Direct-current line low-impedance fault detection device and method

Abstract

The invention belongs to the technical field of line fault detection, and relates to a DC line low-impedance fault detection device and method. The method comprises the following steps: determining the end part of a direct-current bus with a low-impedance fault in a direct-current circuit; injecting an alternating current test signal to the end part of the direct current bus with the low-impedance fault, wherein other direct current buses in the direct current circuit normally operate and are electrified with direct current; fault position detection is conducted from one end of the bridge, magnetic field data and coordinate data along the bridge are obtained in real time, and when it is detected that the magnetic field data changes, the current position is judged to be the low-impedance fault position; and according to the coordinate data of the position where the low-impedance fault occurs, positioning the fault position of the bridge, and based on the fault position of the bridge, carrying out line selection on a direct-current bus where the low-impedance fault occurs in the direct-current circuit. According to the invention, full-section automatic detection of the low-impedance fault of the DC line is realized, the position of the low-impedance fault is accurately positioned, the detection efficiency is improved, the detection accuracy is high, and the stability is good.

Description

Technical Field

[0001] The present invention belongs to the technical field of line fault detection, and relates to a DC line low-impedance fault detection device and method. Background Art

[0002] Photovoltaic power generation, as a representative of clean energy, has been widely applied in residential, commercial, and industrial fields. However, with the popularization of photovoltaic power generation systems, how to ensure the operation safety and stability of photovoltaic power stations has become one of the urgent problems to be solved. The DC power line of the photovoltaic array, as a core component in the system, is particularly prone to low-impedance faults caused by poor contact, aging, or external damage.

[0003] Currently, for the fault detection of DC power lines in cable trays, manual inspection is the main method. Workers carry various fault detectors and, on the premise of opening the cable tray cover, conduct fault detection along the lines. When maintenance personnel conduct manual inspections, contacts, or line replacements, they face the problem of chaotic lines, resulting in low work efficiency. Due to the large number (about 40) and density of DC power lines in the cable tray, with multiple DC cables arranged in parallel, it is easy to cause electromagnetic interference and common-mode interference, which also has a great impact on fault detection. For example, the capacitive impedance between lines and the interference between the line and the cable tray, etc., to a certain extent, affect the measurement results and lead to inaccurate measurements. In addition, this method not only relies on manual experience but also cannot cover a large range of power station equipment, has a low inspection frequency, and is prone to overlooking potential fault points. Especially in harsh environments, it is more difficult to ensure comprehensiveness and timeliness in manual inspections, and the probability of missed inspections and misjudgments is relatively high. Most electrical detection devices require workers to perform operations such as equipment connection, configuration, and measurement. The detection process is cumbersome and has high technical requirements for operators. Moreover, these devices cannot perform dynamic detection, that is, they cannot monitor the occurrence of faults in real time during the operation of the equipment.

[0004] There are a large number (about 40) and high density of DC power lines in the cable tray, all gathered in a small cable tray, with multiple DC cables arranged in parallel, which is easy to cause electromagnetic interference and common-mode interference, having a great impact on fault detection. The large number and close arrangement of DC power lines may cause problems such as chaotic lines when maintenance personnel conduct manual inspections, contacts, or line replacements, resulting in low work efficiency. If a DC power line fails, especially during replacement or repair, it may be necessary to disassemble the entire cable tray or a large number of DC power lines, with a large workload and easy damage to other cables.

[0005] Workers hold various fault detectors and, on the premise of opening the bridge cover, conduct fault detection along the line. Since the DC lines are dense and numerous, there are various interferences between the lines, such as the capacitive impedance between lines and the interference between the line and the bridge. To a certain extent, this affects the measurement results and leads to inaccurate measurement.

[0006] In summary, the existing low-impedance fault detection technologies generally have problems such as low efficiency, limited detection range, poor accuracy, inability to achieve automated monitoring, and difficulty in accurately detecting the fault location of photovoltaic systems. Summary of the Invention

[0007] The purpose of the present invention is to provide a DC line low-impedance fault detection device and method to solve the technical problems existing in the existing low-impedance fault detection technologies, such as low efficiency, limited detection range, poor accuracy, inability to achieve automated monitoring, and difficulty in accurately detecting the fault location of the photovoltaic DC bus. The present invention realizes the full-section automated detection of DC line low-impedance faults, accurately locates the low-impedance fault location, improves the detection efficiency, has high detection accuracy, and good stability.

[0008] To achieve the above purpose, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a DC line low-impedance fault detection method, including the following steps: Determine the end of the DC bus where a low-impedance fault occurs in the DC line; Inject an AC test signal into the end of the DC bus where a low-impedance fault occurs, and the other DC buses in the DC line operate normally with DC power; Start fault location detection from one end of the bridge, and obtain the magnetic field data and coordinate data along the bridge in real time. When the measured magnetic field data changes abnormally, determine that the current position is the low-impedance fault location; According to the coordinate data of the low-impedance fault location, locate the fault location of the bridge, and select the DC bus where the low-impedance fault occurs in the DC line based on the fault location of the bridge.

[0009] As a further improvement of the present invention, the determination of the end of the DC bus where a low-impedance fault occurs in the DC line includes: When a fault occurs in the photovoltaic power transmission system and causes a trip, the current and voltage of the DC bus in the DC line are sequentially tested by a test source, and the total impedance of each DC bus is calculated through the current and voltage. When the total impedance is lower than the threshold, it is determined that the corresponding DC bus has a fault.

[0010] As a further improvement of the present invention, the positioning of the fault location of the bridge according to the coordinate data of the low-impedance fault location further includes: Obtain the real-time time and the number of surface images at the location where the low-impedance fault occurs; Combine the coordinate data, real-time time, and surface image data at the location where the low-impedance fault occurs to accurately locate the fault location of the bridge through multi-source data, specifically including: Align the fault location detection time with the timestamp of the surface image data; superimpose the coordinate data with the digital model of the bridge to determine the specific section of the fault in the three-dimensional structure, and then accurately locate the fault location of the bridge.

[0011] As a further improvement of the present invention, among the real-time acquisition of magnetic field data, surface image data, coordinate data, and real-time time along the bridge, The magnetic field data is obtained by detecting coils located at the bottom of the bridge; The surface image data is obtained by a camera module synchronized with the detection coil; The coordinate data is obtained by a GPS / Beidou module.

[0012] As a further improvement of the present invention, the line selection of the DC bus where a low-impedance fault occurs in the DC line based on the fault location of the bridge includes: Apply a test source to one of the DC buses, and then use a line selection pliers to clamp the DC bus where the low-impedance fault occurs from the DC line.

[0013] In a second aspect, the present invention provides a DC line low-impedance fault detection device for implementing the DC line low-impedance fault detection method, including: An inspection trolley, on which a telescopic robotic arm is provided, and a detection coil is provided on the telescopic robotic arm; The inspection trolley is also provided with a camera module, a Lora module, a GPS / Beidou module, and a control system; The detection coil, the camera module, the telescopic robotic arm, the Lora module, and the GPS / Beidou module are all connected to the control system; the control system controls the inspection trolley to move along the bridge; The camera module and the GPS / Beidou module are both connected to the Lora module.

