Substation insulator pollution flashover monitoring method and device, electronic equipment and storage medium

Abstract

The invention discloses a transformer substation insulator pollution flashover monitoring method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring pollution flashover sound wave data of a target monitoring insulator, and filtering the pollution flashover sound wave data to obtain target sound wave data; target environment data of the environment where the target monitoring insulator is located are determined, and the target environment data comprise at least one of equivalent salt density data, temperature and humidity data and air dust content data; performing pollution flashover evaluation on the input target sound wave data and target environment data through a pollution flashover evaluation model to obtain a target pollution flashover level; and taking the target pollution flashover grade as a pollution flashover monitoring result corresponding to the target monitoring insulator. Pollution flashover monitoring is carried out on the insulator from multiple dimensions (sound waves and environment), and the accuracy of pollution flashover monitoring of the insulator of the transformer substation is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a method, device, electronic equipment and storage medium for monitoring pollution flashover of insulators in a substation. Background Art

[0002] As the scale of power transmission in substations expands, more and more attention is paid to the pollution flashover of insulators in substations. When serious pollution flashover occurs, it is difficult to reclose the power system of the substation, which will lead to large-scale and long-term power outages, causing immeasurable losses.

[0003] In the related art, pollution flashover monitoring is usually performed by analyzing the insulator current or voltage, so as to provide pollution flashover monitoring warnings when the current or voltage is abnormal. However, false pollution flashover warnings usually occur. Therefore, the accuracy of pollution flashover monitoring for substation insulators is currently poor. Summary of the invention

[0004] The present invention provides a method, a device, an electronic device and a storage medium for monitoring pollution flashover of insulators in a substation, so as to solve the problem that the accuracy of monitoring pollution flashover of insulators in a substation is poor.

[0005] According to one aspect of the present invention, a method for monitoring flashover of insulators in a substation is provided, wherein the method comprises:

[0006] Collecting pollution flashover acoustic wave data of target monitoring insulators, filtering the pollution flashover acoustic wave data, and obtaining target acoustic wave data;

[0007] Determine target environmental data of the environment where the target monitored insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data;

[0008] Performing pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level, wherein the pollution flashover assessment model is obtained by training a support vector machine through a training sample set;

[0009] The target pollution flashover level is used as the pollution flashover monitoring result corresponding to the target monitoring insulator.

[0010] According to another aspect of the present invention, a substation insulator flashover monitoring device is provided, wherein the device comprises:

[0011] A pollution flashover acoustic wave processing module is used to collect pollution flashover acoustic wave data of target monitoring insulators, filter the pollution flashover acoustic wave data, and obtain target acoustic wave data;

[0012] An environmental data determination module, used to determine target environmental data of the environment where the target monitoring insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data;

[0013] A pollution flashover assessment module, used for performing pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level, wherein the pollution flashover assessment model is obtained by training a support vector machine through a training sample set;

[0014] A monitoring result determination module is used to use the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the substation insulator flashover monitoring method described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the substation insulator flashover monitoring method described in any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention collects the pollution flashover acoustic wave data of the target monitoring insulator, filters the pollution flashover acoustic wave data, and obtains the target acoustic wave data; determines the target environmental data of the environment where the target monitoring insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data; performs pollution flashover evaluation on the input target acoustic wave data and the target environmental data through a pollution flashover evaluation model to obtain a target pollution flashover level, wherein the pollution flashover evaluation model is obtained by training a support vector machine with a training sample set; and uses the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator. The present invention performs pollution flashover monitoring on insulators from multiple dimensions (acoustic waves and environment), which can improve the accuracy of pollution flashover monitoring of substation insulators.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is a flow chart of a method for monitoring flashover of insulators in a substation according to Embodiment 1 of the present invention;

[0024] Figure 2 is a flow chart of a method for monitoring flashover of insulators in a substation according to a second embodiment of the present invention;

[0025] Figure 3 This is an architecture diagram of a substation insulator flashover monitoring system provided according to an embodiment of the present invention;

