Power system fault location method, system and computer readable storage medium

Abstract

The application relates to a power system fault positioning method, a system and a computer readable storage medium. The power system fault positioning method is applied to an ultrasonic detector, and comprises the following steps: detecting a detection position of a power system by using the ultrasonic detector, and acquiring distance information and imaging information of the detection position; and transmitting the distance information and the imaging information to a cloud network. The cloud network is used for positioning a fault position of the power system according to a comparison result of the distance information and the imaging information. When the ultrasonic technology is used to position the fault position, the imaging information is used to test the fault position, so that the defect that the ultrasonic positioning fault position is inaccurate due to external signal interference can be overcome, and the accuracy and reliability of the positioning result of the fault position are improved.

Description

Technical Field

[0001] This application belongs to the field of power system technology, and in particular relates to a power system fault location method, system and computer-readable storage medium. Background Technology

[0002] Ultrasound is a sound wave with a frequency higher than 2000 Hz. It has good directionality, strong penetrating power, and is easy to concentrate, making it widely used in various fields, such as ranging, speed measurement, cleaning, welding, stone crushing, and sterilization. Especially in power systems, ultrasound is often used for fault location and alarm. However, current ultrasonic positioning methods are susceptible to external signal interference, and the accuracy of fault location cannot be guaranteed when using ultrasound in power systems. Summary of the Invention

[0003] In view of this, embodiments of this application provide a power system fault location method, system, and computer-readable storage medium to solve the problem that the prior art cannot guarantee the accurate location of power system faults.

[0004] A first aspect of this application provides a power system fault location method applied to an ultrasonic detector. The method includes: using the ultrasonic detector to detect a detection point in the power system and obtaining distance information and imaging information of the detection point; transmitting the distance information and the imaging information to a cloud network, wherein the cloud network is used to locate the fault location of the power system based on a comparison result between the distance information and the imaging information.

[0005] In one embodiment, obtaining the distance information of the detection part includes: dividing the detection part into N×N grid parts, obtaining the distance information of the N×N grid parts; and performing adjustment calculation on the distance information of the N×N grid parts to obtain the distance information of the detection part.

[0006] In one embodiment, adjusting the distance information of the N×N grid locations to obtain the distance information of the detection location includes: calculating the average value k of the distance information of the N×N grid locations as follows:

[0007]

[0008] The distance information G of the detected location is calculated based on the average value k:

[0009]

[0010] In one embodiment, transmitting the imaging information to a cloud network includes: dividing the imaging information into N×N raster images and obtaining the grayscale value of each raster image; calculating the difference between the grayscale values ​​of the outer edges of the N×N raster images based on the grayscale values ​​of the centers of the N×N raster images; compressing and encoding the N×N raster images after the difference calculation, and then transmitting them to the cloud network.

[0011] In one embodiment, the cloud network is specifically used for: sequentially arranging the distance information to form a band curve, obtaining the detection location corresponding to the peak point of the band curve; decoding and adjusting the N×N grid images to convert them into imaging data; and comparing the distance information with the imaging data to locate the fault location of the detection location.

[0012] A second aspect of this application provides a power system fault location method applied to a cloud network. The method includes: receiving distance information and imaging information transmitted by an ultrasonic detector, wherein the ultrasonic detector is used to detect a detection part of the power system to obtain the distance information and the imaging information; and locating the fault location of the power system based on a comparison result of the distance information and the imaging information.

[0013] In one embodiment, the ultrasonic detector is specifically used to: divide the detection area into N×N grid areas, obtain the distance information of the N×N grid areas; and perform adjustment calculations on the distance information of the N×N grid areas to obtain the distance information of the detection area.

[0014] In one embodiment, the ultrasonic detector is specifically used to: calculate the average value k of the distance information of the N×N grid locations as follows:

[0015]

[0016] The distance information G of the detected location is calculated based on the average value k:

[0017]

[0018] In one embodiment, the ultrasonic detector is specifically used to: divide the imaging information into N×N grid images and obtain the grayscale value of each grid image; calculate the difference between the grayscale values ​​of the outer edges of the N×N grid images based on the grayscale value of the center of the N×N grid images; and transmit the N×N grid images after the difference calculation to the cloud network after compression encoding.

[0019] In one embodiment, locating the fault location of the power system based on the comparison result of the distance information and the imaging information includes: arranging the distance information sequentially to form a band curve, obtaining the detection location corresponding to the peak point of the band curve; decoding and adjusting the N×N grid images to convert them into imaging data; and comparing the distance information with the imaging data to locate the fault location of the detection location.

