Cable fault abnormity monitoring method and system

Abstract

The invention discloses a cable fault abnormity monitoring method and system, and relates to the technical field of cable monitoring, and the method comprises the steps: obtaining the historical fault data of a to-be-monitored cable, and carrying out the analysis of the historical fault data according to the fault type, and obtaining the fault electric data of the corresponding fault type; analyzing the fault electric data to screen monitoring data items of the monitoring equipment; acquiring attenuation properties of the corresponding data items in the cable according to the monitoring data items, determining data propagation distances of the monitoring data items according to the attenuation properties, and recording the data propagation distances as effective propagation data; setting monitoring points for the cable based on the effective propagation data to obtain monitoring point data; and detecting the cable based on the monitoring point data to obtain monitoring data, determining whether the cable has a fault according to the monitoring data, and outputting a corresponding judgment result. The effect of reducing the construction cost of the monitoring system is achieved through reasonable setting of the monitoring points.

Description

Technical Field

[0001] The present application relates to the technical field of cable monitoring, and in particular to a method and system for monitoring cable fault anomalies. Background Art

[0002] With the increasing complexity of power networks and the widespread use of cables in energy transmission, cable faults pose a serious threat to the stability and security of power supply. Traditional cable fault monitoring methods mostly rely on manual inspections and offline detection, which is not only inefficient but also prone to misjudgment.

[0003] In recent years, with the rapid development of sensor technology, signal processing technology and network communication technology, new technical support has been provided for online monitoring and abnormal detection of cable faults. By installing sensors to monitor the key parameters of the cable in real time, and analyzing and processing the monitored data, comprehensive monitoring of the cable operation status can be achieved. However, since the fault data of the cable will be attenuated when it is transmitted in the cable, when there are too few monitoring points, the monitoring results will be misjudged due to the attenuation of the data. When there are too many monitoring points, it will cause a waste of resources. Therefore, how to arrange the monitoring points needs to be solved urgently and there is room for improvement. Summary of the invention

[0004] In order to reduce the construction cost of the monitoring system, the present application provides a cable fault anomaly monitoring method and system.

[0005] In a first aspect, the present application provides a method for monitoring cable fault anomalies, which adopts the following technical solution:

[0006] A cable fault abnormality monitoring method, comprising:

[0007] Obtain historical fault data of the cable to be monitored, and analyze the historical fault data according to the fault type to obtain fault electrical data corresponding to the fault type;

[0008] Analyze the fault electrical data to screen and obtain the monitoring data items of the monitoring equipment;

[0009] According to the monitoring data item, the attenuation property of the corresponding data item in the cable is obtained, and the data propagation distance of the monitoring data item is determined according to the attenuation property, and recorded as effective propagation data;

[0010] Based on the effective propagation data, monitoring points are set up on the cable to obtain monitoring point data;

[0011] The cable is tested based on the monitoring point data to obtain monitoring data, and whether the cable has a fault is determined based on the monitoring data, and the corresponding judgment result is output.

[0012] Preferably, the historical fault data is divided into historical fault data groups of each fault type according to the fault type;

[0013] Compare each data item in the historical fault data group of the same fault type with the data items of the cable in a normal state to determine the impact of the fault type on each data item in the cable, and record it as the fault impact;

[0014] Based on the impact of the fault, the impact category of the cable data item is judged. If the fault impact increases the value of the data item, the impact category of the data item is judged to be positive impact;

[0015] If the impact of the fault causes the value of the data item to decrease, the impact category of the data item is determined to be a negative impact;

[0016] The data items with positive impact are counted to obtain a positive impact data item group, the data items with negative impact are counted to obtain a negative impact data item group, and the positive impact data item group and the negative impact data item group are recorded as fault electrical data.

[0017] Preferably, the positive impact data item groups of different fault types are compared with each other according to the impact category of the fault electrical data, and the positive impact data items included in different fault types are obtained and recorded as the positive data items to be analyzed;

[0018] Compare the negative impact data item groups of different fault types with each other to obtain the negative impact data items contained in different fault types, and record them as negative data items to be analyzed;

[0019] Based on the historical fault data of the corresponding fault type, the data items in the positive data items to be analyzed and the negative data items to be analyzed are averaged to obtain the average data of each data item, and are recorded as positive average data and negative average data respectively;

[0020] Compare the positive mean data and the negative mean data with the values ​​of the corresponding data items of the cable under normal conditions to determine the magnitude of the value change of the corresponding data items;

[0021] Based on the magnitude of the numerical change, the data items in the positive mean data and the negative mean data are screened to obtain the data item with the largest magnitude of the numerical change, and the data item is recorded as the monitoring data item.

[0022] Preferably, if there are multiple data items with the largest value variation, the impact categories of the multiple data items are judged, and if they are of the same impact category, the effective propagation data is determined according to the attenuation properties of the corresponding data items in the cable;

[0023] The data items are screened according to the effective propagation data to obtain the data item with the largest effective propagation data, and the data item is used as the monitoring data item;

[0024] If multiple data items are not of the same impact category, then according to the priority rule, the priority of the positive impact data item is greater than that of the negative impact data item, so that the data items in the positive impact data item are selected to determine the corresponding monitoring data items.

[0025] Preferably, based on the monitoring data items, mean data of corresponding data items under different fault types are obtained, and based on a preset base value ratio, the mean data is calculated to obtain base value data of the corresponding fault type;

[0026] According to the attenuation properties of the base value data, mean value data and corresponding data items, the effective propagation data of the corresponding fault data under each fault type is calculated.