[0026] Figure 4 is an overall flow chart of a method for monitoring pollution flashover of insulators in a substation provided according to an embodiment of the present invention;

[0027] Figure 5 2 is a schematic diagram of the structure of a substation insulator flashover monitoring device provided according to Embodiment 3 of the present invention;

[0028] Figure 6 The invention is a schematic diagram of the structure of an electronic device for implementing the method for monitoring flashover of insulators in a substation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 A flowchart of a method for monitoring pollution flashover of substation insulators is provided for the first embodiment of the present invention. This embodiment is applicable to the case where pollution flashover monitoring of substation insulators is performed by evaluating the pollution flashover level. The method can be performed by a pollution flashover monitoring device for substation insulators. The pollution flashover monitoring device for substation insulators can be implemented in the form of hardware and / or software. The pollution flashover monitoring device for substation insulators can be configured in a computer. Figure 1 As shown, the method includes:

[0033] S110, collecting pollution flashover acoustic wave data of target monitoring insulators, filtering the pollution flashover acoustic wave data, and obtaining target acoustic wave data.

[0034] The target monitoring insulator can be understood as the target insulator for flashover monitoring in the substation. It should be understood that the insulator in the substation has the probability of flashover accidents, and the occurrence of flashover accidents will seriously affect the safe operation of the substation.

[0035] Specifically, the collecting of the pollution flashover acoustic wave data of the target monitoring insulator may include: when the pollution flashover phenomenon occurs in the target monitoring insulator, collecting the pollution flashover acoustic wave data of the target monitoring insulator through an acoustic wave sensor. The acoustic wave sensor may be used to collect the acoustic waves generated when the pollution flashover phenomenon occurs in the insulator.

[0036] The pollution flashover acoustic wave data can be understood as the data of the acoustic wave generated when the pollution flashover phenomenon occurs in the target monitoring insulator. Optionally, the pollution flashover acoustic wave data may include at least one of the amplitude, period, frequency, phase and wavelength of the pollution flashover acoustic wave.

[0037] The target sound wave data can be understood as the dirty flash sound wave data after filtering.

[0038] Optionally, filtering the pollution flash acoustic wave data includes:

[0039] The pollution flash acoustic wave data is filtered using a Kalman filter algorithm.

[0040] The Kalman filter algorithm can be understood as a recursive filter algorithm.

[0041] In an embodiment of the present invention, the Kalman filtering algorithm can be used to clean the pollution flash sound wave data and remove sound data irrelevant to the pollution flash phenomenon. Compared with the pollution flash sound wave data that has not been filtered, the target sound wave data has better feature expression capabilities.

[0042] S120. Determine target environmental data of the environment where the target monitored insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data.

[0043] The target environment data may characterize the characteristics of the environment in which the target monitored insulator is located.

[0044] The equivalent salt density data may represent the degree of contamination of the environment in which the target monitored insulator is located. In an embodiment of the present invention, the equivalent salt density data may be an equivalent salt density value.

[0045] The temperature and humidity data may represent the speed of change of the temperature and humidity of the environment where the target monitoring insulator is located. In an embodiment of the present invention, the temperature and humidity data may represent the value of the speed of change of the temperature and humidity.

[0046] The air dust content data may represent the air dust content of the environment in which the target monitoring insulator is located. In the embodiment of the present invention, the air dust content data may be a value representing the air dust content.

[0047] In an embodiment of the present invention, the target environment data is collected by a sensor.

[0048] Optionally, the determining target environment data of the environment where the target monitoring insulator is located includes:

[0049] Determine the acoustic wave collection time period of the pollution flashover acoustic wave data, and determine the actual equivalent salt density of the environment where the target monitoring insulator is located within the acoustic wave collection time period;

[0050] A preset standard equivalent salt density is determined, and the equivalent salt density data is determined according to the acoustic wave acquisition time period, the actual equivalent salt density, and the standard equivalent salt density.

