A fault element positioning method and device of a switch cabinet, an electronic device and a storage medium

Abstract

The application provides a fault component positioning method and device of a switch cabinet, electronic equipment and a storage medium. The method comprises: acquiring a three-dimensional image inside the switch cabinet; when a detection value indicates that an arc light sensor detects an arc signal, determining a fault area based on a detection range of the arc light sensor and a spatial geometric relationship, and combining the three-dimensional morphology of each component to screen out a first component that satisfies an optical constraint relationship with the first sensor, and then based on the detection values and time differences of a plurality of microphone sensors, screening out a second component that satisfies an acoustic constraint relationship and the optical constraint relationship as a candidate fault component; evaluating the fault probability of the candidate fault component; and determining a target fault component based on the fault probability. The above method can help to solve the problems of inaccurate positioning of fault components and low efficiency of manual troubleshooting.

Description

Technical Field

[0001] This application relates to the field of switchgear fault detection technology, and more specifically, to a method, apparatus, electronic device, and storage medium for locating faulty components in switchgear. Background Technology

[0002] With the increasing demands for power supply reliability in power systems, the rapid diagnosis and location technology of internal faults in switchgear, as the core equipment for power distribution and protection, has received widespread attention. When an arc fault occurs inside the switchgear, accurately identifying the specific location of the faulty component is of great significance for shortening fault handling time and reducing power outage losses.

[0003] Currently, common methods for locating faulty components mainly rely on arc flash sensors to detect arc signals. When the sensor detects an arc, the system issues an alarm, and maintenance personnel use the alarm information to investigate the area where the arc flash sensor is located to identify the faulty component.

[0004] However, this type of method has obvious limitations in practical applications: arc sensors can only indicate that the arc occurred in a general area and cannot accurately locate the specific component. Maintenance personnel need to check one by one over a large area, which takes a long time. More importantly, the internal structure of the switch cabinet is complex and contains many components. The faulty component that is arcing may be blocked by other components, making it difficult for maintenance personnel to find it directly during manual inspection, which further reduces the efficiency and accuracy of fault location. Summary of the Invention

[0005] In view of this, embodiments of this application provide a method, apparatus, electronic device, and storage medium for locating faulty components in switchgear, in order to solve the problems of inaccurate location of faulty components and low efficiency of manual troubleshooting due to obstruction by components.

[0006] In a first aspect, embodiments of this application provide a method for locating faulty components in a switchgear, the method comprising: Acquire a three-dimensional image of the inside of the switch cabinet and the detection values ​​of each sensor; the sensors include an arc light sensor and a microphone sensor; When the detection value of any arc sensor indicates that an arc signal has been detected, the fault area is determined by spatial geometry based on the detection range of each arc sensor. Within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image, a first component that satisfies an optical constraint relationship with at least one first sensor is selected; the first sensor is an arc light sensor that detects an arc signal, and the optical constraint relationship is: light emitted from the position of the first component reaches the photosensitive surface of the first sensor through the light propagation path and satisfies the triggering condition of the first sensor. Based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, it is verified whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components; The failure probability of each candidate faulty element is evaluated based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, as well as the magnitude of each detection value. Based on the failure probability, the target failure element is determined from the candidate failure elements.

[0007] In one feasible implementation, the sensor includes multiple arc light sensors disposed at different locations; The determination of the fault region based on the detection range of each arc sensor and spatial geometric relationships includes: Obtain a sensing area determined based on the detection range of each of the arc sensors; the sensing area includes a first sensing area corresponding to the first sensor and a second sensing area corresponding to the second sensor, wherein the second sensor is an arc sensor that has not detected an arc signal; The spatial region that is simultaneously located within all of the first sensing regions and not within any of the second sensing regions is defined as the fault region.

[0008] In one feasible implementation, obtaining the sensing area determined based on the detection range of each of the arc sensors includes: For each of the arc light sensors, combined with the three-dimensional shape of each component in the three-dimensional image, starting from the photosensitive surface of the arc light sensor, reverse tracing is performed along the straight line direction, the reflection direction, and / or the refraction direction to obtain several reverse light propagation paths in three-dimensional space; the starting point of the reverse light propagation path is the photosensitive surface, and the ending point is the component. For each of the aforementioned reverse ray propagation paths, based on the geometric propagation distance of the reverse ray propagation path, the first theoretical light intensity value of the light reaching the photosensitive surface is deduced; Select reverse light propagation paths whose first theoretical light intensity value is greater than or equal to the trigger threshold of the photosensitive surface; The area where the component located, indicated by the endpoint of the selected reverse light propagation path, is located is determined as the sensing area of ​​the arc light sensor.

[0009] In one feasible implementation, the switch cabinet is provided with multiple different sensor locations, each sensor location being provided with an arc light sensor and a microphone sensor; Based on the detection values ​​and time differences of sound signals detected by at least two microphone sensors, it is verified whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components, including: Acquire the sound signal detected by each microphone sensor; The location of the electric arc source is determined based on the magnitude of the sound signal detected by the microphone sensors at the locations of the multiple sensors. Based on the time difference of the sound signals detected by the microphone sensors at the locations of the plurality of sensors, the direction of arc propagation from the arc sound source is determined; For each of the first components, verify whether the light propagation path between the first component and the sensor position corresponding to each of the first sensors conforms to the arc propagation direction. The first component corresponding to the direction of arc propagation is selected as a candidate fault component to evaluate the failure probability of each candidate fault component.

[0010] In one feasible implementation, evaluating the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, and the magnitude of each of the detected values, includes: The second theoretical light intensity value reaching each of the first sensors is calculated based on the geometric propagation distance between each of the candidate faulty elements and each of the first sensors and the incident angle of the photosensitive surface of the first sensor. For each candidate faulty element, the fault probability of the candidate faulty element is determined based on the degree of difference between the theoretical light intensity value and the actual detection value of each of the first sensors; the degree of difference is negatively correlated with the fault probability.

[0011] In one feasible implementation, calculating the second theoretical light intensity value reaching each of the first sensors based on the geometric propagation distance between each of the candidate faulty elements and each of the first sensors and the incident angle of the photosensitive surface of the first sensor includes: The angle between the incident ray from the candidate faulty element to the first sensor and the normal direction of the photosensitive surface of the first sensor is determined as the incident angle; Based on Lambert's cosine law, the angle attenuation factor is determined; the angle attenuation factor decreases monotonically as the incident angle increases. Based on the inverse square law, the distance attenuation factor is determined; the distance attenuation factor decreases monotonically as the geometric propagation distance increases. The second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor.

[0012] In a feasible implementation, if the light propagation path between the candidate faulty element and the first sensor includes a reflection path and / or a refraction path, then the second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor, including: The first value is obtained by multiplying the preset reference light intensity value by the distance attenuation factor and the angle attenuation factor. The second value is obtained by multiplying the first value by the reflection attenuation factor and the refraction attenuation factor; the reflection attenuation factor is determined based on the number of reflections and the material of the reflecting surface, and the refraction attenuation factor is determined by the number of refractions and the refractive index of the medium. The second value is determined as the second theoretical light intensity value.

[0013] In one feasible implementation, a three-dimensional image of the interior of the switchgear is acquired, including: Obtain an initial 3D image of the inside of the switch cabinet; Acquire real-time 3D images obtained through point cloud scanning; The initial 3D image is corrected using the real-time 3D image to obtain the current 3D image.

[0014] In one feasible implementation, after determining the target faulty component from the candidate faulty components based on the fault probability, the method further includes: The target faulty components are sorted in descending order of fault probability to obtain a faulty component queue; The queue of faulty components is displayed on the interactive terminal; the interactive terminal includes: the display screen of the switch cabinet, and / or, the equipment terminal of the maintenance personnel.

[0015] Secondly, embodiments of this application also provide a fault component location device for a switchgear, the device comprising: The acquisition module is used to acquire a three-dimensional image of the inside of the switch cabinet and the three-dimensional coordinates of each sensor; the sensors include an arc light sensor and a microphone sensor. The region determination module is used to determine the fault region based on the detection range of each arc sensor and through spatial geometric relationships when the detection value of any arc sensor indicates that an arc signal has been detected. The first screening module is used to screen out first components that satisfy optical constraint relationships with at least one first sensor within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image; the first sensor is an arc light sensor that detects arc signals, and the optical constraint relationship is: light emitted from the position of the first component reaches the photosensitive surface of the first sensor through the light propagation path and satisfies the triggering condition of the first sensor. The second screening module is used to verify whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship based on the detection value and time difference of the sound signals detected by at least two microphone sensors, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components; An evaluation module is used to evaluate the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, as well as the magnitude of each detection value. The positioning module is used to determine the target faulty component from the candidate faulty components based on the fault probability.