[0027] Preferably, historical monitoring data of the cable under normal conditions is obtained, and a change curve of a corresponding data item in the historical monitoring data is determined according to the monitoring data item;

[0028] Based on the change curve of the data item, determine the normal mean and fluctuation range of the data item;

[0029] Based on the normal mean and the fluctuation range, the ratio between the fluctuation range and the normal mean is determined to obtain the fluctuation ratio;

[0030] Obtain the mean data of the monitoring data items under different fault types, and determine the difference data between the mean data and the fluctuation range according to the mean data and the fluctuation range under normal conditions, and determine the ratio between the difference data and the normal mean according to the difference data and the normal mean, and obtain the fault ratio under different fault types;

[0031] Screen the fault proportions of different fault types to obtain the minimum fault proportion;

[0032] The minimum value of the fluctuation ratio and the failure ratio is used as the value interval of the base ratio;

[0033] The value range of the base value ratio is input into the naive Bayes model to select the base value ratio, and the base value ratio with the highest fault judgment accuracy is taken as the specific value of the base value ratio.

[0034] Preferably, based on the effective propagation data of each fault type, the effective propagation data with the smallest data value in the effective propagation data is determined, and recorded as the basic propagation distance;

[0035] Divide the cables based on the basic propagation distance to obtain the location information of the monitoring points;

[0036] Based on the basic propagation distance and the attenuation property of the corresponding data item, determine the data values ​​of the remaining fault types under the basic propagation distance, and record them as the first marked data values;

[0037] Compare the first labeled data value with the mean data corresponding to the basic propagation distance, and if the first labeled data value is greater than the mean data corresponding to the basic propagation distance, no operation is performed;

[0038] If the first marked data value is less than or equal to the mean data corresponding to the basic propagation distance, the distance difference between the effective propagation data of the remaining fault types and the basic propagation data is determined based on the basic propagation distance, and the data value under the distance difference is determined based on the distance difference and the attenuation property, and recorded as the second marked data value;

[0039] Compare the second labeled data value with the mean data of the basic propagation distance, and if the second labeled data value is greater than the mean data of the basic propagation distance, set the mean data corresponding to the first labeled data value and the basic propagation distance as the special data interval;

[0040] If the second marker data value is less than or equal to the mean data of the basic propagation distance, the first marker data value and the second marker data value are set as a special data interval;

[0041] The location data of the monitoring point and the corresponding special data interval are recorded as monitoring point data.

[0042] Preferably, based on the mean data corresponding to the basic propagation data, the numerical change of the corresponding fault type on the basic propagation number is determined to obtain the basic data interval;

[0043] Divide the basic data interval based on the special data interval to obtain multiple data sub-intervals;

[0044] Match the monitored data with multiple data sub-intervals to determine the data sub-interval corresponding to the monitored data. If the monitored data is in the basic data interval and does not belong to the special data interval, the fault is determined to be the fault type corresponding to the basic propagation data, and the position of the corresponding fault is calculated and output according to the attenuation property, the mean data of the corresponding fault type and the monitored data;

[0045] If the monitoring data is in the special data interval in the basic data interval, the fault type of the fault is determined according to the special data interval and the basic data interval, and the fault position of the corresponding fault type is calculated and output according to the attenuation property, the monitoring data and the mean data of the corresponding fault type;

[0046] If the monitoring data is not in the basic data interval, the fault type corresponding to the monitoring data is deleted for the fault type corresponding to the basic propagation data.

[0047] In a second aspect, the present application provides a cable fault anomaly monitoring system, which adopts the following technical solution:

[0048] A cable fault anomaly monitoring system, comprising: a fault data analysis module, a data item screening module, a propagation distance calculation module, a monitoring point establishment module and a fault judgment module;

[0049] The fault data analysis module obtains historical fault data of the cable to be monitored, and analyzes the historical fault data according to the fault type to obtain fault electrical data corresponding to the fault type;

[0050] The data item screening module analyzes the fault electrical data to screen and obtain monitoring data items of the monitoring equipment;

[0051] The propagation distance calculation module obtains the attenuation property of the corresponding data item in the cable according to the monitoring data item, and determines the data propagation distance of the monitoring data item according to the attenuation property, and records it as effective propagation data;

[0052] The monitoring point establishment module establishes monitoring points on the cable based on the effective propagation data to obtain monitoring point data;

[0053] The fault judgment module detects the cable based on the monitoring point data to obtain monitoring data, determines whether the cable has a fault according to the monitoring data, and outputs a corresponding judgment result.

[0054] In summary, the present application includes at least one of the following beneficial technical effects:

[0055] 1. Through the analysis of historical fault data, the fault electrical data corresponding to different fault types are clarified, and then the fault electrical data is analyzed to further screen out the monitoring data items that can be used to determine whether there is a fault, that is, by making data judgment on the monitoring data items, it is determined whether the cable has a fault, which simplifies the fault analysis and judgment process and improves the judgment efficiency. At the same time, according to the attenuation of the monitoring data items in the cable transmission, the maximum feasible distance when the monitoring point is set up is further clarified. At the same time, because the monitoring points are set up according to the effective propagation distance of different fault types, the number of monitoring points will neither be redundant nor lead to missed faults, thereby reducing the possibility of missed monitoring and improving the accuracy of monitoring;

