A photovoltaic charging pile diagnosis operation and maintenance method and system based on a fault tree

Abstract

This invention relates to the field of photovoltaic diagnostic technology, and discloses a method and system for diagnosing and maintaining photovoltaic charging piles based on fault trees. The method includes: collecting multi-source state signals of photovoltaic charging piles to generate a set of fault phenomena of photovoltaic charging piles; logically matching the set of fault phenomena with the fault tree topology to generate a set of fault response nodes of photovoltaic charging piles; synthesizing paths in the set of fault response nodes based on the logical gate relationships of the fault tree topology to generate a minimum fault path; using the minimum fault path as the unique maintenance execution sequence of photovoltaic charging piles, performing targeted maintenance on bottom event nodes based on the unique maintenance execution sequence to generate the maintenance response state of photovoltaic charging piles; if the maintenance response state has not recovered to the preset safe operating range, iteratively executing S2 to S4 until the photovoltaic charging pile recovers to the safe operating range or triggers a manual intervention mechanism. This invention can improve the efficiency of fault handling of photovoltaic charging piles.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic diagnostic technology, and in particular to a method and system for diagnosing and maintaining photovoltaic charging piles based on fault trees. Background Technology

[0002] In existing photovoltaic (PV) diagnostic technologies, traditional fault diagnosis methods mainly rely on manual inspections and threshold alarms. Maintenance personnel periodically check the equipment's appearance and read instrument data to detect anomalies. This single-signal-based monitoring method struggles to capture the inherent correlations between multi-source state signals. When a charging pile malfunctions, it often only indicates a system-level abnormality without pinpointing the specific faulty component. Existing technologies lack systematic analysis of fault propagation paths, making it difficult to clarify the logical relationships between different fault phenomena. This results in maintenance personnel being unable to quickly determine the root cause of complex fault information, forcing them to perform repeated troubleshooting. This leads to prolonged downtime for PV charging piles and low maintenance efficiency, failing to meet the high reliability requirements of PV charging pile operation.

[0003] While existing automated diagnostic systems can collect some operational data, there is a significant disconnect between diagnostic results and maintenance operations. Even after diagnostic reports are generated, manual interpretation and repair plan development are still required. This process lacks a standardized execution sequence, and the experience differences among maintenance personnel lead to inconsistent repair quality. Current methods struggle to directly translate diagnostic results into executable operational instructions. When initial repairs fail to restore normal equipment operation, the lack of an automated feedback and iteration mechanism necessitates restarting the manual troubleshooting process, resulting in insufficient self-healing capabilities of photovoltaic charging piles and high maintenance costs. Therefore, there is an urgent need to develop a fault tree-based diagnostic and maintenance method for photovoltaic charging piles to address the problems of inaccurate fault location, disconnect between diagnosis and maintenance, and lack of automated feedback and iteration in existing technologies, thereby improving the efficiency of photovoltaic charging pile fault diagnosis and the level of maintenance automation. Summary of the Invention

[0004] This invention provides a method and system for diagnosing and maintaining photovoltaic charging piles based on fault trees, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, this invention provides a photovoltaic charging pile diagnosis and maintenance method based on fault tree, comprising: S1: Collect multi-source status signals of the photovoltaic charging pile and generate a set of fault phenomena of the photovoltaic charging pile; S2: Logically match the set of fault phenomena with the preset fault tree topology to generate a set of fault response nodes; S3: Based on the logical gate relationship of the nodes in the fault tree topology, perform path synthesis on the fault response node set to generate the minimum fault path of the photovoltaic charging pile. The minimum fault path is composed of activated bottom event nodes in logical order. S4: Use the minimum fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, perform targeted operation and maintenance on the bottom event node based on the unique operation and maintenance execution sequence, and generate the operation and maintenance response status of the photovoltaic charging pile; S5: If the operation and maintenance response status has not recovered to the preset safe operating range, then S2 to S4 are executed iteratively until the photovoltaic charging pile recovers to the safe operating range or the manual intervention mechanism is triggered.

[0006] In a preferred embodiment, the preset fault tree topology includes: The system failure of the photovoltaic charging pile is taken as the top event node; The failure of the independent operation and maintenance components of the photovoltaic charging pile is taken as the bottom event node; The node between the top event node and the bottom event node is taken as the intermediate event node of the photovoltaic charging pile; The top event node, the bottom event node, and the intermediate event node are logically associated through logic gates to construct a fault tree topology.

[0007] In a preferred embodiment, the step of logically matching the set of fault phenomena with a preset fault tree topology to generate a set of fault response nodes includes: Extract intermediate event nodes and bottom event nodes from the fault tree topology to generate a complete set of nodes to be matched; Semantic association analysis is performed between the set of fault phenomena and the complete set of nodes to be matched, and nodes that match the fault phenomena in the set of fault phenomena are selected to generate a set of matching nodes. Based on the logic gate type of the nodes in the fault tree topology, the nodes in the first matching node set are backtracked upwards for verification to generate a second matching node set. Redundancy merging is performed on the nodes in the secondary matching node set to generate a fault response node set.

