0126] It should be emphasized that the energy focus at the beginning Including the energy focusing result of the local discharge signal collected at the first measuring point at the starting time , and the energy focusing result of the partial discharge signal collected at the second measuring point at the starting time .

[0127] The process shown in S301-S303 above can utilize the partial discharge signal model to obtain the energy focusing result of the partial discharge signal at the starting moment, thereby providing a model basis for subsequent adaptive positioning of the partial discharge signal source.

[0128] like Figure 4 As shown, it is a flow chart of another intelligent positioning method of a UHF partial discharge signal source provided in an embodiment of the present application, including the following steps.

[0129] S401: Based on the partial discharge signal models corresponding to the first measuring point and the second measuring point, an improved Hilport transform of the partial discharge signal is obtained by solving.

[0130] Among them, based on the partial discharge signal model corresponding to the first measuring point , and the partial discharge signal model corresponding to the second measuring point , the improved Hilport transform of the partial discharge signal can be obtained .

[0131] In some examples, The expression of can be seen in formula (7).

[0132] (7)

[0133] S402: Based on the improved Hilport transform and in combination with the partial discharge signal, the envelope characteristics of the partial discharge signal are solved.

[0134] Among them, in the improved Hilport transform After that, combined with the partial discharge signal, the envelope characteristics of the partial discharge signal can be solved. .

[0135] In some examples, assume that the partial discharge signal is , then the envelope characteristic , Improved Hilport Transform And partial discharge signal The relationship between the three can be seen in formula (8).

[0136] (8)

[0137] It should be emphasized that the envelope characteristics of the partial discharge signal Including the envelope characteristics corresponding to the first measurement point , and the envelope characteristics corresponding to the second measuring point .

[0138] The process shown in S401-S402 above can determine the envelope characteristics of the partial discharge signal based on the partial discharge signal model, thereby providing effective support for the subsequent calculation of the energy focusing result.

[0139] like Figure 5 As shown, it is a flow chart of another intelligent positioning method of a UHF partial discharge signal source provided in an embodiment of the present application, including the following steps.

[0140] S501: Based on the energy focusing result at the starting moment, determine the signal peak positions corresponding to the first measuring point and the second measuring point respectively.

[0141] Among them, the energy focusing result at the starting time is obtained Afterwards, the energy focusing results can be , solve for the signal peak position , include as well as , Represents the signal peak position corresponding to the first measurement point, Represents the signal peak position corresponding to the second measuring point.

[0142] In some examples, the energy focusing result at the start time is , signal peak position And the signal amplitude There is a relationship between the three, and the signal peak position can be obtained by solving the relationship. Specifically, the relationship can be shown in formula (13).

[0143] (13)

[0144] It should be noted that the signal amplitude Including the amplitude of the first measuring point And the amplitude of the second measuring point .

[0145] S502: Determine the number of starting points of the partial discharge signal based on the signal peak positions corresponding to the first measuring point and the second measuring point.

[0146] Among them, the signal peak position corresponding to the first measurement point is obtained , and the signal peak position corresponding to the second measurement point After that, we can calculate and The absolute value of the difference between them is used to obtain the starting point number of the partial discharge signal.

[0147] In some examples, the signal peak position It can represent the starting point number of the partial discharge signal collected at the first measuring point and the signal peak position It can represent the starting point number of the partial discharge signal collected by the second measuring point. , as well as The relationship between the three can be seen in formula (14).

[0148] (14)

[0149] S503: Determine, based on the number of starting points, a time delay difference between the first measuring point and the second measuring point when collecting partial discharge signals.

[0150] Among them, the number of starting points based on the partial discharge signal , determine the time delay difference when collecting partial discharge signals at the first measuring point and the second measuring point.

[0151] The process shown in S501-S503 above can use the energy focusing result at the starting time to determine the time delay difference when the first measuring point and the second measuring point collect the partial discharge signal, thereby providing a model basis for the subsequent adaptive positioning of the partial discharge signal source.

[0152] like Figure 6 As shown, it is a flow chart of another intelligent positioning method of a UHF partial discharge signal source provided in an embodiment of the present application, including the following steps.

[0153] S601: Determine the number of interval points between the first measuring point and the second measuring point based on the interval distance between the first measuring point and the second measuring point in combination with the sampling frequency of the partial discharge signal and the electromagnetic wave propagation speed.

[0154] Among them, the distance between the first measuring point and the second measuring point It can be obtained by measuring and combining the sampling frequency and the speed of electromagnetic wave propagation , the number of interval points between the first measuring point and the second measuring point can be calculated .

[0155] In some examples, The calculation expression of can be found in formula (15).

[0156] (15)

[0157] S602: Determine the interval distance between the partial discharge signal source and the first measuring point based on the number of interval points, the electromagnetic wave propagation speed, and the number of starting points corresponding to the time delay difference.

