Power distribution network line power supply fault positioning method and system based on intelligent distribution distance measurement

Abstract

The invention discloses a power distribution network line power supply fault positioning method and system based on intelligent distribution distance measurement, and belongs to the technical field of power grid fault detection, and the method comprises the steps: S10, obtaining historical fault positioning points of a preset line, dividing the preset line into a plurality of line segments, and obtaining the line segments corresponding to the historical fault positioning points; s20, based on the obtained line sections corresponding to the historical fault positioning points, counting the historical fault occurrence frequency of each line section, and obtaining a fault coordinate corresponding to any fault; according to the invention, the fault points of the preset power distribution network line are collected in a segmented manner, and the segmented lines can be distinguished according to the number of times of fault occurrence, so that when a fault occurs in a future time period, the distinguished high-fault-rate line segments can be subjected to fault positioning in a more concentrated manner, thereby improving the fault positioning efficiency, and improving the fault positioning accuracy. And the infrared thermal imaging data corresponding to the infrared thermal imaging data are obtained, so that the accuracy of fault point positioning is improved, and the efficiency of fault point positioning is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid fault detection, and in particular to a method and system for locating power supply faults in a distribution network based on intelligent distributed ranging. Background Art

[0002] As the supply and demand link between the transmission network and electricity users, the distribution network has the characteristics of many changes in line structure and complex fault conditions. Among them, short circuit of wires is one of the common faults in electrical systems. It may cause circuit interruption, equipment damage and even fire and other safety risks. To solve this problem, the focus is on tracking and locating the short-circuit fault point. For the tracking and positioning of distribution network line fault points, the technical application number CN202010081955.X provides a distribution network line fault positioning method and system. The feature of this technical application is that when a single-phase grounding fault and a latent fault occur in the distribution network, a pulse voltage signal is generated, so that the partial discharge detection sensor closest to the fault point is the first to detect the pulse voltage signal, and then the time and corresponding position of the first detection of the pulse signal are analyzed, and then the fault point position is calculated respectively, that is, the fault is located; it can quickly and accurately realize online ranging and fault location, effectively improving the reliability of power supply of the power grid.

[0003] Another technical application number CN202211541520.4 provides a distribution network fault location protection method and system containing distributed power sources. The technical solution includes determining the fault range based on the amplitude of the power frequency current mutation of each line in the distribution network, and comparing the current phase or amplitude of each branch within the fault range to determine the fault line; this technical solution can reduce the amount of calculation on irrelevant branches, reduce the amount of calculation, and alleviate data communication pressure. It can quickly locate the fault line and then perform protection actions on the fault line, effectively protecting the operation of the distribution network containing distributed power sources and avoiding power supply safety hazards caused by untimely fault handling.

[0004] In real life, there are various methods for locating line faults in power systems, but the principle behind all approaches is to measure the resistance or voltage amplitude of the faulted area on the cable or wire, and then calculate and locate the fault location based on the cable or wire parameters. However, the practical application of this method of location calculation has many shortcomings. For example, due to the diverse and complex nature of distribution network lines, the location of current grounding faults, which correspond to power supply faults, is not ideal, sometimes leading to incorrect location. This increases the number of fault location operations and reduces the efficiency of power line maintenance. Summary of the Invention

[0005] In view of the above problems existing in the technical field of existing power grid fault detection, the present invention is proposed.

[0006] Therefore, one of the objects of the present invention is to provide a distribution network line power supply fault location method and system based on intelligent distributed ranging, which can distinguish the segmented lines according to the number of fault occurrences by segmented collection of fault points of a preset distribution network line, so that when a fault occurs in a future time period, the fault location of the distinguished high fault rate line segments can be more concentratedly performed, thereby improving the efficiency of fault location. At the same time, in the corresponding line segment, by giving two fault location points with the farthest interval, when a fault occurs in the corresponding line segment in the future time period, maintenance personnel can collect the fault point between the two fault location points with the farthest interval to obtain the corresponding infrared thermal imaging data, which not only improves the accuracy of fault point location, but also further improves the efficiency of fault point location.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In one aspect, the present invention provides a method for locating a power supply fault in a distribution network based on intelligent distributed ranging, comprising the following steps:

[0009] Step S10: obtaining historical fault location points of a preset line, dividing the preset line into a plurality of line segments, and obtaining line segments corresponding to each historical fault location point;

[0010] Step S20: Based on the acquired line segments corresponding to the historical fault location points, the number of historical fault occurrences of each line segment is counted, and the fault coordinates corresponding to any fault are obtained;

[0011] Step S30: Count the number of fault coordinates, and distinguish the divided line segments based on the counted number of fault coordinates. The distinction method includes dividing the line segments into high fault rate line segments, medium fault rate line segments, and low fault rate line segments. Based on the high fault rate line segment, the current value of the preset line initial point when the fault occurs is collected. At the same time, based on the current value, the current value is collected to the current value of the line segment corresponding to the fault coordinate to generate the current value coefficient A. R ;

[0012] Step S40: At the current value coefficient A R At least 10 current data are collected according to the distance from the preset line initial point to the corresponding line segment. Analyze the current data that appears the most times up to the corresponding line segment, and analyze the change pattern of the current data up to the fault point of the corresponding line segment based on the current data;

[0013] Step S50: When the change rule is that the current data shows an increasing trend, a safety threshold is preset based on the current data that appears the most times to the corresponding line segment. When the current data from the preset line to the initial point of the corresponding line segment in the future time period is consistent with the safety threshold, it is determined that the current of the line segment will increase and a fault warning is issued. Otherwise, no determination is made.

[0014] As a preferred solution of the present invention, in step S10, the preset line is divided into a number of line segments, the number of which is at least 5, and the 5 line segments are marked as L1 segment, L2 segment, L3 segment, L4 segment and L5 segment, and the current value of each line segment when a historical fault occurs is collected, and infrared thermal imaging data corresponding to the fault location point in the corresponding line segment is obtained based on the current value.

[0015] As a preferred solution of the present invention, in step S40, current data is collected according to the distance from the preset line initial point to the corresponding line segment, and the collection method includes:

[0016] When the distance from the preset line initial point to the corresponding line section is 1 to 3 km, the number of current data collected is ≥ 10;

[0017] When the distance from the preset line initial point to the corresponding line section is 3 to 5 km, the number of current data collected is ≥ 13;

[0018] When the distance from the preset line initial point to the corresponding line section is 5 to 7 km, the number of current data collected is ≥ 16;

[0019] Among the different numbers of current data collected, the confidence level of the occurrence of faults in the future time period of different line segments is obtained based on the first three current data, wherein the first three current data are marked as independent group current data, and the acquisition method is calculated according to the following formula:

[0020] Wherein, wj represents the wth independent group of current data collected for the jth time in the line segment;

[0021] Wherein, H represents the number of times the same independent current data set appears in the acquisition cycle with every ten faults as one independent current data acquisition cycle; λ represents the number of times different independent current data sets appear in the acquisition cycle; G x represents the Gth different independent group of current data acquired for the xth time in the acquisition cycle;

[0022] When the number of occurrences of the same independent set of current data is ≤ 5 times in the acquisition cycle, the confidence level is determined to be low; otherwise, no determination is made.

[0023] As a preferred solution of the present invention, in the acquisition cycle, the change pattern of the three current data contained therein is analyzed based on the same independent group current data, and the median current data between the first two current data is analyzed based on the first two current data. When the independent group current data collected in the future time period, if the median current data between the first two current data is inconsistent with the median current data in the acquisition cycle, it is determined that the probability of failure of the corresponding line section is low; otherwise, no determination is made.

[0024] As a preferred solution of the present invention, in the acquisition cycle, two fault location points with the farthest distance between them are collected based on the same independent group of current data; when a fault occurs in the line section in a future period, the infrared thermal imaging data is collected within the interval, and the area within the interval is marked as a primary acquisition area, and the area outside the interval is marked as a secondary acquisition area.

[0025] As a preferred solution of the present invention, in the main acquisition area, the acquired infrared thermal imaging data are sorted in ascending order, and in the sorted data, the infrared thermal imaging data with the largest number of occurrences is analyzed, and the infrared thermal imaging data is marked as the first infrared thermal imaging data. When the infrared thermal imaging data of the corresponding line section needs to be collected according to the fault location point in the future period, the first infrared thermal imaging data is used as the target for collection.