[0056] 2. By means of group matching and screening of the affected data items, data items of different fault types are obtained, and the impact categories of the data items are the same, so that it is possible to judge whether the cable is faulty based on the single impact of a single data item, simplifying the judgment process. At the same time, the screened data items are re-screened by the value change amplitude to ensure that the change amplitude of the second screening result reaches the maximum, thereby ensuring that the possibility of misjudgment is reduced when judging the data fault of the data item, thereby improving the accuracy of the system's fault judgment;

[0057] 3. Comprehensively utilize the effective propagation data of each fault type to determine the basic propagation distance, and then determine the data change range of other fault types at the monitoring point based on the basic propagation distance to determine whether there will be a situation where the same data corresponds to multiple fault types and fault point distances within the monitoring range of the monitoring point, and make special marks on the data change interval for the existing situation, so that the monitoring point can accurately judge the fault type and fault point distance based on the monitored data, thereby improving the accuracy of the system's fault judgment, ensuring the rationality of the establishment of the monitoring point, and reducing the cost of system construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flowchart of the steps of the cable fault abnormality monitoring method of this embodiment;

[0059] Figure 2 Module block diagram of the cable fault anomaly monitoring system of this embodiment.

[0060] Figure numerals: 1. Fault data analysis module; 2. Data item screening module; 3. Propagation distance calculation module; 4. Monitoring point establishment module; 5. Fault judgment module. DETAILED DESCRIPTION

[0061] The following is combined with Figure 1-Figure 2 This application is described in further detail.

[0062] The embodiments of the present application disclose a method and system for monitoring cable fault anomalies.

[0063] Example: Figure 1 As shown, the present invention provides a cable fault abnormality monitoring method, comprising:

[0064] S100, obtaining historical fault data of the cable to be monitored, and analyzing the historical fault data according to the fault type to obtain fault electrical data corresponding to the fault type;

[0065] S200, analyzing the fault electrical data to screen and obtain monitoring data items of the monitoring equipment;

[0066] S300, obtaining the attenuation property of the corresponding data item in the cable according to the monitoring data item, and determining the data propagation distance of the monitoring data item according to the attenuation property, and recording it as effective propagation data; wherein the attenuation property of the cable is the relationship between the data strength and the propagation distance of the monitoring data item in the cable transmission, which can be obtained by actual measurement or calculated by the cable's own parameters, and can be specifically Among them, L is the attenuation length, k is the attenuation coefficient, y is the attenuation result, and x is the fault data of the data item; and a can be obtained through actual experimental measurement.

[0067] S400, establishing monitoring points for the cable based on the effective propagation data to obtain monitoring point data;

[0068] S500, detecting the cable based on the monitoring point data to obtain monitoring data, determining whether the cable has a fault according to the monitoring data, and outputting a corresponding judgment result.

[0069] In this embodiment, by analyzing historical fault data, the fault electrical data corresponding to different fault types are clarified, and then the fault electrical data is analyzed to further screen out monitoring data items that can be used to determine whether a fault exists, that is, by performing data judgment on the monitoring data items to determine whether the cable has a fault, the fault analysis and judgment process is simplified and the judgment efficiency is improved. At the same time, based on the attenuation of the monitoring data items in cable transmission, the maximum feasible distance for setting up the monitoring points is further clarified. At the same time, since the monitoring points are set up according to the effective propagation distances of different fault types, the number of monitoring points will neither be redundant nor lead to missed faults, thereby reducing the possibility of missed monitoring and improving the accuracy of monitoring.

[0070] For example, by analyzing different fault types, it is determined that each fault type will cause the voltage value, current value, and frequency value to change. The voltage value, current value, and frequency value are all fault electrical data. Similarly, the voltage, current, and frequency are data items. Then, by screening the voltage value, current value, and frequency value, the data items used as the fault judgment standard are screened out. For example, if the voltage value is used as the judgment standard, the corresponding voltage is the monitoring data item. The attenuation property of the voltage in the cable is determined by actual measurement as e ad , where a is the measured attenuation coefficient and d is the attenuation length. Therefore, the corresponding effective propagation length is obtained by calculation, and the corresponding monitoring points are set up through the effective propagation length to monitor the voltage, so that the cable can be fully monitored.

[0071] In step S100, historical fault data of the cable to be monitored is obtained, and the historical fault data is analyzed according to the fault type to obtain fault electrical data corresponding to the fault type, including the following steps:

[0072] S110, dividing the historical fault data into historical fault data groups of each fault type according to the fault type;

[0073] S120, comparing each data item in the historical fault data group of the same fault type with the data items of the cable in a normal state to determine the impact of the fault type on each data item in the cable, and recording it as the fault impact;

[0074] S130. Based on the fault impact, determine the impact category of the data items of the cable. If the fault impact causes the value of the data item to increase, it is determined that the impact category of the data item is a positive impact;

[0075] S140. If the fault impact causes the value of the data item to decrease, it is determined that the impact category of the data item is a negative impact;

[0076] S150. Statistically analyze the data items with positive impacts to obtain a positive impact data item group, and statistically analyze the data items with negative impacts as a negative impact data item group. Record the positive impact data item group and the negative impact data item group as fault electricity data.

[0077] In this embodiment, when judging the fault electricity data based on historical fault data, by comparing each data item in the historical fault data with each data item in the normal state one by one to determine the data items with anomalies, and then judging the relationship between the data items with anomalies and the data items in the normal state to further clarify the impact category of the fault type on the data items, which provides convenience for subsequent screening of the data items with anomalies according to the impact category, so that the screening results are more reliable when screening the data items with anomalies subsequently.