[0016] In one feasible implementation, the sensor includes multiple arc light sensors disposed at different locations; The region determination module is used to determine the fault region based on the detection range of each arc sensor and through spatial geometric relationships, including: Obtain a sensing area determined based on the detection range of each of the arc sensors; the sensing area includes a first sensing area corresponding to the first sensor and a second sensing area corresponding to the second sensor, wherein the second sensor is an arc sensor that has not detected an arc signal; The spatial region that is simultaneously located within all of the first sensing regions and not within any of the second sensing regions is defined as the fault region.

[0017] In one feasible implementation, the region determination module is used to obtain a sensing region determined based on the detection range of each of the arc sensors, including: For each of the arc light sensors, combined with the three-dimensional shape of each component in the three-dimensional image, starting from the photosensitive surface of the arc light sensor, reverse tracing is performed along the straight line direction, the reflection direction, and / or the refraction direction to obtain several reverse light propagation paths in three-dimensional space; the starting point of the reverse light propagation path is the photosensitive surface, and the ending point is the component. For each of the aforementioned reverse ray propagation paths, based on the geometric propagation distance of the reverse ray propagation path, the first theoretical light intensity value of the light reaching the photosensitive surface is deduced; Select reverse light propagation paths whose first theoretical light intensity value is greater than or equal to the trigger threshold of the photosensitive surface; The area where the component located, indicated by the endpoint of the selected reverse light propagation path, is located is determined as the sensing area of ​​the arc light sensor.

[0018] In one feasible implementation, the switch cabinet is provided with multiple different sensor locations, each sensor location being provided with an arc light sensor and a microphone sensor; The second screening module is used to verify whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, so as to screen out second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components, including: Acquire the sound signal detected by each microphone sensor; The location of the electric arc source is determined based on the magnitude of the sound signal detected by the microphone sensors at the locations of the multiple sensors. Based on the time difference of the sound signals detected by the microphone sensors at the locations of the plurality of sensors, the direction of arc propagation from the arc sound source is determined; For each of the first components, verify whether the light propagation path between the first component and the sensor position corresponding to each of the first sensors conforms to the arc propagation direction. The first component corresponding to the direction of arc propagation is selected as a candidate fault component to evaluate the failure probability of each candidate fault component.

[0019] In one feasible implementation, the evaluation module is used to evaluate the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, and the magnitude of each of the detection values, including: The second theoretical light intensity value reaching each of the first sensors is calculated based on the geometric propagation distance between each of the candidate faulty elements and each of the first sensors and the incident angle of the photosensitive surface of the first sensor. For each candidate faulty element, the fault probability of the candidate faulty element is determined based on the degree of difference between the theoretical light intensity value and the actual detection value of each of the first sensors; the degree of difference is negatively correlated with the fault probability.

[0020] In one feasible implementation, the evaluation module is configured to calculate a second theoretical light intensity value reaching each of the first sensors based on the geometric propagation distance between each of the candidate faulty components and each of the first sensors and the incident angle of the photosensitive surface of the first sensor, including: The angle between the incident ray from the candidate faulty element to the first sensor and the normal direction of the photosensitive surface of the first sensor is determined as the incident angle; Based on Lambert's cosine law, the angle attenuation factor is determined; the angle attenuation factor decreases monotonically as the incident angle increases. Based on the inverse square law, the distance attenuation factor is determined; the distance attenuation factor decreases monotonically as the geometric propagation distance increases. The second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor.

[0021] In one feasible implementation, the evaluation module is used to determine the second theoretical light intensity value based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor, including: If the light propagation path between the candidate faulty element and the first sensor includes a reflection path and / or a refraction path, then the product of the preset reference light intensity value and the distance attenuation factor and the angle attenuation factor is calculated to obtain the first value. The second value is obtained by multiplying the first value by the reflection attenuation factor and the refraction attenuation factor; the reflection attenuation factor is determined based on the number of reflections and the material of the reflecting surface, and the refraction attenuation factor is determined by the number of refractions and the refractive index of the medium. The second value is determined as the second theoretical light intensity value.

[0022] In one feasible implementation, the first acquisition module is used to acquire a three-dimensional image of the inside of the switch cabinet, including: Obtain an initial 3D image of the inside of the switch cabinet; Acquire real-time 3D images obtained through point cloud scanning; The initial 3D image is corrected using the real-time 3D image to obtain the current 3D image.

[0023] In one feasible implementation, the device further includes: The sorting module is used to sort the target faulty components from the candidate faulty components according to the fault probability after determining the target faulty component based on the fault probability, so as to obtain a faulty component queue. A display module is used to display the queue of faulty components on an interactive terminal; the interactive terminal includes: the display screen of the switch cabinet, and / or, the equipment terminal of the maintenance personnel.

[0024] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the fault component location method for switchgear as described in any one of the first aspects.

[0025] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the fault component location method for switchgear as described in any one of the first aspects.

[0026] This application provides a method, apparatus, electronic device, and storage medium for locating faulty components in a switchgear. First, a three-dimensional image of the switchgear's interior and the detection values ​​of each sensor are acquired. The sensors include an arc light sensor and a microphone sensor, and the three-dimensional image contains three-dimensional morphological information of each component.

[0027] When the detection value of any arc sensor indicates that an arc signal has been detected, the fault area is determined based on the detection range of each arc sensor and spatial geometric relationships, thereby narrowing down the possible range of the faulty component from the entire switch cabinet to a smaller spatial area.

[0028] Based on this, within the fault area, and combining the three-dimensional morphology of each component in the three-dimensional image, components that satisfy the optical constraint relationship with at least one first sensor are selected and referred to as first components. The first sensor is an arc light sensor that detects arc signals. The optical constraint relationship means that light emitted from the component can reach the photosensitive surface of the first sensor through the light propagation path (including straight-line propagation, reflection, or refraction) and satisfy the sensor's triggering conditions. By introducing the optical constraint relationship, interference items that cannot be directly "seen" by the sensor due to component obstruction can be effectively eliminated.

[0029] Furthermore, based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, the light propagation path corresponding to each first component is verified to ensure that it meets the acoustic constraints. Second components that simultaneously meet both optical and acoustic constraints are then selected as candidate faulty components. This combined acoustic-optical verification further improves the reliability of candidate faulty components and reduces misjudgments caused by optical interference such as reflection and refraction.

[0030] Then, based on the geometric propagation distance and incident angle of the light path between each candidate faulty element and each first sensor, as well as the detection value of each arc sensor, the failure probability of each candidate faulty element is evaluated. Specifically, the theoretical light intensity value is calculated based on the geometric propagation distance and incident angle, and compared with the actual detection value; the closer the two are, the higher the failure probability.

[0031] Finally, the target faulty element is determined from the candidate faulty elements based on the fault probability, and the location of the faulty element most likely to cause an electric arc is output.

[0032] Compared with existing technologies that rely on arc light sensor area alarms and manual inspection by maintenance personnel, the embodiments of this application automatically narrow down the fault area, screen visible components, introduce acoustic verification, and quantitatively assess the fault probability by fusing three-dimensional images and sensor data. This helps to solve the problems of existing technologies being unable to accurately locate faulty components and the low efficiency of manual inspection due to component obstruction.

[0033] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 A flowchart of a method for locating faulty components in a switchgear, provided in an embodiment of this application, is shown.

[0036] Figure 2 This illustration shows a schematic diagram of the positions between the sensor and the candidate faulty element provided in an embodiment of this application.

[0037] Figure 3 A schematic diagram of the reverse tracing of the light propagation path provided in the embodiments of this application is shown.

[0038] Figure 4 A schematic diagram of the structure of a fault component locating device for a switchgear provided in an embodiment of this application is shown.

[0039] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0041] With the increasing demands for power supply reliability in power systems, the rapid diagnosis and location technology of internal faults in switchgear, as the core equipment for power distribution and protection, has received widespread attention. When an arc fault occurs inside the switchgear, accurately identifying the specific location of the faulty component is of great significance for shortening fault handling time and reducing power outage losses.

[0042] The internal structure of switchgear is quite complex, typically divided into different functional compartments such as circuit breaker compartment, busbar compartment, cable compartment, and instrument compartment. The circuit breaker compartment houses the circuit breaker body, operating mechanism, and contact box; the busbar compartment contains the main busbar and branch busbars for collecting and distributing electrical energy; the cable compartment contains cable joints, surge arresters, grounding switches, and other equipment; in addition, the cabinet also contains numerous components such as current transformers, voltage transformers, insulators, and supporting components. These components are densely arranged within a limited space, with complex spatial relationships between them, forming a three-dimensional spatial layout.

