Method for monitoring state of drop-out fuse in alpine region

Abstract

The invention relates to the technical field of power equipment monitoring, and discloses a method for monitoring the state of a drop-out fuse in an alpine region. Comprising the steps of constructing a fuse distribution diagram, dividing a monitoring period into sub-sections, collecting comprehensive operation data of the drop-out fuse in the sub-sections, predicting a micro-motion state value of the next sub-section based on a neural network model, marking a fault point location in the fuse distribution diagram, and planning a maintenance path. Compared with the prior art, multi-dimensional data such as vibration, temperature, humidity, current and the like of the drop-out fuse are acquired, and the neural network model is combined to predict the operation state of the drop-out fuse in the future in advance, so that maintenance and replacement prompts can be given out before the drop-out fuse is about to fall off; therefore, an electric power maintainer can carry out maintenance and replacement operation on the drop-out fuse with a fault, and the hysteresis of maintenance and replacement after the drop-out fuse has a drop fault is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment monitoring, and more specifically, to a method for monitoring the state of a drop-out fuse in a high-cold region. Background Art

[0002] Drop-out fuses are the most commonly used short-circuit protection switches for 10kV distribution line branches and distribution transformers. However, in the actual operation of the power system, abnormal melting of high-voltage fuses in the distribution network often occurs, which seriously affects the safety and reliability of the power grid. Especially in the power system in high-altitude and cold areas, drop-out fuses will be affected by the harsh external environment, making drop-out fuses more prone to failure. Therefore, it is necessary to accurately monitor the operating status of drop-out fuses.

[0003] The patent application with reference publication number CN107238774B discloses a status monitoring system for drop-out fuses, which uses wireless communication technology for data transmission and control, avoiding the cable construction caused by traditional data transmission methods, greatly reducing the difficulty of construction and system installation costs. Through telemetry and telesignaling technology, maintenance personnel can query the operating status of drop-out fuses in real time on their mobile phones. Not only in hardware design, the whole machine has high shielding and high sealing design, and has good high temperature resistance and corrosion resistance, but also adopts methods such as watchdog circuit and equipotential grounding to enhance its anti-interference performance and effectively prevent system crashes; When the existing drop-out type fuse is being monitored, it is necessary to manually check the status of each fuse in the area one by one to find the fuse fault point and perform subsequent maintenance and replacement operations. Since the real-time monitoring of the fuse status can only analyze the current status of the fuse, when the fuse fault point is analyzed, the fuse has already dropped out, resulting in a lag in the subsequent fuse maintenance and replacement operations, which is not conducive to the safe and stable operation of the power system.

[0004] In view of this, the present invention proposes a method for monitoring the status of drop-out fuses in high-cold areas to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solutions: a method for monitoring the state of a drop-out fuse in a high-cold area, applied to a power monitoring server, comprising: S1: Obtain geographic data of drop-out fuses in a selected area and construct a fuse distribution map. The geographic data includes tower locations and station numbers. S2: Calculate the monitoring period of the drop-out fuse and divide the monitoring period into sub-segments based on the segment division criterion; S3: Collect comprehensive operation data of the drop-out fuse in the sub-section, including the percentage of over-limit temperature, abnormal current frequency, over-limit value of ambient humidity and percentage of dangerous vibration; S4: Input the collected comprehensive operation data into the pre-trained neural network model, predict the micro-motion state value of the next sub-section, and determine whether to issue a fall warning prompt. The micro-motion state value includes a triggered state and a non-triggered state; if a fall warning prompt is issued, execute S5; if no fall warning prompt is issued, repeat S3-S4; S5: Mark the fault point in the fuse distribution map, and plan the maintenance path of the fault point based on the fault maintenance criteria.

[0006] Furthermore, the method for constructing the fuse distribution map includes: Through the positioning system, we can query the selected areas one by one. The position data of the drop-out fuse is obtained location data; Mark out The interval points of the position data are used as the splitting positions. The position data are split into a first data group and a second data group one by one; Using natural language processing technology, the text part and the number part of the first data group and the second data group are identified one by one; The digital part in the first data group is recorded as the tower position, and the The number in the second data group is recorded as the station number, and the Workstation number; Mark the selected areas one by one on the electronic map The location of the tower, get Tower locations; exist Create a remark box at each tower point and The station numbers are imported one by one into the remarks box of the tower point corresponding to the station number to obtain the circuit breaker distribution map.

[0007] Furthermore, the calculation method of the monitoring period includes: Mark each fuse on the fuse distribution diagram. The location of the power maintenance station is obtained Maintenance points; Draw auxiliary lines between two adjacent maintenance points to obtain Auxiliary lines, respectively The midpoint of the auxiliary line is drawn in the vertical direction dividing line; Respectively The two ends of the dividing line extend outward, dividing the fuse distribution diagram into maintenance area; Through the maintenance management system, we can query The time it takes for each maintenance point to reach the tower point in the same maintenance area is obtained. The first duration value, and After the first duration values ​​are accumulated, a first sub-period is generated; The expression for the first subperiod is: ; In the formula, is the first sub-period, For the The first duration value; Through the maintenance management system, we can query The maximum time for repairing and replacing a drop-out fuse is obtained. The second duration value, and After the second duration values ​​are accumulated, a second sub-period is generated; The expression for the second sub-period is: ; In the formula, is the second sub-period, For the Second duration value; After adding the first sub-period and the second sub-period, a monitoring period is obtained; The expression of the monitoring period is: ; In the formula, For the monitoring cycle.