[0008] In a preferred embodiment, the step of performing semantic association analysis between the set of fault phenomena and the complete set of nodes to be matched, and filtering out nodes that match the fault phenomena in the set of fault phenomena to generate a primary matching node set, includes: Text features are extracted from the fault phenomena in the set of fault phenomena to generate phenomenon feature vectors; The nodes in the complete set of nodes to be matched are parsed using pre-stored labels to generate node feature vectors; Analyze the semantic similarity between the phenomenon feature vector and the node feature vector, and determine the nodes whose semantic similarity exceeds a preset semantic threshold as matching nodes; All the matching nodes are integrated into a single matching node set.

[0009] In a preferred embodiment, the step of performing upward backtracking verification on the nodes in the first-match node set based on the logic gate type of the nodes in the fault tree topology to generate a second-match node set includes: Select a node to be verified from the set of matched nodes, and obtain the parent node and the logic gate type of the parent node in the fault tree topology of the node to be verified. If the logic gate type of the parent node is an AND gate, then check whether all the child nodes associated with the parent node exist in the first matching node set. If there are any missing ones, then mark the node to be verified as a logical conflict node. If the logic gate type of the parent node is an OR gate, then check whether there is a child node associated with the parent node in the first matching node set. If not, then mark the node to be verified as the logic conflict node. Based on the logically conflicting nodes, the set of primary matching nodes is filtered to generate the set of secondary matching nodes.

[0010] In a preferred embodiment, the step of synthesizing paths for the fault response node set based on the logical gate relationships of nodes in the fault tree topology to generate the minimum fault path for the photovoltaic charging pile includes: Starting from the top event node, traverse downwards to each node in the fault response node set, record the complete path from the top event node to each node, and generate an initial path set; Cross-compare each path in the initial path set, delete redundant paths in each path, and generate a simplified path set; Each path in the simplified path set is logically simplified, and adjacent nodes with the same logical gate relationship are merged to generate a candidate fault path set. Calculate the coverage rate of each candidate path in the candidate fault path set, and select the candidate path with the highest coverage rate as the preliminary preferred path; If multiple candidate paths have the same maximum coverage, the path with the shortest path length among the multiple candidate paths is selected as the minimum fault path.

[0011] In a preferred embodiment, the coverage rate is calculated using the following formula:

[0012] in, For the coverage rate, This refers to the number of nodes in the fault response node set covered by the candidate path. The total number of nodes in the fault response node set. The path length of the current candidate path. The minimum path length in the candidate fault path set. The maximum path length in the set of candidate fault paths.

[0013] In a preferred embodiment, the step of using the least fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, performing targeted operation and maintenance on the bottom event nodes based on the unique operation and maintenance execution sequence, and generating the operation and maintenance response status of the photovoltaic charging pile includes: Based on the logical order of the fault tree topology, each bottom event node in the minimum fault path is extracted to generate an ordered list of operation and maintenance nodes. Query the preset operation and maintenance instruction mapping table to obtain the executable operation and maintenance instructions for each bottom event node in the ordered operation and maintenance node list; According to the logical order of the ordered operation and maintenance node list, the executable operation and maintenance instructions are sent to the photovoltaic charging pile in sequence, and the equipment execution feedback signals of the photovoltaic charging pile are monitored in real time. After the executable operation and maintenance instructions are executed, the operation and maintenance response status of the photovoltaic charging piles is summarized.

[0014] In a preferred embodiment, if the operation and maintenance response status does not recover to the preset safe operating range, S2 to S4 are iteratively executed until the photovoltaic charging pile recovers to the safe operating range or a manual intervention mechanism is triggered, including: Determine whether the photovoltaic charging pile is within the preset safe operating range; If the photovoltaic charging pile is outside the safe operation range, then extract the abnormal feature parameters in the operation and maintenance response status, and format and encapsulate the abnormal feature parameters into new fault phenomenon description data. Using the new fault phenomenon description data as input, iteratively execute steps S2 to S4 to generate a new round of operation and maintenance response status; The number of iterations is recorded. When the number of iterations reaches the iteration threshold and the operation and maintenance response status has not yet recovered to the safe operation range, the manual intervention mechanism is triggered, and a manual intervention request signal is sent to the operation and maintenance terminal of the photovoltaic charging pile.

[0015] To address the aforementioned problems, this invention also provides a photovoltaic charging pile diagnostic and maintenance system based on a fault tree, the system comprising: The fault phenomenon generation module is used to collect multi-source status signals of the photovoltaic charging pile and generate a set of fault phenomena of the photovoltaic charging pile. The fault logic matching module is used to logically match the set of fault phenomena with a preset fault tree topology to generate a set of fault response nodes. The fault path synthesis module is used to synthesize the fault response node set based on the logical gate relationship of the nodes in the fault tree topology to generate the minimum fault path of the photovoltaic charging pile. The minimum fault path is composed of activated bottom event nodes in logical order. The targeted operation and maintenance execution module is used to take the minimum fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, perform targeted operation and maintenance on the bottom event node based on the unique operation and maintenance execution sequence, and generate the operation and maintenance response status of the photovoltaic charging pile. The iterative feedback judgment module is used to iteratively execute S2 to S4 if the operation and maintenance response status has not recovered to the preset safe operating range, until the photovoltaic charging pile recovers to the safe operating range or the manual intervention mechanism is triggered.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention constructs a pre-defined fault tree topology to decompose system failures of photovoltaic charging piles layer by layer to independently maintainable bottom event nodes. Based on real-time collected multi-source state signals, it performs logical matching and path synthesis to accurately locate the root cause of the fault. During the logical matching process, the method sequentially performs semantic association analysis, upward backtracking verification, and redundancy merging to ensure the accuracy of the selected fault response node set. During path synthesis, through traversal, simplification, and optimization, it generates the minimum fault path composed of bottom event nodes in logical order. This process not only identifies the currently occurring fault phenomenon but also clarifies the propagation chain between faults, enabling maintenance personnel or automated systems to directly operate on specific repairable components. This avoids repeated troubleshooting caused by inaccurate fault location in traditional methods, significantly shortening downtime and improving the maintenance efficiency of photovoltaic charging piles.