[0043] Currently, common methods for locating faulty components mainly rely on arc sensors to detect arc signals. When the sensor detects an arc, the system issues an alarm, and maintenance personnel check the area where the sensor is located based on the alarm information to identify the faulty component. However, this method has significant limitations in practical applications: arc sensors can only indicate that the arc occurred in a general area and cannot pinpoint the specific component. Maintenance personnel need to check multiple compartments one by one, which is time-consuming. More importantly, because the components inside the switchgear are densely packed and mutually obstructing, the faulty component experiencing the arc may be obscured by other components (such as the contact box in front, adjacent busbars, or insulators), making it difficult for maintenance personnel to directly find it during manual inspection, further reducing the efficiency and accuracy of fault location.

[0044] Based on this, embodiments of this application provide a method, apparatus, electronic device, and storage medium for locating faulty components in a switchgear, which are described below through embodiments.

[0045] To facilitate understanding of this embodiment, a method for locating faulty components in a switchgear disclosed in this application will first be described in detail. For example... Figure 1 As shown, it includes the following steps: Step 101: Obtain a three-dimensional image of the inside of the switch cabinet and the detection value of each sensor; the sensors include an arc light sensor and a microphone sensor.

[0046] First, obtain a 3D image of the switchgear's interior. This 3D image reflects the three-dimensional shape and spatial location of each component within the switchgear (such as circuit breakers, contacts, resistors, etc.). The source of the 3D image can be varied: for example, it can be obtained from the switchgear's developer before commissioning, or an initial model can be pre-established using laser scanning. The specific method of obtaining the 3D image is not limited here.

[0047] Furthermore, the detection values ​​of each arc sensor and each microphone sensor are acquired. The arc sensor detects the light signal generated by the electric arc, and its detection value reflects the intensity of the light received by the photosensitive surface; it can be voltage, current, or a calibrated light intensity value. The microphone sensor detects the sound signal generated by the electric arc, and its detection value reflects the sound pressure level when the sound wave arrives; it can be voltage, current, or a calibrated decibel value. The detection values ​​of both sensors can be read through analog-to-digital conversion or digital communication interfaces. In actual deployments, they are usually connected to the same acquisition unit, and the embodiments of this application can acquire the detection values ​​of each sensor from this unit.

[0048] In addition, the three-dimensional coordinates of each sensor can be obtained. These sensors are pre-installed in different locations inside the switch cabinet, and their coordinates can be measured and recorded during installation or obtained through spatial positioning technology. The purpose of obtaining the coordinates is to provide a basis for subsequent calculations of geometric relationships such as the distance between the sensor and the components, and the angle of incidence.

[0049] Step 102: When the detection value of any arc sensor indicates that an arc signal has been detected, the fault area is determined by spatial geometric relationship based on the detection range of each arc sensor.

[0050] In this embodiment, the detection value of each arc sensor is determined in real time to see if it exceeds the trigger threshold. If it does, the subsequent positioning process is triggered.

[0051] The detection range of each arc sensor is a conical spatial region determined by its three-dimensional coordinates, photosensitive surface orientation, field of view, and maximum detection distance. A sensor that detects a signal (the first sensor) indicates that the fault source must be within its detection range, while a sensor that does not detect a signal (the second sensor) indicates that the fault source is not within its detection range.

[0052] Therefore, the spatial region that is simultaneously within the detection range of all first sensors but not within the detection range of any second sensor is defined as the fault region. This narrows the search area for faulty components from the entire switchgear to a smaller area, reducing the amount of subsequent calculations.

[0053] Step 103: Within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image, select the first component that satisfies the optical constraint relationship with at least one first sensor; the first sensor is an arc light sensor that detects an arc signal, and the optical constraint relationship is: light emitted from the position of the first component reaches the photosensitive surface of the first sensor through the light propagation path and satisfies the triggering condition of the first sensor.

[0054] After identifying the fault area, all components within that area are extracted from the 3D image, and each component is assessed to determine whether it satisfies the optical constraint relationship with each of the first sensors.

[0055] The so-called optical constraint relationship refers to the ability of light emitted from a component to reach the photosensitive surface of a first sensor along a certain propagation path (including straight-line propagation, reflection, or refraction), and the light intensity upon arrival is sufficient to trigger the sensor. This relationship essentially describes the optical path connectivity and light intensity reachability between the component and the sensor, reflecting the objective possibility that the sensor can detect an electric arc generated by the component.

[0056] If a component satisfies the aforementioned optical constraint relationship with at least one first sensor, it is designated as the first component. This screening process narrows down the scope of subsequent evaluations and eliminates interference items that cannot be effectively detected by the sensor due to obstruction, excessive distance, or excessive light intensity attenuation.

[0057] Step 104: Based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, verify whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components.

[0058] After selecting the first component, this embodiment of the application further utilizes a microphone sensor for acoustic calibration.

[0059] An electric arc generates a sound signal. Due to the finite speed of sound (approximately 340 meters per second), microphone sensors at different locations receive the same sound signal at different times. By capturing this time difference using a high-sampling-rate acquisition device, the propagation path difference of the sound can be calculated, thus determining the direction of the sound source. Furthermore, the closer the sound source is to the microphone, the stronger the detected signal value. Comparing the signal values ​​from different microphones can help estimate the relative distance to the sound source.

[0060] For each first component, its position is compared with the acoustic positioning result: if the position of the component is basically consistent with the direction and distance range of the acoustic positioning, it is considered to satisfy the acoustic constraint relationship; otherwise, it is considered not to satisfy it.

[0061] Only the first component that simultaneously satisfies both optical and acoustic constraints is designated as the second component and used as a candidate faulty element for subsequent evaluation. Through combined acousto-optic verification, misjudgments caused by optical interference such as reflection and refraction can be effectively eliminated, improving the reliability of candidate faulty elements.

[0062] Step 105: Evaluate the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, as well as the magnitude of each detection value.

[0063] When each candidate faulty element satisfies the acousto-optic constraint condition, the second theoretical light intensity value reaching each of the first sensors can be calculated based on the geometric propagation distance between each candidate faulty element and each of the first sensors and the incident angle of the photosensitive surface of the first sensor; for each candidate faulty element, the fault probability of the candidate faulty element is determined based on the degree of difference between the theoretical light intensity value and the actual detection value of each of the first sensors; the degree of difference is negatively correlated with the fault probability.

[0064] In other words, for a candidate faulty component, the theoretical light intensity value that each first sensor should detect can be calculated based on the geometric propagation distance and incident angle of the light path between it and each first sensor (the second theoretical light intensity value, as described below). Generally, the greater the geometric propagation distance or the larger the incident angle, the smaller this theoretical light intensity value will be. Meanwhile, each first sensor has an actual detected light intensity value (actual detection value). By comparing the theoretical calculation result with the actual detection value, the closer the two are, the better the candidate faulty component matches the actual electric arc, and the higher its failure probability; conversely, the greater the difference between the two, the lower the failure probability.

[0065] In other words, for a candidate faulty component, the theoretical light intensity value that the sensor should detect can be calculated based on its distance from each first sensor and the incident angle. Generally, the greater the distance or the larger the incident angle, the smaller the second theoretical light intensity value. Comparing this theoretical value with the actual light intensity value detected by the sensor, the closer the two are, the better the candidate component matches the actual arc condition, and the higher the probability of failure; conversely, the greater the difference, the lower the probability of failure.

[0066] The calculation of the second theoretical light intensity value reaching each of the first sensors, based on the geometric propagation distance between each candidate faulty element and each of the first sensors and the incident angle of the light onto the photosensitive surface of the first sensor, includes: The angle between the incident ray from the candidate faulty element to the first sensor and the normal direction of the photosensitive surface of the first sensor is determined as the incident angle.

[0067] like Figure 2 As shown, taking the example that the light propagation path is a straight line, let's assume that the spatial straight line from this candidate faulty element 202 to this first sensor 201 is denoted as a vector. The geometrical propagation distance from this candidate faulty component to the first sensor is then... The incident ray from the candidate faulty element to the first sensor, and the direction of the normal to the photosensitive surface of the first sensor. The included angle between them is This reflects the degree of incident tilt (incident angle) of light relative to the photosensitive surface of the first sensor.

[0068] Based on Lambert's cosine law, an angular attenuation factor is determined; the angular attenuation factor decreases monotonically as the incident angle increases. Based on the inverse square law, a distance attenuation factor is determined; the distance attenuation factor decreases monotonically as the distance increases.