[0008] Furthermore, the segment division criteria are: the duration of any two sub-segments are the same; The sub-segment division methods include: Adding the maximum value of the first duration value and the maximum value of the second duration value to generate a divided duration value; The expression for dividing the duration value is: ; In the formula, To divide the duration value, is the maximum value of the first duration value, is the maximum value of the second duration value; The duration corresponding to the division duration value is used as the division standard to divide the monitoring period into continuous sub-segments to obtain subsections.

[0009] Furthermore, the method for obtaining the over-limit temperature ratio value includes: exist In each sub-section, the temperature in the fuse tube is detected in real time by the temperature sensor to obtain the real-time temperature value; The real-time temperature value greater than the preset temperature upper limit is recorded as the first abnormal value, and the The duration of the first abnormal value in the sub-segment is obtained The first abnormal duration; The real-time temperature value that is less than the preset lower limit of temperature is recorded as the second abnormal value, and the The duration of the second abnormal value in the sub-segment is obtained The second abnormal duration; Will The first abnormal duration and the corresponding After adding the second abnormal durations and comparing them with the duration of the sub-segment, we get The percentage of over-limit temperature; The expression of the over-limit temperature ratio is: ; In the formula, For the The percentage of over-limit temperature in each sub-section, For the The first abnormal duration of the sub-segment, For the The second abnormal duration of the sub-segment.

[0010] Furthermore, the method for obtaining the abnormal current frequency includes: A1: Based on the preset marking interval, Mark s current moments in each sub-segment, and number the s current moments in ascending order according to the order of marking; A2: Taking the interval of one number as the first standard, the current moment corresponding to the next number is recorded as the first moment; A3: After the first moment, the current moment corresponding to the next number is recorded as the second moment, with the interval of two numbers as the second standard; A4: Repeat steps A2-A3 r times to obtain r first moments and r second moments; A5: At r first moments and r second moments, the real-time current of the drop-out fuse is detected by the current sensor, which is recorded as the detected current value; A6: Record the detected current value greater than the standard current value as an abnormal current value and count it The number of abnormal current values ​​in each sub-segment is obtained. Number of abnormalities; A7; The number of abnormalities is compared with the duration of the sub-segment one by one to obtain Abnormal current frequency; The expression of abnormal current frequency is: ; In the formula, For the The abnormal current frequency of each sub-section, For the The number of anomalies in each sub-segment.

[0011] Furthermore, the method for obtaining the excess value of ambient humidity includes: exist In each sub-section, the real-time humidity of the fuse tube at s current moments is detected by the humidity sensor to obtain s humidity values; The humidity value greater than the preset safe humidity value is recorded as the excess humidity value. Exceeding humidity value; Will After subtracting each excess humidity value from the safe humidity value one by one, the differences are accumulated and averaged to obtain the excess humidity value. The expression of the ambient humidity exceeding the limit is: ; In the formula, For the The ambient humidity of each sub-segment exceeds the limit value. For the The sub-segment Exceeding humidity value, It is a safe humidity value.

[0012] Furthermore, the method for obtaining the dangerous vibration ratio value includes: Based on the preset vibration period, The sub-segments are divided into adjacent vibration periods; Mark out The starting time, midpoint time and end time of each vibration period are measured, and the vibration frequency at the starting time, midpoint time and end time is detected by a vibration sensor to obtain The starting frequency value, The midpoint frequency value and End point frequency value; Will The starting frequency value, The midpoint frequency value and The end frequency values ​​are added and averaged to obtain Frequency value of each period; The expression for the period frequency value is: ; In the formula, For the The sub-segment The period frequency value of each vibration period, For the The sub-segment The starting frequency value of each vibration period, For the The sub-segment The midpoint frequency value of a vibration period, For the The sub-segment The end frequency value of each vibration period; The frequency value of the period greater than the upper limit of the vibration frequency is recorded as the dangerous frequency value, and the vibration period where the dangerous frequency value is located is recorded as the dangerous period. Dangerous period; Will The duration of each dangerous period is accumulated one by one and compared with the duration of the sub-segment to obtain The percentage of dangerous vibrations; The expression of dangerous vibration ratio is: ; In the formula, For the The percentage of dangerous vibration in each sub-segment, For the The sub-segment The length of the dangerous period.

[0013] Furthermore, the training method of the neural network model includes: Pre-collecting multiple sets of comprehensive operation data and micro-motion state values ​​corresponding to the comprehensive operation data; The comprehensive operation data is converted into multiple feature vectors using a sliding window method. The micro-motion state value is converted into a label corresponding to the comprehensive operation data according to the sliding step size. The untriggered state is converted into 0, and the triggered state is converted into 1. One feature vector corresponds to one label and constitutes a set of training data. Multiple sets of training data constitute a training set. The comprehensive operation data are arranged in the order of collection time, and the prediction time step size Z, sliding step size Q and sliding window length N are preset. The feature vector is used as the input of the neural network model, the micromotion state value of the next sub-segment after the predicted time step Z is used as the output, the subsequent micromotion state value of each training set is used as the prediction target, and the minimized sum of prediction errors is used as the training target to train the neural network model to generate a neural network model.