[0014] As a further improvement of the present invention, a power supply unit is provided on the inspection trolley, and the power supply unit is electrically connected to the detection coil, the telescopic robotic arm, the camera module, the Lora module, the GPS / Beidou module, and the control system respectively; Preferably, the inspection trolley includes a counterweight unit. The counterweight unit is connected to wheels through a shock absorption unit. The counterweight unit is also provided with a telescopic robotic arm, a camera module, a Lora module, a GPS / Beidou module, a control system, and a driving motor. The output end of the driving motor is connected to the input shaft of the wheel through a transmission unit, and the driving motor is electrically connected to the control system; The telescopic robotic arm includes a first telescopic part and a second telescopic part. Both the first telescopic part and the second telescopic part are electrically connected to the control system. The end of the first telescopic part is connected to the inspection trolley. The telescopic end of the first telescopic part is connected to the second telescopic part. The telescopic end of the second telescopic part is connected to the detection coil, and the detection coil is located at the bottom of the inspection trolley; Preferably, the detection coil is located at the bottom of the counterweight unit; The first telescopic part is arranged vertically, and the second telescopic part is arranged horizontally; The camera module is located on one side in the forward direction of the inspection trolley.

[0015] As a further improvement of the present invention, the inspection trolley starts from one end of the bridge to detect the fault location until the fault location where the low-impedance fault occurs is detected. The specific process of the fault location detection is as follows: Control the state of the telescopic robotic arm through the control system to make the detection coil located at the position with the strongest magnetic field under the bridge; Obtain the surface image data of the bridge in real time through the camera module, and the control system plans the driving trajectory of the inspection trolley according to the image data; Obtain the magnetic field data in real time through the detection coil, and transmit the magnetic field data to the control system for judgment. When the magnetic field data changes abnormally, it is judged that a low-impedance fault occurs in the DC bus at the current position.

[0016] As a further improvement of the present invention, the camera module obtains the surface image data of the bridge in real time, and the control system plans the driving trajectory of the inspection trolley according to the image data, specifically as follows: Obtain the surface image data of the bridge in real time through the camera module; Use Canny edge detection to process the surface image data of the bridge to extract the edge features of the bridge; Plan the driving trajectory of the inspection trolley according to the edge features of the bridge.

[0017] As a further improvement of the present invention, the detection coil obtains the magnetic field data in real time, and transmits the magnetic field data to the control system for judgment. When the magnetic field data changes abnormally, it is judged that a low-impedance fault occurs in the DC bus at the current position, specifically as follows: When the fluctuation range of the magnetic field intensity detected by the detection coil exceeds the threshold range, the inspection trolley stops moving forward. The detection coil is driven by a telescopic robotic arm to reciprocate horizontally and vertically for detection, further detecting the magnetic field intensity, and transmitting the magnetic field data to the control system; If the maximum detected magnetic field intensity is within the threshold range, the DC bus at that location is normal; If the maximum detected magnetic field intensity in this area is greater than the maximum threshold, it is determined that a low-impedance fault has occurred in the DC bus at the current position.

[0018] Preferably, compared with the prior art, the present invention has the following beneficial effects: Furthermore, the method of the present invention determines the ends of the DC bus where the low-impedance fault occurs, narrowing the detection range; an AC test signal is injected into the ends of the DC bus where the low-impedance fault occurs, and the other DC buses operate normally with direct current. While detecting the faulty line, the normal operation of other DC buses is not affected. The inspection trolley starts from one end of the bridge to detect the fault location until the location where the low-impedance fault occurs is detected. The image data of the bridge surface is obtained in real time through the camera module, and the control system plans the driving trajectory of the inspection trolley according to the image data to achieve full-section detection of the DC bus, improving the efficiency and reducing the risk of electric shock. The magnetic field data is obtained in real time through the detection coil and transmitted to the control system for judgment. When the magnetic field data changes abnormally, it is determined that a low-impedance fault has occurred in the DC bus at the current position, and the fault point is quickly determined based on the preset threshold. The coordinate data of the current fault location is obtained using the GPS / Beidou module, and the coordinate data and magnetic field data of the fault location are transmitted to the front-end machine through the Lora module to achieve remote reporting and real-time monitoring of the fault coordinates. The test source frequency is remotely switched to the line selection frequency, and then the line selection clamp is used to clamp each line in turn until the specific faulty line is selected. The present invention realizes the full-section automatic detection of low-impedance faults in DC lines, accurately locates the low-impedance fault location, improves the detection efficiency, has high detection accuracy, and good stability.

[0019] The inspection trolley of the present invention is used to carry detection equipment and move along the bridge to achieve full-section detection of the DC bus, solving the problem that some line personnel cannot detect. By replacing manual inspection with the inspection trolley, the efficiency is improved and the electric shock risk is reduced. The relative position between the detection coil and the DC bus is adjusted by a telescopic robotic arm to ensure that the detection coil maintains the best coupling distance from the line. At the same time, the retraction function of the telescopic robotic arm can avoid collisions between the robotic arm and line brackets or other obstacles, preventing secondary faults. Based on the principle of electromagnetic induction, the detection coil captures the current mutation signal caused by low-impedance faults in the DC line. The detection coil does not need to directly contact the live line, which is beneficial to ensuring the safety of the device. The camera module is used to obtain image data of the bridge surface in real time, facilitating the control system to plan the driving trajectory of the inspection trolley according to the image data and ensuring the stable movement of the inspection trolley on the bridge. The GPS / Beidou module is used to obtain coordinate data of the current position of the inspection trolley. The control system is used to plan the driving trajectory of the inspection trolley according to the image data, judge whether there is a low-impedance fault in the DC bus at the current position according to the magnetic field data, and is also used to control the telescopic movement of the telescopic robotic arm to make the detection coil located at the position with the strongest magnetic field under the bridge. The Lora module is used to send the detection results, image data, coordinate data, and magnetic field data to the front-end machine. The present invention realizes full-section automatic detection of low-impedance faults in DC lines, accurately locates the low-impedance fault positions, improves the detection efficiency, has high detection accuracy, and good stability.

[0020] Furthermore, the inspection trolley of the present invention includes a counterweight unit, and the counterweight unit is used to ensure the stability of the inspection trolley during driving. The intelligent trolley design of the present invention can adapt to different bridge layouts and on-site environments, and has high flexibility. With the expansion of the scale of photovoltaic power stations, traditional manual inspection and electrical testing methods are difficult to meet the needs of large-scale monitoring. The intelligent trolley can automatically inspect multiple photovoltaic arrays according to the preset path and perform maintenance in a timely manner, having good scalability and applicability, and being able to meet the intelligent operation and maintenance needs of future photovoltaic power stations.

[0021] Furthermore, the telescopic robotic arm of the present invention includes a first telescopic part and a second telescopic part. The first telescopic part is vertically arranged, and the second telescopic part is horizontally arranged to realize the adjustment of the position of the detection coil in the horizontal and vertical directions.