[0078] In this embodiment, first, judge the data items of the historical fault data group of the same fault type through the fault type. For example, there are data items in the historical fault data: voltage: a volts, current: b amperes; frequency: c hertz, and the data items in the normal state are: voltage: A volts, current: B amperes; frequency: C hertz; by comparing a with A, b with B, and c with C with each other to determine which data items are abnormal. For example, if two data items, voltage and current, are abnormal, then re-judge according to the relationship between a and A, and b and B. For example, a > A and b < B, then it indicates that this fault type has a positive impact on the data item voltage and a negative impact on the data item current.

[0079] In step S200, analyze the fault electricity data to screen out the monitoring data items of the monitoring device, including the following steps:

[0080] S210. Compare the positive impact data item groups of different fault types with each other according to the impact category of the fault electricity data to obtain the positive impact data items included in different fault types, and record them as the positive data items to be analyzed;

[0081] S220. Compare the negative impact data item groups of different fault types with each other to obtain the negative impact data items included in different fault types, and record them as the negative data items to be analyzed;

[0082] S230, performing mean calculation on the data items in the positive data items to be analyzed and the negative data items to be analyzed based on the historical fault data of the corresponding fault type, obtaining mean data of each data item, and recording them as positive mean data and negative mean data respectively;

[0083] S240, comparing the positive mean data and the negative mean data with the values ​​of the corresponding data items of the cable in a normal state to determine the magnitude of the value change of the corresponding data items;

[0084] S250, screening the data items in the positive mean data and the negative mean data based on the magnitude of the numerical changes, obtaining the data item with the largest magnitude of the numerical changes, and recording the data item as the monitoring data item.

[0085] In this embodiment, after determining the data items affected by the fault type, the data items affected by different fault types are analyzed and screened to ensure that the data items finally obtained are capable of performing fault judgment on all fault types, thereby ensuring the functionality of the screened data items, and thereby simplifying the monitoring system's fault identification steps and improving identification efficiency and accuracy.

[0086] By grouping, matching and screening the affected data items, we can obtain data items that include different fault types, and the impact categories of the data items are the same, so that we can judge whether the cable is faulty based on the single impact of a single data item, which simplifies the judgment process. At the same time, by re-screening the numerical change amplitude of the screened data items, it is ensured that the change amplitude of the second screening result reaches the maximum, thereby ensuring that when judging the data fault of the data item, the possibility of misjudgment is reduced, thereby improving the accuracy of the system's fault judgment.

[0087] Exemplarily, in the process of selecting data items for fault electrical data, for example, voltage, current, and frequency are all fault electrical data, and fault 1 affects voltage and current, and fault 2 affects voltage and frequency. When screening data items for the fault electrical data, the data item voltage is a fault data item included in both fault 1 and fault 2. If the data item voltage is used as the basis for judging the fault, it is only necessary to judge the data item voltage to determine whether the cable has a fault. On the contrary, if current and frequency are used as the basis for judging the fault, it is necessary to judge the current once and then judge the frequency once, thereby reducing the recognition efficiency.

[0088] If fault 1 affects voltage, current and frequency, and fault 2 affects voltage and frequency, then when screening the fault electrical data, since both fault 1 and fault 2 contain data items voltage and frequency, the data items voltage and frequency can be used as the basis for judging fault 1 and fault 2. Therefore, the data items voltage and frequency can be re-screened to obtain the best basis for judgment. For example, when fault 1 and fault 2 occur, the voltage changes from data 10 to data 100, and the frequency changes from data 10 to data 50. The corresponding faults 1 and 2 have a greater impact on the voltage. Therefore, when data fluctuations occur, the result obtained by judging the voltage is more credible than the result obtained by judging the frequency. Therefore, voltage is used as the monitoring data item for fault 1 and fault 2.

[0089] In step S200, the fault electrical data is analyzed to screen and obtain monitoring data items of the monitoring device, and the following steps are also included:

[0090] S260, if there are multiple data items with the largest value change, determine the impact category of the multiple data items, and if they are of the same impact category, determine the effective propagation data according to the attenuation properties of the corresponding data items in the cable;

[0091] S270, screening the data items according to the effective propagation data, obtaining the data item with the largest effective propagation data, and using the data item as the monitoring data item;

[0092] S280, if the multiple data items are not of the same impact category, then according to the priority rule, the priority of the positive impact data item is greater than that of the negative impact data item, so that the data items in the positive impact data item are selected to determine the corresponding monitoring data items.

[0093] In this embodiment, when selecting monitoring data items for fault electrical data, if there are multiple data items in the screening results, the screened data items are re-screened to perform a first screening by determining whether the impact categories of the multiple data items are the same. When the impact categories are the same, the data items of the same impact category are screened for a second time based on the attenuation properties of the data items in the cable to obtain the data items with the largest effective propagation data, thereby reducing the number of monitoring points when setting up monitoring points based on the effective propagation data, thereby reducing the construction cost of the cable monitoring system.

[0094] Exemplarily, for example, the data items in the screening result are voltage and current. Among them, if the voltage is a data item with a positive impact and the current is a data item with a negative impact, since the increase of positive data is unlimited while the decrease of negative data is limited, the priority of the data item with a positive impact is greater than that of the data item with a negative impact. Therefore, the data item voltage is directly selected as the detection data item. And if both the voltage and the current are data items with a positive impact, then through the attenuation property, the effective propagation data a of the voltage is determined, and the effective propagation data b of the current is determined. If a > b, the voltage is used as the monitoring data item, and if a < b, the current is used as the monitoring data item.