[0069] As an example implementation, an angle attenuation factor can be introduced. and distance decay factor :

[0070]

[0071] Therefore, without considering light refraction and reflection, the second theoretical light intensity value, based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor, can be calculated using the following formula: Second Theoretical Light Intensity Value The formula is:

[0072] Among them, the preset base light intensity value Indicates unit distance (like 1 meter) and directly facing the normal ( The standard luminous intensity of the electric arc can be set based on experimental calibration or empirical values; angle attenuation factor Follow The increase and monotonically decrease ( (decreasing within the range of 0° to 90°), reflecting Lambert's cosine law; distance attenuation factor. Follow The increase and monotonically decrease ( Follow The ratio of light intensity to its magnitude (increases and decreases) reflects the inverse square law. The combined theoretical value of light intensity describes the physical law that light intensity decreases with increasing distance and angle of inclination.

[0073] It should be noted that: (1) In actual calculations, distance Using standard distance Substituting the ratio form into the formula, we get:

[0074] in By taking a unit distance (e.g., 1 meter), the distance attenuation factor becomes dimensionless. For simplicity, this paper will still use... This represents the dimensionless decay relationship.

[0075] (2) The above formula applies to cases where light travels in a straight line without reflection or refraction. For paths involving reflection or refraction, the reflection attenuation factor and / or refraction attenuation factor must be multiplied.

[0076] (3) , This is merely an exemplary implementation; those skilled in the art can use other monotonically decreasing functions as alternatives based on actual needs.

[0077] For example, if the light propagation path between the candidate faulty element and the first sensor includes a reflection path and / or a refraction path, then the second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor, including: Calculate the product of the preset reference light intensity value and the distance attenuation factor and the angle attenuation factor to obtain a first value; calculate the product of the first value and the reflection attenuation factor and the refraction attenuation factor to obtain a second value; the reflection attenuation factor is determined based on the number of reflections and the material of the reflecting surface, and the refraction attenuation factor is determined based on the number of refractions and the refractive index of the medium; determine the second value as the second theoretical light intensity value.

[0078] In this case, since the light intensity will decrease after multiple reflections or refractions, the calculation of the second theoretical light intensity value needs to take into account the additional refraction attenuation and reflection attenuation.

[0079] At this point, the first value is calculated using the formula described above, as follows: First value =

[0080] Multiplying the first value by the reflection attenuation factor and the refraction attenuation factor, we obtain the second theoretical light intensity value, as shown in the following formula:

[0081] That is:

[0082] in, The reflectivity attenuation factor is determined based on the number of reflections and the material of the reflecting surface (when the number of reflections is 0, ...). When the number of reflections is greater than 0, ), The refractive attenuation factor is determined based on the number of refractions and the refractive index of the medium (when the number of refractions is 0, ...). When the number of refractions is greater than 0, In the embodiments of this application, and The value can be set based on experience, or it can be automatically generated based on a pre-trained algorithm model after determining the medium, reflective surface material, number of refractions, and number of reflections. The medium, reflective surface material, number of refractions, and number of reflections are determined by combining the three-dimensional image and the light propagation path.

[0083] When the calculated second theoretical light intensity value is lower than the sensor's trigger threshold, it means that even if the light can reach the photosensitive surface of the arc light sensor along this light propagation path, the second theoretical light intensity value is not enough to trigger the arc light sensor (it does not reach the trigger threshold), thus the arc light sensor cannot detect this part of the light propagating along the light propagation path formed by refraction and reflection.

[0084] In summary, for each candidate faulty component, the second theoretical light intensity value corresponding to each first sensor is compared with the actual detected value. The closer the two values ​​are, the better the candidate faulty component matches the actual electric arc, and the higher its failure probability; conversely, the greater the difference, the lower the failure probability. In this way, a quantified failure probability can be obtained for each candidate faulty component, which is used to subsequently determine the final faulty component. This evaluation process comprehensively considers geometric relationships and measured data, effectively distinguishing the credibility of different candidate components and improving the accuracy of location.

[0085] Step 106: Based on the failure probability, determine the target failure element from the candidate failure elements.

[0086] After calculating the failure probability of each candidate faulty component, the embodiments of this application will determine the final target faulty component accordingly.

[0087] There are several ways to determine the target fault element. As one example, the candidate fault element with the highest probability of failure can be directly identified as the target fault element, because a higher probability means a higher degree of matching between the element and the actual arc condition. As another example, a threshold can be set, and only candidate fault elements with a fault probability exceeding this threshold are identified as the target fault element. In another embodiment, if there is only one target fault element, but multiple candidate fault elements meet this threshold, then the one with the highest probability needs to be selected; if no candidate exceeds the threshold, an alarm message can be output, indicating that automatic determination is not possible or manual review is required; alternatively, steps 101-106 can be re-executed.

[0088] Through the above methods, the embodiments of this application can automatically output one or more faulty components most likely to be arcing, providing maintenance personnel with accurate location references and reducing the workload of manual troubleshooting.

[0089] This application provides a method, apparatus, electronic device, and storage medium for locating faulty components in a switchgear. First, a three-dimensional image of the switchgear's interior and the detection values ​​of each sensor are acquired. The sensors include an arc light sensor and a microphone sensor, and the three-dimensional image contains three-dimensional morphological information of each component.

[0090] When the detection value of any arc sensor indicates that an arc signal has been detected, the fault area is determined based on the detection range of each arc sensor and spatial geometric relationships, thereby narrowing down the possible range of the faulty component from the entire switch cabinet to a smaller spatial area.

[0091] Based on this, within the fault area, and combining the three-dimensional morphology of each component in the three-dimensional image, components that satisfy the optical constraint relationship with at least one first sensor are selected and referred to as first components. The first sensor is an arc light sensor that detects arc signals. The optical constraint relationship means that light emitted from the component can reach the photosensitive surface of the first sensor through the light propagation path (including straight-line propagation, reflection, or refraction) and satisfy the sensor's triggering conditions. By introducing the optical constraint relationship, interference items that cannot be directly "seen" by the sensor due to component obstruction can be effectively eliminated.

[0092] Furthermore, based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, the light propagation path corresponding to each first component is verified to ensure that it meets the acoustic constraints. Second components that simultaneously meet both optical and acoustic constraints are then selected as candidate faulty components. This combined acoustic-optical verification further improves the reliability of candidate faulty components and reduces misjudgments caused by optical interference such as reflection and refraction.

[0093] Then, based on the geometric propagation distance and incident angle of the light path between each candidate faulty element and each first sensor, as well as the detection value of each arc sensor, the failure probability of each candidate faulty element is evaluated. Specifically, the theoretical light intensity value is calculated based on the geometric propagation distance and incident angle, and compared with the actual detection value; the closer the two are, the higher the failure probability.

[0094] Finally, the target faulty element is determined from the candidate faulty elements based on the fault probability, and the location of the faulty element most likely to cause an electric arc is output.

[0095] Compared with existing technologies that rely on arc light sensor area alarms and manual inspection by maintenance personnel, the embodiments of this application automatically narrow down the fault area, screen visible components, introduce acoustic verification, and quantitatively assess the fault probability by fusing three-dimensional images and sensor data. This helps to solve the problems of existing technologies being unable to accurately locate faulty components and the low efficiency of manual inspection due to component obstruction.

[0096] In one feasible implementation, the sensor includes multiple arc light sensors disposed at different locations.

[0097] The determination of the fault region based on the detection range of each arc sensor and spatial geometric relationships includes: Obtain a sensing area determined based on the detection range of each of the arc sensors; the sensing area includes a first sensing area corresponding to the first sensor and a second sensing area corresponding to the second sensor, wherein the second sensor is an arc sensor that has not detected an arc signal; the spatial area that is simultaneously located within all the first sensing areas and not located within any of the second sensing areas is determined as the fault area.

[0098] Multiple arc sensors are installed in different locations inside the switch cabinet. Each sensor has its own detection range, which determines the spatial area in which the sensor can effectively detect arc signals.

[0099] When an arc fault occurs, some sensors will detect the signal (called the first sensor), while others will not (called the second sensor). Both types of sensors can be used to help determine the fault area.

[0100] First, the sensing area corresponding to each first sensor (referred to as the first sensing area) and the sensing area corresponding to each second sensor (referred to as the second sensing area) are obtained. The first sensing area represents the spatial range in which the first sensor can detect the arc signal, and the second sensing area represents the spatial range in which the second sensor can detect the arc signal.