[0022] Furthermore, the present invention uses Canny edge detection to process the surface image data of the bridge to extract the edge features of the bridge, ensuring the stability of the driving track of the inspection trolley. Description of the Drawings

[0023] Figure 1 It is a relationship diagram of current and induced voltage of the detection coil when there is a crossbeam and when there is no crossbeam in the embodiment of the present invention; Figure 2Schematic diagram of current when the detection coil of the embodiment of the present invention is directly below the DC bus to be measured; Figure 3 Schematic diagram of magnetic field when the detection coil of the embodiment of the present invention is directly below the DC bus to be measured; Figure 4 Schematic diagram of current when the detection coil of the embodiment of the present invention is at the lower right corner of the DC bus to be measured; Figure 5 Schematic diagram of magnetic field when the detection coil of the embodiment of the present invention is at the lower right corner of the DC bus to be measured; Figure 6 Graph of the effective value of current and the induced voltage of the coil when the detection coil of the embodiment of the present invention is at different positions of the DC bus; Figure 7 Schematic diagram of the structure of the inspection trolley of the embodiment of the present invention; Figure 8 Schematic diagram of the working state of the inspection trolley of the embodiment of the present invention; Figure 9 Relative position diagram of the retractable robotic arm and the detection coil working with the DC bus in the embodiment of the present invention; Figure 10 Schematic diagram of the structure of the detection coil of the embodiment of the present invention; Figure 11 System architecture diagram of the inspection trolley of the embodiment of the present invention; Figure 12 Method flow chart of the embodiment of the present invention; Figure 13 Schematic diagram of a photovoltaic DC line; Figure 14 Schematic diagram of a test source; Figure 15 Schematic diagram of a line selection clamp; Figure 16 Schematic diagram of a bridge; Wherein: 1. Bridge; 2. Detection coil; 3. Retractable robotic arm; 4. Camera module; 5. Wheels; 6. Shock absorption unit; 7. Lora module; 8. Counterweight unit; 9. GPS / Beidou module; 10. Drive motor; 11. Transmission unit; 12. DC bus; 13. Control system; 14. Magnetic field direction; 15. Winding; 16. Detection coil fixing part; 17. Inspection trolley; 18. First telescopic part; 19. Second telescopic part; 20. Electrode; 21. Clip; 22. Bridge cover; 23. Cross beam 23. Detailed implementation manners

[0024] To enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the description of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0026] To solve the problem of accurately detecting the fault location of a photovoltaic DC bus, such as Figure 12 , the present invention provides a method for detecting low-impedance faults in a DC line, which includes the following steps: Determine the end of the DC bus 12 where a low-impedance fault occurs in the DC line; Inject an AC test signal into the end of the DC bus 12 where a low-impedance fault occurs, and the other DC buses in the DC line operate normally through DC; Start detecting the fault location from one end of the bridge 1, and obtain the magnetic field data and coordinate data along the bridge 1 in real time. When the measured magnetic field data changes abnormally, it is judged that the current position is the low-impedance fault location; According to the coordinate data of the low-impedance fault location, locate the fault location of the bridge 1, and select the line of the DC bus 12 where a low-impedance fault occurs in the DC line based on the fault location of the bridge 1.

[0027] Before this, when a fault occurs in the photovoltaic power transmission system and causes a trip, this device can be used for line selection. The alligator clip corresponding to the cathode of the test source is clamped on the bridge, and the alligator clip corresponding to the anode is successively clamped on the lines on the busbar box. The display screen installed on the test source will display the measured current and voltage, and then calculate the total impedance of each DC bus 12. When the total impedance is lower than a certain threshold, it is judged that the line has a fault.

[0028] More specifically, connect the negative electrode of the test source to the bridge, and connect the positive electrode to each DC bus in sequence. Inject an AC test signal into each DC bus through the test source. While the test source injects a signal source into the line, it will detect the voltage and current values of the injected signal itself. Since the load of each line is different, the signal injected by the test source will vary according to the load value in the line. The test voltage will be automatically adjusted to an optimal measurement range according to the load in each line.

[0029] The specific process after the line trips is as follows: 1. Use the test source to detect each line in sequence to determine the low impedance of each line, and then determine the port of the faulty line; 2. Connect the test source to the port of the faulty line and inject an AC test source into the faulty line; 3. The trolley travels along the bridge to detect the magnetic field intensity of the line to determine the faulty area; 4. Send the faulty location information to the front-end machine and the server. After the worker confirms the location, they arrive at the faulty location; 5. Remotely switch the detection frequency to the line selection frequency through a button, manually open the bridge cover at the faulty location, and use the line selection clamp to clamp each line in sequence until the faulty line is selected.

[0030] Furthermore, when the port of the faulty line is selected, the test source is continuously applied to the faulty line. Only the frequency during detection is different from the frequency during line selection, and a button is required for switching. The test source is still connected to the port of the faulty line. The main circuit board is installed inside the trolley and will lead out a switch for switching the frequency of the test source. The test frequency and the line selection frequency are two different frequencies, and the frequency can be remotely switched through the switch.

[0031] See Figure 7 , to implement the above method, the present invention provides a DC line low impedance fault detection device, including an inspection trolley 17. The inspection trolley 17 is used to carry detection equipment and move along the bridge 1 to achieve full-section detection of the DC bus 12, solving the problem that some lines cannot be detected by personnel. The inspection trolley 17 replaces manual inspection to improve efficiency and reduce the risk of electric shock.

[0032] The inspection trolley 17 is provided with a telescopic robotic arm 3. The telescopic robotic arm 3 is provided with a detection coil 2. The relative position between the detection coil 2 and the DC bus 12 is adjusted through the telescopic robotic arm 3 to ensure that the detection coil 2 maintains the best coupling distance from the line. At the same time, the retraction function of the telescopic robotic arm 3 can avoid the robotic arm colliding with the line support or other obstacles, avoiding secondary faults. The detection coil 2 captures the current mutation signal caused by the low impedance fault in the DC line based on the principle of electromagnetic induction. The detection coil 2 does not need to directly contact the live line, which is beneficial to ensuring the safety of the device.

[0033] The inspection trolley 17 is also provided with a camera module 4, a Lora module 7, a GPS / Beidou module 9, and a control system 13. The camera module 4 is used to obtain the image data of the surface of the bridge 1 in real time, so that the control system 13 can plan the driving trajectory of the inspection trolley 17 according to the image data, ensuring the stable movement of the inspection trolley 17 on the bridge 1. The GPS / Beidou module 9 is used to obtain the current coordinate data of the inspection trolley 17.

[0034] The detection coil 2, the camera module 4, the telescopic robotic arm 3, the Lora module 7, and the GPS / Beidou module 9 are all connected to the control system 13. The control system 13 is used to plan the driving trajectory of the inspection trolley 17 according to the image data, judge whether a low-impedance fault occurs in the current position of the DC bus 12 according to the magnetic field data, and is also used to control the telescopic movement of the telescopic robotic arm 3 so that the detection coil 2 is located at the position with the strongest magnetic field under the bridge 1.

[0035] The camera module 4 and the GPS / Beidou module 9 are both connected to the Lora module 7, and the Lora module 7 is used to send the detection results, image data, coordinate data, and magnetic field data to the front-end computer.

[0036] The present invention realizes the full-section automatic detection of low-impedance faults in DC lines, accurately locates the low-impedance fault positions, improves the detection efficiency, has high detection accuracy, and good stability.

[0037] The device and method of the present invention will be described in detail below in conjunction with specific embodiments and drawings.

[0038] Embodiment 1: See Figure 7 and Figure 8 As shown in, a DC line low-impedance fault detection device provided in this embodiment includes an inspection trolley 17. A telescopic robotic arm 3 is provided on the inspection trolley 17, and a detection coil 2 is provided on the telescopic robotic arm 3. When the detection coil 2 works, it is perpendicular to the magnetic field direction 14 generated by the DC bus 12. See Figure 8 ; The inspection trolley 17 is also provided with a camera module 4, a Lora module 7, a GPS / Beidou module 9, and a control system 13; the detection coil 2, the camera module 4, the telescopic robotic arm 3, the Lora module 7, and the GPS / Beidou module 9 are all connected to the control system 13; the camera module 4 and the GPS / Beidou module 9 are both connected to the Lora module 7.