[0014] Furthermore, the fault repair criteria are: the fault points in the same repair area are connected only once; The planning methods of maintenance path include: The distances between the maintenance points and the fault points in the same maintenance area are measured one by one, and the fault point corresponding to the minimum distance is recorded as the starting point of the path; Taking the path start point as the starting point, the remaining fault points in the same maintenance area are connected in sequence according to the laying direction of the transmission line to obtain the initial path; According to the order of the fault point connection, the fault points on the initial path are numbered in ascending order, and the fault point corresponding to the maximum number is recorded as the path end point to obtain the maintenance path.

[0015] The technical effects and advantages of the method for monitoring the state of drop-out fuses in high-cold areas of the present invention are as follows: The present invention acquires geographical data of drop-out fuses in a selected area, constructs a fuse distribution map, calculates the monitoring period of drop-out fuses, divides the monitoring period into sub-segments based on the segment division criteria, collects comprehensive operation data of drop-out fuses in the sub-segments, inputs the collected comprehensive operation data into a neural network model trained in advance, predicts the micro-motion state value of the next sub-segment, determines whether to issue a drop-out warning prompt, marks the fault point on the fuse distribution map, and plans the maintenance path of the fault point based on the fault maintenance criteria; compared with the prior art, the drop-out fuse distribution map can be accurately constructed by acquiring geographical data of the drop-out fuse. The distribution map of fuses is used as a guide for the location of subsequent maintenance and replacement of drop-out fuses. At the same time, the collection of multi-dimensional data such as vibration, temperature, humidity and current of drop-out fuses, combined with the neural network model, can predict the operating status of drop-out fuses in the future in advance. A maintenance and replacement reminder can be issued before the drop-out fuse is about to drop, and a reasonable maintenance path can be planned, so that power maintenance personnel can quickly perform maintenance and replacement operations on drop-out fuses with faults, avoiding the lag caused by maintenance and replacement after the drop-out fuse has a drop fault, thereby ensuring the safe and stable operation of the power supply system in high-altitude cold areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of a flow chart of a method for monitoring the state of a drop-out type fuse in a high-cold region provided in the first embodiment of the present invention; Figure 2 A schematic diagram of a system for monitoring the status of drop-out fuses in high-cold areas provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0018] Example 1: Please refer to Figure 1 As shown, the method for monitoring the status of a drop-out fuse in a high-cold region described in this embodiment is applied to a power monitoring server, comprising: S1: Obtain geographic data of drop-out fuses in a selected area and construct a fuse distribution map; Geographic data refers to data that can accurately represent the location of drop-out fuses in a selected area, which can locate the location of each drop-out fuse in the selected area and provide an accurate data basis for the subsequent construction of a fuse distribution map, ensuring that the fuse distribution map can locate the drop-out fuses in the selected area; Geographic data includes tower location and station number; tower location refers to the specific geographical location of the tower where the drop-out fuse is located, which can be used to locate the tower location of the drop-out fuse as a whole; station number refers to the number of the specific line on the tower where the drop-out fuse is located, which can be used to locate the line location of the drop-out fuse in detail; The method for constructing the fuse distribution map includes: Through the positioning system, we can query the selected areas one by one. The position data of the drop-out fuse is obtained location data; Mark out The interval points of the position data are used as the splitting positions. The position data are split into the first data group and the second data group one by one; the interval point refers to the point in the position data used to distinguish different types of data, that is, the tower data and the workstation data in the position data can be effectively distinguished, thereby ensuring the accuracy of the subsequent splitting of the first data group and the second data group; Using natural language processing technology, the text part and the number part of the first data group and the second data group are identified one by one; The digital part in the first data group is recorded as the tower position, and the The number in the second data group is recorded as the station number, and the Workstation number; Mark the selected areas one by one on the electronic map The location of the tower, get Tower locations; exist Create a remark box at each tower point and The station numbers are imported one by one into the remark box of the tower point corresponding to the station number to obtain the circuit breaker distribution map. The remark box refers to the text box on the tower point used to summarize and bind the station numbers, so that the tower point and the station number can maintain a corresponding relationship.

[0019] It should be noted that since there are multiple transmission lines on the same tower, and a drop-out fuse can be deployed on each transmission line, and the station number is a specific representation of the line where the drop-out fuse is located, and the tower position is the position of the tower where the drop-out fuse is located, therefore, the number of tower positions will be less than the number of station numbers, that is, Less than The constructed fuse distribution map can not only locate the location of the tower, but also indicate the number of the line where each drop-out fuse is located, so as to ensure that the specific location of each drop-out fuse can be accurately and independently located and marked later.

[0020] S2: Calculate the monitoring period of the drop-out fuse and divide the monitoring period into sub-segments based on the segment division criterion; The monitoring cycle refers to the overall time it takes for the power maintenance station in the selected area to reach the tower location of the corresponding drop-out fuse and complete the drop-out fuse maintenance operation, which can ensure that the power maintenance station can effectively perform maintenance on the corresponding drop-out fuse in the selected area; The calculation method of the monitoring period includes: Mark each fuse on the fuse distribution diagram. The location of the power maintenance station is obtained Maintenance points; Draw auxiliary lines between two adjacent maintenance points to obtain Auxiliary lines, respectively The midpoint of the auxiliary line is drawn in the vertical direction dividing line; Respectively The two ends of the dividing line extend outward, dividing the fuse distribution diagram into Maintenance area; by dividing the fuse distribution map through dividing lines, it can ensure that each maintenance area contains an independent power maintenance station, and at the same time, the positions of towers at different locations can be divided into corresponding maintenance areas, so as to facilitate the subsequent maintenance and replacement of faulty drop-out fuses; Through the maintenance management system, we can query The time it takes for each maintenance point to reach the tower point in the same maintenance area is obtained. The first duration value, and After the first duration values ​​are accumulated, a first sub-period is generated; The expression for the first subperiod is: ; In the formula, is the first sub-period, For the The first duration value; Through the maintenance management system, we can query The maximum time for repairing and replacing a drop-out fuse is obtained. The second duration value, and After the second duration values ​​are accumulated, a second sub-period is generated; The expression for the second sub-period is: ; In the formula, is the second sub-period, For the Second duration value; After adding the first sub-period and the second sub-period, a monitoring period is obtained; The expression of the monitoring period is: ; In the formula, For the monitoring cycle.