[0026] As a preferred solution of the present invention, the current data corresponding to the first infrared thermal imaging data is obtained, and the closest values ​​greater than and less than the current data are obtained based on the current data. When the first infrared thermal imaging data is collected in the future time period based on the current data corresponding to the first infrared thermal imaging data but the collection is not successful, the data is re-collected based on the closest values ​​greater than and / or less than the current data.

[0027] As a preferred solution of the present invention, the proportion of successful acquisition of the infrared thermal imaging data based on the closest value greater than and / or less than the current data is obtained. When the proportion of one of the two values ​​is larger, the one with the larger proportion is used as the closest value as the basis for re-acquisition.

[0028] On the other hand, the present invention provides a distribution network line power supply fault location system based on intelligent distributed ranging, which is applied to a distribution network line power supply fault location method based on intelligent distributed ranging, comprising:

[0029] A data acquisition module is configured to acquire historical fault location points of a preset line, divide the preset line into a plurality of line segments, and acquire line segments corresponding to each historical fault location point; and based on the acquired line segments corresponding to each historical fault location point, count the number of historical fault occurrences of each line segment, and acquire the fault coordinates corresponding to any fault;

[0030] a data differentiation module, configured to count the number of fault coordinates and differentiate the divided line segments based on the counted number of fault coordinates;

[0031] The distinction method includes dividing the line segment into a high fault rate line segment, a medium fault rate line segment and a low fault rate line segment, and collecting the current value of the preset line initial point when the fault occurs based on the high fault rate line segment, and collecting the current value of the line segment corresponding to the fault coordinate based on the current value to generate the current value coefficient A R ;

[0032] Fusion analysis unit, in the current value coefficient A R In the embodiment, the current data of at least 10 items are collected according to the distance from the initial point of the preset line to the corresponding line segment. Analyze the current data with the largest number of occurrences up to the corresponding line segment, and analyze the change pattern of the current data up to the fault point of the corresponding line segment based on the current data; the fusion analysis unit includes a determination module;

[0033] The determination module is configured to, when the change pattern is that the current data is increasing, preset a safety threshold based on the current data that appears the most times up to the corresponding line segment; when the current data from the preset line to the initial point of the corresponding line segment in a future time period is consistent with the safety threshold, determine that the current of the line segment will increase and issue a fault warning; otherwise, no determination is made;

[0034] A confidence calculation module, which responds to the fusion analysis unit and is used to obtain the confidence of faults occurring in different line segments in future time periods based on the first three current data among different numbers of current data collected.

[0035] Beneficial effects:

[0036] The present invention collects fault points of a preset distribution network line in sections, and can distinguish the sectioned lines according to the number of fault occurrences, so that when a fault occurs in a future time period, the fault location can be more concentrated on the distinguished high-fault rate line sections, thereby improving the efficiency of fault location. In addition, the fault point can be locked by tracking the current data with the largest number of occurrences corresponding to historical faults in the corresponding line section, so that infrared thermal imaging data can be collected more quickly in the corresponding line section, and then the corresponding line section can be repaired. At the same time, in the corresponding line section, by giving two fault location points with the farthest interval, when a fault occurs in the corresponding line section in the future time period, maintenance personnel can collect the fault point between the two fault location points with the farthest interval to obtain the corresponding infrared thermal imaging data, which not only improves the accuracy of fault location, but also further improves the efficiency of fault location. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0038] Figure 1 Schematic diagram of the modular structure of a distribution network line power supply fault location system based on intelligent distributed ranging according to an embodiment of the present invention;

[0039] Figure 2 Schematic diagram of a method flow in an embodiment of the present invention;

[0040] Numbers in the figure: 110 - data acquisition module; 120 - data differentiation module; 130 - fusion analysis unit; 1301 - determination module; 140 - confidence calculation module. DETAILED DESCRIPTION

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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 described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0042] The existing technology has many shortcomings in the actual application of fault location calculation. Among them, due to the diversity and complexity of distribution network lines, the location effect of current grounding faults corresponding to power supply faults in the power grid line is not ideal, which sometimes leads to positioning errors, thereby increasing the number of fault location operations and reducing the efficiency of power line maintenance.