[0017] 2. This invention uses the least fault path as the sole operation and maintenance execution sequence, executing preset operation and maintenance instructions corresponding to each bottom event node sequentially according to logical order, achieving precise alignment between diagnostic results and operation and maintenance operations. Simultaneously, this invention establishes an iterative feedback mechanism. When the initial operation and maintenance response state fails to recover to the preset safe operating range, the system automatically treats the current state as a new set of fault phenomena and re-executes the diagnostic and operation and maintenance process until the fault is eliminated or manual intervention is triggered. This closed-loop control method enables photovoltaic charging piles to possess automated fault self-healing capabilities, allowing them to complete multiple diagnostic and repair attempts without human intervention. Manual intervention is only requested when the number of iterations reaches a threshold and the fault is still not eliminated, greatly reducing the need for manual on-site inspections, lowering operation and maintenance labor costs, and improving the long-term reliability and stability of photovoltaic charging piles. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a photovoltaic charging pile diagnosis and maintenance method based on fault tree according to an embodiment of the present invention. Figure 2 This is a functional module diagram of a photovoltaic charging pile diagnostic and maintenance system based on a fault tree, provided in an embodiment of the present invention. The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides a fault tree-based diagnostic and maintenance method for photovoltaic charging piles. The execution entity of this fault tree-based photovoltaic charging pile diagnostic and maintenance method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the fault tree-based photovoltaic charging pile diagnostic and maintenance method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0021] Reference Figure 1The diagram shown is a flowchart illustrating a fault tree-based diagnostic and maintenance method for photovoltaic charging piles according to an embodiment of the present invention. In this embodiment, the reference information generation method based on artificial intelligence and smart home technology includes: S1: Collect multi-source status signals of the photovoltaic charging pile and generate a set of fault phenomena of the photovoltaic charging pile; In this embodiment of the invention, during the operation of the photovoltaic charging pile, various sensors installed in the photovoltaic modules, charging modules, energy storage units, control units, and environmental monitoring points collect various types of physical quantity signals such as voltage, current, power, temperature, humidity, and insulation resistance in real time. These sensors convert the detected analog quantities into electrical signals and transmit them to the data acquisition unit. The data acquisition unit quantizes the analog signals according to a fixed sampling period, converting the continuous signals into discrete digital signals.

[0022] The digital signal is then filtered to remove abnormal spikes caused by electromagnetic interference or sensor noise. Next, the cleaned data is normalized to convert signals of different dimensions into values ​​within a standard range. These standardized data are then compared item by item with pre-stored normal operating parameter thresholds in the system. When the value of a signal continuously exceeds the set normal range, the system determines that the event corresponding to the signal is abnormal. Based on the type and severity of the abnormality, the system retrieves the corresponding standard fault statements from a predefined fault phenomenon description library, such as low output power of photovoltaic array, over-temperature protection of charging module, and decreased insulation impedance. These statements are sorted and deduplicated according to the order of occurrence and severity, ultimately forming a fault phenomenon set containing all current abnormal situations.

[0023] The beneficial effects are that by collecting multi-source status signals from photovoltaic charging piles and generating a set of fault phenomena, a comprehensive perception of the equipment's operating status and a structured expression of abnormal information are achieved. This process transforms scattered sensor data into a unified fault description, providing accurate and complete input for subsequent fault diagnosis, significantly improving the comprehensiveness and real-time performance of fault identification, and avoiding missed or false alarms caused by monitoring a single signal. At the same time, the standardized format of the fault phenomenon set facilitates efficient matching with the fault tree topology, thereby accelerating the speed of fault location and laying a reliable data foundation for the intelligent operation and maintenance of photovoltaic charging piles.

[0024] S2: Logically match the set of fault phenomena with the preset fault tree topology to generate the fault response node set of the photovoltaic charging pile; In this embodiment of the invention, the preset fault tree topology includes: The system failure of the photovoltaic charging pile is taken as the top event node; The bottom event node of the fault tree topology is determined based on the fault of the independent operation and maintenance component of the photovoltaic charging pile; The nodes between the top event node and the bottom event node are used as intermediate event nodes in the fault tree topology. Based on the logic gates, the top event node, the bottom event node, and the intermediate event node are logically associated to construct the fault tree topology of the photovoltaic charging pile.

[0025] The step of logically matching the set of fault phenomena with a preset fault tree topology to generate a set of fault response nodes includes: Extract intermediate event nodes and bottom event nodes from the fault tree topology to generate a complete set of nodes to be matched in the fault tree topology. Semantic association analysis is performed on the set of fault phenomena and the complete set of nodes to be matched, and nodes that match the fault phenomena in the set of fault phenomena are selected to generate the first matching node set of the fault tree topology. Based on the logic gate type of the nodes in the fault tree topology, the nodes in the first-match node set are backtracked upwards for verification to generate the second-match node set of the fault tree topology. Redundancy merging is performed on the nodes in the secondary matching node set to generate a fault response node set.