[0020] A third aspect of this application provides a positioning system including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method as described in either the first or second aspect.

[0021] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in either the first or second aspect.

[0022] The present application discloses a power system fault location method, system, and computer-readable storage medium, which have the following advantages compared with the prior art:

[0023] (1) In this embodiment, an ultrasonic detector is used to acquire distance and imaging information of different detection points within the power system. The distance information of these different detection points is then arranged on a cloud network to form a band curve. The peak point on the band curve is marked as the fault location. The accuracy of the fault location is further verified by comparing the imaging information with the distance information of the fault location. When using ultrasonic technology to locate fault points, using imaging information to verify the fault location can overcome the inaccuracy of ultrasonic fault location due to external signal interference, thus improving the accuracy and reliability of the fault location results.

[0024] (2) In this embodiment, the detection area is divided into N×N grid areas, and the distance information of the N×N grid areas is used for adjustment to obtain the distance information of the detection area. When there are damaged parts in the detection area, digital grid processing and adjustment of the detection area can improve the positioning accuracy of the damaged parts, reduce measurement errors, and determine the fault location inside the power system more accurately and quickly.

[0025] (3) In this embodiment of the application, the imaging information is divided into N×N grid images and encoded and compressed according to the gray value, which can greatly reduce the total size of ultrasonic imaging transmission, reduce the imaging transmission time, improve the efficiency of data transmission, ensure the accuracy of imaging information, and thus ensure the accuracy of the inspection results of fault points. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram illustrating the implementation process of a power system fault location method provided in an embodiment of this application;

[0028] Figure 2 This is a schematic diagram of the distance information of 3×3 grid areas of the detection area provided in the embodiments of this application;

[0029] Figure 3 This is a simplified distance information diagram provided in an embodiment of this application;

[0030] Figure 4 This is a schematic diagram of the imaging information of the detection area provided in the embodiments of this application;

[0031] Figure 5 This is a schematic diagram of the imaging information compression and encoding process provided in the embodiments of this application;

[0032] Figure 6 This is a schematic diagram of a curve formed by arranging distance information of a power system according to an embodiment of this application;

[0033] Figure 7 This is a schematic diagram illustrating the implementation process of a power system fault location method provided in an embodiment of this application;

[0034] Figure 8 This is a schematic diagram of a positioning system provided in an embodiment of this application. Detailed Implementation

[0035] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0036] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0037] An ultrasonic detector emits ultrasonic waves towards the detection point and starts timing simultaneously. The ultrasonic waves return after encountering an obstacle during propagation, and timing stops upon receiving the reflected wave. During this process, the ultrasonic detector uses the propagation speed of the ultrasonic waves and the detection time t to calculate the distance between the detection point and the ultrasonic detector, using the formula L = 340t. Because ultrasonic waves are easily interfered with by external signals, current methods for locating faults in power systems using ultrasonic detectors are prone to inaccurate fault location results if the ultrasonic waves are affected by external signals.

[0038] Based on the problems existing in the current technology, such as Figure 1 As shown, a first aspect of this application provides a power system fault location method, applied to an ultrasonic detector, the method comprising the following steps:

[0039] S101. Use an ultrasonic detector to detect the detection points of the power system and obtain the distance information and imaging information of the detection points respectively.

[0040] In one implementation, obtaining distance information of the detection location includes:

[0041] The detection area is divided into N×N grid areas, and the distance information of the N×N grid areas is obtained;

[0042] The distance information of the N×N grid locations is adjusted and converted to obtain the distance information of the detected location.

[0043] Specifically, the distance information of N×N grid locations is adjusted and converted to obtain the distance information of the detected location, including:

[0044] The average value k of the distance information of N×N grid locations is calculated as follows:

[0045]

[0046] The distance information G of the detected location is calculated based on the average value k:

[0047]

[0048] In this embodiment, power system detection refers to detecting the interior of the power system lines to identify fault points and factors. The area detected by the ultrasonic detector is called the detection area. The ultrasonic detector utilizes an external piezoelectric lens to achieve ultrasonic detection sensing and imaging. By calculating the transmission speed of the ultrasonic wave and the detection time for receiving the reflected wave, the distance between the detection area and the ultrasonic detector can be calculated. Based on the distance between different detection areas and the ultrasonic detector, imaging information about the interior of the power line can be obtained.