[0095] In step S300, according to the monitoring data item, obtain the attenuation property of the corresponding data item in the cable, and determine the data propagation distance of the monitoring data item according to the attenuation property, and record it as the effective propagation data, including the following steps:

[0096] S310, based on the monitoring data item, obtain the mean data of the corresponding data item under different fault types, and calculate the mean data based on the preset base value ratio to obtain the base value data of the corresponding fault type;

[0097] S320, according to the base value data, the mean data and the attenuation property of the corresponding data item, calculate the effective propagation data of the corresponding fault data under each fault type;

[0098] Among them, the base value ratio is specifically:

[0099] S311, obtain the historical monitoring data of the cable in the normal state, and determine the change curve of the corresponding data item in the historical monitoring data according to the monitoring data item;

[0100] S312, based on the change curve of the data item, determine the normal mean value and the fluctuation range of the data item;

[0101] S313, based on the normal mean value and the fluctuation range, determine the ratio between the fluctuation range and the normal mean value to obtain the fluctuation ratio;

[0102] S314, obtain the mean data of the monitoring data item under different fault types, and determine the difference data between the mean data and the fluctuation range according to the mean data and the fluctuation range in the normal state. According to the difference data and the normal mean value, determine the ratio between the difference data and the normal mean value to obtain the fault ratio under different fault types;

[0103] S315, screen the fault ratios of different fault types to obtain the minimum value of the fault ratio;

[0104] S316, use the fluctuation ratio and the minimum value of the fault ratio as the value range of the base value ratio;

[0105] S317, inputting the value range of the base value ratio into the naive Bayes model to select the base value ratio, and taking the base value ratio with the highest fault judgment accuracy as the specific value of the base value ratio.

[0106] In this embodiment, by determining the mean data of the monitoring data item, the base value data of the corresponding data item under different fault types is determined, and then the effective propagation data of the data item in the corresponding fault type is determined in combination with the attenuation property, and then the monitoring points are established according to the effective propagation data. This not only ensures that the monitoring points can effectively monitor all faults, but also optimizes the number of monitoring points, thereby reducing the cost of system construction.

[0107] In the process of determining the base value data of the corresponding data item based on the mean data of the monitored data item, the base value data is calculated by the base value ratio, which reduces the possibility of misjudgment caused by changes in the value of the data item due to external environmental factors. At the same time, the base value ratio determines the fluctuation range of the fault data of the corresponding data item by the ratio of the values ​​under the fault state and the normal state, and then analyzes the fluctuation range of the fault data based on the naive Bayes model to determine the minimum fault data that can be judged as a cable fault, thereby ensuring the accuracy of the system's judgment on the cable.

[0108] For example, if the mean value data of the fault is a, and the preset base value ratio is b%, then the base value data is c=a×b%, and the effective propagation data is calculated by the attenuation property as L, where when calculating the base value ratio, the normal mean value under normal conditions is U 正 , the fluctuation range is U 波 , the corresponding fluctuation ratio T 波 =U 正 ÷U 波 Similarly, the proportion of the mean data under the fault state in the normal state is calculated to obtain the corresponding T 障 =(U 障 -U 波 )÷U 正 , and then the value range of the base value ratio is determined, and then the base value ratio within the value range is selected through the naive Bayes model, and the historical fault data in the model is judged by the selected base value ratio to determine the judgment accuracy of the corresponding base value ratio, and the best base value ratio is selected according to the accuracy.

[0109] In step S400, monitoring points are set up for the cable based on the effective propagation data to obtain monitoring point data, including the following steps:

[0110] S410, based on the effective propagation data of each fault type, determining the effective propagation data with the smallest data value among the effective propagation data, and recording it as the basic propagation distance;

[0111] S420, dividing the cables based on the basic propagation distance to obtain location information of the monitoring points;

[0112] S430, based on the basic propagation distance and the attenuation property of the corresponding data item, determining the data values ​​of the remaining fault types at the basic propagation distance, and recording them as the first marked data values;

[0113] S440, comparing the first marked data value with the mean data corresponding to the basic propagation distance, if the first marked data value is greater than the mean data corresponding to the basic propagation distance, no operation is performed;

[0114] S450, if the first marked data value is less than or equal to the mean data corresponding to the basic propagation distance, then determining the distance difference between the effective propagation data of the remaining fault types and the basic propagation data based on the basic propagation distance, and determining the data value under the distance difference based on the distance difference and the attenuation property, and recording it as the second marked data value;

[0115] S460, comparing the second labeled data value with the mean data of the basic propagation distance, if the second labeled data value is greater than the mean data of the basic propagation distance, setting the mean data corresponding to the first labeled data value and the basic propagation distance as a special data interval;

[0116] S470, if the second marker data value is less than or equal to the mean data of the basic propagation distance, setting the first marker data value and the second marker data value as a special data interval;

[0117] S480, recording the location data of the monitoring point and the corresponding special data interval as monitoring point data.

[0118] In this embodiment, since data will be attenuated during cable transmission, when different fault data are transmitted within the basic propagation distance, there may be multiple different fault types with the same data results presented to the monitoring points at different positions within the basic propagation distance. Therefore, it is necessary to judge the data interval to further judge the fault type, thereby improving the effectiveness of the judgment result.