[0026] The step of performing semantic association analysis between the set of fault phenomena and the complete set of nodes to be matched, filtering out nodes that match the fault phenomena in the set of fault phenomena, and generating a set of matching nodes includes: Text features are extracted from the fault phenomena in the fault phenomenon set to generate a phenomenon feature vector for the fault phenomenon set. The nodes in the complete set of nodes to be matched are parsed using pre-stored labels to generate the node feature vector of the fault phenomenon set; Analyze the semantic similarity between the phenomenon feature vector and the node feature vector, and determine the nodes whose semantic similarity exceeds a preset semantic threshold as matching nodes; All the matching nodes are integrated into a single matching node set.

[0027] The step of performing upward backtracking verification on the nodes in the first-match node set based on the logic gate type of the nodes in the fault tree topology to generate a second-match node set includes: Select a node to be verified from the set of matched nodes, and obtain the parent node and the logic gate type of the parent node in the fault tree topology of the node to be verified. If the logic gate type of the parent node is an AND gate, then check whether all the child nodes associated with the parent node exist in the first matching node set. If there are any missing ones, then mark the node to be verified as a logical conflict node. If the logic gate type of the parent node is an OR gate, then check whether there is a child node associated with the parent node in the first matching node set. If not, then mark the node to be verified as the logic conflict node. Based on the logically conflicting nodes, the set of primary matching nodes is filtered to generate the set of secondary matching nodes.

[0028] When constructing the fault tree topology, the state in which the photovoltaic charging pile as a whole cannot work properly is defined as the top event node, the event of each independently replaceable or repairable component in the charging pile failing is defined as the bottom event node, and the event between the top event node and the bottom event node consisting of the failure of component functional modules or subsystems is defined as the intermediate event node. Then, based on the causal relationship between these nodes, logic gates are used to connect the top event node, intermediate event node, and bottom event node. Here, an AND gate indicates that all events in the lower layer must occur simultaneously to trigger an event in the upper layer, and an OR gate indicates that any event in the lower layer can trigger an event in the upper layer. In this way, a complete fault tree topology is formed.

[0029] When performing logical matching, the intermediate event nodes and bottom event nodes are first extracted from the already constructed fault tree topology. These nodes are then gathered together to form a complete set of nodes to be matched. This complete set contains the event descriptions corresponding to all intermediate and bottom level components that may fail.

[0030] Then, semantic association analysis is performed on each fault phenomenon in the fault phenomenon set and each node in the set of nodes to be matched. Specifically, feature extraction is performed on the descriptive text of the fault phenomenon, and keywords and phrases that can represent the core meaning of the phenomenon are extracted to form a phenomenon feature vector. At the same time, the same feature extraction is performed on the fault label text pre-stored by the node to obtain the node feature vector. The feature vector of the fault phenomenon is compared with the feature vector of the node. The similarity between the two vectors is determined by calculating the matching degree of keywords and the semantic closeness between keywords. When this similarity exceeds a preset threshold, the node is determined to match the fault phenomenon. All nodes determined to be matched are collected to form a matching node set.

[0031] After obtaining the first set of matching nodes, logical consistency verification needs to be performed on the nodes. Select one node from the first set of matching nodes as the node to be verified. In the fault tree topology, find the parent node of the node and the type of logic gate connected to the parent node. If the logic gate type of the parent node is an AND gate, check whether all the child nodes connected to the parent node appear in the first set of matching nodes. If any child node is not found, it means that the fault event represented by the node to be verified cannot be logically independent. Therefore, the node is marked as a logical conflict node and is prepared to be removed. If the logic gate type of the parent node is an OR gate, check whether there is at least one child node connected to the parent node in the first set of matching nodes. If there are no child nodes, the node is also marked as a logical conflict node and is prepared to be removed. After checking all the nodes to be verified, the nodes that are not marked as logical conflicts are retained to form the second set of matching nodes.

[0032] Finally, the nodes in the secondary matching node set are redundancy merged. It is checked whether there are nodes that describe the same fault event but with slightly different descriptions, or whether there are identical nodes that appear repeatedly through different paths. These duplicate nodes are merged into one node to eliminate redundant information in the set. The final node set obtained after merging is the fault response node set. Each node in this set is a fault event node that is logically consistent with the current fault phenomenon and has been verified.

[0033] The beneficial effect is that by logically matching the set of fault phenomena with the fault tree topology, an accurate and logically verified set of fault response nodes is generated. This process significantly improves the accuracy of fault location. It uses semantic association analysis to filter nodes related to the current phenomenon from the entire set of nodes to be matched, and then removes nodes that conflict with the logical gate relationship through backtracking verification. Finally, a clean set of fault response nodes is obtained through redundancy merging, which effectively avoids misjudgment caused by semantic ambiguity or logical contradiction. At the same time, this structured matching method greatly improves the diagnostic efficiency, enabling subsequent operation and maintenance to directly target logically confirmed fault nodes, thereby shortening the fault investigation time and enhancing the reliability and automation level of the photovoltaic charging pile diagnostic process.