[0158] Among them, based on the interval points , Electromagnetic wave propagation speed And the starting point number corresponding to the delay difference , the interval distance between the partial discharge signal source and the first measuring point can be calculated, and based on the interval distance between the partial discharge signal source and the first measuring point, the reference position of the partial discharge signal source is determined. .

[0159] In some examples, the reference position The calculation expression of can be seen in formula (16).

[0160] (16)

[0161] S603: Determine a reference position of the partial discharge signal source based on the interval distance between the partial discharge signal source and the first measuring point.

[0162] Wherein, after the reference position of the partial discharge signal source is determined based on the interval distance between the partial discharge signal source and the first measuring point, the reference position can realize effective positioning of the partial discharge signal source.

[0163] The process shown in S601-S603 above can use the time delay difference to calculate the reference position of the partial discharge signal source, eliminating the random error caused by manual positioning, and laying a theoretical foundation for the analysis of the ultra-high frequency partial discharge signal source on site and the judgment of equipment operation.

[0164] like Figure 7 As shown, it is a schematic diagram of the architecture of an intelligent positioning device for a UHF partial discharge signal source provided in an embodiment of the present application, including the units shown below.

[0165] The model determination unit 100 is used to determine the partial discharge signal model of a measuring point pair based on characteristic parameters of the partial discharge signal; the measuring point pair includes a first measuring point and a second measuring point that are adjacent in position.

[0166] Optionally, the model determination unit 100 is specifically used to: obtain characteristic parameters of the local discharge signal; the characteristic parameters include pulse width, sampling frequency, oscillation frequency, and voltage amplitude; determine a first duration sequence based on the pulse width and the sampling frequency; determine a duration model of the local discharge signal based on the first duration sequence in combination with the oscillation frequency and the voltage amplitude; obtain the interval distance between the first measuring point and the second measuring point in the measuring point pair; determine a second duration sequence corresponding to the duty cycle of the local discharge signal based on the interval distance between the first measuring point and the second measuring point and the sampling frequency; determine the full time parameters based on the first duration sequence and the second duration sequence; and determine the local discharge signal model of the measuring point pair based on the duration model and the full time parameters.

[0167] The energy focusing unit 200 is used to obtain the energy focusing result of the local discharge signal at the starting time based on the local discharge signal model; the energy focusing result represents the peak value of the local discharge signal.

[0168] Optionally, the energy focusing unit 200 is specifically used to: determine the envelope characteristics of the local discharge signal based on the local discharge signal model; use a preset sum differential filter model to convolve the envelope characteristics to obtain an energy focusing result of the envelope characteristics; perform modulus calculation on the energy focusing result to obtain the energy focusing result of the local discharge signal at the starting time.

[0169] Optionally, the energy focusing unit 200 is specifically used to: solve an improved Hilport transform of the local discharge signal based on the local discharge signal models corresponding to the first measuring point and the second measuring point respectively; and solve an envelope feature of the local discharge signal based on the improved Hilport transform in combination with the local discharge signal.

[0170] The position determination unit 300 is used to determine the reference position of the partial discharge signal source based on the energy focusing result at the starting moment.

[0171] Optionally, the position determination unit 300 is specifically used to: determine the time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal based on the energy focusing result at the starting moment; and determine the reference position of the partial discharge signal source based on the time delay difference.

[0172] Optionally, the position determination unit 300 is specifically used to: determine the signal peak positions corresponding to the first measuring point and the second measuring point based on the energy focusing result at the starting moment; determine the starting point number of the local discharge signal based on the signal peak positions corresponding to the first measuring point and the second measuring point; determine the time delay difference when the first measuring point and the second measuring point collect the local discharge signal based on the starting point number.

[0173] Optionally, the position determination unit 300 is specifically used to: determine the number of interval points between the first measuring point and the second measuring point based on the interval distance between the first measuring point and the second measuring point, in combination with the sampling frequency of the local discharge signal and the electromagnetic wave propagation speed; determine the interval distance between the local discharge signal source and the first measuring point based on the number of interval points, the electromagnetic wave propagation speed and the number of starting points corresponding to the time delay difference; and determine the reference position of the local discharge signal source based on the interval distance between the local discharge signal source and the first measuring point.

[0174] The above-mentioned units can realize the intelligent positioning of the UHF partial discharge signal source, eliminate the random errors caused by manual positioning, and lay a theoretical foundation for the analysis of the partial discharge signal source and the judgment of equipment operation.

[0175] The present application also provides a computer-readable storage medium, which includes a stored program, wherein the program executes the intelligent positioning method for the ultra-high frequency partial discharge signal source provided by the present application.