[0039] Preferably, a power supply unit is provided on the inspection trolley 17. The power supply unit is electrically connected to the detection coil 2, the telescopic robotic arm 3, the camera module 4, the Lora module 7, the GPS / Beidou module 9, and the control system 13 respectively. The power supply unit is used to supply power to the detection coil 2, the telescopic robotic arm 3, the camera module 4, the Lora module 7, the GPS / Beidou module 9, and the control system 13.

[0040] Preferably, the inspection trolley 17 includes a counterweight unit 8. The counterweight unit 8 is used to ensure the stability of the inspection trolley 17 during driving. The counterweight unit 8 is connected to the wheels 5 through a shock absorption unit 6. The counterweight unit 8 is also provided with a telescopic robotic arm 3, a camera module 4, a Lora module 7, a GPS / Beidou module 9, a control system 13, and a drive motor 10. The output end of the drive motor 10 is connected to the input shaft of the wheels 5 through a transmission unit 11. The drive motor 10 is electrically connected to the control system 13, and the control system 13 controls the trolley to move forward according to the planned path.

[0041] Preferably, referring to FIGS. 7 and 9, the telescopic robotic arm 3 includes a first telescopic part 18 and a second telescopic part 19. Both the first telescopic part 18 and the second telescopic part 19 are electrically connected to the control system 13. The end of the first telescopic part 18 is connected to the inspection trolley 17. The telescopic end of the first telescopic part 18 is connected to the second telescopic part 19. The telescopic end of the second telescopic part 19 is connected to the detection coil 2. The detection coil 2 is located at the bottom of the inspection trolley 17.

[0042] Preferably, referring to Figure 10 , the detection coil 2 is fixedly connected to the telescopic end of the second telescopic part 19 through a detection coil fixing component 16. The inside of the detection coil 2 is a winding 15. The detection coil 2 is located at the bottom of the counterweight unit 8. The first telescopic part 18 is arranged vertically. The first telescopic part 18 is used to move the second telescopic part 19 and the detection coil 2 in the vertical direction. The second telescopic part 19 is arranged horizontally. The second telescopic part 19 is used to move the detection coil 2 in the horizontal direction, so as to realize the adjustment of the position of the detection coil 2 in the horizontal and vertical directions. The camera module 4 is located on one side of the inspection trolley 17 in the forward direction.

[0043] Based on the above structure, the present invention also discloses a method for detecting low-impedance faults in a DC line. Referring to Figure 12 , it includes the following steps: S1, determine the end of the DC busbar 12 where the low-impedance fault occurs, narrow the detection range, and avoid blind investigation of the entire line; S2. Inject an AC test signal into the end of the DC bus 12 where a low-impedance fault occurs. The other DC buses operate normally with DC power. While detecting the fault line, the normal operation of other DC buses 12 is not affected.

[0044] S3. The inspection trolley 17 starts from one end of the bridge 1 to detect the fault location until the location of the low-impedance fault is detected. The specific fault location detection is as follows: Control the state of the telescopic robotic arm 3 through the control system 13 to make the detection coil 2 located at the position with the strongest magnetic field under the bridge 1; Obtain the surface image data of the bridge 1 in real time through the camera module 4. The control system 13 plans the driving trajectory of the inspection trolley 17 according to the image data to achieve full-section detection of the DC bus 12. By replacing manual inspection with the inspection trolley 17, the efficiency is improved and the electric shock risk is reduced. The specific steps are as follows: Obtain the surface image data of the bridge 1 in real time through the camera module 4; Use Canny edge detection to process the surface image data of the bridge 1 to extract the edge features of the bridge 1; Plan the driving trajectory of the inspection trolley 17 according to the edge features of the bridge 1.

[0045] Obtain the magnetic field data in real time through the detection coil 2 and transmit the magnetic field data to the control system 13 for judgment. When the magnetic field data changes abnormally, it is judged that the DC bus 12 at the current position has a low-impedance fault, and the fault point is quickly determined based on a preset threshold. The specific steps are as follows: When the fluctuation range of the magnetic field intensity detected by the detection coil 2 exceeds the threshold range, the inspection trolley 17 stops moving forward. Use the telescopic robotic arm 3 to drive the detection coil 2 to move back and forth in the horizontal and vertical directions for detection, further detect the magnetic field intensity in this area, and transmit the magnetic field data to the control system 13; If the maximum magnetic field intensity detected in this area is within the threshold range, the DC bus 12 at this place is normal; If the maximum magnetic field intensity detected in this area is greater than the maximum threshold, it is judged that the DC bus 12 at the current position has a low-impedance fault.

[0046] S4. Use the GPS / Beidou module 9 to obtain the coordinate data of the fault location, and transmit the coordinate data of the fault location and the magnetic field data to the front-end machine through the Lora module 7 to achieve remote reporting and real-time monitoring of the fault coordinates; S5. Manually open the bridge cover 22 according to the coordinate data of the fault location, and use a line selection pliers to select the faulty DC bus 12 from among many DC buses 12. In the complex and numerous DC buses 12, combine the magnetic field positioning results to manually screen the faulty line.

[0047] Inject power at the combiner box side in combination with the test source, detect faults along the bridge with the detection coil, and select the faulty line from 40 lines based on the capacitance coupling principle. This method can be used to detect low-impedance faults in the DC lines of the photovoltaic array in real time and accurately, improving the efficiency and accuracy of fault detection, thereby solving various problems in the prior art.

[0048] Embodiment 2: Please refer to Figure 7 and Figure 8 , this embodiment discloses a device for detecting low-impedance faults in DC lines. Figure 7 is the front view of the inspection trolley. Figure 8 is the side view of the inspection trolley. The inspection trolley 17 includes: a detection coil 2, a telescopic robotic arm 3, wheels 5, a shock absorption unit 6, a counterweight unit 8, a drive motor 10, a transmission unit 11, and a detection coil fixing part 16. The shock absorption unit 6 includes components such as shock absorbers, springs, rubber pads, and dampers. The shock absorption unit 6 is used to absorb and relieve the vibration and impact during the running of the inspection trolley 17. The shock absorbers and springs provide the main vibration buffering function. One end of the shock absorbers and springs is connected to the body of the intelligent trolley, and the other end is connected to the wheel bracket, and rubber pads are placed at the connection points. The damper further controls the transmission of vibration. The damper is directly connected to the body and the wheels, assisting the work between the shock absorbers and springs. The rubber pads reduce friction and impact, ensuring that the trolley runs smoothly during vibration. One side of the shock absorption unit 6 is directly connected to the body of the intelligent trolley, and the other side is connected to the wheels.

[0049] The counterweight unit 8 is made of steel material, and the influence on the surrounding magnetic field can be ignored. It is mainly used to ensure that the trolley always maintains balance and is not affected by external factors.

[0050] The drive motor 10 and the transmission unit 11 provide power for the inspection trolley 17. It is mainly composed of a motor, a gear reducer, a transmission shaft, a chain or a belt, etc. The motor rotates by electric drive, converting electrical energy into mechanical energy. The gear reducer converts the high-speed rotation of the motor into a low-speed high-torque output. The transmission shaft or chain transmits the power to the wheels 5 of the trolley, making the inspection trolley 17 move. By adjusting the motor speed and torque, it is ensured that the trolley runs smoothly under different ground conditions and provides sufficient driving force to support the forward movement, turning, and stability of the inspection trolley 17.

