Hydropower station intelligent lock control management method, device and equipment, storage medium and computer program product

Abstract

The application relates to the technical field of hydropower station operation and maintenance, and particularly relates to a hydropower station intelligent lock control management method, device, equipment, storage medium and computer program product. The method comprises the following steps: obtaining operation ticket text data, performing semantic identification on operation steps, obtaining target equipment identification, action category and precondition; matching the target equipment identification with equipment account to obtain standard equipment code; performing restricted traversal on the target equipment node in the electrical main wiring topology based on the standard equipment code and the action category, determining the topology associated equipment, and associating the equipment codes of the target equipment and the topology associated equipment with intelligent lock registration data to obtain a lock list; determining the precondition dependency relationship between lock items based on the precondition and the correspondence relationship between the equipment and the lock, and performing topology sorting on the lock list to obtain a lock control task execution sequence; and performing bidirectional consistency checking on the lock control task execution sequence and the operation ticket text data, and issuing the lock control task execution sequence to an intelligent key after the consistency checking is passed.

Description

Technical Field

[0001] This application relates to the field of hydropower station operation and maintenance technology, and in particular to a method, device, equipment, storage medium and computer program product for intelligent lock control management of hydropower stations. Background Technology

[0002] During the operation and maintenance of hydropower stations, maintenance personnel typically perform corresponding operations on equipment such as turbine generator units, circuit breakers, disconnect switches, and grounding switches based on operation tickets issued by the dispatch center. To restrict unauthorized personnel from operating the equipment, hydropower stations can install smart locks on relevant equipment and issue unlocking tasks to smart keys through a lock control management system. Operation tickets usually describe each operation step using natural language or semi-structured text, including the equipment to be operated, the operation actions, and the corresponding prerequisites. Current lock management methods typically involve maintenance personnel manually identifying the equipment names on operation tickets, associating the identified equipment with the equipment ledger and smart locks, and then scheduling lock control tasks according to the operation steps. However, equipment names on operation tickets may contain abbreviations, aliases, or inconsistent numbering, easily leading to equipment matching errors. Furthermore, individual operation steps may implicitly involve other devices with electrical topology relationships to the target device, making it easy to overlook corresponding locks during manual association. In addition, when an operation ticket involves multiple devices with pre-dependent relationships, manual scheduling struggles to accurately determine the execution order of each lock task, and the existing method cannot simultaneously check whether the operation steps are completely covered by the lock tasks and whether the lock tasks can be traced back to the corresponding operation steps before task issuance. Therefore, improving the accuracy and completeness of the association between operation ticket devices and smart locks has become a pressing technical problem to be solved. Summary of the Invention

[0003] The main purpose of this application is to provide a method, device, equipment, storage medium and computer program product for intelligent lock control management of hydropower stations, aiming to solve the technical problem of how to improve the accuracy and integrity of the association between the operation ticket equipment and the intelligent lock.

[0004] To achieve the above objectives, this application provides a method for intelligent interlocking management of hydropower stations, the method comprising the following steps: Obtain operation ticket text data, perform semantic recognition on the operation steps in the operation ticket text data, and obtain the target device identifier, action category and prerequisite conditions; The target device identifier is matched with the standard device record in the equipment ledger to obtain the standard device code; Based on the standard device code and the action category, a restricted traversal is performed on the target device node in the electrical main wiring topology data to determine the topology-associated device. The standard device code and the device code corresponding to the topology-associated device are then associated with the smart lock registration data to obtain a lock list. Based on the aforementioned preconditions and the correspondence between devices and locks in the lock list, the preconditions between lock entries are determined, and the lock list is topologically sorted to obtain the lock control task execution sequence. A two-way consistency check is performed between the lock control task execution sequence and the operation ticket text data, and if the check passes, the lock control task execution sequence is sent to the smart key.