[0034] S3: Based on the logical gate relationship of the nodes in the fault tree topology, perform path synthesis on the fault response node set to generate the minimum fault path of the photovoltaic charging pile. The minimum fault path is composed of activated bottom event nodes in logical order. In this embodiment of the invention, the step of synthesizing paths for the fault response node set based on the logical gate relationships of nodes in the fault tree topology to generate the minimum fault path for the photovoltaic charging pile includes: Starting from the top event node, traverse downwards to each node in the fault response node set, record the complete path from the top event node to each node, and generate an initial path set; Cross-compare each path in the initial path set, delete redundant paths in each path, and generate a simplified path set; Each path in the simplified path set is logically simplified, and adjacent nodes with the same logical gate relationship are merged to generate a candidate fault path set. Calculate the coverage rate of each candidate path in the candidate fault path set, and select the candidate path with the highest coverage rate as the preliminary preferred path; If multiple candidate paths have the same maximum coverage, the path with the shortest path length among the multiple candidate paths is selected as the minimum fault path.

[0035] The formula for calculating the coverage rate is:

[0036] in, For the coverage rate, This represents the number of nodes in the fault response node set covered by the candidate path. The total number of nodes in the fault response node set. The path length of the current candidate path. The minimum path length in the candidate fault path set. The maximum path length in the set of candidate fault paths.

[0037] After obtaining the fault response node set, the system takes the top event node of the fault tree topology as the starting point and traverses downwards along the connection relationship between the nodes determined by the logic gates. For each node in the fault response node set, the system records all the intermediate nodes and bottom event nodes passed from the top event node to the node and forms a complete path according to the order of the passes. All the paths obtained in this way are gathered together to form the initial path set.

[0038] All paths in the initial path set are compared pairwise to check if any path is completely contained by another path. For example, if all nodes on a shorter path appear in another longer path in the same order, the shorter path is determined to be a redundant path. The system removes these redundant paths from the set, and the remaining paths form a simplified path set. Each path in this set is a unique and necessary path to a certain node in the fault response node set.

[0039] Each path in the simplified path set is logically simplified. The logic gate types between adjacent nodes on each path are analyzed one by one. When multiple adjacent nodes are found to be connected by the same type of logic gate and these nodes belong to the same logical level in the fault propagation, the system merges these nodes into an equivalent node. The merged path reduces the number of nodes while maintaining the original logical relationship. All the simplified paths constitute the candidate fault path set.

[0040] For each candidate path in the candidate fault path set, a coverage rate is calculated. The coverage rate is calculated by comparing the nodes contained in the candidate path with the nodes in the fault response node set. The system counts the number of nodes in the candidate path that appear in the fault response node set and compares this number with the total number of nodes in the fault response node set. The length of the candidate path is also taken into account. The shorter the path length and the more nodes in the fault response node set it covers, the higher the coverage rate. The system calculates the coverage rate of each candidate path according to this principle.

[0041] All candidate paths are sorted from highest to lowest coverage, and the candidate path with the highest coverage is selected as the initial preferred path. If multiple candidate paths have the same highest coverage, the system further compares the lengths of these candidate paths and selects the shortest path. This selected path is the minimum fault path, which consists of a series of activated bottom event nodes arranged in a logical order from the top event to the faulty element.

[0042] Coverage This is the final metric calculated when evaluating each path in the candidate fault path set. This value measures the overall performance of each candidate path during the diagnostic process. The system calculates the coverage based on each path. The size of the path determines which path is most likely to become the final minimum failure path.

[0043] Number of nodes in the fault response node set covered by the candidate path When analyzing a specific candidate path, the process involves comparing each node along the path from the top event node to the end of the path with the nodes in the fault response node set, and counting the number of nodes that are simultaneously present in the fault response node set.

[0044] Total number of nodes in the fault response node set It is obtained by counting all nodes in the final fault response node set after completing the redundancy merging of the secondary matching node set. This value reflects the overall scale of intermediate event nodes and bottom event nodes that are confirmed to be related to the fault phenomenon after logical matching and verification within the current diagnostic cycle.

[0045] Path length of the current candidate path When traversing a specific candidate path, the path length is calculated by counting each node along the path, starting from the top event node at the beginning of the path, and continuing until the bottom event node at the end of the path is reached. .

[0046] Minimum path length in the candidate fault path set After completing the logical simplification of all simplified paths to generate a set of candidate fault paths, the path lengths of all paths in this set are compared with each other, and the smallest path length value is selected.

[0047] Maximum path length in the candidate fault path set It is a baseline value used in generating a set of candidate fault paths and determining the minimum path length. At the same time, by comparing the path lengths of all paths in the set, the largest path length value is selected.

[0048] The beneficial effects are that by synthesizing the fault response node set based on the logical gate relationship of the fault tree topology and generating the minimum fault path, accurate tracing from system-level faults to underlying component faults is achieved. This process, through traversal, redundancy removal, simplification, and optimization, extracts the most core path from many possible fault propagation paths, significantly improving the accuracy of fault root cause location. At the same time, the minimum fault path clarifies the logical order of the bottom event nodes, providing clear guidance for subsequent operation and maintenance, avoiding blind troubleshooting and repeated repairs, effectively shortening fault handling time, and enhancing the systematicness and automation level of photovoltaic charging pile fault diagnosis.