[0051] The detection coil fixing component 16 mainly uses a cross-shaped fixator, and a retractable mechanical rod is directly connected in the middle of the cross-shaped fixator. One end of the retractable mechanical rod is directly fixedly connected to the cross-shaped fixator in the middle of the detection coil, and the other end is directly fixed on the right side of the trolley. The control board is installed inside the trolley body, and the Lora module and the GPS / Beidou module are magnetically adsorbed on the upper side of the vehicle body. The detection coil 2 is composed of a winding 15 wound ten times. The detection coil 2 is oval, with a length of 100 mm, a width of 25 mm, and a thickness of 5 mm. The detection coil is placed vertically and along the bridge, so that the detection value is more accurate.

[0052] The telescopic robotic arm 3 is a cylinder-type push rod to achieve the telescoping of the telescopic robotic arm 3. The telescopic robotic arm 3 is equipped with a position sensor or an encoder inside to monitor the length of the rod in real time and feed the data back to the control system to ensure precise adjustment. The telescopic robotic arm 3 is divided into two parts, namely the second telescopic part 19 that contracts in the horizontal direction and the first telescopic part 18 that contracts in the vertical direction. When magnetic field detection is required, the telescopic robotic arm 3 extends and contracts under the bridge so that the detection coil 2 can accurately approach the cable line to monitor whether a fault occurs.

[0053] The wire selection pliers are mainly used to screen out the faulty one from many lines. It is mainly composed of a copper sheet and a signal output line. The detection method is to touch each DC line with the copper sheet. The copper sheet mainly transmits the induced signal to the main circuit board through the signal output line by the principle of capacitive coupling. The test source emits an AC test source. When the copper sheet touches the faulty DC bus, the main circuit board will produce a beeping reaction, and there will be no reaction when it is a non-faulty line. The main circuit board is installed inside the trolley body.

[0054] The present invention utilizes the principle of electromagnetic induction to detect low-impedance faults on the DC bus 12 of the photovoltaic array by installing a detection coil 2 on the inspection trolley 17. Specifically, first, an AC test source is applied to the DC bus 12. The positive pole of the AC test source is connected to the bus, and the negative pole is grounded to the bridge, thereby generating an alternating electromagnetic field around the line. Under normal circumstances, the current is stable and will not have a significant impact on the magnetic field. However, when a low-impedance fault occurs, the resistance at the fault location will decrease, resulting in abnormal or increased current flow in this area, which will cause a local magnetic field enhancement.

[0055] In the present invention, the horizontal and vertical translations of the detection coil 2 are controlled by the telescopic robotic arm 3 on the side of the inspection trolley, and the detection coil 2 is perpendicular to the bridge 1.

[0056] See Figure 9 , the telescopic robotic arm 3 includes a first telescopic part 18 and a second telescopic part 19. The first telescopic part 18 is used to achieve the vertical translation of the detection coil 2, and the second telescopic part 19 is used to achieve the horizontal translation of the detection coil 2.

[0057] The detection coil 2 is installed on the second telescopic part 19 of the telescopic robotic arm 3 of the inspection trolley. It can be translated horizontally and vertically through the telescopic robotic arm 3. The detection coil 2 is precisely placed at the position with the strongest magnetic field on the side of the bridge 1. When the current changes and causes a magnetic field anomaly, the detection coil 2 will generate an electromotive force in the alternating magnetic field, and the electromotive force is the induced voltage. The induced voltage is proportional to the intensity and change rate of the magnetic field. Therefore, the detection coil 2 can detect the fluctuation of the magnetic field intensity and transmit this signal to the control system of the inspection trolley. When the fluctuation range of the magnetic field intensity detected by the detection coil 2 exceeds the threshold range, the inspection trolley 17 stops moving forward. The telescopic robotic arm 3 is used to drive the detection coil 2 to move back and forth in the horizontal and vertical directions for detection, and further detect the magnetic field intensity in this area. If the maximum magnetic field intensity detected in this area is within the threshold range, the DC bus 12 at this place is normal, and the magnetic field intensity fluctuation is caused by factors such as the bending of the DC bus 12. If the maximum magnetic field intensity detected in this area is greater than the maximum threshold, it is determined that this position is a fault area.

[0058] The detected magnetic field change signal is amplified and denoised through the measurement circuit, and the finally collected data is uploaded to the front-end computer through the Lora module 7. The front-end computer receives the data and performs fault judgment. When the maximum magnetic field intensity detected in a certain area collected is greater than the set fault threshold, it is determined that a fault has occurred in this section, and the fault information is reported to the server. The server then transmits it to the client app, and the maintenance personnel can immediately receive an alarm and locate the fault point.

[0059] The system architecture of the inspection trolley is referred to Figure 11 , Figure 14 for the schematic diagram of the test source; as Figure 14 shown, it is the test schematic diagram of the present invention. Among them, it is mainly a schematic diagram of the hardware circuit connection to implement Figure 11 the technical solution.

[0060] Based on the core control of the system, the main control module uses an STM32 single-chip microcomputer, which integrates rich internal resources and is equipped with a GH05V2S05S voltage conversion chip, capable of converting the voltage from 300VDC to 1500VDC into 5V to 32V. The STM32 single-chip microcomputer has higher computing power and is equipped with multiple timers and peripheral communication serial ports to meet the development needs of large-scale systems. In addition, the library functions of STM32 are simple and easy to use, and support multiple pin modes and pin multiplexing functions, greatly improving the development efficiency.

[0061] In the present invention, the GPS / Beidou module 9 is mainly used to trigger the acquisition of time and position when the inspection trolley detects a fault. The specific process is as follows: When the detection coil 2 of the inspection trolley detects an abnormal magnetic field change and the system analyzes and confirms a low impedance fault, the GPS / Beidou module 9 will be immediately activated to obtain the precise coordinates and real-time time of the current fault occurrence location. At this time, the GPS / Beidou module 9 provides precise longitude and latitude data through satellite positioning and records the timestamp of the current moment. Next, the inspection trolley packages the GPS data together with the fault information to form a message packet containing the fault location and occurrence time. This data packet is transmitted to the front-end machine through the Lora module 7. After receiving this information, the system will display the specific location and time of the fault in real time, helping the operation and maintenance personnel quickly locate the fault area and perform repairs or inspections in a timely manner.

[0062] The wireless communication module of the present invention can transmit fault information to the control platform in real time, enabling the operator to receive alarms in a timely manner and obtain the fault location, significantly improving the fault response speed. Traditional detection methods often rely on manual analysis and manual positioning, with low efficiency and easy delay in repair time. Through the real-time feedback of the intelligent trolley, the staff can quickly locate the fault point, shorten the repair time, and improve the overall operation efficiency and safety of the photovoltaic power station.

[0063] In the present invention, the main function of the camera module 4 is to help the inspection trolley ensure the correct running route along the bridge and provide visual feedback to ensure the stable and precise driving of the trolley. A camera module 4 is installed in front of the inspection trolley 17. By capturing the environmental image of the bridge in real time, the camera module 4 can help the inspection trolley 17 perceive surrounding obstacles, path markers, and the characteristics of the bridge itself. Specifically, using image processing and path planning techniques, the camera module 4 obtains the image information of the bridge in real time and uses the Canny edge detection to extract the edge of the bridge. By identifying the edge features, the trolley can determine the specific position and driving path of the bridge. The image processing technology converts these edge features into coordinate information to help the trolley perform path planning.