[0176] The present application also provides an electronic device, including: a processor, a memory and a bus. The processor and the memory are connected via a bus, the memory is used to store programs, and the processor is used to run the programs, wherein when the programs are run, the intelligent positioning method for ultra-high frequency partial discharge signal sources provided by the present application is executed.

[0177] In addition, the functions described above in the embodiments of the present application may be at least partially performed by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), etc.

[0178] Although several specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present application. Certain features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0179] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. An intelligent positioning method for a UHF partial discharge signal source, characterized in that: include: Determining a partial discharge signal model of a pair of measuring points based on characteristic parameters of the partial discharge signal; the pair of measuring points includes a first measuring point and a second measuring point that are adjacent in position; Based on the local discharge signal model, obtaining an energy focusing result of the local discharge signal at a starting time; the energy focusing result represents a peak value of the local discharge signal; Based on the energy focusing result at the starting moment, a reference position of the local discharge signal source is determined.

2. The method according to claim 1, characterized in that Based on the characteristic parameters of the partial discharge signal, the partial discharge signal model of the measuring point pair is determined, including: Obtaining characteristic parameters of a partial discharge signal; the characteristic parameters include pulse width, sampling frequency, oscillation frequency, and voltage amplitude; Determining a first duration sequence based on the pulse width and the sampling frequency; Determine a duration model of the partial discharge signal based on the first duration sequence in combination with the oscillation frequency and the voltage amplitude; Obtaining the interval distance between the first measuring point and the second measuring point in the measuring point alignment; Determining a second duration sequence corresponding to the duty cycle of the partial discharge signal based on the interval distance between the first measuring point and the second measuring point and the sampling frequency; determining a full-time parameter based on the first duration sequence and the second duration sequence; Based on the duration model and the full-time parameter, a partial discharge signal model of the pair of measurement points is determined.

3. The method according to claim 1, characterized in that Based on the local discharge signal model, obtaining an energy focusing result of the local discharge signal at a starting time includes: Based on the partial discharge signal model, determining envelope characteristics of the partial discharge signal; Using a preset sum differential filter model, convolution processing is performed on the envelope feature to obtain an energy focusing result of the envelope feature; A modulus calculation is performed on the energy focusing result to obtain the energy focusing result of the local discharge signal at the starting moment.

4. The method according to claim 3, characterized in that Determining an envelope feature of the partial discharge signal based on the partial discharge signal model includes: Based on the partial discharge signal models corresponding to the first measuring point and the second measuring point, respectively, solving and obtaining an improved Hilport transform of the partial discharge signal; Based on the improved Hilport transform and in combination with the partial discharge signal, the envelope characteristics of the partial discharge signal are obtained by solving.

5. The method according to claim 1, characterized in that Determining a reference position of a local discharge signal source based on the energy focusing result at the starting time includes: Based on the energy focusing result at the starting time, determining the time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal; Based on the time delay difference, a reference position of the partial discharge signal source is determined.

6. The method according to claim 5, characterized in that Determining the time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal based on the energy focusing result at the starting time includes: Based on the energy focusing result at the starting time, determining the signal peak positions corresponding to the first measuring point and the second measuring point respectively; Determining the number of starting points of the partial discharge signal based on the signal peak positions corresponding to the first measuring point and the second measuring point respectively; Based on the number of starting points, a time delay difference between the first measuring point and the second measuring point when collecting the partial discharge signal is determined.

7. The method according to claim 6, characterized in that Determining a reference position of a partial discharge signal source based on the time delay difference includes: Based on the interval distance between the first measuring point and the second measuring point, combined with the sampling frequency of the partial discharge signal and the propagation speed of the electromagnetic wave, determining the number of interval points between the first measuring point and the second measuring point; Determine the interval distance between the partial discharge signal source and the first measuring point based on the number of interval points, the electromagnetic wave propagation speed, and the number of starting points corresponding to the time delay difference; A reference position of the partial discharge signal source is determined based on the interval distance between the partial discharge signal source and the first measuring point.

8. An intelligent positioning device for ultra-high frequency partial discharge signal source, characterized in that: include: A model determination unit, configured to determine a partial discharge signal model of a pair of measuring points based on characteristic parameters of the partial discharge signal; the pair of measuring points comprises a first measuring point and a second measuring point that are adjacent in position; An energy focusing unit, used for obtaining an energy focusing result of the local discharge signal at a starting time based on the local discharge signal model; the energy focusing result represents a peak value of the local discharge signal; The position determination unit is used to determine the reference position of the partial discharge signal source based on the energy focusing result at the starting moment.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein the program, when executed by a processor, executes the intelligent positioning method for a UHF partial discharge signal source according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: processor, memory, and bus; The processor is connected to the memory via the bus; The memory is used to store programs, and the processor is used to run programs, wherein the program, when run by the processor, executes the intelligent positioning method for ultra-high frequency partial discharge signal sources according to any one of claims 1 to 7.

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