[0005] In one embodiment, the steps of obtaining operation ticket text data and performing semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions include: The system receives operation ticket text data from the scheduling system, divides the operation ticket text data according to the operation step number and text boundary to obtain multiple operation step text fragments, and establishes the association between each operation step text fragment and the corresponding operation step number. Named entity recognition and semantic element extraction are performed on the text fragments of each operation step to identify the device entities, action descriptions and condition descriptions in each operation step text fragment, and obtain device entity data, action description data and condition description data. Based on the aforementioned association, the semantic association between the device entity data, the action description data, and the condition description data is parsed to determine the device entity as the operation object, the corresponding action type, and the device entity as the execution condition. The device entity as the operation object is identified as the target device identifier, the action type is identified as the action category, and the preconditions are generated based on the device entity as the execution condition.

[0006] In one embodiment, the step of matching the target device identifier with standard device records in the device ledger to obtain a standard device code includes: Extract the standard device name from each standard device record, determine the edit distance between the target device identifier and each standard device name, and determine the character-level similarity score corresponding to each standard device record based on the edit distance; Semantic vector transformation is performed on the target device identifier and each standard device name respectively to determine the semantic vector similarity between the target device identifier and each standard device name, and the corresponding semantic similarity score is mapped to a value range consistent with the character similarity score to obtain a standardized semantic similarity score; The character-level similarity score and the standardized semantic-level similarity score are weighted and fused to obtain the comprehensive matching score corresponding to each standard device record. The standard device record with the largest comprehensive matching score is determined as the candidate standard device record. When the candidate standard device record meets the preset matching conditions, the corresponding device code is extracted. Alternatively, when the preset matching conditions are not met, the target standard device record is determined based on the received confirmation result and the corresponding device code is extracted to obtain the standard device code.

[0007] In one embodiment, the step of performing a restricted traversal of the target device node in the electrical main wiring topology data based on the standard device code and the action category to determine the topology-associated device, and associating the standard device code and the device code corresponding to the topology-associated device with the smart lock registration data to obtain a lock list includes: Based on the standard equipment code, the target equipment node is determined in the electrical main wiring topology data, and the preset topology association rules are queried according to the action category to determine the corresponding traversal depth and the range of associated equipment types, thereby obtaining the topology traversal constraint data. Starting with the target device node, the adjacent device nodes are visited layer by layer according to the topology traversal constraint data. Device nodes whose device type belongs to the range of the associated device types are retained. Traversal stops when the traversal depth is reached. The device corresponding to the retained device node is determined as the topology associated device. Extract the device code corresponding to the topology-associated device, perform an association query between the standard device code and the device code corresponding to the topology-associated device and the smart lock registration data, and generate a lock missing mark for device codes that are not associated with lock registration records. Based on the association query results and the lock missing mark, obtain the lock list.

[0008] In one embodiment, the step of determining the prerequisite dependencies between lock entries based on the preconditions and the correspondence between devices and locks in the lock list, and performing topological sorting on the lock list to obtain the lock control task execution sequence, includes: Based on the preconditions corresponding to each target device, the corresponding precondition devices are determined, and based on the correspondence between devices and locks, the lock entries corresponding to the target devices and the precondition devices are determined respectively, and the precondition dependency relationship between the lock entries corresponding to the precondition devices and the lock entries corresponding to the target devices is established. Using the lock entries in the lock list as nodes and the preceding dependencies as directed edges, a lock dependency directed graph is constructed. Loop detection is performed on the lock dependency directed graph. If no loop is detected, the lock dependency directed graph is determined as a lock dependency graph to be sorted. The dependency graph of the locks to be sorted is topologically sorted to determine the execution level corresponding to each lock entry. Lock entries with prerequisite dependencies are marked as executed sequentially, and lock entries at the same execution level without mutual dependencies are marked as executed in parallel. The lock entries are then arranged according to the execution level to obtain the lock control task execution sequence.

[0009] In one embodiment, the step of performing a bidirectional consistency check on the lock control task execution sequence and the operation ticket text data, and, if the check passes, sending the lock control task execution sequence to the smart key, includes: Using each operation step in the operation ticket text data as a verification benchmark, it is detected whether the device involved in each operation step has a corresponding lock entry in the lock control task execution sequence, and the operation steps that do not have a corresponding lock entry are marked as uncovered abnormal entries, thus obtaining the first verification result; Using each lock item in the lock control task execution sequence as the verification benchmark, based on the device and lock source corresponding to each lock item, it is detected whether each lock item can be associated with the operation steps in the operation ticket text data, and lock items that cannot be associated with the corresponding operation steps are marked as isolated abnormal items to obtain the second verification result; If the first verification result does not contain any uncovered abnormal entries and the second verification result does not contain any isolated abnormal entries, the bidirectional consistency verification is determined to be successful. The lock control task execution sequence is then encapsulated into a lock control task data packet and sent to the smart key through a preset communication channel.