[0043] Based on this, the present invention proposes a distribution network line power supply fault location method and system based on intelligent distributed ranging. By segmenting and collecting the fault points of the preset distribution network lines, the segmented lines can be distinguished according to the number of fault occurrences, so that when a fault occurs in the future time period, the fault location can be more concentrated on the distinguished high fault rate line segments, thereby improving the efficiency of fault location.

[0044] The present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0045] Reference Figures 1 to 2 , is an embodiment of the present invention, which provides a method for locating a power supply fault in a distribution network based on intelligent distributed ranging, comprising the following steps:

[0046] Step S10: Obtain historical fault location points of a preset line, divide the preset line into several line segments, and obtain the line segments corresponding to each historical fault location point;

[0047] It should be noted that in this embodiment, a preset line is divided into a plurality of line segments, the number of which is at least 5 or more. The 5 line segments are marked as L1 segment, L2 segment, L3 segment, L4 segment, and L5 segment. The current value of each line segment when a historical fault occurs is collected, and infrared thermal imaging data corresponding to the fault location point in the corresponding line segment is obtained based on the current value.

[0048] Operating experience in distribution network lines shows that during a ground fault, when a short circuit occurs, the current increases. This is because the resistance in the circuit decreases while the voltage remains constant during a short circuit. According to Ohm's law (I = U / R), when the voltage U remains constant, the decrease in resistance R causes the current I to increase. During a short circuit, the current provided by the power supply will be much greater than when the circuit is open, causing the current to flow directly through the conductor without passing through the load, forming a closed loop. Therefore, using the current value as a reference is of practical significance.

[0049] Step S20: Based on the acquired line segments corresponding to the historical fault location points, the number of historical fault occurrences of each line segment is counted, and the fault coordinates corresponding to any fault are obtained;

[0050] It should be noted that the fault coordinates correspond to the fault location point;

[0051] Step S30: Count the number of fault coordinates and differentiate the divided line segments based on the counted number of fault coordinates. The differentiation method includes dividing the line segments into high fault rate line segments, medium fault rate line segments, and low fault rate line segments. The current value of the preset line initial point when the fault occurs is collected based on the high fault rate line segment. At the same time, the current value is collected based on the current value to the current value of the line segment corresponding to the fault coordinate to generate the current value coefficient A. R ;

[0052] Step S40: At the current coefficient A R At least 10 current data points are collected based on the distance from the preset line initial point to the corresponding line segment. Analyze the current data that appears the most times up to the corresponding line section, and analyze the change pattern of the current data up to the fault point of the corresponding line section based on the current data;

[0053] Specifically, in this embodiment, current data is collected based on the distance from a preset line initial point to a corresponding line segment, and the collection method includes:

[0054] When the distance from the preset line initial point to the corresponding line section is 1 to 3 km, the number of current data collected is ≥ 10;

[0055] When the distance from the preset line initial point to the corresponding line section is 3 to 5 km, the number of current data collected is ≥ 13;

[0056] When the distance from the preset line initial point to the corresponding line section is 5 to 7 km, the number of current data collected is ≥ 16;

[0057] Among the different numbers of current data collected, the confidence level of fault occurrence in different line sections in the future period is obtained based on the first three current data. The first three current data are marked as independent group current data. The acquisition method is calculated according to the following formula:

[0058] Wherein, wj represents the wth independent group of current data collected at the jth time in the line segment;

[0059] In the formula, H represents the number of times the same independent group current data appears in the acquisition cycle, with every ten faults as an independent group current data acquisition cycle; λ represents the number of times different independent group current data appears in the acquisition cycle; G x Indicates the Gth different independent group current data obtained for the xth time in the acquisition cycle;

[0060] If the number of times the same independent group current data appears is ≤5 in the acquisition cycle, the confidence level is low; otherwise, no confidence level is determined.