[0021] After the monitoring cycle is generated, since the duration corresponding to the monitoring cycle is the duration for replacing all drop-out fuses in the selected area, the duration span of the monitoring cycle is relatively large, and the corresponding amount of data when the operating status of the drop-out fuse changes during the monitoring cycle is also too much. In order to achieve a more detailed drop-out fuse status monitoring effect in a short time, it is necessary to divide the monitoring cycle with a long duration span into sub-segments with a shorter duration span; When dividing the monitoring period into sub-segments, it is necessary to ensure that each sub-segment after division can maintain consistency and continuity under the constraints of the segment division criteria; The segment division criterion is: the duration of any two sub-segments are consistent; this ensures that two adjacent sub-segments are in a continuous state on the timeline, so that the sub-segments can perform complete and continuous division processing on the monitoring period; The sub-segment division methods include: Adding the maximum value of the first duration value and the maximum value of the second duration value to generate a divided duration value; The expression for dividing the duration value is: ; In the formula, To divide the duration value, is the maximum value of the first duration value, is the maximum value of the second duration value; The duration corresponding to the division duration value is used as the division standard to divide the monitoring period into continuous sub-segments to obtain subsections.

[0022] When the monitoring period is divided into After a sub-section is formed, an accurate time basis can be provided for subsequent data collection related to the operating status of the drop-out fuse, so that each sub-section can independently represent the operating status of the drop-out fuse.

[0023] S3: Collect comprehensive operation data of the drop-out fuse in the sub-section, including the percentage of over-limit temperature, abnormal current frequency, over-limit value of ambient humidity and percentage of dangerous vibration; Comprehensive operation data refers to data that can represent the change of the operating state of the drop-out fuse in the sub-section, so as to serve as the data basis for subsequent prediction of the state of the drop-out fuse; Comprehensive operation data includes the percentage of over-limit temperature, abnormal current frequency, over-limit ambient humidity and dangerous vibration; The over-limit temperature ratio value refers to the ratio of the time that the real-time temperature in the fuse tube of the drop-out type fuse in the sub-section is outside the preset temperature range to the total time, which can be used to numerically represent the over-limit temperature time in the fuse tube. When the over-limit temperature ratio value is larger, it means that the real-time temperature in the fuse tube of the drop-out type fuse in the sub-section is outside the preset temperature range. The ratio of the total time is larger, and the operating state of the drop-out type fuse is worse at this time, and the probability of a drop is greater; Methods for obtaining the over-limit temperature ratio value include: exist In each sub-section, the temperature in the fuse tube is detected in real time by the temperature sensor to obtain the real-time temperature value; The real-time temperature value greater than the preset temperature upper limit is recorded as the first abnormal value, and the The duration of the first abnormal value in the sub-segment is obtained The preset temperature upper limit refers to the maximum value of the temperature in the fuse tube of the drop-out fuse when it is in the normal range, which can distinguish between excessively high temperature and normal temperature, so as to accurately identify excessively high temperature data; The real-time temperature value that is less than the preset lower limit of temperature is recorded as the second abnormal value, and the The duration of the second abnormal value in the sub-segment is obtained The preset lower limit of temperature refers to the minimum value of the temperature in the fuse tube of the drop-out fuse within the normal range, which can distinguish between too low temperature and normal temperature, so as to accurately identify too low temperature data; Will The first abnormal duration and the corresponding After adding the second abnormal durations and comparing them with the duration of the sub-segment, we get The percentage of over-limit temperature; The expression of the over-limit temperature ratio is: ; In the formula, For the The percentage of over-limit temperature in each sub-section, For the The first abnormal duration of the sub-segment, For the The second abnormal duration of the sub-segment.