[0119] In order to ensure that the established monitoring points can effectively monitor all faults, the effective propagation data of each fault type is screened once to obtain the effective propagation data with the smallest value as the basic propagation data, thereby ensuring the comprehensiveness of the monitoring point's fault monitoring. At the same time, according to the attenuation properties of the data item in the cable, the numerical variation range of different fault types presented to the monitoring point in the basic propagation data is determined. The first marked data value is obtained by calculating the numerical value presented under the farthest monitoring range, and then the first marked data value is compared with the mean data corresponding to the basic propagation distance to determine whether the fault type has a data intersection with the fault type corresponding to the basic propagation distance. If the first marked data value is greater than the mean data corresponding to the basic propagation distance, it indicates that the minimum value of the fault type in the basic propagation data is greater than the maximum value of the fault type corresponding to the basic propagation data in the basic propagation data, that is, there is no data intersection, so there will be no misjudgment when making a judgment. If the first marked data value is less than or equal to the mean data corresponding to the basic propagation data, it indicates that there is a data intersection, so it is necessary to The data of the set is marked. Similarly, since the first marked data value is less than or equal to the mean data corresponding to the basic propagation data, it only indicates the minimum value of the data intersection interval, so it is necessary to judge the maximum value of the data intersection. Since the basic propagation data is the smallest propagation data in the effective propagation data, when the distance between the fault and the monitoring point on the current basic propagation data reaches a certain degree, the next monitoring point can also detect the data of the fault. Therefore, the data of the monitoring point of the fault on the basic propagation data in this state is calculated to determine the second marked data value. The second marked data value is compared with the mean value of the basic propagation distance to determine whether the monitoring point on the basic propagation data will be misjudged when the fault is detected by the next monitoring point. If the second marked data value is less than or equal to the mean data of the basic propagation distance, it indicates that a misjudgment will occur. Therefore, the second marked data value is recorded as the maximum value of the data intersection interval. If the second marked data value is greater than the mean data of the basic propagation distance, it indicates that no misjudgment will occur. Therefore, the mean data of the basic propagation distance is recorded as the maximum value of the data intersection interval. By dividing the data interval obtained by monitoring the monitoring point, the judgment result is more accurate.

[0120] Exemplarily, the monitoring point on the basic propagation distance is recorded as monitoring point 1, and the next monitoring point is recorded as monitoring point 2 according to the data transmission direction. The mean data of the basic propagation distance corresponding to the fault type A is recorded as a, so the performance of other fault types on the basic propagation distance is judged, and other fault types are recorded as B. For example, if the basic propagation distance is L meters, the performance of fault type B on L meters is calculated. When the fault point of fault type B is L meters away from monitoring point 1, the corresponding fault type B has the smallest value at monitoring point 1, which is recorded as b1. By comparing b1 with a, it is determined whether there is an intersection between the data performance of fault type B and fault type A at monitoring point 1. If b1 is greater than a, it indicates that there is no intersection. If b1 is less than or equal to a, it indicates that There is an intersection, and b1 is set as the minimum value of the data intersection interval; the effective propagation data of fault type B and fault type A are calculated to obtain the distance difference q, and then the fault type B is re-judged by the distance difference to determine the value presented by the fault point of fault type B on monitoring point 1 when the fault point is q away from monitoring point 1, and recorded as b2. By comparing b2 with a, it is determined whether monitoring point 1 misjudges fault type B when fault type B is monitored by monitoring point 2. If b2 is greater than a, it indicates that no misjudgment will occur, so a is taken as the maximum value of the data intersection interval. If b2 is less than or equal to a, it indicates that a misjudgment will occur, so b2 is taken as the maximum value of the data intersection interval to ensure the accuracy of the monitoring point's judgment on fault type B.

[0121] In step S500, the cable is detected based on the monitoring point data to obtain monitoring data, and whether the cable has a fault is determined according to the monitoring data, and a corresponding judgment result is output, including the following steps:

[0122] S510, determining the value change of the corresponding fault type on the basic propagation number based on the mean data corresponding to the basic propagation data, and obtaining the basic data interval;

[0123] S520, dividing the basic data interval based on the special data interval to obtain multiple data sub-intervals;

[0124] S530, matching the monitored data with multiple data sub-intervals to determine the data sub-interval corresponding to the monitored data. If the monitored data is in the basic data interval and does not belong to the special data interval, the fault is determined to be a fault type corresponding to the basic propagation data, and the position of the corresponding fault is calculated based on the attenuation property, the mean data of the corresponding fault type and the monitored data and outputted;

[0125] S540, if the monitoring data is in the special data interval in the basic data interval, the fault type of the fault is determined according to the special data interval and the basic data interval, and the fault position of the corresponding fault type is calculated according to the attenuation property, the monitoring data and the mean data of the corresponding fault type and outputted;

[0126] S550: If the monitoring data is not in the basic data interval, the fault type corresponding to the basic propagation data is deleted for the fault type corresponding to the monitoring data.

[0127] In this embodiment, the basic data interval is divided by special data intervals, so that the monitoring point can match the divided data sub-intervals according to the monitored data to determine the fault type existing in the corresponding data and the location data corresponding to the fault, which simplifies the judgment process of the fault type corresponding to the monitoring data and thereby improves the system's efficiency in judging faults.