[0101] Since the first sensor has detected an arc signal, the fault source must be located within its sensing area. Therefore, the fault source must simultaneously be located within the overlapping area of ​​all first sensing areas. Conversely, since the second sensor has not detected an arc signal, the fault source should not be located within its sensing area. Therefore, the fault source must avoid all second sensing areas.

[0102] Based on the above analysis, the spatial region that is simultaneously located within all first sensing regions but not within any second sensing region is defined as the fault region. This can be described using set operations: taking the intersection of all first sensing regions and subtracting the union of all second sensing regions. The region delineated in this way represents the most likely spatial location of the fault source. Subsequent candidate component screening will focus on this region, thereby significantly narrowing the search range, reducing computational load, and improving localization efficiency.

[0103] It should be noted that the sensing area of ​​each sensor is determined based on its detection range. The detection range includes not only the area where light travels directly to the photosensitive surface (direct area), but also the area where light reaches the photosensitive surface after being reflected or refracted by internal components of the switch cabinet (indirect area). This implementation scheme does not distinguish between direct and indirect areas when determining the sensing area; instead, it combines both into the overall sensing area of ​​the sensor for fault area determination. This approach is simple to implement, covers the effects of reflected and refracted light, and is suitable for scenarios where ease of implementation is crucial.

[0104] In a feasible implementation, when the components inside the switchgear are relatively sparsely distributed with minimal obstruction, or when the positioning accuracy requirement is relatively low, only the direct path of light without reflection or refraction can be considered, and reflected and refracted light can be treated as interference factors and ignored. In this case, within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image, the first component that satisfies the optical constraint relationship with at least one first sensor is selected, including: For each target component and each first sensor within the fault area, a spatial straight-line path for the propagation of light from the target component to the first sensor is determined.

[0105] Based on the three-dimensional image, determine whether the spatial straight path is blocked by the component; determine the geometric propagation distance of the spatial straight path; determine the angle between the direction of the spatial straight path (the direction of the incident ray along the light propagation path between the target component and the first sensor) and the normal direction of the photosensitive surface of the first sensor, as the incident angle.

[0106] If the spatial straight line is not blocked by the component, the incident angle is less than half of the field of view of the first sensor, and the geometric propagation distance is less than the maximum detection distance of the first sensor (at this time, the first theoretical light intensity value of the light from the target component to the photosensitive surface of the first sensor is greater than or equal to the trigger threshold of the photosensitive surface of the first sensor, that is, it can be detected by the first sensor), then it is determined that the target component and the first sensor satisfy the optical constraint relationship, and it is regarded as the first component.

[0107] In this scheme, since reflection and refraction paths are not considered, only components whose direct path can be detected by the sensor will enter the candidate set. This method has low computational complexity, is simple to implement, and is suitable for scenarios with high real-time positioning requirements or relatively simple internal structures of switch cabinets.

[0108] When the components inside the switch cabinet are densely packed, severely obstructed, or when high positioning accuracy is required, it is necessary to further consider the influence of reflection and refraction paths, and include non-linear propagating light in the analysis scope to improve the coverage of candidate faulty components and the accuracy of positioning.

[0109] In this embodiment of the application, to simplify the calculation, the determination can be made in the following way: First, determine if there are any other components besides yourself in the path of the light beam. If there are no other components blocking it, then further check two conditions: one is the angle between the incident ray direction of the light beam and the normal direction of the sensor's photosensitive surface (i.e., the incident angle). Is it smaller than the sensor's full field of view? The first is whether the component is within the sensor's effective field of view; the second is whether the length of the light propagation path (i.e., the geometric propagation distance) is less than the maximum distance at which the sensor can reliably detect an electric arc. .

[0110] That is, if the following three conditions are met simultaneously: Condition 1: The straight path is not obstructed.

[0111] Condition two:

[0112] Condition three:

[0113] Among them, the maximum detection distance It is determined by both the sensor's trigger threshold and the light intensity attenuation law. If all three conditions are met simultaneously, it proves that the straight path between the candidate faulty component and the first sensor is not blocked, and the incident angle is... Within the field of view detectable by the first sensor, and the path length Not exceeding the maximum detection distance of this first sensor It is assumed that the candidate faulty component satisfies the optical constraint relationship between the first sensor and the component in this scenario. Therefore, this component is listed as the first component.

[0114] This judgment method is based on the rectilinear propagation principle of geometric optics, combining constraints from three dimensions: obstruction, field of view, and distance. It can accurately screen out components that are truly likely to be "seen" by the sensor (the first component). Furthermore, since it only involves geometric calculations (straight path judgment, angle comparison, and distance comparison), it does not require complex light intensity attenuation model iterations or reflection and refraction tracking. Therefore, the computational load is small, and component screening can be completed within milliseconds after an arc occurs, meeting the real-time requirements for switchgear fault location.

[0115] In scenarios requiring higher positioning accuracy, the analysis of reflection and refraction paths can be further introduced based on this solution, but the computational load will increase accordingly. The line-of-sight filtering scheme provided in this application embodiment can cover the positioning needs of most internal faults in switchgear while ensuring real-time performance.

[0116] In a feasible implementation, when the components inside the switchgear are densely packed and severely obstructed, and the requirements for positioning accuracy are high while the requirements for real-time performance are relatively low (for example, after detecting an arc and cutting off the power, it is not necessary to immediately troubleshoot the fault, and a certain amount of calculation time can be tolerated), it is necessary to fully consider the propagation path of light after reflection or refraction to improve the accuracy of fault location. In this case, obtaining the sensing area determined based on the detection range of each arc sensor includes: For each of the arc light sensors, combined with the three-dimensional shape of each component in the three-dimensional image, starting from the photosensitive surface of the arc light sensor, several reverse light propagation paths in three-dimensional space are obtained by tracing in the opposite direction along the straight line, the reflection direction, and / or the refraction direction; the starting point of the reverse light propagation path is the photosensitive surface, and the ending point is the component.

[0117] For each of the reverse light propagation paths, based on the geometric propagation distance of the reverse light propagation path, the first theoretical light intensity value of the light reaching the photosensitive surface is deduced; reverse light propagation paths with the first theoretical light intensity value greater than or equal to the trigger threshold of the photosensitive surface are selected; the area where the component indicated by the endpoint in the selected reverse light propagation path is located is determined as the sensing area of ​​the arc light sensor.

[0118] First, for each arc light sensor, based on the three-dimensional shape of each component in the three-dimensional image, several reverse ray propagation paths are obtained in three-dimensional space by tracing back from the photosensitive surface of the arc light sensor along the straight line, reflection direction, and / or refraction direction (the forward ray propagation path is from the component to the photosensitive surface). The starting point of each reverse ray propagation path is the photosensitive surface, and the ending point is the component that the end of the reverse ray propagation path points to.

[0119] When tracing backwards along a straight line, starting from the photosensitive surface and extending along the straight line, the first component encountered is the end point of the path, corresponding to the case where light propagates directly without reflection or refraction. When tracing backwards along the direction of reflection or refraction, the light may undergo one or more reflections and refractions during its propagation. Each time it encounters a reflecting or refracting surface, it changes direction according to the laws of reflection or refraction and continues tracing until it finally points to a certain component, which is the end point of the path, corresponding to the case where light propagates after reflection or refraction.

[0120] It is important to note that, based on the fundamental principles of the law of reflection, and combined with the position and orientation of the reflecting surface in the 3D image, the propagation direction of the reflected path can be calculated. Specifically, given the direction of the incident ray incident on the reflecting surface and the normal to the reflecting surface, the direction of the reflected ray can be calculated using vector formulas.

[0121] Similarly, based on the fundamental principles of Snell's law of refraction, and combined with the position and orientation of the refracting surface in the 3D image, as well as the refractive indices of each medium, the propagation direction of the refracted path can be calculated. Specifically, given the direction of the incident ray, the interface normal, and the refractive indices of the two media, the direction of the refracted ray can be calculated using vector formulas. When the angle of incidence exceeds the critical angle, total internal reflection occurs, and in this case, it is handled according to the law of reflection.

[0122] By performing the reverse tracing described above, several reverse light propagation paths can be obtained from the sensor, pointing towards each component through different propagation methods (straight line, reflection, and / or refraction). These paths reflect which components can propagate light to the sensor via which paths.

[0123] Combination Figure 3 Please provide an explanation, such as Figure 3 The top view of light propagation shown shows that, tracing back from the position of the arc sensor 301, if it extends along a straight line (ignoring refraction and reflection), the first encountered component 304 is the end point of the path, so the reverse light propagation route 311 can be traced back.