[0010] Furthermore, to achieve the above objectives, this application also proposes an intelligent lock control management device for hydropower stations, the intelligent lock control management device for hydropower stations comprising: The semantic recognition module is used to acquire operation ticket text data, perform semantic recognition on the operation steps in the operation ticket text data, and obtain the target device identifier, action category and preconditions. The equipment coding module is used to match the target equipment identifier with the standard equipment record in the equipment ledger to obtain the standard equipment code; The lock list module is used to perform a restricted traversal of the target device node in the electrical main wiring topology data based on the standard device code and the action category, determine the topology-associated device, and associate the standard device code and the device code corresponding to the topology-associated device with the smart lock registration data to obtain the lock list; The execution sequence module is used to determine the pre-dependencies between lock entries based on the preconditions and the correspondence between devices and locks in the lock list, and to perform topological sorting on the lock list to obtain the lock control task execution sequence; The verification and distribution module is used to perform bidirectional consistency verification between the lock control task execution sequence and the operation ticket text data, and if the verification passes, distribute the lock control task execution sequence to the smart key.

[0011] In addition, to achieve the above objectives, this application also proposes a hydropower station intelligent lock control management device, the device comprising: a memory, a processor, and a hydropower station intelligent lock control management program stored in the memory and executable on the processor, the hydropower station intelligent lock control management program being configured to implement the steps of the hydropower station intelligent lock control management method described above.

[0012] In addition, to achieve the above objectives, this application also proposes a storage medium storing a hydropower station intelligent lock control management program, which, when executed by a processor, implements the steps of the hydropower station intelligent lock control management method described above.

[0013] In addition, to achieve the above objectives, this application also proposes a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the intelligent lock control management method for hydropower stations as described above.

[0014] This application obtains operation ticket text data, performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions; matches the target device identifier with the standard device record in the equipment ledger to obtain the standard device code; based on the standard device code and action category, performs a restricted traversal of the target device node in the electrical main wiring topology data to determine the topology-associated devices, and associates the standard device code and the device code corresponding to the topology-associated devices with the smart lock registration data to obtain the lock list; based on the preconditions and the correspondence between devices and locks in the lock list, determines the precondition dependencies between lock entries, and performs topological sorting on the lock list to obtain the lock control task execution sequence; performs a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and if the check passes, sends the lock control task execution sequence to the smart key. This application performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions, converting the unstructured description in the operation ticket into structured information that can be used for device matching, topology traversal, and sequence determination. By matching the target device identifier with standard device records in the device ledger, the target device is uniformly represented by a standard device code, reducing the interference caused by inconsistencies between the device description in the operation ticket and the device ledger record on lock association. Furthermore, by combining the standard device code and action category, a restricted traversal is performed on the target device node, so that the determined topology-related devices correspond to the current target device and operation action, and the device codes of both the target device and the topology-related devices are associated with the smart lock. The registration data is linked to ensure that the lock list covers both the target devices explicitly recorded in the operation ticket and the associated devices determined by the electrical main wiring topology, thereby improving the accuracy and completeness of the device-lock association. Based on this, the prerequisite dependencies between lock entries are determined according to the preconditions and the correspondence between devices and locks, and a lock control task execution sequence is formed through topological sorting, ensuring that the lock association results are organized in an orderly manner according to the dependencies between devices. Finally, a bidirectional consistency check is performed between the lock control task execution sequence and the operation ticket text data, and only the lock control task execution sequence that passes the check is sent to the smart key, thereby further improving the consistency between the lock control task content and the operation ticket, as well as the reliability of the lock control task issuance. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the first embodiment of the intelligent lock control management method for hydropower stations according to this application; Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the intelligent lock control management method for hydropower stations in this application; Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the intelligent lock control management method for hydropower stations in this application; Figure 4This is a schematic diagram of the module structure of the intelligent lock control management device for hydropower stations, as described in an embodiment of this application. Figure 5 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the intelligent lock control management method for hydropower stations in this application embodiment.