[0051] The acoustic wave collection time period may be understood as a collection time period for the pollution flash acoustic wave data.

[0052] The actual equivalent salt density can be understood as the actual equivalent salt density of the environment where the target monitoring insulator is located. In the embodiment of the present invention, the specific method for determining the actual equivalent salt density is not specifically limited here.

[0053] The standard equivalent salt density can be understood as the standard equivalent salt density, can also be understood as the normal equivalent salt density of the environment where the target monitoring insulator is located, and can also be understood as a parameter for calculating the equivalent salt density. In an embodiment of the present invention, the standard equivalent salt density can be determined based on the historical equivalent salt density of the environment where the target monitoring insulator is located when no pollution flashover has occurred in the past.

[0054] Specifically, the determining of the equivalent salt density data according to the acoustic wave acquisition time period, the actual equivalent salt density, and the standard equivalent salt density can be implemented based on the following formula:

[0055]

[0056] in, represents the equivalent salt density data, ΔT represents the acoustic wave acquisition time period, ρ0(T) represents the standard equivalent salt density, and ρ1(T) represents the actual equivalent salt density.

[0057] In the embodiment of the present invention, the sound wave collection time period may also be the sound wave collection frequency.

[0058] Optionally, the determining target environment data of the environment where the target monitoring insulator is located includes:

[0059] Determine a first temperature and humidity value and a second temperature and humidity value of the environment where the target monitoring insulator is located within the acoustic wave collection time period;

[0060] The temperature and humidity data are determined according to the sound wave collection time period, the first temperature and humidity value, and the second temperature and humidity value.

[0061] The first temperature and humidity value may be the maximum value of the temperature and humidity. The second temperature and humidity value may be the minimum value of the temperature and humidity. In the embodiment of the present invention, the first temperature and humidity value and the second temperature and humidity value may be different or the same.

[0062] Specifically, the determining of the temperature and humidity data according to the sound wave collection time period, the first temperature and humidity value, and the second temperature and humidity value may be implemented based on the following formula:

[0063]

[0064] in, represents the temperature and humidity data, ΔT represents the acoustic wave collection time period, h max (T) represents the first temperature and humidity value, h min (T) represents the second temperature and humidity value.

[0065] Optionally, the determining target environment data of the environment where the target monitoring insulator is located includes:

[0066] Determine the dust content at each target moment in the environment where the target monitoring insulator is located during the acoustic wave collection time period;

[0067] The air dust content data is determined according to a plurality of the sub-dust contents.

[0068] The dust content of the insulator can be understood as the dust content of the air in the environment where the target monitored insulator is located at the target moment.

[0069] Specifically, the determining of the air dust content data according to the plurality of sub-dust contents can be implemented based on the following formula:

[0070]

[0071] in, Indicates the air dust content data, C i Indicates the dust content in the air at the target time i.

[0072] The technical solution of the above embodiment uses the target environmental data (at least one of the equivalent salt density data, temperature and humidity data, and air dust content data) that affects the severity of pollution flashover as reference data for pollution flashover assessment of target monitored insulators, which can effectively improve the accuracy of pollution flashover level assessment.

[0073] S130. Perform pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level, wherein the pollution flashover assessment model is obtained by training a support vector machine through a training sample set.

[0074] The target pollution flashover level can be understood as the level of pollution flashover phenomenon occurring in the target monitoring insulator. Optionally, the target pollution flashover level can represent the severity of the pollution flashover phenomenon. Exemplarily, the target pollution flashover level can include mild level 1, moderate level 2, and severe level 3.

[0075] The training sample set can be understood as a collection of training samples.

[0076] The support vector machine can be understood as a binary classification model.

[0077] The pollution flashover assessment model can be understood as a model with a specific pollution flashover level assessment function. The pollution flashover assessment model can assess the severity of the pollution flashover phenomenon based on the pollution flashover acoustic wave data collected when the pollution flashover phenomenon occurs on the target monitoring insulator and the target environmental data of the environment where the target monitoring insulator is located, and obtain the target pollution flashover level corresponding to the pollution flashover phenomenon.