[0128] When the monitoring data is within the basic data interval, it indicates that the fault point is within the monitoring range, so the corresponding fault point location can be calculated through the monitoring data. When the monitoring data is in a special data interval, it indicates that the fault point is not only within the monitoring range, but also there are multiple fault types. Therefore, it is necessary to calculate the fault point location through different fault types to facilitate maintenance by the staff. When the monitoring data is not within the basic data interval, it indicates that the fault point of the fault can be monitored by the next monitoring point, and the fault type of the fault is not the fault type corresponding to the basic propagation data, thereby improving the accuracy of the next monitoring point's judgment on the fault type of the fault.

[0129] Exemplarily, the basic data interval corresponding to fault type A is (10, 20), where the special data interval is (15, 20). When the monitoring data is 14, it indicates that fault type A exists within the monitoring range, and the fault point is calculated based on the attenuation property. For example, at x1, when the monitoring data is 17, it indicates that fault type A or fault type B corresponding to the special data interval exists within the monitoring range, and the fault point for fault type A is calculated based on the attenuation property, and the fault point for fault type B is calculated. When the monitoring data is 22, the fault type of the fault is not fault type A, and a corresponding analysis is performed based on the monitoring data of the fault type at the next monitoring point to determine the corresponding fault type and fault location.

[0130] Based on the description of the above cable fault abnormality monitoring method embodiment, the embodiment of the present invention also discloses a cable fault abnormality monitoring system:

[0131] like Figure 2As shown, a cable fault abnormality monitoring system, by applying the above cable fault abnormality monitoring method, includes: a fault data analysis module 1, a data item screening module 2, a propagation distance calculation module 3, a monitoring point establishment module 4 and a fault judgment module 5;

[0132] Fault data analysis module 1, obtains historical fault data of the cable to be monitored, and analyzes the historical fault data according to the fault type to obtain fault electrical data corresponding to the fault type;

[0133] The data item screening module 2 analyzes the fault electrical data to screen out the monitoring data items of the monitoring equipment;

[0134] The propagation distance calculation module 3 obtains the attenuation property of the corresponding data item in the cable according to the monitoring data item, and determines the data propagation distance of the monitoring data item according to the attenuation property, and records it as the effective propagation data;

[0135] Monitoring point establishment module 4, establishes monitoring points for the cable based on effective propagation data to obtain monitoring point data;

[0136] The fault judgment module 5 detects the cable based on the monitoring point data to obtain monitoring data, determines whether the cable has a fault according to the monitoring data, and outputs a corresponding judgment result.

[0137] Compared with the existing cable fault anomaly monitoring method and system, the present invention reduces the system construction cost.

[0138] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A cable fault abnormality monitoring method, characterized in that: include: Obtain historical fault data of the cable to be monitored, and analyze the historical fault data according to the fault type to obtain fault electrical data corresponding to the fault type; Analyze the fault electrical data to screen and obtain the monitoring data items of the monitoring equipment; According to the monitoring data item, the attenuation property of the corresponding data item in the cable is obtained, and the data propagation distance of the monitoring data item is determined according to the attenuation property, and recorded as effective propagation data; Based on the effective propagation data, monitoring points are set up on the cable to obtain monitoring point data; The cable is tested based on the monitoring point data to obtain monitoring data, and whether the cable has a fault is determined based on the monitoring data, and the corresponding judgment result is output.

2. A cable fault abnormality monitoring method according to claim 1, characterized in that: The method of obtaining historical fault data of the cable to be monitored and analyzing the historical fault data according to the fault type to obtain fault electrical data of the corresponding fault type is as follows: Dividing the historical fault data into historical fault data groups of each fault type according to the fault type; Compare each data item in the historical fault data group of the same fault type with the data items of the cable in a normal state to determine the impact of the fault type on each data item in the cable, and record it as the fault impact; Based on the impact of the fault, the impact category of the cable data item is judged. If the fault impact increases the value of the data item, the impact category of the data item is judged to be positive impact; If the impact of the fault causes the value of the data item to decrease, the impact category of the data item is determined to be a negative impact; The data items with positive impact are counted to obtain a positive impact data item group, the data items with negative impact are counted to obtain a negative impact data item group, and the positive impact data item group and the negative impact data item group are recorded as fault electrical data.

3. A cable fault abnormality monitoring method according to claim 2, characterized in that: The fault electrical data is analyzed to screen out monitoring data items of the monitoring equipment, specifically: According to the impact category of the fault electrical data, the positive impact data item groups of different fault types are compared with each other to obtain the positive impact data items contained in different fault types and record them as the positive data items to be analyzed; Compare the negative impact data item groups of different fault types with each other to obtain the negative impact data items contained in different fault types, and record them as negative data items to be analyzed; Based on the historical fault data of the corresponding fault type, the data items in the positive data items to be analyzed and the negative data items to be analyzed are averaged to obtain the average data of each data item, and are recorded as positive average data and negative average data respectively; Compare the positive mean data and the negative mean data with the values ​​of the corresponding data items of the cable under normal conditions to determine the magnitude of the value change of the corresponding data items; Based on the magnitude of the numerical change, the data items in the positive mean data and the negative mean data are screened to obtain the data item with the largest magnitude of the numerical change, and the data item is recorded as the monitoring data item.

4. A cable fault abnormality monitoring method according to claim 3, characterized in that: The analyzing of the fault electrical data to screen out monitoring data items of the monitoring equipment also includes: If there are multiple data items with the largest value change, the impact categories of the multiple data items are judged. If they are of the same impact category, the effective propagation data is determined based on the attenuation properties of the corresponding data items in the cable; The data items are screened according to the effective propagation data to obtain the data item with the largest effective propagation data, and the data item is used as the monitoring data item; If multiple data items are not of the same impact category, then according to the priority rule, the priority of the positive impact data item is greater than that of the negative impact data item, so that the data items in the positive impact data item are selected to determine the corresponding monitoring data items.