[0061] Furthermore, in this embodiment, during an acquisition cycle, the variation patterns of the three current data included therein are analyzed based on the same independent group current data, and the median current data between the first two current data is analyzed based on the first two current data. If the median current data between the first two current data in the independent group current data collected in a future period is inconsistent with the median current data in the acquisition cycle, then the probability of a fault occurring in the corresponding line segment is determined to be low; otherwise, no fault is determined.

[0062] This embodiment further includes collecting data from two fault location points that are furthest apart from each other among the fault location points that appear during the acquisition cycle based on the same independent set of current data. When a fault occurs in the line section in the future time period, infrared thermal imaging data is collected within the interval, and the area within the interval is marked as a primary acquisition area, and the area outside the interval is marked as a secondary acquisition area.

[0063] At the same time, in this embodiment, the acquired infrared thermal imaging data are sorted in ascending order in the main acquisition area. The infrared thermal imaging data with the highest number of occurrences is analyzed in the sorted data and marked as the first infrared thermal imaging data. When infrared thermal imaging data of the corresponding line segment needs to be collected based on the fault location point in the future, the first infrared thermal imaging data is used as the target for collection.

[0064] Furthermore, current data corresponding to the first infrared thermal imaging data is obtained, and the closest values ​​greater than and less than the current data are obtained based on the current data. When the first infrared thermal imaging data is not successfully collected in a future period using the current data corresponding to the first infrared thermal imaging data, the data is re-collected based on the closest values ​​greater than and / or less than the current data.

[0065] On the basis of the above, this embodiment obtains the proportion of successful infrared thermal imaging data acquisition based on the closest value greater than and / or less than the current data. When the proportion of one of the two is larger, the one with the larger proportion is used as the closest value as the basis for re-acquisition.

[0066] Step S50: When the changing rule is that the current data shows an increasing trend, a safety threshold is preset based on the current data that appears the most times up to the corresponding line segment. When the current data from the preset line to the initial point of the corresponding line segment in the future time period is consistent with the safety threshold, it is determined that the current of the line segment will increase and a fault warning is issued. Otherwise, no determination is made.

[0067] Based on the above, it can be seen that the present application can distinguish the segmented lines according to the number of fault occurrences by segmented collection of fault points of the preset distribution network lines, so that when a fault occurs in a future time period, the fault location of the distinguished high fault rate line segments can be more concentrated, thereby improving the efficiency of fault location. At the same time, in the corresponding line segment, by giving two fault location points with the farthest interval, when a fault occurs in the corresponding line segment in the future time period, the maintenance personnel can collect the fault point between the two fault location points with the farthest interval to obtain the corresponding infrared thermal imaging data, which not only improves the accuracy of fault point location, but also further improves the efficiency of fault point location.

[0068] This embodiment combines the above-mentioned distribution network line power supply fault location method based on intelligent distributed ranging and also proposes a working system applied to this method, as follows:

[0069] The data acquisition module 110 is configured to obtain historical fault location points of a preset line, divide the preset line into a number of line segments, and obtain line segments corresponding to each historical fault location point; based on the obtained line segments corresponding to each historical fault location point, count the number of historical faults that occurred in each line segment, and obtain the fault coordinates corresponding to any fault;

[0070] A data differentiation module 120 is configured to count the number of fault coordinates and differentiate the divided line segments based on the counted number of fault coordinates;

[0071] The distinction method includes dividing the line segment into a high fault rate line segment, a medium fault rate line segment, and a low fault rate line segment, and collecting the current value of the preset line initial point when the fault occurs based on the high fault rate line segment, and at the same time collecting the current value based on the current value to the current value of the line segment corresponding to the fault coordinate to generate the current value coefficient A R ;

[0072] Fusion analysis unit 130, in the current value coefficient A R It is used to collect at least 10 current data points based on the distance from the preset line initial point to the corresponding line segment. Analyze the current data that appears the most times up to the corresponding line segment, and analyze the change pattern of the current data up to the fault point of the corresponding line segment based on the current data; the fusion analysis unit 130 includes a determination module 1301;

[0073] The determination module 1301 is configured to, when the current data shows an increasing trend, preset a safety threshold based on the current data that appears the most times up to the corresponding line segment. If the current data from the preset line to the initial point of the corresponding line segment in the future period is consistent with the safety threshold, it is determined that the current of the line segment will increase and a fault warning is issued. Otherwise, no determination is made.