[0049] For the distance information of the detection location, this embodiment divides the detection location into N×N grid locations using a digital grid. By changing the detection direction of the ultrasonic detector, the distance information of each grid location can be obtained. The distance information of the detection location can be obtained by adjusting the distance information of the N×N grid locations. The specific process of adjustment is as follows: calculate the average value k of the distance information of the N×N grid locations, and calculate the difference average value based on the average value k to obtain the distance information G of the detection location.

[0050] For example, such as Figure 2 and Figure 3 As shown, in this embodiment, the detection area is divided into 3×3 grid areas. The distance information of the 3×3 grid areas are g1, g2, g3, g4, g5, g6, g7, g8, and g9, respectively (distances are 1430653, 1430438, 1430278, 1430645, 1429998, 1429732, 1430656, 1429432, and 1428523, or the difference between the peripheral data and the data based on the center point). The average value k of the distance information of the 3×3 grid areas is calculated as follows: Using the calculated average value k, the distance information G of the detected location is obtained by adjusting the distance information of the 3×3 grid area:

[0051]

[0052] This application embodiment digitally rasterizes the detection area into N×N grid areas, and adjusts the distance information of the N×N grid areas to obtain the distance information of the detection area. When there is partial line damage at the detection area, the damaged area is farther from the ultrasonic detector than other areas. If a traditional ultrasonic detector is used to detect the area, the distance obtained does not take into account the distance of the damaged area, making it impossible to accurately determine whether the detection area is damaged, thus affecting the accuracy of fault location. Therefore, this application embodiment can improve the positioning accuracy of the detection area and more accurately and quickly determine the fault location within the power system.

[0053] As mentioned above, for imaging information of power systems, the internal imaging information of the line can be obtained based on the distance between different detection points and the ultrasonic detector. This internal imaging information is composed of different detection points. For example, based on the maximum distance of a certain point, the ratio of that maximum distance to the distances of other points in the power system is calculated. This ratio is then used as a grayscale value, and a grayscale image is displayed from white to black to form the imaging information. Figure 4As shown. Additionally, gamma correction can be applied to the imaging information within the circuit to further improve image contrast.

[0054] S102. The distance information and imaging information are transmitted to the cloud network, which is used to locate the fault location of the power system based on the comparison results of the distance information and imaging information.

[0055] In this embodiment, the ultrasonic detector transmits the processed distance and imaging information to a cloud network. The cloud network refers to a network that uses computer terminals to process data. By comparing the distance and imaging information using the cloud network, the fault location of the power system can be accurately located.

[0056] The distance information is transmitted to the cloud network, and the data is packaged and uploaded to the cloud network via wireless signal transmission. For details, please refer to the existing technology. This application will not elaborate on this aspect in the embodiments.

[0057] In one implementation, transmitting imaging information to a cloud network includes the following steps:

[0058] The imaging information is divided into N×N raster images, and the grayscale value of each raster image is obtained;

[0059] Based on the gray values ​​of the center of N×N raster images, the difference between the gray values ​​of the outer perimeter of N×N raster images is calculated.

[0060] After the N×N raster images with the difference calculated are compressed and encoded, they are transmitted to the cloud network.

[0061] Transmitting imaging information to the cloud network requires compression and encoding of the imaging information first. The compression and encoding process in this embodiment mainly includes: converting the grayscale value of the imaging information of the detected part into a digital raster form, that is, dividing the imaging information into N×N raster images and obtaining the grayscale value corresponding to each raster image; in order to further reduce the total amount of imaging information transmitted and improve the transmission efficiency, this embodiment calculates the difference between the grayscale value of the center of the raster image and the grayscale value of the periphery of the raster image; and then encodes and compresses the raster image after the difference calculation in a preset order.

[0062] For example, such as Figure 5As shown, in this embodiment, the imaging information inside the line is divided into m×n 3×3 grid images. Each 3×3 grid image corresponds to a detection part, and the value of each grid image corresponds to a gray value. Taking the gray value at the center of the grid image as a reference, the difference between the gray values ​​of the surrounding areas is calculated. For example, taking the imaging information of one detection part as an example, the gray value at the center of the 3×3 grid image is 025, and the gray values ​​of the surrounding areas are 031, 027, 026, 030, 024, 032, 022, and 018, respectively. The difference between the gray values ​​of the other grid images is calculated based on 025, resulting in 6, 2, 1, 5, -1, 7, -3, and -7, respectively. Similarly, the 3×3 grid images of other imaging information are processed. Then, the processed m×n 3×3 grid images are encoded and compressed in order from left to right and from top to bottom. The encoding and data compression operations can be found in existing technologies, and will not be described in detail in the embodiments of this application.