[0078] S140. Use the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitored insulator.

[0079] The technical solution of the embodiment of the present invention can collect the pollution flashover acoustic wave data of the target monitoring insulator in real time based on the preset data collection frequency and determine the target environmental data of the environment where the target monitoring insulator is located in real time, so as to realize real-time pollution flashover monitoring of substation insulators.

[0080] The pollution flashover monitoring result can be understood as the result of the pollution flashover monitoring of the substation insulators.

[0081] Optionally, after taking the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator, the method further includes:

[0082] Determine the preset early warning pollution flashover level;

[0083] When the target pollution flashover level exceeds the warning pollution flashover level, a warning is issued on the pollution flashover monitoring result through a target warning device.

[0084] The warning pollution flashover level can be understood as a pollution flashover level used for warning judgment. In the embodiment of the present invention, the warning pollution flashover level can be preset according to the scene requirements and is not specifically limited here. Optionally, the warning pollution flashover level can be moderate level 2 or severe level 3, etc.

[0085] Specifically, taking the warning pollution flashover level as the severe level 3 as an example, when the target pollution flashover level is the mild level 1 or the moderate level 2, no warning is issued; when the target pollution flashover level is the severe level 3, a warning is issued.

[0086] The target warning device can be understood as a device with a warning function. In the embodiment of the present invention, the target warning device can be preset according to the scene requirements, and is not specifically limited here.

[0087] The technical solution of the embodiment of the present invention collects the pollution flashover acoustic wave data of the target monitoring insulator, filters the pollution flashover acoustic wave data, and obtains the target acoustic wave data; determines the target environmental data of the environment where the target monitoring insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data; performs pollution flashover evaluation on the input target acoustic wave data and the target environmental data through a pollution flashover evaluation model to obtain a target pollution flashover level, wherein the pollution flashover evaluation model is obtained by training a support vector machine with a training sample set; and uses the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator. The present invention performs pollution flashover monitoring on insulators from multiple dimensions (acoustic waves and environment), which can improve the accuracy of pollution flashover monitoring of substation insulators.

[0088] Embodiment 2

[0089] Figure 2 The flowchart of a method for monitoring pollution flashover of insulators in a substation provided in the second embodiment of the present invention is an addition to the pollution flashover assessment of the input target acoustic wave data and the target environmental data by the pollution flashover assessment model described in the above embodiment. Figure 2 As shown, the method includes:

[0090] S210, obtaining the training sample set, wherein the training sample set includes a plurality of training samples and a sample label corresponding to each of the training samples, and the training samples include pollution flash acoustic wave samples and sample environment data corresponding to the pollution flash acoustic wave samples.

[0091] The training samples may be understood as samples for training the support vector machine.

[0092] The sample label can be understood as the label of the training sample. The sample label can represent the real pollution flashover level of the training sample.

[0093] The pollution flash sound wave sample can be understood as sample data of the pollution flash sound wave. The pollution flash sound wave sample can be sample data of the pollution flash sound wave collected historically.

[0094] The sample environmental data may be understood as environmental data corresponding to the pollution flash acoustic wave sample.

[0095] Optionally, the sample environment data includes at least one of sample equivalent salt density, sample temperature and humidity, and sample dust content.

[0096] In the embodiment of the present invention, the method for determining the sample environment data may be consistent with the method for determining the target environment data in the above embodiment, and will not be described in detail here.

[0097] S220: For each of the training samples, perform pollution flashover assessment on the input pollution flashover acoustic wave sample and the sample environmental data by using the pre-constructed support vector machine to obtain a sample pollution flashover level.

[0098] The sample pollution flashover level may be understood as the pollution flashover level obtained by performing pollution flashover evaluation on training samples using the support vector machine.

[0099] S230. Determine an assessment loss value according to the sample pollution flashover level and the sample label, and adjust the model parameters of the support vector machine based on the assessment loss value to obtain the pollution flashover assessment model.