[0124] If refraction is considered, then component 304 is a reflective surface, allowing the tracking of component 302. The starting point is the photosensitive surface of the arc sensor 301, and the ending point is component 302. The reverse light propagation path (including the refraction path) between them is path 312 (refraction through the surface of component 304). Component 303 is located between components 304 and 302, forming a barrier that blocks some of the refracted light.

[0125] It should be noted that there are several routes from component 304 or component 302 to arc sensor 301, and the figure only shows one possible route as an example.

[0126] Secondly, for each reverse ray propagation path, the first theoretical light intensity value when the light travels forward along that path to reach the photosensitive surface needs to be deduced based on the geometric propagation distance of that path. Considering that reverse tracing in three-dimensional space may generate a large number of reverse ray propagation paths, especially when the number of reflections and refractions is high, the number of paths will increase exponentially. However, not all (forward) ray propagation paths can effectively deliver light to the sensor. For example, for paths with excessively long propagation distances, the light intensity will attenuate due to the inverse square law, failing to reach the trigger threshold of the photosensitive surface and thus failing to trigger the sensor; for paths with too many reflections or refractions, each reflection or refraction introduces additional light intensity loss (e.g., reflectivity or transmittance is less than 1), resulting in the final light intensity reaching the photosensitive surface being lower than the trigger threshold. Furthermore, paths with excessively long propagation paths or too many reflections and refractions are highly unlikely to be detected by the sensor in actual arc faults. Therefore, by calculating the first theoretical light intensity value for each path, the practical significance of that path can be quantitatively assessed. The calculation process for the first theoretical light intensity value is the same as the calculation principle for the second theoretical light intensity value (first theoretical light intensity value...). (This will not be elaborated upon here.)

[0127] Then, the first theoretical light intensity value corresponding to each reverse ray propagation path is compared with the trigger threshold of the photosensitive surface, and reverse ray propagation paths with a first theoretical light intensity value greater than or equal to the trigger threshold are selected. Only paths that meet this condition are considered to have the ability to effectively propagate along the path in the forward direction and trigger the sensor. For paths with a first theoretical light intensity value lower than the trigger threshold, even if a geometric propagation path exists, it cannot actually be detected by the sensor and is therefore ignored in subsequent processing. Through this screening step, a large number of invalid or low-probability paths can be eliminated, effectively controlling the computational load while ensuring the focus of subsequent analysis.

[0128] Finally, the area where the endpoint of the selected reverse light propagation path indicates the location of the component is determined as the sensing area of ​​the arc light sensor. In other words, a component is considered to belong to the sensor's sensing area only if it is located at the endpoint of at least one valid light propagation path. These components represent all possible fault sources that can propagate light to the sensor via direct, reflected, or refracted paths, provided that the light intensity constraint is met. The sensing area determined in this way covers both components along the direct path and components that can be effectively detected by the sensor through a limited number of reflections or refractions. This allows for a more comprehensive capture of potential fault locations within densely populated and heavily obstructed switchgear, providing accurate spatial constraints for the subsequent screening of candidate faulty components.

[0129] In summary, the sensing area determined in this way includes not only components along the direct path of light but also those that can be "seen" by the sensor through reflection or refraction. Inside switchgear cabinets with densely packed components and significant obstructions, many fault sources may not be detectable by the sensor through the direct path but can be detected through reflection or refraction. Therefore, this scheme can more comprehensively cover potential fault sources, improving the recall rate of candidate faulty components and the accuracy of final location. However, due to the need for multi-directional reverse tracking and light intensity attenuation calculations, this scheme has a relatively large computational load, and its real-time performance is somewhat lower than a simplified scheme that only considers the direct path. It is suitable for scenarios with high positioning accuracy requirements but relatively relaxed real-time requirements.

[0130] In one feasible implementation, the switch cabinet is provided with multiple different sensor locations, each sensor location being provided with an arc light sensor and a microphone sensor; Based on the detection values ​​and time differences of sound signals detected by at least two microphone sensors, it is verified whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components, including: Acquire the sound signal detected by each microphone sensor.

[0131] The location of the electric arc source is determined based on the magnitude of the sound signal detected by the microphone sensors at the multiple sensor locations; the direction of arc propagation from the electric arc source is determined based on the time difference of the sound signal detected by the microphone sensors at the multiple sensor locations.

[0132] For each of the first components, verify whether the light propagation path between the first component and the sensor position corresponding to each of the first sensors conforms to the arc propagation direction; the first components that conform to the arc propagation direction are selected as candidate faulty components to evaluate the failure probability of each candidate faulty component.

[0133] When an arc fault occurs, the sound signal detected by each microphone sensor is acquired first.

[0134] By analyzing the magnitude and time difference of sound signals detected by multiple microphone sensors, the location or propagation direction of the arc sound source can be determined. In scenarios with low precision requirements or limited computing resources, a macroscopic directional information (e.g., from left to right, from east to west, from the busbar room to the cable room) can be obtained by comparing the magnitude of the detected values ​​and the order of the time differences. In scenarios with high precision requirements and sufficient computing resources, more refined positioning calculations can be performed using the time differences between multiple microphones, including determining the approximate coordinates of the sound source in space.

[0135] For each first component, determine whether its position matches the acoustic localization result (direction or position). If they match, the first component is identified as the second component. This second component is a candidate faulty element that simultaneously meets both acoustic and optical constraints, and proceeds to the subsequent probability evaluation step.

[0136] It should be noted that the specific accuracy of acoustic positioning depends on the number of microphones, their deployment method, and the sampling time resolution; this application does not limit these aspects. Regardless of whether acoustic positioning provides a macroscopic direction or a fine location, its core function is to cross-verify with the optical analysis results: the component location given by the optical analysis should fall within the direction or area indicated by the acoustic positioning. Through this joint acoustic-optical verification, potential false positives that may arise from optical path analysis can be effectively eliminated.

[0137] In one feasible implementation, acquiring a three-dimensional image of the switch cabinet interior includes: Acquire an initial 3D image of the switch cabinet interior; acquire a real-time 3D image obtained through point cloud scanning; and use the real-time 3D image to correct the initial 3D image to obtain the current 3D image.

[0138] First, an initial 3D image of the switchgear's interior is obtained. This initial image can be a CAD model created when the switchgear leaves the factory or is initially installed and commissioned, or it can be 3D modeling data obtained through scanning at a certain reference point. It reflects the shape and positional relationship of the various components inside the switchgear at that reference point.

[0139] Simultaneously, real-time 3D images obtained through point cloud scanning are acquired. Point cloud scanning refers to using LiDAR, depth cameras, or structured light scanning devices to collect real-time data of the interior of the switch cabinet, obtaining the 3D coordinate data of each component's surface points at the current moment.

[0140] Because switchgear may change during operation or maintenance (such as component removal and replacement, cable rearrangement, loose screws causing part displacement, etc.), the positions or shapes of some components in the initial 3D image may deviate from the actual situation. Therefore, real-time 3D images can be used to correct the initial 3D image. By comparing real-time point cloud data with the initial image, the changed locations are identified, and the corresponding parts in the initial image are updated to match the actual state. The corrected result is the current 3D image.

[0141] The three-dimensional images obtained in this way can accurately reflect the current state inside the switch cabinet, avoiding positioning deviations caused by changes in the position of components, and helping to improve the accuracy of subsequent fault component screening.

[0142] In one feasible implementation, after determining the target faulty component from the candidate faulty components based on the fault probability, the method further includes: The target faulty components are sorted in descending order of fault probability to obtain a faulty component queue; the faulty component queue is displayed on the interactive terminal; the interactive terminal includes: the display screen of the switch cabinet, and / or, the equipment terminal of the maintenance personnel.

[0143] In other words, after identifying the target faulty component, the results can be further organized and displayed. For example, the candidate faulty components can be sorted in descending order of their failure probability to form a faulty component queue. Components with higher failure probabilities are placed further up in the queue, indicating that they are more likely to be the true source of the failure.

[0144] Subsequently, the queue of faulty components is displayed on the interactive terminal. The interactive terminal can take different forms: for example, it can be displayed directly on the display screen built into the switchgear itself, making it convenient for on-site maintenance personnel to view it immediately; it can also be pushed to the mobile devices (such as mobile phones, tablets, or dedicated handheld terminals) held by maintenance personnel, making it convenient to receive and view remotely; it can also be sent to multiple devices simultaneously to ensure that information can be transmitted in a timely manner.

[0145] This display method allows maintenance personnel to quickly understand the order of the most likely faulty components and prioritize checking components with higher probability of failure according to the queue order, thereby further improving fault diagnosis efficiency and shortening power outage time.