[0063] This application embodiment digitally rasterizes the imaging information of the detection area into N×N raster images, and then simplifies and compresses these N×N raster images to reduce the total amount and time of imaging information transmission, thereby improving the efficiency of data transmission, ensuring the accuracy of imaging information, and thus ensuring the accuracy of the test results.

[0064] In one implementation, the cloud network is used to locate the fault location of the power system based on a comparison of distance information and imaging information, specifically for:

[0065] The distance information is arranged sequentially to form a band curve, and the detection location corresponding to the peak point of the band curve is obtained.

[0066] Adjustment and conversion are performed on N×N raster images to convert them into imaging data;

[0067] By comparing distance information with imaging data, the location of the fault in the power system can be determined.

[0068] Understandably, after transmitting the packaged distance information and the compressed imaging information to the cloud network, the cloud network receives the packaged distance information and the compressed imaging information, performs parsing processing on the distance information and reverse decoding processing on the imaging information, and accurately locates the fault location of the power system based on the distance information and the imaging information.

[0069] Specifically, such as Figure 6As shown, the distance information of different detection locations is arranged sequentially to form band curves. A band curve is a curve with fluctuating changes. The detection location corresponding to the peak point in the band curve is marked as the fault location. Then, the N×N grid images after decoding are adjusted and transformed. The principle of the adjustment and transformation process for the distance information is the same as that of the distance information adjustment and transformation process mentioned above, and will not be repeated here. The imaging data corresponding to the detection location is obtained after adjustment and transformation. The imaging data of different detection locations are arranged sequentially to form the band curve of the imaging data. The peak point of the band curve of the imaging data is compared with the peak point of the band curve of the distance information. If the peak points of the two band curves are the same, the detection location corresponding to the peak point of the band curve of the distance information is determined to be the fault location. If the peak points of the two band curves are different, the detection location corresponding to the peak point of the band curve of the distance information is not the fault location.

[0070] This application embodiment arranges the distance information of different detection locations to form a band curve, and locates the peak point on the band curve as the fault location of the power system. The imaging information is converted into imaging data using the same adjustment and conversion data method as the distance information. The imaging data is arranged to form a band curve. By comparing the peak point of the imaging data band curve with the peak point on the band curve formed by the distance information, it can be verified whether the fault location located by the distance information is accurate.

[0071] The second aspect of this application provides a method for locating faults in a power system, such as... Figure 7 As shown, when applied to a cloud network, the method includes the following steps:

[0072] S201. Receive distance information and imaging information transmitted by an ultrasonic detector, wherein the ultrasonic detector is used to detect the detection parts of the power system and obtain distance information and imaging information.

[0073] S202. Based on the comparison results of distance information and imaging information, locate the fault location of the power system.

[0074] In one implementation, the ultrasonic detector is specifically used for:

[0075] The detection area is divided into N×N grid areas, and the distance information of the N×N grid areas is obtained;

[0076] The distance information of the N×N grid locations is adjusted and converted to obtain the distance information of the detected location.

[0077] In one implementation, the ultrasonic detector is specifically used for:

[0078] The average value k of the distance information of N×N grid locations is calculated as follows:

[0079]

[0080] The distance information G of the detected location is calculated based on the average value k:

[0081]

[0082] In one implementation, the ultrasonic detector is specifically used for:

[0083] The imaging information is divided into N×N raster images, and the grayscale value of each raster image is obtained;

[0084] Based on the gray values ​​of the center of N×N raster images, the difference between the gray values ​​of the outer perimeter of N×N raster images is calculated.

[0085] After the N×N raster images with the difference calculated are compressed and encoded, they are transmitted to the cloud network.

[0086] In one implementation, locating the fault location of the power system based on a comparison of distance information and imaging information includes:

[0087] The distance information is arranged sequentially to form a band curve, and the detection location corresponding to the peak point of the band curve is obtained;

[0088] Adjustment and conversion are performed on N×N raster images to convert them into imaging data;

[0089] By comparing distance information with imaging data, the location of the fault in the power system can be determined.

[0090] The principle and implementation process of the second aspect of this application are the same as those of the above embodiments. For details, please refer to the description of the above embodiments, which will not be repeated here.

[0091] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0092] like Figure 8 As shown, a third aspect of this application provides a positioning system, including: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80. When the processor 80 executes the computer program 82, it implements the steps described in the above-described power system fault location method embodiments.