[0016] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0018] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0019] It should be noted that during the operation and maintenance of hydropower stations, maintenance personnel typically perform corresponding operations on equipment such as turbine generator units, circuit breakers, disconnect switches, and grounding switches based on operation tickets issued by the dispatch center. To restrict unauthorized personnel from operating the equipment, hydropower stations can install smart locks on relevant equipment and issue unlocking tasks to smart keys through a lock control management system. Operation tickets usually describe each operation step using natural language or semi-structured text, including the equipment to be operated, the operation actions, and the corresponding prerequisites. Current lock management methods typically involve maintenance personnel manually identifying the equipment names on operation tickets, associating the identified equipment with the equipment ledger and smart locks, and then scheduling lock control tasks according to the operation steps. However, equipment names on operation tickets may contain abbreviations, aliases, or inconsistent numbering, easily leading to equipment matching errors. Furthermore, individual operation steps may implicitly involve other devices with electrical topology relationships to the target device, making it easy to overlook corresponding locks during manual association. In addition, when an operation ticket involves multiple devices with pre-dependent relationships, manual scheduling struggles to accurately determine the execution order of each lock task, and the existing method cannot simultaneously check whether the operation steps are completely covered by the lock tasks and whether the lock tasks can be traced back to the corresponding operation steps before task issuance. Therefore, improving the accuracy and completeness of the association between operation ticket devices and smart locks has become a pressing technical problem to be solved.

[0020] The main solution of this application is as follows: Obtain operation ticket text data; perform semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions; match the target device identifier with the standard device record in the equipment ledger to obtain the standard device code; based on the standard device code and action category, perform a restricted traversal of the target device nodes in the electrical main wiring topology data to determine the topology-associated devices, and associate the standard device code and the device code corresponding to the topology-associated devices with the smart lock registration data to obtain the lock list; based on the preconditions and the correspondence between devices and locks in the lock list, determine the precondition dependencies between lock entries, and perform topological sorting on the lock list to obtain the lock control task execution sequence; perform a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and if the check passes, send the lock control task execution sequence to the smart key.

[0021] This application performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions, converting the unstructured description in the operation ticket into structured information that can be used for device matching, topology traversal, and sequence determination. By matching the target device identifier with standard device records in the device ledger, the target device is uniformly represented by a standard device code, reducing the interference caused by inconsistencies between the device description in the operation ticket and the device ledger record on lock association. Furthermore, by combining the standard device code and action category, a restricted traversal is performed on the target device node, so that the determined topology-related devices correspond to the current target device and operation action, and the device codes of both the target device and the topology-related devices are associated with the smart lock. The registration data is linked to ensure that the lock list covers both the target devices explicitly recorded in the operation ticket and the associated devices determined by the electrical main wiring topology, thereby improving the accuracy and completeness of the device-lock association. Based on this, the prerequisite dependencies between lock entries are determined according to the preconditions and the correspondence between devices and locks, and a lock control task execution sequence is formed through topological sorting, ensuring that the lock association results are organized in an orderly manner according to the dependencies between devices. Finally, a bidirectional consistency check is performed between the lock control task execution sequence and the operation ticket text data, and only the lock control task execution sequence that passes the check is sent to the smart key, thereby further improving the consistency between the lock control task content and the operation ticket, as well as the reliability of the lock control task issuance.

[0022] It should be noted that the executing entity of the method in this embodiment can be a computing service device with data processing, network communication, and program execution functions, or it can be the aforementioned intelligent lock control management device for hydropower stations with the same or similar functions. This embodiment and the following embodiments will be described using an intelligent lock control management device for hydropower stations as an example.

[0023] Based on this, the first embodiment of the intelligent lock control management method for hydropower stations proposed in this application is presented. Please refer to [the relevant documentation]. Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the intelligent lock control management method for hydropower stations according to this application.