[0146] This application provides a method, apparatus, electronic device, and storage medium for locating faulty components in a switchgear. First, a three-dimensional image of the switchgear's interior and the detection values ​​of each sensor are acquired. The sensors include an arc light sensor and a microphone sensor, and the three-dimensional image contains three-dimensional morphological information of each component.

[0147] When the detection value of any arc sensor indicates that an arc signal has been detected, the fault area is determined based on the detection range of each arc sensor and spatial geometric relationships, thereby narrowing down the possible range of the faulty component from the entire switch cabinet to a smaller spatial area.

[0148] Based on this, within the fault area, and combining the three-dimensional morphology of each component in the three-dimensional image, components that satisfy the optical constraint relationship with at least one first sensor are selected and referred to as first components. The first sensor is an arc light sensor that detects arc signals. The optical constraint relationship means that light emitted from the component can reach the photosensitive surface of the first sensor through the light propagation path (including straight-line propagation, reflection, or refraction) and satisfy the sensor's triggering conditions. By introducing the optical constraint relationship, interference items that cannot be directly "seen" by the sensor due to component obstruction can be effectively eliminated.

[0149] Furthermore, based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, the light propagation path corresponding to each first component is verified to ensure that it meets the acoustic constraints. Second components that simultaneously meet both optical and acoustic constraints are then selected as candidate faulty components. This combined acoustic-optical verification further improves the reliability of candidate faulty components and reduces misjudgments caused by optical interference such as reflection and refraction.

[0150] Then, based on the geometric propagation distance and incident angle of the light path between each candidate faulty element and each first sensor, as well as the detection value of each arc sensor, the failure probability of each candidate faulty element is evaluated. Specifically, the theoretical light intensity value is calculated based on the geometric propagation distance and incident angle, and compared with the actual detection value; the closer the two are, the higher the failure probability.

[0151] Finally, the target faulty element is determined from the candidate faulty elements based on the fault probability, and the location of the faulty element most likely to cause an electric arc is output.

[0152] Compared with existing technologies that rely on arc light sensor area alarms and manual inspection by maintenance personnel, the embodiments of this application automatically narrow down the fault area, screen visible components, introduce acoustic verification, and quantitatively assess the fault probability by fusing three-dimensional images and sensor data. This helps to solve the problems of existing technologies being unable to accurately locate faulty components and the low efficiency of manual inspection due to component obstruction.

[0153] Based on the same technical concept, embodiments of this application also provide a fault component location device for switchgear, such as... Figure 4 As shown, the device includes: The acquisition module 401 is used to acquire a three-dimensional image of the inside of the switch cabinet and the three-dimensional coordinates of each sensor; the sensors include an arc light sensor and a microphone sensor.

[0154] The region determination module 402 is used to determine the fault region based on the detection range of each arc sensor and through spatial geometric relationships when the detection value of any arc sensor indicates that an arc signal has been detected.

[0155] The first screening module 403 is used to screen out first components that satisfy optical constraint relationships with at least one first sensor within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image; the first sensor is an arc light sensor that detects arc signals, and the optical constraint relationship is: light emitted from the position of the first component reaches the photosensitive surface of the first sensor through the light propagation path and satisfies the triggering condition of the first sensor.

[0156] The second screening module 404 is used to verify whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship based on the detection value and time difference of the sound signals detected by at least two microphone sensors, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components.

[0157] Evaluation module 405 is used to evaluate the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, as well as the magnitude of each detection value.

[0158] The positioning module 406 is used to determine the target faulty component from the candidate faulty components based on the fault probability.

[0159] In one feasible implementation, the sensor includes multiple arc light sensors disposed at different locations.

[0160] The region determination module is used to determine the fault region based on the detection range of each arc sensor and through spatial geometric relationships, including: A sensing area is obtained based on the detection range of each of the arc sensors; the sensing area includes a first sensing area corresponding to the first sensor and a second sensing area corresponding to the second sensor, wherein the second sensor is an arc sensor that has not detected an arc signal.

[0161] The spatial region that is simultaneously located within all of the first sensing regions and not within any of the second sensing regions is defined as the fault region.

[0162] In one feasible implementation, the region determination module is used to obtain a sensing region determined based on the detection range of each of the arc sensors, including: For each of the arc light sensors, combined with the three-dimensional shape of each component in the three-dimensional image, starting from the photosensitive surface of the arc light sensor, several reverse light propagation paths in three-dimensional space are obtained by tracing in the opposite direction along the straight line, the reflection direction, and / or the refraction direction; the starting point of the reverse light propagation path is the photosensitive surface, and the ending point is the component.

[0163] For each of the aforementioned reverse ray propagation paths, based on the geometric propagation distance of the reverse ray propagation path, the first theoretical light intensity value of the light reaching the photosensitive surface is deduced.

[0164] The reverse light propagation path is selected when the first theoretical light intensity value is greater than or equal to the trigger threshold of the photosensitive surface.

[0165] The area where the component located, indicated by the endpoint of the selected reverse light propagation path, is located is determined as the sensing area of ​​the arc light sensor.

[0166] In one feasible implementation, the switch cabinet is provided with multiple different sensor locations, each sensor location being equipped with an arc light sensor and a microphone sensor.

[0167] The second screening module is used to verify whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, so as to screen out second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components, including: Acquire the sound signal detected by each microphone sensor.

[0168] The location of the electric arc source is determined based on the magnitude of the sound signal detected by the microphone sensors at the locations of the multiple sensors.

[0169] Based on the time difference of the sound signals detected by the microphone sensors at the locations of the plurality of sensors, the direction of arc propagation from the arc sound source is determined.

[0170] For each of the first components, verify whether the light propagation path between the first component and the sensor position corresponding to each of the first sensors conforms to the arc propagation direction. The first component corresponding to the direction of arc propagation is selected as a candidate fault component to evaluate the failure probability of each candidate fault component.

[0171] In one feasible implementation, the evaluation module is used to evaluate the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, and the magnitude of each of the detection values, including: The second theoretical light intensity value reaching each of the first sensors is calculated based on the geometric propagation distance between each of the candidate faulty elements and each of the first sensors and the incident angle of the photosensitive surface of the first sensor.

[0172] For each candidate faulty element, the fault probability of the candidate faulty element is determined based on the degree of difference between the theoretical light intensity value and the actual detection value of each of the first sensors; the degree of difference is negatively correlated with the fault probability.

[0173] In one feasible implementation, the evaluation module is configured to calculate a second theoretical light intensity value reaching each of the first sensors based on the geometric propagation distance between each of the candidate faulty components and each of the first sensors and the incident angle of the photosensitive surface of the first sensor, including: The angle between the incident ray from the candidate faulty element to the first sensor and the normal direction of the photosensitive surface of the first sensor is determined as the incident angle.

[0174] Based on Lambert's cosine law, the angle attenuation factor is determined; the angle attenuation factor decreases monotonically as the incident angle increases.

[0175] Based on the inverse square law, a distance attenuation factor is determined; the distance attenuation factor decreases monotonically as the geometric propagation distance increases.

[0176] The second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor.

[0177] In one feasible implementation, the evaluation module is used to determine the second theoretical light intensity value based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor, including: If the light propagation path between the candidate faulty element and the first sensor includes a reflection path and / or a refraction path, then the product of the preset reference light intensity value and the distance attenuation factor and the angle attenuation factor is calculated to obtain the first value.

[0178] The second value is obtained by multiplying the first value by the reflection attenuation factor and the refraction attenuation factor; the reflection attenuation factor is determined based on the number of reflections and the material of the reflecting surface, and the refraction attenuation factor is determined by the number of refractions and the refractive index of the medium.

[0179] The second value is determined as the second theoretical light intensity value.

[0180] In one feasible implementation, the first acquisition module is used to acquire a three-dimensional image of the inside of the switch cabinet, including: Obtain an initial 3D image of the inside of the switch cabinet.

[0181] Acquire real-time 3D images obtained through point cloud scanning.

[0182] The initial 3D image is corrected using the real-time 3D image to obtain the current 3D image.

[0183] In one feasible implementation, the device further includes: The sorting module is used to sort the target faulty components from the candidate faulty components according to the fault probability after determining the target faulty component based on the fault probability, thereby obtaining a faulty component queue.

[0184] A display module is used to display the queue of faulty components on an interactive terminal; the interactive terminal includes: the display screen of the switch cabinet, and / or, the equipment terminal of the maintenance personnel.

[0185] Figure 5 A schematic diagram of an electronic device provided in this application embodiment includes: a processor 501, a storage medium 502, and a bus 503. The storage medium 502 stores machine-readable instructions executable by the processor 501. When the electronic device runs the fault component location method of the switch cabinet as described in the embodiment, the processor 501 communicates with the storage medium 502 through the bus 503, and the processor 501 executes the machine-readable instructions to perform the steps as described in the embodiment.