[0100] The evaluation loss value may be understood as the loss value between the sample pollution flashover level and the sample label.

[0101] The pollution flashover assessment model obtained by training a support vector machine using a training sample set is further described as follows:

[0102] The support vector machine can seek the best parameters between the complexity of the model (i.e., the learning accuracy for a specific training sample) and the learning ability (i.e., the ability to identify any training sample without error) based on limited training samples to obtain the best generalization ability. The training sample set can be as follows:

[0103] L={(x1,y1,s1),(x2,y2,s2),…,(x n ,y n ,s n )}

[0104] stx i ∈R N ,y i ∈{-1,1},(i=1,…,n)

[0105] Among them, x i represents the training samples (including the pollution flash sound wave samples after filtering and the quantitative index values ​​of the sample environment data); y i Indicates the sample label (real pollution flashover level); s i Indicates fuzzy membership (preset according to scene requirements), s i Not zero; ε≤s i ≤1,ε represents an arbitrarily small positive number, R N Represents an N-dimensional Gaussian feature space, and n represents the number of training samples (e.g., 30 days in a month, 24 hours).

[0106] The calculation formula related to the support vector machine can be as follows:

[0107]

[0108] Among them, ω represents the classification interface vector; ξ i represents the relaxation factor; C represents the penalty factor; b represents the classification threshold; Indicates the mapping from input space to high-dimensional space. Among them, the relaxation factor / penalty factor / classification threshold is set according to the actual model training situation and is not specifically limited here. If the above quantitative indicator values ​​are entered, the values ​​of different geographical locations can be different.

[0109] For the test sample, we can calculate:

[0110]

[0111] Here, α represents the Lagrange multiplier.

[0112] The weighted feature function is as follows:

[0113]

[0114] in, Represents the weight of the kth feature, which can be set according to the geographical location.

[0115] S240, collecting pollution flashover acoustic wave data of target monitoring insulators, filtering the pollution flashover acoustic wave data, and obtaining target acoustic wave data.

[0116] The following further describes the filtering of the pollution flash acoustic wave data by the Kalman filter algorithm to obtain the target acoustic wave data:

[0117] The Kalman filter algorithm is used to process the collected pollution flash acoustic wave data to improve the feature representation ability of the data. Kalman filtering is a recursive filter that uses the recursion of output values ​​and input values ​​to calculate and update the minimum mean square error estimate of the state. The key process is the establishment of the state equation and the measurement equation. The relevant calculation formula of the Kalman filter algorithm is explained as follows:

[0118] The state estimation equation is as follows:

[0119]

[0120] in, Represents the state quantity of the system; c k-1 A represents the input of the system at time k-1 (i.e., the pollution flash acoustic wave data); k-1 Represents the state transfer matrix (according to different moments The state transfer matrix composed of values) k-1Represents the control input matrix (a matrix input according to the actual situation on site. For example, if data needs to be collected every day in winter, the value in the matrix is ​​1. If data does not need to be collected on a certain day, the value in the matrix is ​​0).

[0121] The formula for calculating the error covariance matrix is ​​as follows:

[0122]

[0123] Among them, P k∣k-1 Represents the error covariance matrix, through the above A k-1 Can be obtained; matrix Q k-1 Represents the system noise of Gaussian white noise (a constant set according to the actual situation on site).

[0124] The formula for calculating the Kalman gain is as follows:

[0125]

[0126] Among them, K k represents the Kalman gain; C k Represents the observation matrix of the system (the observation matrix is ​​the above c k-1 The matrix composed of input quantities); R k Represents observation noise (a constant set according to actual on-site conditions).

[0127] The formula for calculating the measurement update for the state estimate is as follows:

[0128]

[0129] Among them, D k represents the control output matrix (which is the same as the control input matrix B k Corresponding, input and output correspond one to one).

[0130] The formula for calculating the measurement update of the error covariance matrix is ​​as follows:

[0131] P k =(IK k C k ) k∣k-1

[0132] Where I represents the identity matrix.