[0074] The confidence calculation module 140 responds to the fusion analysis unit 130 and is used to obtain the confidence of faults occurring in different line sections in future time periods based on the first three current data among different numbers of current data collected.

[0075] In summary, the present invention can distinguish the segmented lines according to the number of fault occurrences by segmented collection of fault points of the preset distribution network lines, so that when a fault occurs in a future time period, the fault location of the distinguished high fault rate line segments can be more concentrated, thereby improving the efficiency of fault location. In addition, the fault point can be locked by tracking the current data with the largest number of occurrences corresponding to historical faults in the corresponding line segment, so that infrared thermal imaging data can be collected more quickly in the corresponding line segment, and then the corresponding line segment can be repaired. At the same time, in the corresponding line segment, by giving two fault location points with the farthest interval, when a fault occurs in the corresponding line segment in the future time period, maintenance personnel can collect the fault point between the two fault location points with the farthest interval to obtain the corresponding infrared thermal imaging data, which not only improves the accuracy of fault location, but also further improves the efficiency of fault location.

[0076] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for locating power supply faults in a distribution network based on intelligent distributed ranging, characterized in that: The following steps are involved: step S10: Obtain historical fault location points of a preset line, divide the preset line into a plurality of line segments, and obtain line segments corresponding to each historical fault location point; Step S20: based on the obtained line segments corresponding to each historical fault location point, counting the number of historical fault occurrences of each line segment, and obtaining the fault coordinates corresponding to any one fault; Step S30: Count the number of fault coordinates, and distinguish the divided line segments based on the counted number of fault coordinates. The distinguishing method includes distinguishing the line segments into high fault rate line segments, medium fault rate line segments, and low fault rate line segments, and collecting the current value of the preset line initial point when the fault occurs based on the high fault rate line segment, and collecting the current value to the line segment corresponding to the fault coordinate based on the current value to generate the current value coefficient A R ; Step S40: At the current value coefficient A R At least 10 current data are collected according to the distance from the preset line initial point to the corresponding line segment. Analyze the current data with the largest number of occurrences up to the corresponding line segment, and analyze the change pattern of the current data up to the fault point of the corresponding line segment based on the current data; Step S50: When the change rule is that the current data shows an increasing trend, a safety threshold is preset based on the current data that appears the most times to the corresponding line segment. When the current data from the preset line to the initial point of the corresponding line segment in the future time period is consistent with the safety threshold, it is determined that the current of the line segment will increase and a fault warning is issued. Otherwise, no determination is made.

2. The method for locating power supply faults in a distribution network based on intelligent distributed ranging according to claim 1, characterized in that: In the step S10, the preset line is divided into a plurality of line segments, the number of which is at least 5, and the 5 line segments are marked as L1 section, L2 section, L3 section, L4 section and L5 section, and the current value of each line segment when a historical fault occurs is collected, and infrared thermal imaging data corresponding to the fault location point in the corresponding line segment is obtained based on the current value.

3. The method for locating power supply faults in a distribution network based on intelligent distributed ranging according to claim 1, characterized in that: In the step S40, current data is collected according to the distance from the preset line initial point to the corresponding line segment, and the collection method includes: When the distance from the preset line initial point to the corresponding line section is 1 to 3 km, the number of current data collected is ≥ 10; When the distance from the preset line initial point to the corresponding line section is 3-5 km, the number of current data collected is ≥13; When the distance from the preset line initial point to the corresponding line section is 5 to 7 km, the number of current data collected is ≥ 16; Among the different numbers of current data collected, the confidence of the occurrence of faults in different line segments in the future period is obtained based on the first three current data, wherein the first three current data are marked as independent group current data, and the acquisition method is calculated according to the following formula: Wherein, wj represents the wth independent group of current data collected for the jth time in the line segment; Wherein, H represents the number of times the same independent group current data appears in the acquisition cycle with every ten faults as one independent group current data acquisition cycle; λ represents the number of times different independent group current data appears in the acquisition cycle, G x represents the Gth different independent group current data acquired for the xth time in the acquisition cycle; When the number of occurrences of the same independent set of current data is ≤5 times in the acquisition cycle, it is determined that the confidence is low; otherwise, no determination is made.