[0064] It should be noted that the Canny algorithm is a commonly used edge detection method, which mainly extracts edges in an image through five steps: First, use a Gaussian filter to smooth the image to reduce noise; Then calculate the gradient intensity and direction of each pixel to identify areas with large changes in the image; Next, apply non-maximum suppression to accurately locate the edges; Distinguish strong edges, weak edges, and non-edges through double-threshold processing; Finally, connect the weak edges to the strong edges through the edge connection step.

[0065] Furthermore, the camera module 4 of this embodiment analyzes the captured images through image processing algorithms and feeds them back to the control system 13 of the trolley in real time. The images captured by the camera module are transmitted to the image processing unit of the inspection trolley, and image recognition technologies such as edge detection and path calibration are used to analyze the shape, signs, and road conditions of the bridge. Based on this information, the system can automatically identify the correct driving path of the bridge and correct the driving direction of the trolley by adjusting the control signal when the path deviates. Specifically, the camera module 4 can detect factors such as uneven road surfaces and the degree of curvature of the path in real time to ensure that the trolley travels along the most suitable route. The camera module can also help the inspection trolley 17 identify obstacles or other potential risk factors on the bridge. When the camera module 4 detects an obstacle, the inspection trolley 17 can automatically adjust its driving strategy to maintain a safe operating state by avoiding or bypassing the obstacle. The camera module 4 is not only used for navigation but also can record image data in real time during operation and synchronously transmit the path information and environmental status to the front-end computer or control platform. These image information can be used as the basis for fault analysis and later traceability, helping maintenance personnel better understand the on-site situation after a fault occurs and even providing reference for subsequent manual repairs. The camera module 4 works in cooperation with the GPS / Beidou module 9 and the detection coil 2 to provide multi-dimensional information input. When a fault is detected, the image data of the camera module 4 can be combined with the positioning information of the GPS / Beidou module 9 to accurately mark the fault location, ensuring that maintenance personnel can reach the site for processing in the shortest possible time.

[0066] In the present invention, the Lora module 7 transmits the fault information, location information, and other data detected by the inspection trolley to the front-end computer in real time through a low-power and efficient wireless communication method. LoRa has an extremely long transmission distance, strong anti-interference ability, and low-power characteristics, enabling reliable data transmission in the complex environment of a photovoltaic power station and ensuring the real-time feedback of fault information and the efficient operation of the remote monitoring system.

[0067] In the present invention, the GPIO driver module completes the reception and processing of input signals and the transmission and driving of output signals by controlling the hardware interface of the inspection trolley. It is responsible for obtaining data from sensors in real time and controlling the states of devices such as motors. The GPIO driver module ensures the stable transmission of signals through level conversion and enhanced driving ability, and at the same time supports event triggering and interrupt control to ensure that the system responds promptly and sensitively.

[0068] In the present invention, the power supply module converts the high-voltage power supply into a low-voltage power supply suitable for the operation of the system to ensure the stable operation of the system.

[0069] In the present invention, the measurement circuit module collects, conditions, and converts sensor signals to ensure that the inspection trolley can accurately sense parameters such as current, voltage, and magnetic field. Through precise signal amplification, filtering, and analog-to-digital conversion, it can convert weak analog signals into data that can be analyzed by the microcontroller, and judge the fault situation through data processing. Once an abnormality is detected, the measurement circuit module will immediately trigger an alarm and transmit the relevant data to the front-end machine, realizing real-time fault location and remote monitoring.

[0070] In the present invention, the conditioning circuit module processes the signals collected by the detection coil 2 through amplification, filtering, gain adjustment, anti-interference, etc., to ensure that the signals can meet the requirements of the subsequent processing unit after conditioning, and ensure the accuracy and stability of the data. It not only plays a key role in improving the signal quality, but also optimizes the overall performance of the system through means such as level matching and dynamic control.

[0071] Traditional manual inspection and electrical detection equipment are easily affected by factors such as uneven road surfaces and equipment vibrations, resulting in unstable detection results. In the present invention, by installing a shock absorption system on the four wheels of the intelligent trolley, it can effectively cope with the uneven road surface on the bridge and ensure the smooth operation of the trolley. At the same time, the counterweight system design ensures the balance of the trolley and avoids inaccurate fault detection caused by the center of gravity shift. In this way, the intelligent trolley can work stably in a complex environment, improving the reliability of fault detection.

[0072] Embodiment Three: Refer to Figure 7 and Figure 8 , this embodiment discloses a DC line low-impedance fault detection device, including an inspection trolley 17, a telescopic robotic arm 3 is provided on the inspection trolley 17, and a detection coil 2 is provided on the telescopic robotic arm 3; A camera module 4, a Lora module 7, a GPS / Beidou module 9, and a control system 13 are also provided on the inspection trolley 17; The detection coil 2, the camera module 4, the telescopic robotic arm 3, the Lora module 7, and the GPS / Beidou module 9 are all connected to the control system 13; The camera module 4 and the GPS / Beidou module 9 are both connected to the Lora module 7.

[0073] DC line fault detection and location process: Figure 13 is a schematic diagram of a photovoltaic DC line; as Figure 13 shown, it is a schematic diagram of a photovoltaic DC line, showing the application environment of the present invention. In actual applications, the number of photovoltaic modules is as many as dozens. The present invention mainly solves the detection and location problem of the middle part located in the bridge 1. The schematic diagram of the bridge 1 is as Figure 16As shown in the figure, the cable tray includes a cable tray cover 22 and a crossbeam 23 at the bottom. The DC busbar 12 is placed on the crossbeam 23, and the cable tray cover 22 is set on the top. The cable tray 1 is a structural system for supporting and protecting cables or lines, which is widely used in various fields such as power, communication, automation, and photovoltaic. The sectional cable tray provides an environment for efficient heat dissipation and drainage. The presence or absence of the crossbeam 23 on the cable tray has a great impact on the magnetic field detected by the coil, and the position of the detection coil 2 will also have a relative impact.

[0074] Figure 16 It is a schematic diagram of the cable tray. When keeping the positions of the DC busbar 12 and the detection coil 2 unchanged, the influence of the presence or absence of the crossbeam 23 on the magnetic field is explored. The DC busbar 12 is placed close to the crossbeam 23. When the number of turns of the induction coil is 10 and the frequency is 100 Hz, it is the same as when there is no crossbeam 23 with the number of turns of the induction coil being 10 and the frequency being 100 Hz. The change trend of the coil induced voltage under different effective current values on the DC busbar 12 in the area with or without the crossbeam 23 of the cable tray is as Figure 1 shown. It can be seen from the figure that when there is no crossbeam 23, the detection result of the detection coil 2 is more ideal and reliable. When the current is the same, the induced voltage of the detection coil 2 without the crossbeam 23 is greater than that of the detection coil 2 with the crossbeam 23.

[0075] When ensuring that there is no crossbeam 23 under the DC busbar 12, the influence of the DC busbar 12 and the detection coil 2 in different directions on the magnetic field strength. When the number of turns of the induction coil is 10 and the frequency is 100 Hz, the placement of the coil and the DC busbar is as Figure 2 and Figure 4 shown. Among them, Figure 2 is the current schematic diagram when the coil is directly below the DC busbar to be measured, Figure 3 is the magnetic field schematic diagram when the coil is directly below the DC busbar to be measured, Figure 4 is the current schematic diagram when the coil is at the lower right corner of the DC busbar to be measured, Figure 5 is the magnetic field schematic diagram when the coil is at the lower right corner of the DC busbar to be measured.