[0024] In this embodiment, the method includes the following steps: S1: Obtain operation ticket text data, perform semantic recognition on the operation steps in the operation ticket text data, and obtain the target device identifier, action category and prerequisite conditions; S2: Match the target device identifier with the standard device record in the device ledger to obtain the standard device code; It should be noted that: operation ticket text data refers to data issued by the dispatch system that records equipment operation tasks in natural language or semi-structured form; operation steps refer to the individual operation contents divided into execution order in the operation ticket; semantic recognition refers to the process of identifying semantic elements such as equipment, actions, and conditions from the operation steps and determining the relationship between these semantic elements; target equipment identifier refers to the equipment name, abbreviation, or equipment number used to represent the current operation object; action category refers to the operation type corresponding to the target equipment, including opening and closing; prerequisite conditions refer to the equipment status or preceding equipment conditions that need to be met before executing the current operation; equipment ledger refers to a data set that centrally stores information such as the standard name, equipment code, and equipment type of each piece of equipment in the hydropower station; standard equipment record refers to the standardized record corresponding to a single piece of equipment in the equipment ledger; and standard equipment code refers to the identification information configured for equipment according to unified coding rules.

[0025] First, the lock management server receives operation ticket text data from the scheduling system. It divides the operation ticket text data according to the operation step number and text boundaries, obtaining multiple operation step text fragments, and establishes the association between each operation step text fragment and its corresponding operation step number. Named entity recognition and semantic element extraction are performed on each operation step text fragment to identify device entities, action descriptions, and condition descriptions. Based on the association between semantic elements, it distinguishes between device entities that are the current operation object and device entities that are execution conditions. The device entity that is the current operation object is identified as the target device identifier, the corresponding action description is categorized into action categories, and preconditions are generated based on the device entities that are execution conditions and their status descriptions. When the same operation step contains multiple device entities, the semantic role corresponding to each device entity is determined, and the identification results are associated with the same operation step number.

[0026] Secondly, for each identified target device identifier, the standard device name and standard device code corresponding to each standard device record are read from the device ledger. The character-level similarity between the target device identifier and each standard device name is calculated, and the target device identifier and each standard device name are converted into semantic vectors to determine the corresponding semantic-level similarity. After adjusting the character-level similarity and semantic-level similarity to a consistent value range, a weighted fusion is performed to obtain the comprehensive matching result between the target device identifier and each standard device record. The standard device record with the highest matching degree is selected as the candidate matching record. When the candidate matching record meets the preset matching conditions, its standard device code is extracted. When the candidate matching record does not meet the preset matching conditions, it is marked as pending confirmation, and the corresponding standard device record is determined based on the received confirmation result to obtain the standard device code.

[0027] By segmenting and semantically recognizing the operation ticket text data, the equipment, actions, and preconditions in the operation steps can be converted into interrelated structured information, reducing the interference of natural language expressions on equipment recognition. On this basis, by combining character-level matching and semantic-level matching to comprehensively judge the target equipment identifier and standard equipment records, it can take into account both the literal differences and semantic consistency of equipment names. The confirmation mechanism restricts the direct adoption of low-matching results, thereby improving the accuracy and completeness of operation ticket equipment recognition and equipment ledger matching, reducing the probability of incorrect mapping or omission of target equipment, and providing a unified and reliable standard equipment code for subsequent topological association and smart lock query.

[0028] S3: Based on the standard device code and the action category, perform a restricted traversal of the target device node in the electrical main wiring topology data to determine the topology-associated device, and associate the standard device code and the device code corresponding to the topology-associated device with the smart lock registration data to obtain a lock list; S4: Based on the aforementioned preconditions and the correspondence between devices and locks in the lock list, determine the preconditions between lock entries, and perform topological sorting on the lock list to obtain the lock control task execution sequence; S5: Perform a two-way consistency check on the lock control task execution sequence and the operation ticket text data, and if the check passes, send the lock control task execution sequence to the smart key.