[0024] The abnormal current frequency refers to the number of times the abnormal current appears in the fuse tube of the drop-out type fuse in the sub-section within a unit time, which can be used to indicate the number of abnormal currents in the fuse tube. When the abnormal current frequency is greater, it means that the number of times the abnormal current appears in the fuse tube of the drop-out type fuse in the sub-section within a unit time is greater. At this time, the operating state of the drop-out type fuse is worse, and the probability of drop is greater; Methods for obtaining abnormal current frequency include: A1: Based on the preset marking interval, Mark s current moments in a sub-segment, and number the s current moments in ascending order according to the order of marking; the preset marking interval refers to the interval between two adjacent current detection moments, which can play an independent role in distinguishing each current detection moment, and prevent the phenomenon of the current data being consistent or repeated when the current is detected at two adjacent current detection moments; A2: Taking the interval of one number as the first standard, the current moment corresponding to the next number is recorded as the first moment; A3: After the first moment, the current moment corresponding to the next number is recorded as the second moment, with the interval of two numbers as the second standard; A4: Repeat steps A2-A3 r times to obtain r first moments and r second moments; A5: At r first moments and r second moments, the real-time current of the drop-out fuse is detected by the current sensor, which is recorded as the detected current value; A6: Record the detected current value greater than the standard current value as an abnormal current value and count it The number of abnormal current values ​​in each sub-segment is obtained. The standard current value refers to the maximum temperature of the drop-out fuse under normal conditions, which can accurately represent the excessively high temperature data, thereby accurately identifying the abnormal current phenomenon; A7; The number of abnormalities is compared with the duration of the sub-segment one by one to obtain Abnormal current frequency; The expression of abnormal current frequency is: ; In the formula, For the The abnormal current frequency of each sub-section, For the The number of anomalies in each sub-segment.

[0025] The environmental humidity over-limit value refers to the difference between the humidity of the environment where the fuse tube of the drop-out type fuse in the sub-section is located and the safe humidity, which can be used to indicate the humidity of the environment where the fuse tube is located. When the environmental humidity over-limit value is larger, it means that the difference between the humidity of the environment where the fuse tube of the drop-out type fuse in the sub-section is larger and the safe humidity is larger. At this time, the operating state of the drop-out type fuse is worse, and the probability of drop is greater. Methods for obtaining the ambient humidity excess limit value include: exist In each sub-section, the real-time humidity of the fuse tube at s current moments is detected by the humidity sensor to obtain s humidity values; The humidity value greater than the preset safe humidity value is recorded as the excess humidity value. The preset safe humidity value refers to the maximum humidity of the external environment where the fuse tube of the drop-out fuse is located under the normal range, which can distinguish between excessive humidity and normal humidity, so as to accurately identify excessive humidity data; Will After subtracting each excess humidity value from the safe humidity value one by one, the differences are accumulated and averaged to obtain the excess humidity value. The expression of the ambient humidity exceeding the limit is: ; In the formula, For the The ambient humidity of each sub-segment exceeds the limit value. For the The sub-segment Exceeding humidity value, It is a safe humidity value.

[0026] The dangerous vibration ratio refers to the ratio of the time that the fuse tube of the drop-out type fuse in the sub-section is at the dangerous vibration frequency to the total time, which can represent the dangerous vibration phenomenon of the fuse tube. When the dangerous vibration ratio is larger, it means that the ratio of the time that the fuse tube of the drop-out type fuse in the sub-section is at the dangerous vibration frequency to the total time is larger, and at this time, the operating state of the drop-out type fuse is worse, and the probability of falling is greater; Methods for obtaining the percentage of dangerous vibration include: Based on the preset vibration period, The sub-segments are divided into The preset vibration period refers to the interval between two adjacent vibration moments, which can ensure that the interval between two adjacent vibration moments remains consistent, thereby providing an accurate time point for subsequent vibration frequency detection; Mark out The starting time, midpoint time and end time of each vibration period are measured, and the vibration frequency at the starting time, midpoint time and end time is detected by a vibration sensor to obtain The starting frequency value, The midpoint frequency value and The end frequency value; through the frequencies corresponding to the starting time, midpoint time and end time, the frequency of each vibration period can be represented in the early, middle and late stages, improving the comprehensiveness of the vibration data; Will The starting frequency value, The midpoint frequency value and The end frequency values ​​are added and averaged to obtain Frequency value of each period; The expression for the period frequency value is: ; In the formula, For the The sub-segment The period frequency value of each vibration period, For the The sub-segment The starting frequency value of each vibration period, For the The sub-segment The midpoint frequency value of a vibration period, For the The sub-segment The end frequency value of each vibration period; The frequency value of the period greater than the upper limit of the vibration frequency is recorded as the dangerous frequency value, and the vibration period where the dangerous frequency value is located is recorded as the dangerous period. The upper limit of vibration frequency refers to the maximum value of the vibration frequency of the fuse tube of the drop-out fuse in the normal range, which can distinguish between excessive vibration frequency and normal vibration frequency; Will The duration of each dangerous period is accumulated one by one and compared with the duration of the sub-segment to obtain The percentage of dangerous vibrations; The expression of dangerous vibration ratio is: ; In the formula, For the The percentage of dangerous vibration in each sub-segment, For the The sub-segment The length of the dangerous period.