[0076] It can be seen from Figures 2 to 5 that: The current is mainly concentrated at both ends of the cable tray and on the cable tray stretcher, the magnetic field strength in the central area is relatively strong, and the magnetic field gradually weakens as the distance increases.

[0077] The change trend of the coil induced voltage under different effective current values of the DC busbar at different positions is as Figure 6 shown. It can be obtained that: The closer the detection coil 2 is to the DC busbar 12, the greater the induced voltage, and the induced voltage shows an obvious linear growth with the increase of the current. The farther the detection coil 2 is from the DC busbar 12, the slower the increase of the induced voltage, and the electromagnetic induction effect weakens significantly. By adjusting the relative position of the DC busbar 12 and the detection coil 2, the output of the induced voltage can be optimized, and then more precise control of the system can be achieved.

[0078] Therefore, how to shorten the distance between the detection coil 2 and the DC bus 12 becomes the top priority. In the present invention, the horizontal and vertical translation of the detection coil 2 is controlled by the telescopic robotic arm 3 on the side of the inspection trolley 17, and the detection coil 2 is placed perpendicular to the bridge.

[0079] Based on the above solution, the present invention proposes the design and automated detection of a mine-sweeping type low-impedance fault detection device through the design and optimization of the detection coil. For the pain points, an effective solution is proposed. The horizontal and vertical translation of the detection coil is controlled by the robotic arm on the side of the intelligent inspection trolley and is accurately placed at the position with the strongest magnetic field on the bridge side. The detection coil is placed perpendicular to the bridge 1.

[0080] The detection process of the present invention further includes the following steps: S10, The leakage current transformer in the intelligent busbar trunking system monitors each pair of DC lines in real time, and will give an alarm prompt when a low-impedance fault occurs in a certain line.

[0081] S20, When it is known that a fault has occurred, disconnect the DC bus terminal where the fault occurs on the intelligent busbar trunking system side, inject a test signal into this DC bus 12 through a test source, and the other DC buses operate normally with direct current.

[0082] S30, The inspection trolley 17 first adjusts the position of the detection coil 2 through the telescopic robotic arm 3. After finding the position of the maximum magnetic field, the inspection trolley 17 runs along the bridge to find the fault occurrence position.

[0083] S40, After finding the fault position, manually open the bridge cover 22, use a wire selection pliers to select the specific fault line from many lines, and then repair it.

[0084] Traditional electrical testing methods (such as impedance testing and thermal imaging) usually cannot detect the low-impedance fault position in real time and accurately, and are limited by the test range and external environment. By using magnetic field changes for fault detection in the present invention, the intelligent trolley can accurately identify the low-impedance fault points on the DC line, avoiding the limitations of traditional methods. Magnetic field changes can reflect the electrical state of the line in real time, and the coil on the intelligent trolley can quickly detect magnetic field anomalies, greatly improving the sensitivity and accuracy of fault detection.

[0085] It should be noted that the 40 DC lines in the cable tray are not arranged neatly, but are intertwined and coiled, and the length is up to 1 km. Therefore, even if a fault is detected in a certain line by the leakage current transformer in the intelligent busbar trunking distribution box, only the port of the faulty line can be known, not the entire line. There is no numbering for the lines between the cable trays. Therefore, the faulty line in the cable tray needs to be further selected. This requires the use of the line selection function. An AC test source is injected into the terminals of the pair of DC lines with faults on the side of the busbar trunking distribution box. When the cable tray cover 22 is opened at the fault point, the line selection pliers are used to probe one by one. When the detected line is the faulty line, a beeping sound will be emitted to prompt the staff.

[0086] As a preferred solution, the present invention combines the coordinate data of the low-impedance fault, the real-time time, and the surface image data to accurately locate the fault position of the cable tray 1, mainly by detecting circuit anomalies in real time through magnetic field data. When the impedance value drops suddenly (that is, when the magnetic field data changes abnormally, it is a low-impedance fault), the system triggers data recording. The coordinates of the fault point are provided by a built-in positioning system (such as GPS), marking the approximate area of the fault in the cable tray. The exact time (UTC or local time) when the fault occurs is recorded to ensure the time consistency of the subsequent data. The camera is triggered to take a real-time image near the fault coordinates to capture the surface state.

[0087] As a preferred solution, the positioning of the fault position of the cable tray 1 according to the coordinate data of the position where the low-impedance fault occurs further includes: Obtaining the real-time time and surface image data of the position where the low-impedance fault occurs; Combining the coordinate data, real-time time, and surface image data of the position where the low-impedance fault occurs to accurately locate the fault position of the cable tray 1 through multi-source data, specifically including: Aligning the fault position detection time with the time stamp of the surface image data; superimposing the coordinate data on the digital model of the cable tray 1 to determine the specific section of the fault in the three-dimensional structure, and further accurately locating the fault position of the cable tray 1.

[0088] Furthermore, aligning the fault time with the image time stamp to ensure that the analyzed image reflects the fault moment or subsequent impacts. The coordinate data is superimposed on the digital model of the cable tray (such as BIM or GIS map) to determine the specific section of the fault in the three-dimensional structure. If the magnetic field data changes abnormally indicating a fault and the time is consistent with the fault record, the positioning is confirmed through the coordinate data. Multi-source data verification and accurate positioning can be achieved, realizing a closed-loop positioning from "electrical signal anomaly" to "physical position confirmation" by integrating spatio-temporal and visual information, significantly improving the efficiency of cable tray fault handling.

[0089] As a specific solution, after the DC line fault of the present invention is located, the accurate line selection process is as follows: Apply the test source to one of the DC buses 12, and then use the wire selection pliers to clamp the required wire from the DC circuit. This verification experiment is divided into two aspects. The first aspect is to place all the buses as close together as possible. The second aspect is to separate the buses by a certain distance. Figure 15 Schematic diagram of the wire selection pliers provided by the present invention. Among them, the clip 21 is an arc structure, and the positive and negative electrodes 20 are connected to the clip 21. The DC bus 12 for specific faults can be selected through the wire selection pliers. The specific experimental data are as follows: Verification experiment when the buses are closely attached. See Table 1 for the experimental data; Table 1. Changes in coupled voltage when injecting signals when closely attached

[0090] Verification experiment when there is a certain distance between the buses. See Table 2 for the experimental data; Table 2. Changes in coupled voltage when injecting signals when there is a 3 cm distance

[0091] According to the experimental data, when multiple wires are gathered together, it will cause significant errors and impacts on the measurement accuracy, mainly due to the coupling and interference between the wires. Therefore, when selecting wires, the distance between the bus to be measured and other wires should be kept as much as possible to ensure higher measurement accuracy and more accurate results.

[0092] Therefore, it can be concluded that the method of the present invention reduces manual operations, does not require opening the bridge cover 22 of the bridge, reduces the operation complexity, the intelligent trolley has a full-automatic operation function, and the operator does not need to manually perform complex equipment connection or electrical tests. Just start the trolley and set the running path, and the equipment can independently complete the magnetic field detection and transmit the detection results in real time. This design greatly simplifies the operation process, reduces the requirements for the technical level of the operator, and at the same time reduces the errors and the possibility of missed inspections caused by manual operations.