[0029] It should be noted that electrical main wiring topology data refers to data used to characterize electrical equipment such as circuit breakers, disconnectors, and grounding switches, and their connection relationships; target device nodes refer to the nodes corresponding to the standard device codes in the electrical main wiring topology data; restricted traversal refers to a processing method that visits device nodes around the target device node layer by layer according to a preset traversal depth and the range of associated device types; topology-associated devices refer to devices that are determined through restricted traversal, have an electrical topology association with the target device, and meet the device type requirements; smart lock registration data refers to data that records information such as lock codes, associated device codes, and lock status; the lock list refers to a set of lock entries compiled based on the target device and topology-associated devices; the correspondence between devices and locks refers to the relationship between the device code and the lock installed on the target device. The relationships between lock codes at the corresponding devices; lock entries refer to data records in the lock list that describe a single lock and its associated devices, lock source, and execution attributes; prerequisite dependencies refer to the relationship where the execution of one lock entry is conditional on the completion or satisfaction of another lock entry's corresponding state; topological sorting refers to the process of determining the execution level and order of each lock entry according to the prerequisite dependencies between lock entries; lock control task execution sequence refers to the sorted task data containing lock entries and corresponding execution constraints; bidirectional consistency verification refers to performing coverage and traceability checks in both directions, from operation ticket to lock task and from lock task to operation ticket; smart key refers to the terminal device used to receive lock control tasks and open the corresponding smart lock according to lock control authorization.

[0030] First, based on the standard device code, the corresponding target device node is located in the electrical main wiring topology data. Then, according to the action category, a preset topology association rule is queried to determine the traversal depth and associated device type range corresponding to the current action category. Starting from the target device node, adjacent device nodes are visited layer by layer. During the traversal, device nodes whose device type belongs to the associated device type range are retained, and traversal stops when the corresponding traversal depth is reached, thus determining the topology-associated devices. The device code corresponding to the topology-associated device is cross-compared with the standard device codes in other operation steps, and the association source of duplicate devices is recorded. Subsequently, the standard device code of the target device and the device code corresponding to the topology-associated device are associated with the smart lock registration data to determine the corresponding lock code and lock source, and the execution priority is set according to the lock source. For device codes for which no lock registration record is found, a lock missing mark is generated. The lock association results and lock missing marks are summarized to obtain a lock list.

[0031] Secondly, based on the preconditions corresponding to each target device, the precondition devices are determined. Using the correspondence between devices and locks in the lock list, the corresponding lock entries for both the precondition devices and the target devices are determined, establishing precondition dependencies between lock entries. A lock dependency graph is constructed using lock entries as nodes and precondition dependencies as directed edges, and loop detection is performed on the graph. If no loops are detected, topological sorting is performed to determine the execution level of each lock entry. Lock entries with precondition dependencies are set to serial execution, while lock entries at the same execution level without mutual dependencies are set to parallel execution, resulting in a lock control task execution sequence. Using the operation steps in the operation ticket as a benchmark, it is checked whether there are operation steps not associated with lock entries. Then, using the lock entries in the lock control task execution sequence as a benchmark, it is checked whether there are lock entries that cannot be associated with operation steps. If no anomalies are found in either direction, the verification is considered successful. The lock control task execution sequence is then encapsulated into a lock control task data packet and sent to the smart key via the communication channel.

[0032] By performing a restricted traversal of the electrical main wiring topology data based on standard equipment codes and action categories, the associated equipment relevant to the current operation can be identified within a limited topology range, reducing the omission of associated equipment and the incorrect inclusion of irrelevant equipment. By unifying the association of target equipment and topology-related equipment with smart lock registration data and marking equipment lacking lock registration records, the coverage completeness of the lock list can be improved. Furthermore, by converting the preconditions at the device level into precondition dependencies between lock entries and determining the serial or parallel execution mode through loop detection and topology sorting, the rationality of the lock control task execution order can be improved. Finally, by checking the lock coverage of operation steps and the source of operation steps for lock entries through bidirectional consistency verification, and only issuing lock control task execution sequences that pass the verification, the completeness, consistency, and issuance reliability of lock control tasks can be improved.