[0093] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the power system fault location method described above.

[0094] For example, the computer program 82 may be divided into one or more modules / units, which are stored in the memory 81 and executed by the processor 80 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 82 in the thermal printer.

[0095] The processor 80 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0096] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0097] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0098] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0099] In the embodiments provided in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0100] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0101] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0102] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0103] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for locating faults in a power system, characterized in that, Applied to an ultrasonic detector, the method includes: The ultrasonic detector is used to detect the detection points of the power system and obtain the distance information of the detection points. Based on the maximum distance information of a certain detection point, the ratio of the maximum distance information to the distance information of other detection points in the power system is calculated. The ratio is used as a gray value and gray value image is displayed from white to black to form imaging information. The distance information and the imaging information are transmitted to a cloud network. The cloud network is used to arrange the distance information of different detection locations to form band curves, locate the peak points on the band curves as the fault locations of the power system, and arrange the imaging information after adjustment to form band curves. The peak points on the band curves formed by the imaging information are compared with the peak points on the band curves formed by the distance information to locate the fault locations of the power system.

2. The power system fault location method according to claim 1, characterized in that, The process of obtaining the distance information of the detected location includes: The detection area is divided into N×N grid areas, and the distance information of the N×N grid areas is obtained; The distance information of the N×N grid locations is adjusted and converted to obtain the distance information of the detection location.

3. The power system fault location method according to claim 2, characterized in that, The adjustment and conversion of the distance information of the N×N grid locations to obtain the distance information of the detected location includes: The average value k of the distance information of the N×N grid locations is calculated as follows: ； The distance information G of the detected location is calculated based on the average value k: 。 4. The power system fault location method according to claim 1, characterized in that, The step of transmitting the imaging information to the cloud network includes: The imaging information is divided into N×N grid images, and the grayscale value of each grid image is obtained; Based on the gray values ​​of the centers of the N×N raster images, the difference between the gray values ​​of the outer edges of the N×N raster images is calculated. After the N×N raster images with the difference calculated are compressed and encoded, they are transmitted to the cloud network.

5. A power system fault location method according to claim 4, characterized in that, The cloud network is specifically used for: The distance information is arranged sequentially to form a band curve, and the detection location corresponding to the peak point of the band curve is obtained; The N×N raster images are adjusted and converted into imaging data; The distance information is compared with the imaging data to locate the fault location of the power system.

6. A method for locating faults in a power system, characterized in that, Applied to cloud networks, the method includes: The system receives distance information and imaging information transmitted by an ultrasonic detector. The ultrasonic detector is used to detect the detection points of the power system and obtain the distance information. Based on the maximum distance information of a certain detection point, the system calculates the ratio of the maximum distance information to the distance information of other detection points in the power system. The ratio is used as a grayscale value to form the imaging information by displaying a grayscale image from white to black. Distance information from different detection locations is arranged to form band curves. The peak points on the band curves are used to locate the fault locations of the power system. After adjustment and conversion of the imaging information, the band curves are arranged to form band curves. The peak points on the band curves formed by the imaging information are compared with the peak points on the band curves formed by the distance information to locate the fault locations of the power system.

7. A power system fault location method according to claim 6, characterized in that, The ultrasonic detector is specifically used for: The detection area is divided into N×N grid areas, and the distance information of the N×N grid areas is obtained; The distance information of the N×N grid locations is adjusted and converted to obtain the distance information of the detection location.

8. A power system fault location method according to claim 7, characterized in that, The ultrasonic detector is specifically used for: The average value k of the distance information of the N×N grid locations is calculated as follows: ； The distance information G of the detected location is calculated based on the average value k: 。 9. A power system fault location method according to claim 6, characterized in that, The ultrasonic detector is specifically used for: The imaging information is divided into N×N grid images, and the grayscale value of each grid image is obtained; Based on the gray values ​​of the centers of the N×N raster images, the difference between the gray values ​​of the outer edges of the N×N raster images is calculated. After the N×N raster images with the difference calculated are compressed and encoded, they are transmitted to the cloud network.

10. A power system fault location method according to claim 9, characterized in that, The step of locating the fault location of the power system based on the comparison result of the distance information and the imaging information includes: The distance information is arranged sequentially to form a band curve, and the detection location corresponding to the peak point of the band curve is obtained; The N×N raster images are adjusted and converted into imaging data; The distance information is compared with the imaging data to locate the fault location of the power system.

11. A positioning system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5 or any one of claims 6 to 10.

12. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5 or any one of claims 6 to 10.

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