[0027] S4: input the collected comprehensive operation data into the pre-trained neural network model, predict the micro-motion state value of the next sub-section, and determine whether to issue a fall warning prompt; The micro-motion state value refers to the stroke state of the micro-switch in the drop-out fuse, which can indicate whether the drop-out fuse triggers the micro-switch action. The micro-motion state value includes a triggered state and an untriggered state. The triggered state indicates that the micro-switch in the drop-out fuse has a stroke and generates a drop-out warning signal. The untriggered state indicates that the micro-switch in the drop-out fuse has no stroke and generates no drop-out warning signal. The micro-motion state value is obtained by monitoring the warning signal of the micro-switch. After obtaining the comprehensive operation data, the neural network model can be used to predict the comprehensive operation data, so that the neural network model can accurately predict the micro-motion state value of the next sub-section, thereby realizing the prediction effect of the micro-motion state value of the drop-out fuse at the future moment, ensuring that the power monitoring platform can be advanced and accurate, so as to achieve the effect of early prediction of the drop-out fuse state; The training methods of neural network models include: Pre-collecting multiple sets of comprehensive operation data and micro-motion state values ​​corresponding to the comprehensive operation data; The comprehensive operation data is converted into multiple feature vectors using a sliding window method. The micro-motion state value is converted into a label corresponding to the comprehensive operation data according to the sliding step size. The untriggered state is converted into 0, and the triggered state is converted into 1. One feature vector corresponds to one label and constitutes a set of training data. Multiple sets of training data constitute a training set. The comprehensive operation data are arranged in the order of collection time, and the prediction time step size Z, sliding step size Q and sliding window length N are preset. The feature vector is used as the input of the neural network model, the micromotion state value of the next sub-segment after the predicted time step Z is used as the output, the subsequent micromotion state value of each training set is used as the prediction target, and the neural network model is trained with the minimized sum of prediction errors as the training target to generate a neural network model that predicts the micromotion state value of the next sub-segment based on the comprehensive operation data of the previous sub-segment.

[0028] Exemplarily, the neural network model is any one of CNN or AlexNet; The calculation formula for the prediction error is: ; In the formula, is the prediction error, is the group number of the eigenvector; For the The predicted state value corresponding to the group feature vector, For the The actual state value corresponding to the group training data; In the neural network model, the feature vector is the comprehensive operation data, and the state value is the micro-motion state value.

[0029] The drop warning prompt is a warning prompt issued when the drop-type fuse is about to fall in the future, so as to provide early warning information for the power monitoring platform and make subsequent processing operations for the drop-type fuse that issued the drop warning information; The determination method of whether to issue a fall warning prompt includes: When the output of the neural network model is 0, it means that the predicted micro-motion state value of the next sub-section is an untriggered state. At this time, the probability of the drop-out fuse at a future time is low, and no early warning is required, so it is determined that no drop-out early warning will be issued; When the output of the neural network model is 1, it indicates that the predicted micro-motion state value of the next sub-section is a trigger state. At this time, the probability of the drop-out fuse dropping in the future is high and an early warning is required. Then, it is determined to issue a drop-out early warning.

[0030] S5: Mark the fault point in the fuse distribution map, and plan the maintenance path of the fault point based on the fault maintenance criteria; The fault point refers to the point of the electric tower where the drop-out fuse is located when the micro-motion state value of the next sub-section predicted by the neural network model is the trigger state, which can be used as the point for subsequent maintenance or replacement of the drop-out fuse that issues a drop-out warning prompt, thereby achieving the effect of early maintenance or replacement of the drop-out fuse in poor operating condition; When marking the fault point, it is necessary to obtain the workstation number of the drop-out fuse that issues the drop-out warning prompt, and identify the remark box where the workstation number is located, so that the tower point corresponding to the remark box is the fault point; It should be noted that the number of drop-out fuses that issue a drop-out warning may be one or more, and the fault points corresponding to the drop-out fuses that issue a drop-out warning may be one or more. When there are multiple fault points, it is necessary to arrange the multiple fault points in order to facilitate subsequent maintenance and processing. In order to ensure that the multiple fault points remain fast and reasonable during maintenance, it is necessary to perform route planning under the constraints of the fault maintenance criteria, so that the maintenance path can be planned, so that the maintenance path can be used as the maintenance route for the drop-out fuses at the subsequent fault points; The fault repair principle is: the fault points in the same repair area are only connected once; it can ensure that the fault points in the same repair area can be connected in sequence, and ensure that the fault points in the same repair area can be repaired and replaced in the shortest time; The planning methods of maintenance path include: The distances between the maintenance points and the fault points in the same maintenance area are measured one by one, and the fault point corresponding to the minimum distance is recorded as the starting point of the path; Taking the path start point as the starting point, the remaining fault points in the same maintenance area are connected in sequence according to the laying direction of the transmission line to obtain the initial path; the method of connecting points along the laying direction of the transmission line can ensure that the connection between each fault point remains orderly and there will be no disorder in the connection sequence, and at the same time, it also ensures that each fault point will only be connected once and there will be no repeated connection phenomenon; According to the order of the fault point connection, the fault points on the initial path are numbered in ascending order, and the fault point corresponding to the maximum number is recorded as the path end point to obtain the maintenance path.

[0031] It should be noted that since each maintenance area corresponds to a power maintenance station, when multiple fault points are distributed in different maintenance paths, it is only necessary to plan the maintenance paths in each maintenance area separately, thereby ensuring that each power maintenance station can locate and repair the faults in its own maintenance area, and ultimately achieve the maintenance effect of all fault points.

[0032] In this embodiment, by acquiring the geographic data of the drop-out fuses in the selected area, a fuse distribution map is constructed, the monitoring period of the drop-out fuses is calculated, and based on the section division criteria, the monitoring period is divided into sub-sections, and the comprehensive operation data of the drop-out fuses in the sub-sections are collected, and the collected comprehensive operation data are input into the neural network model trained in advance, and the micro-motion state value of the next sub-section is predicted, and it is determined whether to issue a drop warning prompt, and the fault point is marked on the fuse distribution map, and based on the fault maintenance criteria, the maintenance path of the fault point is planned; compared with the prior art, by acquiring the geographic data of the drop-out fuse, the drop-out fuse distribution map can be accurately constructed. The distribution map of the drop-type fuses is obtained, and it serves as a location guide for the subsequent maintenance and replacement of the drop-type fuses. At the same time, the collection of multi-dimensional data such as vibration, temperature, humidity and current of the drop-type fuses, combined with the neural network model, can predict in advance the operating status of the drop-type fuses in the future. A maintenance and replacement reminder can be issued before the drop-type fuse is about to fall, and a reasonable maintenance path can be planned, so that the power maintenance personnel can quickly perform maintenance and replacement operations on the drop-type fuses with faults, avoiding the lag caused by maintenance and replacement after the drop-type fuses have a fall failure, thereby ensuring the safe and stable operation of the power supply system in high-cold areas.