[0133] S250, determining target environmental data of the environment where the target monitored insulator is located.

[0134] S260. Perform pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level.

[0135] S270. Use the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitored insulator.

[0136] The technical solution of the embodiment of the present invention is to obtain the training sample set, wherein the training sample set includes multiple training samples and sample labels corresponding to each training sample, and the training samples include pollution flashover acoustic wave samples and sample environmental data corresponding to the pollution flashover acoustic wave samples; for each training sample, the input pollution flashover acoustic wave samples and the sample environmental data are evaluated for pollution flashover by the pre-constructed support vector machine to obtain the sample pollution flashover level; the evaluation loss value is determined according to the sample pollution flashover level and the sample label, and the model parameters of the support vector machine are adjusted based on the evaluation loss value to obtain the pollution flashover evaluation model. The effect of training a pollution flashover evaluation model with high pollution flashover evaluation accuracy is achieved.

[0137] Figure 3 1 is an architecture diagram of a substation insulator flashover monitoring system provided according to an embodiment of the present invention. Figure 3 As shown, in an environment where electromagnetic interference is serious in a substation, an optocoupler isolation chip is used. Through the optocoupler isolation chip, the external electromagnetic interference damage is blocked to protect the controller; the sound change data (i.e., the pollution flashover sound wave data) generated by the relevant power equipment in the substation due to pollution flashover is automatically detected by a sound collector (i.e., the sound wave sensor), so that the collected relevant data is transmitted to the controller module. In order to ensure that the collected sound data better reflects the pollution flashover of the power equipment, multiple collection sensors can be installed next to the power equipment, and the collected pollution flashover sound wave data can be transmitted through wireless communication; the system of the present invention has the function of wireless communication, and can transmit real-time data to the relevant staff terminal. Key input can be used to adjust the required relevant parameters of the system; the data can be transmitted back to the background, and solved through relevant models, so as to realize the early warning of the pollution flashover changes of the power equipment, and provide the staff with pollution flashover sound information and early warning signals in time; the present invention uses solar power supply technology, and solar radiation can be directly converted into electrical energy through solar panels to realize the system power supply of the present invention.

[0138] Figure 4 FIG. 1 is an overall flow chart of a method for monitoring flashover of insulators in a substation according to an embodiment of the present invention. Figure 3 and Figure 4 As shown, specifically, the overall process of the substation insulator flashover monitoring method can be:

[0139] Using the sound collector and controller as the hardware basis, the pollution flashover information is collected through the collection module;

[0140] The analysis shows that the severity of pollution flashover is related to factors such as equivalent salt density, ambient temperature and humidity, and air dust, and corresponding quantitative indicators are constructed.

[0141] By analyzing the characteristics of acoustic signals of insulator pollution flashover discharge, it is determined that there is a correlation between acoustic signals and insulator pollution flashover.

[0142] Use Kalman filter algorithm to improve the anti-interference ability of the acquisition device;

[0143] Combined with improved support vector machine to accurately classify processed sound signals;

[0144] Realize accurate identification of the sound signal of pollution flashover and precise assessment of the degree of pollution flashover of insulators.

[0145] The present invention can improve the reliability of substation equipment operation and the work efficiency of staff, and reduce the occurrence rate of pollution flashover accidents.

[0146] Embodiment 3

[0147] Figure 5 This is a schematic diagram of the structure of a substation insulator flashover monitoring device provided by the third embodiment of the present invention. Figure 5 As shown, the device includes: a pollution flashover acoustic wave processing module 310, an environmental data determination module 320, a pollution flashover assessment module 330 and a monitoring result determination module 340.

[0148] Among them, the pollution flashover acoustic wave processing module 310 is used to collect the pollution flashover acoustic wave data of the target monitoring insulator, filter the pollution flashover acoustic wave data, and obtain target acoustic wave data; the environmental data determination module 320 is used to determine the target environmental data of the environment where the target monitoring insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data; the pollution flashover assessment module 330 is used to perform pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level, wherein the pollution flashover assessment model is obtained by training a support vector machine with a training sample set; the monitoring result determination module 340 is used to use the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator.