[0093] The manual inspection method in the prior art is inefficient and prone to missed inspections, and cannot achieve full-automatic monitoring. Through the intelligent trolley of the present invention running along the bridge and performing automatic detection, and including wire selection terminals, not only can the location where the fault occurs be clearly known, but also the specific fault wire can be screened out from many wires (about 40). It can greatly improve the efficiency and accuracy of fault detection. The intelligent trolley not only automatically follows the bridge to travel, but also can real-time locate the fault location, reduces manual intervention, and saves a large amount of time and labor costs.

[0094] The above content is only to illustrate the technical idea of the present invention, and the protection scope of the present invention cannot be limited thereby. Any modification made on the basis of the technical solution according to the technical idea proposed by the present invention falls within the protection scope of the present invention.

Claims

1. A method for detecting low-impedance faults in a DC line, characterized in that, Including the following steps: Determine the end of the DC bus (12) where a low-impedance fault occurs in the DC power line; Inject an AC test signal into the end of the DC bus (12) where a low-low impedance fault occurs, and the other DC buses in the DC power line operate normally with DC power; Start fault location detection from one end of the bridge (1), and obtain the magnetic field data and coordinate data along the bridge (1) in real time. When the measured magnetic field data changes abnormally, determine that the current position is the low-impedance fault position; According to the coordinate data of the low-impedance fault position, locate the fault position of the bridge (1), and based on the fault position of the bridge (1), select the DC bus (12) where the low-impedance fault occurs in the DC power line.

2. A DC line low-impedance fault detection method according to claim 1, characterized in that, The determination of the end of the DC bus (12) where a low-impedance fault occurs in the DC power line includes: When a fault occurs in the photovoltaic power transmission system and causes a trip, use a test source to test the current and voltage of the DC bus (12) in the DC power line in turn, calculate the total impedance of each DC bus (12) through the current and voltage, and when the total impedance is lower than the threshold, determine that the corresponding DC bus (12) has a fault.

3. A method for detecting low-impedance faults in a DC line according to claim 1, characterized in that, The positioning of the fault position of the bridge (1) according to the coordinate data of the low-impedance fault position further includes: Obtain the real-time time and surface image data of the low-impedance fault position; Combine the coordinate data, real-time time and surface image data of the low-impedance fault position to accurately locate the fault position of the bridge (1) through multi-source data, specifically including: Align the fault location detection time with the time stamp of the surface image data; superimpose the coordinate data on the digital model of the bridge (1) to determine the specific section of the fault in the three-dimensional structure, and then accurately locate the fault position of the bridge (1).

4. A DC line low-impedance fault detection method according to claim 3, characterized in that, Among the real-time acquisition of the magnetic field data, surface image data, coordinate data and real-time time along the bridge (1), The magnetic field data is detected by a detection coil (2) located at the bottom of the bridge (1); The surface image data is obtained by a camera module (4) synchronized with the detection coil (2); The coordinate data is obtained by a GPS / Beidou module (9).

5. A method for detecting low-impedance faults in a DC line according to claim 1, characterized in that, The selection of the DC bus (12) where a low-impedance fault occurs in the DC power line based on the fault position of the bridge (1) includes: Apply the test source to one of the DC buses 12, and then use a wire selection pliers to clamp the DC bus (12) where the low-impedance fault occurs from the DC power line.

6. A DC line low-impedance fault detection device, characterized in that, Including: An inspection trolley (17), on which a telescopic robotic arm (3) is provided, and a detection coil (2) is provided on the telescopic robotic arm (3); The inspection trolley (17) is also provided with a camera module (4), a Lora module (7), a GPS / Beidou module (9) and a control system (13); The detection coil (2), the camera module (4), the telescopic robotic arm (3), the Lora module (7) and the GPS / Beidou module (9) are all connected to the control system (13); the control system (13) controls the inspection trolley (17) to move along the bridge (1); The camera module (4) and the GPS / Beidou module (9) are both connected to the Lora module (7).

7. The DC line low impedance fault detection device according to claim 6, characterized in that, A power supply unit is provided on the inspection trolley (17), and the power supply unit is electrically connected to the detection coil (2), the telescopic robotic arm (3), the camera module (4), the Lora module (7), the GPS / Beidou module (9), and the control system (13) respectively; Preferably, the inspection trolley (17) includes a counterweight unit (8), the counterweight unit (8) is connected to the wheels (5) through a shock absorption unit (6), and the counterweight unit (8) is further provided with a telescopic robotic arm (3), a camera module (4), a Lora module (7), a GPS / Beidou module (9), a control system (13), and a drive motor (10). The output end of the drive motor (10) is connected to the input shaft of the wheels (5) through a transmission unit (11), and the drive motor (10) is electrically connected to the control system (13); The telescopic robotic arm (3) includes a first telescopic part (18) and a second telescopic part (19). The first telescopic part (18) and the second telescopic part (19) are both electrically connected to the control system (13). The end of the first telescopic part (18) is connected to the inspection trolley (17), the telescopic end of the first telescopic part (18) is connected to the second telescopic part (19), and the telescopic end of the second telescopic part (19) is connected to the detection coil (2). The detection coil (2) is located at the bottom of the inspection trolley (17); Preferably, the detection coil (2) is located at the bottom of the counterweight unit (8); The first telescopic part (18) is arranged vertically, and the second telescopic part (19) is arranged horizontally; The camera module (4) is located on one side of the inspection trolley (17) in the forward direction; 8. A DC line low-impedance fault detection device according to claim 6, characterized in that, The inspection trolley (17) starts from one end of the bridge (1) to detect the fault location until the fault location where the low-impedance fault occurs is detected. The fault location detection process is as follows: Control the state of the telescopic robotic arm (3) through the control system (13) to make the detection coil (2) located at the position with the strongest magnetic field under the bridge (1); Obtain the surface image data of the bridge (1) in real time through the camera module (4), and the control system (13) plans the driving trajectory of the inspection trolley (17) according to the image data; Obtain the magnetic field data in real time through the detection coil (2), and transmit the magnetic field data to the control system (13) for judgment. When the magnetic field data changes abnormally, it is judged that the DC bus (12) at the current position has a low-impedance fault.

9. The DC line low-impedance fault detection device according to claim 6, characterized in that, The camera module (4) obtains the surface image data of the bridge (1) in real time, and the control system (13) plans the driving trajectory of the inspection trolley (17) according to the image data, specifically as follows: Obtain the surface image data of the bridge (1) in real time through the camera module (4); Use the Canny edge detection to process the surface image data of the bridge (1) to extract the edge features of the bridge (1); Plan the driving trajectory of the inspection trolley (17) according to the edge features of the bridge (1).

10. A DC line low-impedance fault detection device according to claim 6, characterized in that, The detection coil (2) obtains magnetic field data in real time and transmits the magnetic field data to the control system (13) for judgment. When the magnetic field data changes abnormally, it is judged that a low-impedance fault occurs in the DC bus (12) at the current position, specifically as follows: When the fluctuation range of the magnetic field intensity detected by the detection coil (2) exceeds the threshold range, the inspection trolley 17 stops advancing, and the detection coil (2) is driven by the telescopic robotic arm (3) to reciprocate horizontally and vertically for detection, further detecting the magnetic field intensity, and transmitting the magnetic field data to the control system (13); If the maximum magnetic field intensity detected is within the threshold range, the DC bus (12) at that location is normal; If the maximum magnetic field intensity detected in this area is greater than the maximum threshold, it is judged that a low-impedance fault occurs in the DC bus (12) at the current position.

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