[0033] This embodiment acquires operation ticket text data, performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions; matches the target device identifier with the standard device records in the device ledger to obtain the standard device code; based on the standard device code and action category, performs a restricted traversal of the target device nodes in the electrical main wiring topology data to determine the topology-associated devices, and associates the standard device code and the device codes corresponding to the topology-associated devices with the smart lock registration data to obtain the lock list; based on the preconditions and the correspondence between devices and locks in the lock list, determines the precondition dependencies between lock entries, and performs topological sorting on the lock list to obtain the lock control task execution sequence; performs a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and if the check passes, sends the lock control task execution sequence to the smart key. This embodiment performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions, converting the unstructured description in the operation ticket into structured information that can be used for device matching, topology traversal, and sequence determination. By matching the target device identifier with standard device records in the device ledger, the target device is uniformly represented by a standard device code, reducing the interference caused by inconsistencies between the device description in the operation ticket and the device ledger record on the lock association. Furthermore, by combining the standard device code and action category, a restricted traversal is performed on the target device node, so that the determined topology-associated devices correspond to the current target device and operation action, and the device codes of both the target device and the topology-associated devices are associated with the smart lock. The registration data is linked to ensure that the lock list covers both the target devices explicitly recorded in the operation ticket and the associated devices determined by the electrical main wiring topology, thereby improving the accuracy and completeness of the device-lock association. Based on this, the prerequisite dependencies between lock entries are determined according to the preconditions and the correspondence between devices and locks, and a lock control task execution sequence is formed through topological sorting, ensuring that the lock association results are organized in an orderly manner according to the dependencies between devices. Finally, a bidirectional consistency check is performed between the lock control task execution sequence and the operation ticket text data, and only the lock control task execution sequence that passes the check is sent to the smart key, thereby further improving the consistency between the lock control task content and the operation ticket, as well as the reliability of the lock control task issuance.

[0034] Based on the first embodiment described above, a second embodiment of the intelligent lock control management method for hydropower stations according to this application is proposed. Please refer to... Figure 2 , Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the intelligent lock control management method for hydropower stations in this application.

[0035] like Figure 2 As shown, in this embodiment, step S1 includes: S11: Receive operation ticket text data issued by the scheduling system, divide the operation ticket text data according to the operation step sequence number and text boundary to obtain multiple operation step text fragments, and establish the association relationship between each operation step text fragment and the corresponding operation step sequence number. S12: Perform named entity recognition and semantic element extraction on each operation step text fragment to identify the device entity, action description and condition description in each operation step text fragment, and obtain device entity data, action description data and condition description data. S13: Based on the association, the semantic association between the device entity data, the action description data and the condition description data is parsed to determine the device entity as the operation object, the corresponding action type and the device entity as the execution condition. The device entity as the operation object is determined as the target device identifier, the action type is determined as the action category, and the precondition is generated according to the device entity as the execution condition.

[0036] It should be noted that the scheduling system refers to the business system used to generate, review, and issue operation tickets to the hydropower station's interlocking management server; the operation step sequence number refers to the numbering information used to indicate the execution order of various operation contents; the text boundary refers to the separating position of adjacent operation steps in the operation ticket text, which can be determined by the step sequence number, line break character, and statement end marker; the operation step text fragment refers to the continuous text content corresponding to a single operation step divided from the operation ticket text; the association relationship refers to the correspondence between the operation step text fragment and its operation step sequence number; named entity recognition refers to the process of locating and classifying entities such as equipment names, equipment abbreviations, and equipment numbers from the text using a preset recognition model; semantics Element extraction refers to extracting information with specific semantic functions, such as equipment, actions, and conditions, from text; equipment entities refer to text objects representing specific electrical equipment in the operation steps text; action descriptions refer to text content indicating what kind of operation is performed on the equipment; condition descriptions refer to text content indicating the equipment state or sequential conditions that need to be met before the equipment is operated; equipment entity data, action description data, and condition description data are data formed after the corresponding text content and its location, the step it belongs to, and its semantic category are structured and recorded; semantic association refers to the pointing, dominating, or constraining relationship between equipment entities, action descriptions, and condition descriptions in the same operation step; operation object refers to the equipment entity directly affected by the action description.