[0149] The technical solution of the embodiment of the present invention collects the pollution flashover acoustic wave data of the target monitoring insulator, filters the pollution flashover acoustic wave data, and obtains the target acoustic wave data; determines the target environmental data of the environment where the target monitoring insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data; performs pollution flashover evaluation on the input target acoustic wave data and the target environmental data through a pollution flashover evaluation model to obtain a target pollution flashover level, wherein the pollution flashover evaluation model is obtained by training a support vector machine with a training sample set; and uses the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator. The present invention performs pollution flashover monitoring on insulators from multiple dimensions (acoustic waves and environment), which can improve the accuracy of pollution flashover monitoring of substation insulators.

[0150] Optionally, the pollution flash acoustic wave processing module includes: a filtering processing unit, which is specifically used to filter the pollution flash acoustic wave data through a Kalman filtering algorithm.

[0151] Optionally, the substation insulator pollution flashover monitoring device further includes: a warning level determination module and a pollution flashover warning module;

[0152] Wherein, the warning level determination module is used to determine a preset warning pollution flashover level after taking the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator;

[0153] The pollution flashover warning module is used to issue an early warning on the pollution flashover monitoring result through a target early warning device when the target pollution flashover level exceeds the early warning pollution flashover level.

[0154] Optionally, the substation insulator flashover monitoring device further includes: a sample acquisition module, a sample evaluation module and a model parameter adjustment module;

[0155] The sample acquisition module is used to acquire the training sample set before performing pollution flashover assessment on the input target acoustic wave data and the target environmental data through the pollution flashover assessment model, wherein the training sample set includes a plurality of training samples and a sample label corresponding to each training sample, and the training samples include pollution flashover acoustic wave samples and sample environmental data corresponding to the pollution flashover acoustic wave samples;

[0156] The sample evaluation module is used for performing pollution flashover evaluation on the input pollution flashover acoustic wave sample and the sample environmental data by using the pre-built support vector machine for each training sample to obtain a sample pollution flashover level;

[0157] The model parameter adjustment module is used to determine the assessment loss value according to the sample pollution flashover level and the sample label, and adjust the model parameters of the support vector machine based on the assessment loss value to obtain the pollution flashover assessment model.

[0158] Optionally, the substation insulator flashover monitoring device also includes: a sample determination module, used to determine the flashover sound wave sample before obtaining the training sample set, and determine the sample environmental data corresponding to the flashover sound wave sample, wherein the sample environmental data includes at least one of the sample equivalent salt density, sample temperature and humidity, and sample dust content.

[0159] Optionally, the sample determination module is specifically used to:

[0160] Determine a sample collection time period of the pollution flashover acoustic wave sample, and determine an actual equivalent salt density of the environment where the target monitoring insulator is located within the sample collection time period;

[0161] A preset standard equivalent salt density is determined, and the sample equivalent salt density is determined according to the sample collection time period, the actual equivalent salt density, and the standard equivalent salt density.

[0162] Optionally, the sample determination module is specifically used to:

[0163] Determine a first temperature and humidity value and a second temperature and humidity value of the environment where the target monitoring insulator is located within a sample collection time period;

[0164] The sample temperature and humidity are determined according to the sample collection time period, the first temperature and humidity value, and the second temperature and humidity value.

[0165] Optionally, the sample determination module is specifically used to:

[0166] Determine the dust content of the target monitoring insulator at each target moment in the environment within the sample collection period;

[0167] The sample dust content is determined based on a plurality of the sub-dust contents.

[0168] The substation insulator pollution flashover monitoring device provided in the embodiment of the present invention can execute the substation insulator pollution flashover monitoring method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0169] Embodiment 4

[0170] Figure 6A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0171] like Figure 6 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0172] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0173] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a substation insulator flashover monitoring method.