[0049] S4: Use the minimum fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, perform targeted operation and maintenance on the bottom event node based on the unique operation and maintenance execution sequence, and generate the operation and maintenance response status of the photovoltaic charging pile; In this embodiment of the invention, the step of using the minimum fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, performing targeted operation and maintenance on the bottom event node based on the unique operation and maintenance execution sequence, and generating the operation and maintenance response status of the photovoltaic charging pile includes: Based on the logical order of the fault tree topology, each bottom event node in the minimum fault path is extracted to generate an ordered list of operation and maintenance nodes. Query the preset operation and maintenance instruction mapping table to obtain the executable operation and maintenance instructions for each bottom event node in the ordered operation and maintenance node list; According to the logical order of the ordered operation and maintenance node list, the executable operation and maintenance instructions are sent to the photovoltaic charging pile in sequence, and the equipment execution feedback signals of the photovoltaic charging pile are monitored in real time. After the executable operation and maintenance instructions are executed, the operation and maintenance response status of the photovoltaic charging piles is summarized.

[0050] After obtaining the minimum fault path, the system parses the path and extracts all the bottom event nodes at the end of the path according to the logical propagation direction from the top event node to the bottom event node in the fault tree topology. The system then arranges these nodes according to the order in which they appear in the path to form an ordered list of maintenance nodes. This list clearly indicates the specific components that need to be maintained and the order in which these components should be processed.

[0051] The system accesses a pre-built and stored operation and maintenance instruction mapping table in the database. This mapping table uses the unique identifier of the bottom event node as an index. Each bottom event node corresponds to one or more executable operation and maintenance instructions. These instructions include specific operations such as resetting, calibrating, adjusting parameters, and controlling on / off states of components. Based on each bottom event node in the ordered operation and maintenance node list, the system queries and extracts the corresponding executable operation and maintenance instructions from the mapping table, organizes these instructions in the same order as the nodes, and prepares them for subsequent execution.

[0052] Following the logical order determined by the orderly maintenance node list, the executable maintenance instructions corresponding to each bottom event node are sent to the controller of the photovoltaic charging pile through the communication interface. After each instruction is issued, the system listens for the device execution feedback signal returned by the controller in real time. This feedback signal includes whether the instruction has been successfully received, whether the instruction is being executed, whether the instruction execution has been completed, and any abnormal information during the execution process. The system records and parses each feedback signal to ensure that every step of the operation is accurately tracked.

[0053] After all executable maintenance commands are executed in sequence, the system collects various operational data of the photovoltaic charging pile through sensors again. This data is then combined with the equipment execution feedback signals recorded during the command execution process. All information reflecting the current status of the equipment is summarized in a preset format to form a complete maintenance response status. This status includes all operating parameters and execution result records of the equipment after this targeted maintenance.

[0054] The beneficial effects are that by using the least fault path as the only maintenance execution sequence and performing targeted maintenance on the bottom event nodes, the diagnostic results and maintenance operations are accurately matched. This process directly transforms the theoretically analyzed fault path into an executable sequence of operation instructions, avoiding the deviations and delays caused by manual interpretation of diagnostic reports. At the same time, the instructions are executed in a logical order and feedback is monitored in real time, ensuring the standardization and traceability of maintenance operations, significantly improving the accuracy and efficiency of maintenance operations, and enhancing the automation level of photovoltaic charging pile fault handling.

[0055] S5: If the operation and maintenance response status has not recovered to the preset safe operating range, then S2 to S4 are executed iteratively until the photovoltaic charging pile recovers to the safe operating range or the manual intervention mechanism is triggered.

[0056] In this embodiment of the invention, if the operation and maintenance response status does not recover to the preset safe operating range, then S2 to S4 are iteratively executed until the photovoltaic charging pile recovers to the safe operating range or a manual intervention mechanism is triggered, including: Determine whether the photovoltaic charging pile is within the preset safe operating range; If the photovoltaic charging pile is outside the safe operation range, then extract the abnormal feature parameters in the operation and maintenance response status, and format and encapsulate the abnormal feature parameters into new fault phenomenon description data. Using the new fault phenomenon description data as input, iteratively execute steps S2 to S4 to generate a new round of operation and maintenance response status; The number of iterations is recorded. When the number of iterations reaches the iteration threshold and the operation and maintenance response status has not yet recovered to the safe operation range, the manual intervention mechanism is triggered, and a manual intervention request signal is sent to the operation and maintenance terminal of the photovoltaic charging pile.

[0057] After completing a round of operation and maintenance and generating an operation and maintenance response status, the system compares each operating parameter recorded in the operation and maintenance response status with the corresponding upper and lower limit thresholds in the preset safe operation range. The preset safe operation range is a normal range determined based on equipment design standards and historical operating data. The system determines whether the photovoltaic charging pile is in a safe operation state by comparing whether the value of each parameter falls entirely within this range.

[0058] If, after comparison, it is found that the value of any operating parameter exceeds the preset safe operating range, the system determines that the photovoltaic charging pile is still outside the safe operating range. At this time, the system extracts all parameters that exceed the normal range, as well as the specific values ​​and trends of these parameters, from the operation and maintenance response status. This information is used as abnormal feature parameters. Then, according to the predefined data format, these abnormal feature parameters are combined and encapsulated into standard fault phenomenon description statements to form new fault phenomenon description data.

[0059] The system uses this newly generated fault description data as input for a new round of diagnostic operations and restarts the complete process from step S2 to step S4. This involves again performing logical matching of the fault phenomenon set and fault tree topology, generating the fault response node set, synthesizing the minimum fault path, and executing targeted operations and maintenance, ultimately resulting in a new round of operations and maintenance response status.