[0186] In this embodiment, the storage medium 502 may also execute other machine-readable instructions to perform other methods as described in the embodiment. For details on the specific execution steps and principles, please refer to the description of the embodiment, which will not be repeated here.

[0187] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to perform the steps as described in the embodiments.

[0188] In this embodiment, the computer program, when run by the processor, can also execute other machine-readable instructions to perform other methods as described in the embodiments. For details on the specific execution steps and principles, please refer to the description of the embodiments, which will not be repeated here.

[0189] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0190] The modules described as separate components may or may not be physically separate. The components shown as modules 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.

[0191] In addition, 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.

[0192] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0193] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for locating faulty components in a switchgear, characterized in that, The method includes: Acquire a three-dimensional image of the inside of the switch cabinet and the detection values ​​of each sensor; the sensors include an arc light sensor and a microphone sensor; When the detection value of any arc sensor indicates that an arc signal has been detected, the fault area is determined by spatial geometry based on the detection range of each arc sensor. Within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image, a first component that satisfies an optical constraint relationship with at least one first sensor is selected; the first sensor is an arc light sensor that detects an arc signal, and the optical constraint relationship is: light emitted from the position of the first component reaches the photosensitive surface of the first sensor through the light propagation path and satisfies the triggering condition of the first sensor. Based on the detection values ​​and time differences of the sound signals detected by at least two microphone sensors, it is verified whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components; The failure probability of each candidate faulty element is evaluated based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, as well as the magnitude of each detection value. Based on the failure probability, the target failure element is determined from the candidate failure elements; The sensor includes multiple arc light sensors disposed at different locations; The determination of the fault region based on the detection range of each arc sensor and spatial geometric relationships includes: Obtain a sensing area determined based on the detection range of each of the arc sensors; the sensing area includes a first sensing area corresponding to the first sensor and a second sensing area corresponding to the second sensor, wherein the second sensor is an arc sensor that has not detected an arc signal; The spatial region that is simultaneously located within all of the first sensing regions and not located within any of the second sensing regions is defined as the fault region; Obtaining the sensing area determined based on the detection range of each of the arc sensors includes: For each of the arc light sensors, combined with the three-dimensional shape of each component in the three-dimensional image, starting from the photosensitive surface of the arc light sensor, reverse tracing is performed along the straight line direction, the reflection direction, and / or the refraction direction to obtain several reverse light propagation paths in three-dimensional space; the starting point of the reverse light propagation path is the photosensitive surface, and the ending point is the component. For each of the aforementioned reverse ray propagation paths, based on the geometric propagation distance of the reverse ray propagation path, the first theoretical light intensity value of the light reaching the photosensitive surface is deduced; Select reverse light propagation paths whose first theoretical light intensity value is greater than or equal to the trigger threshold of the photosensitive surface; The area where the component located, indicated by the endpoint of the selected reverse light propagation path, is located is determined as the sensing area of ​​the arc light sensor.

2. The method according to claim 1, characterized in that, The switch cabinet is equipped with multiple different sensor locations, and each sensor location is equipped with an arc light sensor and a microphone sensor. Based on the detection values ​​and time differences of sound signals detected by at least two microphone sensors, it is verified whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components, including: Acquire the sound signal detected by each microphone sensor; The location of the electric arc source is determined based on the magnitude of the sound signal detected by the microphone sensors at the locations of the multiple sensors. Based on the time difference of the sound signals detected by the microphone sensors at the locations of the plurality of sensors, the direction of arc propagation from the arc sound source is determined; For each of the first components, verify whether the light propagation path between the first component and the sensor position corresponding to each of the first sensors conforms to the arc propagation direction. The first component corresponding to the direction of arc propagation is selected as a candidate fault component to evaluate the failure probability of each candidate fault component.

3. The method according to claim 1, characterized in that, The assessment of the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, and the magnitude of each detection value, includes: The second theoretical light intensity value reaching each of the first sensors is calculated based on the geometric propagation distance between each of the candidate faulty elements and each of the first sensors and the incident angle of the photosensitive surface of the first sensor. For each candidate faulty element, the fault probability of the candidate faulty element is determined based on the degree of difference between the theoretical light intensity value and the actual detection value of each of the first sensors; the degree of difference is negatively correlated with the fault probability.

4. The method according to claim 3, characterized in that, The step of calculating the second theoretical light intensity value reaching each of the first sensors based on the geometric propagation distance between each of the candidate faulty components and each of the first sensors and the incident angle of the light onto the photosensitive surface of the first sensor includes: The angle between the incident ray from the candidate faulty element to the first sensor and the normal direction of the photosensitive surface of the first sensor is determined as the incident angle; Based on Lambert's cosine law, the angle attenuation factor is determined; the angle attenuation factor decreases monotonically as the incident angle increases. Based on the inverse square law, the distance attenuation factor is determined; the distance attenuation factor decreases monotonically as the geometric propagation distance increases. The second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor.

5. The method according to claim 4, characterized in that, If the light propagation path between the candidate faulty element and the first sensor includes a reflection path and / or a refraction path, then the second theoretical light intensity value is determined based on the product of a preset reference light intensity value and the distance attenuation factor and the angle attenuation factor, including: The first value is obtained by multiplying the preset reference light intensity value by the distance attenuation factor and the angle attenuation factor. The second value is obtained by multiplying the first value by the reflection attenuation factor and the refraction attenuation factor; the reflection attenuation factor is determined based on the number of reflections and the material of the reflecting surface, and the refraction attenuation factor is determined by the number of refractions and the refractive index of the medium. The second value is determined as the second theoretical light intensity value.

6. A fault component location device for a switchgear, characterized in that, The device includes: The acquisition module is used to acquire a three-dimensional image of the inside of the switch cabinet and the three-dimensional coordinates of each sensor; the sensors include an arc light sensor and a microphone sensor. The region determination module is used to determine the fault region based on the detection range of each arc sensor and through spatial geometric relationships when the detection value of any arc sensor indicates that an arc signal has been detected. The first screening module is used to screen out first components that satisfy optical constraint relationships with at least one first sensor within the fault area, based on the three-dimensional morphology of each component in the three-dimensional image; the first sensor is an arc light sensor that detects arc signals, and the optical constraint relationship is: light emitted from the position of the first component reaches the photosensitive surface of the first sensor through the light propagation path and satisfies the triggering condition of the first sensor. The second screening module is used to verify whether the light propagation path corresponding to each of the first components satisfies the acoustic constraint relationship based on the detection value and time difference of the sound signals detected by at least two microphone sensors, so as to screen out the second components that simultaneously satisfy the optical constraint relationship and the acoustic constraint relationship as candidate faulty components; An evaluation module is used to evaluate the failure probability of each candidate faulty element based on the geometric propagation distance and incident angle of the light propagation path between each candidate faulty element and each of the first sensors, as well as the magnitude of each detection value. A positioning module is used to determine a target faulty component from the candidate faulty components based on the fault probability; The sensor includes multiple arc light sensors disposed at different locations; The region determination module is used to determine the fault region based on the detection range of each arc sensor and through spatial geometric relationships, including: Obtain a sensing area determined based on the detection range of each of the arc sensors; the sensing area includes a first sensing area corresponding to the first sensor and a second sensing area corresponding to the second sensor, wherein the second sensor is an arc sensor that has not detected an arc signal; The spatial region that is simultaneously located within all of the first sensing regions and not located within any of the second sensing regions is defined as the fault region; The region determination module is used to obtain a sensing region determined based on the detection range of each arc light sensor, including: For each of the arc light sensors, combined with the three-dimensional shape of each component in the three-dimensional image, starting from the photosensitive surface of the arc light sensor, reverse tracing is performed along the straight line direction, the reflection direction, and / or the refraction direction to obtain several reverse light propagation paths in three-dimensional space; the starting point of the reverse light propagation path is the photosensitive surface, and the ending point is the component. For each of the aforementioned reverse ray propagation paths, based on the geometric propagation distance of the reverse ray propagation path, the first theoretical light intensity value of the light reaching the photosensitive surface is deduced; Select reverse light propagation paths whose first theoretical light intensity value is greater than or equal to the trigger threshold of the photosensitive surface; The area where the component located, indicated by the endpoint of the selected reverse light propagation path, is located is determined as the sensing area of ​​the arc light sensor.

7. An electronic device, characterized in that, include: The device includes a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is in operation, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the fault component location method for the switch cabinet as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the fault component location method for the switchgear as described in any one of claims 1 to 5.

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