4. The method for locating power supply fault in a distribution network based on intelligent distributed ranging according to claim 3, characterized in that: In the acquisition cycle, the change rules of the three current data contained therein are analyzed based on the same independent group current data, and the median current data between the first two current data are analyzed based on the first two current data. When the median current data between the first two current data in the independent group current data collected in the future time period is inconsistent with the median current data in the acquisition cycle, it is determined that the probability of failure of the corresponding line section is low, otherwise, no determination is made.

5. The method for locating power supply fault in a distribution network based on intelligent distributed ranging according to claim 4, characterized in that: In the acquisition cycle, two fault location points with the farthest interval among the fault location points are collected based on the same independent group of current data. When a fault occurs in the line section in a future period, the infrared thermal imaging data is collected within the interval distance, and the area within the interval distance is marked as the main collection area, and the area outside the interval distance is marked as the secondary collection area.

6. The method for locating power supply fault in a distribution network based on intelligent distributed ranging according to claim 5, characterized in that: In the main acquisition area, the acquired infrared thermal imaging data are sorted in ascending order. In the sorted data, the infrared thermal imaging data with the largest number of occurrences is analyzed, and the infrared thermal imaging data is marked as the first infrared thermal imaging data. When the infrared thermal imaging data of the corresponding line segment needs to be collected according to the fault location point in the future period, the first infrared thermal imaging data is used as the target for collection.

7. The method for locating power supply fault in a distribution network based on intelligent distributed ranging according to claim 6, characterized in that: Acquire current data corresponding to the first infrared thermal imaging data, and acquire the closest values ​​greater than and less than the current data based on the current data; when the first infrared thermal imaging data is acquired in a future time period based on the current data corresponding to the first infrared thermal imaging data but the acquisition is unsuccessful, re-acquire based on the closest values ​​greater than and / or less than the current data.

8. The method for locating power supply fault in a distribution network based on intelligent distributed ranging according to claim 7, characterized in that: The proportion of successful acquisition of the infrared thermal imaging data based on the closest value greater than and / or less than the current data is obtained. When one of the values ​​greater than and / or less than the current data accounts for a larger proportion, the data is re-acquired based on the closest value.

9. A distribution network line power supply fault location system based on intelligent distributed ranging, applied to the distribution network line power supply fault location method based on intelligent distributed ranging as claimed in claim 1, characterized in that: include: A data acquisition module is used to obtain historical fault location points of a preset line, divide the preset line into a number of line segments, and obtain line segments corresponding to each historical fault location point; and based on the obtained line segments corresponding to each historical fault location point, count the number of historical fault occurrences of each line segment, and obtain the fault coordinates corresponding to any fault; A data differentiation module, used for counting the number of fault coordinates and distinguishing the divided line segments based on the counted number of fault coordinates; The distinguishing method includes distinguishing the line segment into a high fault rate line segment, a medium fault rate line segment and a low fault rate line segment, and collecting the current value of the preset line initial point when the fault occurs based on the high fault rate line segment, and collecting the current value to the current value of the line segment corresponding to the fault coordinate based on the current value to generate the current value coefficient A R ; Fusion analysis unit, in the current value coefficient A R In the embodiment, at least 10 current data are collected according to the distance from the preset line initial point to the corresponding line segment. Analyze the current data with the most occurrences up to the corresponding line segment, and analyze the change law of the current data up to the fault point of the corresponding line segment based on the current data; the fusion analysis unit includes a determination module; The determination module is used for, when the change rule is that the current data shows an increasing trend, presetting a safety threshold based on the current data that appears the most times to the corresponding line segment, and when the current data from the preset line to the initial point of the corresponding line segment in the future period is consistent with the safety threshold, determining that the current of the line segment will increase and issuing a fault warning, otherwise, no determination is made; A confidence calculation module, which responds to the fusion analysis unit and is used to obtain the confidence of faults occurring in different line segments in future time periods based on the first three current data collected from different numbers of current data.

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