[0060] Each time a new iteration begins, the system records the current iteration count in a dedicated counter. This counter starts from zero and automatically increments with each iteration. The system compares this iteration count with a pre-set manual intervention threshold. When the iteration count reaches or exceeds this threshold, and the latest maintenance response status still shows that the photovoltaic charging pile has not returned to a safe operating range, the system immediately triggers the manual intervention mechanism. It sends a manual intervention request signal to the maintenance personnel's terminal device through the communication network. This signal includes the device identifier, current fault status, number of iterations executed, and all historical maintenance records, awaiting manual intervention.

[0061] The beneficial effects are that by establishing an iterative execution mechanism and a manual intervention mechanism, the system can automatically repeat the diagnostic operation and maintenance process when the problem cannot be solved during the first operation and maintenance. It can re-analyze the fault with the latest equipment status as input, realizing closed-loop feedback and continuous optimization of fault handling. This process significantly improves the fault self-healing capability and avoids the cumbersome process of having to manually restart after a single operation failure. At the same time, by recording the number of iterations and requesting manual intervention in a timely manner when the threshold is reached, it not only ensures sufficient attempts at automated processing, but also prevents the waste of resources caused by infinite loops, effectively improving the operation and maintenance efficiency and reliability of photovoltaic charging piles.

[0062] like Figure 2 The diagram shown is a functional block diagram of a photovoltaic charging pile diagnostic and maintenance system based on a fault tree, provided by an embodiment of the present invention.

[0063] The fault tree-based photovoltaic charging pile diagnostic and maintenance system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the fault tree-based photovoltaic charging pile diagnostic and maintenance system 100 may include a fault phenomenon generation module 101, a fault logic matching module 102, a fault path synthesis module 103, a directional maintenance execution module 104, and an iterative feedback judgment module 105. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0064] In this embodiment, the functions of each module / unit are as follows: The fault phenomenon generation module 101 is used to collect multi-source status signals of the photovoltaic charging pile and generate a set of fault phenomena of the photovoltaic charging pile. The fault logic matching module 102 is used to logically match the set of fault phenomena with a preset fault tree topology to generate a set of fault response nodes. The fault path synthesis module 103 is used to synthesize the fault response node set based on the logical gate relationship of the nodes in the fault tree topology to generate the minimum fault path of the photovoltaic charging pile. The minimum fault path is composed of activated bottom event nodes in logical order. The targeted maintenance execution module 104 is used to take the minimum fault path as the unique maintenance execution sequence of the photovoltaic charging pile, perform targeted maintenance on the bottom event node based on the unique maintenance execution sequence, and generate the maintenance response status of the photovoltaic charging pile. The iterative feedback judgment module 105 is used to iteratively execute S2 to S4 if the operation and maintenance response status has not recovered to the preset safe operation range, until the photovoltaic charging pile recovers to the safe operation range or the manual intervention mechanism is triggered.

[0065] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0066] 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 modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0067] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0068] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0069] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for diagnosing and maintaining photovoltaic charging piles based on fault tree, characterized in that, The method includes: S1: Collect multi-source status signals of the photovoltaic charging pile and generate a set of fault phenomena of the photovoltaic charging pile; S2: Logically match the set of fault phenomena with the preset fault tree topology to generate the fault response node set of the photovoltaic charging pile; S3: Based on the logical gate relationship of the nodes in the fault tree topology, perform path synthesis on the fault response node set to generate the minimum fault path of the photovoltaic charging pile. The minimum fault path is composed of activated bottom event nodes in logical order. S4: Use the minimum fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, perform targeted operation and maintenance on the bottom event node based on the unique operation and maintenance execution sequence, and generate the operation and maintenance response status of the photovoltaic charging pile; S5: If the operation and maintenance response status has not recovered to the preset safe operating range, then S2 to S4 are executed iteratively until the photovoltaic charging pile recovers to the safe operating range or the manual intervention mechanism is triggered.

2. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 1, characterized in that, The preset fault tree topology includes: The system failure of the photovoltaic charging pile is taken as the top event node; The bottom event node of the fault tree topology is determined based on the fault of the independent operation and maintenance component of the photovoltaic charging pile; The nodes between the top event node and the bottom event node are used as intermediate event nodes in the fault tree topology. Based on the logic gates, the top event node, the bottom event node, and the intermediate event node are logically associated to construct the fault tree topology of the photovoltaic charging pile.

3. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 1, characterized in that, The step of logically matching the set of fault phenomena with a preset fault tree topology to generate a set of fault response nodes includes: Extract intermediate event nodes and bottom event nodes from the fault tree topology to generate a complete set of nodes to be matched in the fault tree topology. Semantic association analysis is performed on the set of fault phenomena and the complete set of nodes to be matched, and nodes that match the fault phenomena in the set of fault phenomena are selected to generate the first matching node set of the fault tree topology. Based on the logic gate type of the nodes in the fault tree topology, the nodes in the first-match node set are backtracked upwards for verification to generate the second-match node set of the fault tree topology. Redundancy merging is performed on the nodes in the secondary matching node set to generate a fault response node set.

4. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 3, characterized in that, The step of performing semantic association analysis between the set of fault phenomena and the complete set of nodes to be matched, filtering out nodes that match the fault phenomena in the set of fault phenomena, and generating a set of matching nodes includes: Text features are extracted from the fault phenomena in the fault phenomenon set to generate a phenomenon feature vector for the fault phenomenon set. The nodes in the complete set of nodes to be matched are parsed using pre-stored labels to generate the node feature vector of the fault phenomenon set; Analyze the semantic similarity between the phenomenon feature vector and the node feature vector, and determine the nodes whose semantic similarity exceeds a preset semantic threshold as matching nodes; All the matching nodes are integrated into a single matching node set.

5. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 3, characterized in that, The step of performing upward backtracking verification on the nodes in the first-match node set based on the logic gate type of the nodes in the fault tree topology to generate a second-match node set includes: Select a node to be verified from the set of matched nodes, and obtain the parent node and the logic gate type of the parent node in the fault tree topology of the node to be verified. If the logic gate type of the parent node is an AND gate, then check whether all the child nodes associated with the parent node exist in the first matching node set. If there are any missing ones, then mark the node to be verified as a logical conflict node. If the logic gate type of the parent node is an OR gate, then check whether there is a child node associated with the parent node in the first matching node set. If not, then mark the node to be verified as the logic conflict node. Based on the logically conflicting nodes, the set of primary matching nodes is filtered to generate the set of secondary matching nodes.

6. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 2, characterized in that, The step of synthesizing paths for the fault response node set based on the logical gate relationships of nodes in the fault tree topology to generate the minimum fault path for the photovoltaic charging pile includes: Starting from the top event node, traverse downwards to each node in the fault response node set, record the complete path from the top event node to each node, and generate an initial path set; Cross-compare each path in the initial path set, delete redundant paths in each path, and generate a simplified path set; Each path in the simplified path set is logically simplified, and adjacent nodes with the same logical gate relationship are merged to generate a candidate fault path set. Calculate the coverage rate of each candidate path in the candidate fault path set, and select the candidate path with the highest coverage rate as the preliminary preferred path; If multiple candidate paths have the same maximum coverage, the shortest path among the candidate paths is selected as the minimum fault path.

7. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 6, characterized in that, The formula for calculating the coverage rate is: in, For the coverage rate, This represents the number of nodes in the fault response node set covered by the candidate path. The total number of nodes in the fault response node set. The path length of the current candidate path. The minimum path length in the candidate fault path set. The maximum path length in the candidate fault path set.

8. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 1, characterized in that, The step of using the minimum fault path as the unique operation and maintenance execution sequence for the photovoltaic charging pile, and performing targeted operation and maintenance on the bottom event nodes based on the unique operation and maintenance execution sequence to generate the operation and maintenance response status of the photovoltaic charging pile includes: Based on the logical order of the fault tree topology, each bottom event node in the minimum fault path is extracted to generate an ordered list of operation and maintenance nodes. Query the preset operation and maintenance instruction mapping table to obtain the executable operation and maintenance instructions for each bottom event node in the ordered operation and maintenance node list; According to the logical order of the ordered operation and maintenance node list, the executable operation and maintenance instructions are sent to the photovoltaic charging pile in sequence, and the equipment execution feedback signals of the photovoltaic charging pile are monitored in real time. After the executable operation and maintenance instructions are executed, the operation and maintenance response status of the photovoltaic charging piles is summarized.

9. The photovoltaic charging pile diagnosis and maintenance method based on fault tree as described in claim 1, characterized in that, If the operation and maintenance response status does not recover to the preset safe operating range, then S2 to S4 are executed iteratively until the photovoltaic charging pile recovers to the safe operating range or a manual intervention mechanism is triggered, including: Determine whether the photovoltaic charging pile is within the preset safe operating range; If the photovoltaic charging pile is outside the safe operation range, then extract the abnormal feature parameters in the operation and maintenance response status, and format and encapsulate the abnormal feature parameters into new fault phenomenon description data. Using the new fault phenomenon description data as input, steps S2 to S4 are executed iteratively to generate a new round of operation and maintenance response status; The number of iterations is recorded. When the number of iterations reaches the iteration threshold and the operation and maintenance response status has not yet recovered to the safe operation range, the manual intervention mechanism is triggered, and a manual intervention request signal is sent to the operation and maintenance terminal of the photovoltaic charging pile.

10. A photovoltaic charging pile diagnostic and maintenance system based on fault tree, characterized in that, The system for implementing the fault tree-based photovoltaic charging pile diagnosis and maintenance method as described in claim 1 includes: The fault phenomenon generation module is used to collect multi-source status signals of the photovoltaic charging pile and generate a set of fault phenomena of the photovoltaic charging pile. The fault logic matching module is used to logically match the set of fault phenomena with a preset fault tree topology to generate a set of fault response nodes. The fault path synthesis module is used to synthesize the fault response node set based on the logical gate relationship of the nodes in the fault tree topology to generate the minimum fault path of the photovoltaic charging pile. The minimum fault path is composed of activated bottom event nodes in logical order. The targeted operation and maintenance execution module is used to take the minimum fault path as the unique operation and maintenance execution sequence of the photovoltaic charging pile, perform targeted operation and maintenance on the bottom event node based on the unique operation and maintenance execution sequence, and generate the operation and maintenance response status of the photovoltaic charging pile. The iterative feedback judgment module is used to iteratively execute S2 to S4 if the operation and maintenance response status has not recovered to the preset safe operating range, until the photovoltaic charging pile recovers to the safe operating range or the manual intervention mechanism is triggered.

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