[0033] Example 2: Please refer to Figure 2 As shown, the part not described in detail in this embodiment is described in the first embodiment, which provides a high-cold area drop-out type fuse state monitoring system, which is applied to a power monitoring server and is used to implement a high-cold area drop-out type fuse state monitoring method, including a distribution map construction module, a sub-section division module, a data acquisition module, a model prediction module and a path planning module, wherein each module is connected through a wired or wireless network; A distribution map building module is used to obtain geographic data of drop-out fuses in a selected area and build a fuse distribution map, wherein the geographic data includes tower locations and station numbers; A sub-section division module is used to calculate the monitoring period of the drop-out fuse and divide the monitoring period into sub-sections based on the section division criterion; A data acquisition module is used to collect comprehensive operation data of the drop-out fuse in the sub-section, the comprehensive operation data including the percentage of over-limit temperature, abnormal current frequency, over-limit value of ambient humidity and percentage of dangerous vibration; The model prediction module is used to input the collected comprehensive operation data into the pre-trained neural network model, predict the micro-motion state value of the next sub-section, and determine whether to issue a fall warning prompt. The micro-motion state value includes a triggered state and an untriggered state; The path planning module is used to mark the fault point in the fuse distribution map and plan the maintenance path of the fault point based on the fault maintenance criteria.

[0034] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for monitoring the status of drop-out fuses in high-cold areas, applied to a power monitoring server, characterized in that: include: S1: Obtain geographic data of drop-out fuses in a selected area and construct a fuse distribution map. The geographic data includes tower locations and station numbers. S2: Calculate the monitoring period of the drop-out fuse and divide the monitoring period into sub-segments based on the segment division criterion; S3: Collect comprehensive operation data of the drop-out fuse in the sub-section, including the percentage of over-limit temperature, abnormal current frequency, over-limit value of ambient humidity and percentage of dangerous vibration; S4: Input the collected comprehensive operation data into the pre-trained neural network model, predict the micro-motion state value of the next sub-section, and determine whether to issue a fall warning prompt. The micro-motion state value includes a triggered state and a non-triggered state; if a fall warning prompt is issued, execute S5; if no fall warning prompt is issued, repeat S3-S4; S5: Mark the fault point in the fuse distribution map, and plan the maintenance path of the fault point based on the fault maintenance criteria.

2. The method for monitoring the status of drop-out fuses in high-cold areas according to claim 1 is characterized in that: The method for constructing the fuse distribution map includes: Through the positioning system, we can query the selected areas one by one. The position data of the drop-out fuse is obtained location data; Mark out The interval points of the position data are used as the splitting positions. The position data are split into a first data group and a second data group one by one; Using natural language processing technology, the text part and the number part of the first data group and the second data group are identified one by one; The digital part in the first data group is recorded as the tower position, and the The number in the second data group is recorded as the station number, and the Workstation number; Mark the selected areas one by one on the electronic map The location of the tower, get Tower locations; exist Create a remark box at each tower point and The station numbers are imported one by one into the remarks box of the tower point corresponding to the station number to obtain the circuit breaker distribution map.

3. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 2, characterized in that: The calculation method of the monitoring period includes: Mark each fuse on the fuse distribution diagram. The location of the power maintenance station is obtained Maintenance points; Draw auxiliary lines between two adjacent maintenance points to obtain Auxiliary lines, respectively The midpoint of the auxiliary line is drawn in the vertical direction dividing line; Respectively The two ends of the dividing line extend outward, dividing the fuse distribution diagram into maintenance area; Through the maintenance management system, we can query The time it takes for each maintenance point to reach the tower point in the same maintenance area is obtained. The first duration value, and After the first duration values ​​are accumulated, a first sub-period is generated; The expression for the first subperiod is: ； In the formula, is the first sub-period, For the The first duration value; Through the maintenance management system, we can query The maximum time for repairing and replacing a drop-out fuse is obtained. The second duration value, and After the second duration values ​​are accumulated, a second sub-period is generated; The expression for the second sub-period is: ； In the formula, is the second sub-period, For the Second duration value; After adding the first sub-period and the second sub-period, a monitoring period is obtained; The expression of the monitoring period is: ； In the formula, For the monitoring cycle.

4. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 3, characterized in that: The segment division criteria are: the duration of any two sub-segments are the same; The sub-segment division methods include: Adding the maximum value of the first duration value and the maximum value of the second duration value to generate a divided duration value; The expression for dividing the duration value is: ； In the formula, To divide the duration value, is the maximum value of the first duration value, is the maximum value of the second duration value; The duration corresponding to the division duration value is used as the division standard to divide the monitoring period into continuous sub-segments to obtain subsections.

5. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 4, characterized in that: The method for obtaining the over-limit temperature ratio value includes: exist In each sub-section, the temperature in the fuse tube is detected in real time by the temperature sensor to obtain the real-time temperature value; The real-time temperature value greater than the preset temperature upper limit is recorded as the first abnormal value, and the The duration of the first abnormal value in the sub-segment is obtained The first abnormal duration; The real-time temperature value that is less than the preset lower limit of temperature is recorded as the second abnormal value, and the The duration of the second abnormal value in the sub-segment is obtained The second abnormal duration; Will The first abnormal duration and the corresponding After adding the second abnormal durations and comparing them with the duration of the sub-segment, we get The percentage of over-limit temperature; The expression of the over-limit temperature ratio is: ； In the formula, For the The percentage of over-limit temperature in each sub-section, For the The first abnormal duration of the sub-segment, For the The second abnormal duration of the sub-segment.

6. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 5, characterized in that: The method for obtaining the abnormal current frequency includes: A1: Based on the preset marking interval, Mark s current moments in each sub-segment, and number the s current moments in ascending order according to the order of marking; A2: Taking the interval of one number as the first standard, the current moment corresponding to the next number is recorded as the first moment; A3: After the first moment, the current moment corresponding to the next number is recorded as the second moment, with the interval of two numbers as the second standard; A4: Repeat steps A2-A3 r times to obtain r first moments and r second moments; A5: At r first moments and r second moments, the real-time current of the drop-out fuse is detected by the current sensor, which is recorded as the detected current value; A6: Record the detected current value greater than the standard current value as an abnormal current value and count it The number of abnormal current values ​​in each sub-segment is obtained. Number of abnormalities; A7; The number of abnormalities is compared with the duration of the sub-segment one by one to obtain Abnormal current frequency; The expression of abnormal current frequency is: ； In the formula, For the The abnormal current frequency of each sub-section, For the The number of anomalies in each sub-segment.

7. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 6, characterized in that: The method for obtaining the excess value of ambient humidity includes: exist In each sub-section, the real-time humidity of the fuse tube at s current moments is detected by the humidity sensor to obtain s humidity values; The humidity value greater than the preset safe humidity value is recorded as the excess humidity value. Exceeding humidity value; Will After subtracting each excess humidity value from the safe humidity value one by one, the differences are accumulated and averaged to obtain the excess humidity value. The expression of the ambient humidity exceeding the limit is: ； In the formula, For the The ambient humidity of each sub-segment exceeds the limit value. For the The sub-segment Exceeding humidity value, It is a safe humidity value.

8. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 7, characterized in that: The method for obtaining the dangerous vibration ratio value includes: Based on the preset vibration period, The sub-segments are divided into adjacent vibration periods; Mark out The starting time, midpoint time and end time of each vibration period are measured, and the vibration frequency at the starting time, midpoint time and end time is detected by a vibration sensor to obtain The starting frequency value, The midpoint frequency value and End point frequency value; Will The starting frequency value, The midpoint frequency value and The end frequency values ​​are added and averaged to obtain Frequency value of each period; The expression for the period frequency value is: ； In the formula, For the The sub-segment The period frequency value of each vibration period, For the The sub-segment The starting frequency value of each vibration period, For the The sub-segment The midpoint frequency value of a vibration period, For the The sub-segment The end frequency value of each vibration period; The frequency value of the period greater than the upper limit of the vibration frequency is recorded as the dangerous frequency value, and the vibration period where the dangerous frequency value is located is recorded as the dangerous period. Dangerous period; Will The duration of each dangerous period is accumulated one by one and compared with the duration of the sub-segment to obtain The percentage of dangerous vibrations; The expression of dangerous vibration ratio is: ； In the formula, For the The percentage of dangerous vibration in each sub-segment, For the The sub-segment The length of the dangerous period.

9. A method for monitoring the status of drop-out fuses in high-cold regions according to claim 8, characterized in that: The training method of the neural network model includes: Pre-collecting multiple sets of comprehensive operation data and micro-motion state values ​​corresponding to the comprehensive operation data; The comprehensive operation data is converted into multiple feature vectors using a sliding window method. The micro-motion state value is converted into a label corresponding to the comprehensive operation data according to the sliding step. The untriggered state is converted to 0, and the triggered state is converted to 1. One feature vector corresponds to one label and constitutes a set of training data. Multiple sets of training data constitute a training set. The comprehensive operation data are arranged in the order of collection time, and the prediction time step Z, sliding step Q and sliding window length N are preset. The feature vector is used as the input of the neural network model, the micromotion state value of the next sub-segment after the predicted time step Z is used as the output, the subsequent micromotion state value of each training set is used as the prediction target, and the minimized sum of prediction errors is used as the training target to train the neural network model to generate a neural network model.

10. A method for monitoring the status of drop-out fuses in high-cold areas according to claim 9, characterized in that: The fault repair criteria are: the fault points in the same repair area are connected only once; The planning methods of maintenance path include: The distances between the maintenance points and the fault points in the same maintenance area are measured one by one, and the fault point corresponding to the minimum distance is recorded as the starting point of the path; Taking the path start point as the starting point, the remaining fault points in the same maintenance area are connected in sequence according to the laying direction of the transmission line to obtain the initial path; According to the order of the fault point connection, the fault points on the initial path are numbered in ascending order, and the fault point corresponding to the maximum number is recorded as the path end point to obtain the maintenance path.

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