[0174] In some embodiments, the substation insulator pollution flashover monitoring method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the substation insulator pollution flashover monitoring method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the substation insulator pollution flashover monitoring method in any other appropriate manner (e.g., by means of firmware).

[0175] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0176] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0177] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0178] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0179] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0180] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0181] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0182] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring flashover of insulators in a substation, characterized in that: include: Collecting pollution flashover acoustic wave data of target monitoring insulators, filtering the pollution flashover acoustic wave data, and obtaining target acoustic wave data; Determine target environmental data of the environment where the target monitored insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data; Performing pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level, wherein the pollution flashover assessment model is obtained by training a support vector machine through a training sample set; The target pollution flashover level is used as the pollution flashover monitoring result corresponding to the target monitoring insulator.

2. The method according to claim 1, characterized in that The filtering process of the pollution flash acoustic wave data comprises: The pollution flash acoustic wave data is filtered using a Kalman filter algorithm.

3. The method according to claim 1, characterized in that After taking the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator, the method further includes: Determine the preset early warning pollution flashover level; When the target pollution flashover level exceeds the warning pollution flashover level, a warning is issued on the pollution flashover monitoring result through a target warning device.

4. The method according to claim 1, characterized in that: The determining of target environment data of the environment where the target monitoring insulator is located includes: Determine the acoustic wave collection time period of the pollution flashover acoustic wave data, and determine the actual equivalent salt density of the environment where the target monitoring insulator is located within the acoustic wave collection time period; A preset standard equivalent salt density is determined, and the equivalent salt density data is determined according to the acoustic wave acquisition time period, the actual equivalent salt density, and the standard equivalent salt density.

5. The method according to claim 1, characterized in that The determining of target environment data of the environment where the target monitoring insulator is located includes: Determine a first temperature and humidity value and a second temperature and humidity value of the environment where the target monitoring insulator is located within the acoustic wave collection time period; The temperature and humidity data are determined according to the sound wave collection time period, the first temperature and humidity value, and the second temperature and humidity value.

6. The method according to claim 1, characterized in that The determining of target environment data of the environment where the target monitoring insulator is located includes: Determine the dust content at each target moment in the environment where the target monitoring insulator is located during the acoustic wave collection time period; The air dust content data is determined according to a plurality of the sub-dust contents.

7. The method according to claim 1, characterized in that Before performing pollution flashover assessment on the input target acoustic wave data and the target environment data through the pollution flashover assessment model, the method further includes: Acquire the training sample set, wherein the training sample set includes a plurality of training samples and a sample label corresponding to each of the training samples, and the training samples include pollution flash acoustic wave samples and sample environment data corresponding to the pollution flash acoustic wave samples; For each of the training samples, the input pollution flashover acoustic wave samples and the sample environmental data are evaluated for pollution flashover by using the pre-constructed support vector machine to obtain the sample pollution flashover level; An assessment loss value is determined according to the sample pollution flashover level and the sample label, and the model parameters of the support vector machine are adjusted based on the assessment loss value to obtain the pollution flashover assessment model.

8. A substation insulator flashover monitoring device, characterized in that: include: A pollution flashover acoustic wave processing module is used to collect pollution flashover acoustic wave data of target monitoring insulators, filter the pollution flashover acoustic wave data, and obtain target acoustic wave data; An environmental data determination module, used to determine target environmental data of the environment where the target monitoring insulator is located, wherein the target environmental data includes at least one of equivalent salt density data, temperature and humidity data, and air dust content data; A pollution flashover assessment module, used for performing pollution flashover assessment on the input target acoustic wave data and the target environmental data through a pollution flashover assessment model to obtain a target pollution flashover level, wherein the pollution flashover assessment model is obtained by training a support vector machine through a training sample set; A monitoring result determination module is used to use the target pollution flashover level as the pollution flashover monitoring result corresponding to the target monitoring insulator.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the task processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the substation insulator flashover monitoring method according to any one of claims 1 to 7 when executed.

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