5. A cable fault abnormality monitoring method according to claim 4, characterized in that: The attenuation property of the corresponding data item in the cable is obtained according to the monitoring data item, and the data propagation distance of the monitoring data item is determined according to the attenuation property, and recorded as effective propagation data, specifically: Based on the monitoring data items, the mean data of the corresponding data items under different fault types are obtained, and based on the preset base value ratio, the mean data is calculated to obtain the base value data of the corresponding fault type; According to the attenuation properties of the base value data, mean value data and corresponding data items, the effective propagation data of the corresponding fault data under each fault type is calculated.

6. A cable fault abnormality monitoring method according to claim 5, characterized in that: The base value ratio is specifically: Obtain historical monitoring data of the cable under normal conditions, and determine a change curve of a corresponding data item in the historical monitoring data according to the monitoring data items; Based on the change curve of the data item, determine the normal mean and fluctuation range of the data item; Based on the normal mean and the fluctuation range, the ratio between the fluctuation range and the normal mean is determined to obtain the fluctuation ratio; Obtain the mean data of the monitoring data items under different fault types, and determine the difference data between the mean data and the fluctuation range according to the mean data and the fluctuation range under normal conditions, and determine the ratio between the difference data and the normal mean according to the difference data and the normal mean, and obtain the fault ratio under different fault types; Screen the fault proportions of different fault types to obtain the minimum fault proportion; The minimum value of the fluctuation ratio and the failure ratio is used as the value interval of the base ratio; The value range of the base value ratio is input into the naive Bayes model to select the base value ratio, and the base value ratio with the highest fault judgment accuracy is taken as the specific value of the base value ratio.

7. A cable fault abnormality monitoring method according to claim 6, characterized in that: The monitoring points of the cable are set up based on the effective propagation data to obtain the monitoring point data, specifically: Based on the effective propagation data of each fault type, determine the effective propagation data with the smallest data value in the effective propagation data, and record it as the basic propagation distance; Divide the cables based on the basic propagation distance to obtain the location information of the monitoring points; Based on the basic propagation distance and the attenuation property of the corresponding data item, determine the data values ​​of the remaining fault types under the basic propagation distance, and record them as the first marked data values; Compare the first labeled data value with the mean data corresponding to the basic propagation distance, and if the first labeled data value is greater than the mean data corresponding to the basic propagation distance, no operation is performed; If the first marked data value is less than or equal to the mean data corresponding to the basic propagation distance, the distance difference between the effective propagation data of the remaining fault types and the basic propagation data is determined based on the basic propagation distance, and the data value under the distance difference is determined based on the distance difference and the attenuation property, and recorded as the second marked data value; Compare the second labeled data value with the mean data of the basic propagation distance, and if the second labeled data value is greater than the mean data of the basic propagation distance, set the mean data corresponding to the first labeled data value and the basic propagation distance as the special data interval; If the second marker data value is less than or equal to the mean data of the basic propagation distance, the first marker data value and the second marker data value are set as a special data interval; The location data of the monitoring point and the corresponding special data interval are recorded as monitoring point data.

8. A cable fault abnormality monitoring method according to claim 7, characterized in that: The cable is detected based on the monitoring point data to obtain monitoring data, and whether the cable has a fault is determined according to the monitoring data, and a corresponding judgment result is output, specifically: Based on the mean data corresponding to the basic propagation data, determine the numerical change of the corresponding fault type on the basic propagation number to obtain the basic data interval; Divide the basic data interval based on the special data interval to obtain multiple data sub-intervals; Match the monitored data with multiple data sub-intervals to determine the data sub-interval corresponding to the monitored data. If the monitored data is in the basic data interval and does not belong to the special data interval, the fault is determined to be the fault type corresponding to the basic propagation data, and the position of the corresponding fault is calculated and output according to the attenuation property, the mean data of the corresponding fault type and the monitored data; If the monitoring data is in the special data interval in the basic data interval, the fault type of the fault is determined according to the special data interval and the basic data interval, and the fault position of the corresponding fault type is calculated and output according to the attenuation property, the monitoring data and the mean data of the corresponding fault type; If the monitoring data is not in the basic data interval, the fault type corresponding to the monitoring data is deleted for the fault type corresponding to the basic propagation data.

9. A cable fault abnormality monitoring system, characterized in that: The system is used to implement a cable fault anomaly monitoring method as described in any one of claims 1 to 8: comprising: a fault data analysis module, a data item screening module, a propagation distance calculation module, a monitoring point establishment module and a fault judgment module; The fault data analysis module obtains historical fault data of the cable to be monitored, and analyzes the historical fault data according to the fault type to obtain fault electrical data corresponding to the fault type; The data item screening module analyzes the fault electrical data to screen and obtain monitoring data items of the monitoring equipment; The propagation distance calculation module obtains the attenuation property of the corresponding data item in the cable according to the monitoring data item, and determines the data propagation distance of the monitoring data item according to the attenuation property, and records it as effective propagation data; The monitoring point establishment module establishes monitoring points on the cable based on the effective propagation data to obtain monitoring point data; The fault judgment module detects the cable based on the monitoring point data to obtain monitoring data, determines whether the cable has a fault according to the monitoring data, and outputs a corresponding judgment result.

Images