[0037] The lock control management server receives operation ticket text data from the dispatch system through a data interface and scans the operation step numbers in the original text order. When the current operation step number is identified, the starting position corresponding to that number is determined as the text start point of the current operation step, and the starting position corresponding to the next operation step number or the ending position of the operation ticket text is determined as the text end point of the current operation step. For text recorded across lines in the same operation step, it is merged according to line breaks and sentence continuity to obtain continuous operation step text segments. The operation step text segments are arranged according to the operation step number, and the step number, text start and end positions, and original text content of each text segment are recorded to establish the association between each operation step text segment and its corresponding operation step number. Subsequently, each operation step text segment is input into a named entity recognition model trained on hydropower station equipment corpus. The model performs position labeling and entity classification on the equipment name, equipment abbreviation, and equipment number in the text, and simultaneously identifies action words indicating equipment operation and conditional statements indicating state requirements or sequence requirements. The data is then organized into equipment entity data, action description data, and conditional description data according to the step number and text position.

[0038] Within each operation step text segment, the main action statement and conditional statement are identified based on the location and relationship of the device entity, action description, and conditional description. The device entity directly associated with the action description in the main action statement is identified as the operation object, and the device entity located in the conditional statement and used to restrict the execution of the main action is identified as the device entity corresponding to the execution condition. Simultaneously, action descriptions are categorized to determine their corresponding action types, and the status descriptions associated with the execution condition device in the conditional statements are extracted. For cases where the same operation step contains multiple operation objects, semantic records are established between each operation object and its corresponding action type and execution condition, and each semantic record is associated with the same operation step number. The name or number corresponding to the device entity as the operation object is identified as the target device identifier, the action type is identified as the action category, and preconditions are generated based on the device entity and its status description used as the execution condition.

[0039] By dividing the operation ticket text into steps according to the operation step number and text boundaries, and preserving the correspondence between text fragments and step numbers, the confusion between equipment, action, and condition information in different operation steps can be reduced. By locating equipment entities, action descriptions, and condition descriptions respectively through named entity recognition and semantic element extraction, the relevant information in the operation ticket can be converted into structured data with location and step attributes. Furthermore, by distinguishing the operation object directly affected by the action from the equipment entity in the condition statement based on the statement position and semantic relationship, the probability of misidentifying the precondition equipment as the target equipment can be reduced. When the same operation step contains multiple equipment entities, corresponding semantic records are established for each, thereby improving the accuracy and completeness of target equipment identification, action category, and precondition extraction, and providing a reliable data foundation for subsequent standardized equipment matching.

[0040] Based on the first embodiment described above, in this embodiment, step S2 includes: S21: Extract the standard device name from each standard device record, determine the edit distance between the target device identifier and each standard device name, and determine the character-level similarity score corresponding to each standard device record based on the edit distance; S22: Perform semantic vector transformation on the target device identifier and each standard device name respectively, determine the semantic vector similarity between the target device identifier and each standard device name, and map the corresponding semantic similarity score to a value range consistent with the character similarity score to obtain a standardized semantic similarity score; S23: The character-level similarity score and the standardized semantic-level similarity score are weighted and fused to obtain the comprehensive matching score corresponding to each standard device record. The standard device record with the largest comprehensive matching score is determined as the candidate standard device record. When the candidate standard device record meets the preset matching conditions, the corresponding device code is extracted. Or, when the preset matching conditions are not met, the target standard device record is determined based on the received confirmation result and the corresponding device code is extracted to obtain the standard device code.

[0041] It should be noted that: Standard equipment name refers to the full name of the equipment recorded in the equipment ledger according to a unified naming rule; edit distance refers to the number of character insertion, deletion, or replacement operations required to convert one character sequence into another; character-level similarity score refers to the degree of matching determined based on the difference in character composition between the target equipment identifier and the standard equipment name; semantic vector conversion refers to converting the equipment name into vector data that reflects its semantic features using a pre-defined semantic representation model; semantic vector similarity refers to the closeness between the semantic vectors corresponding to the target equipment identifier and the standard equipment name; semantic-level similarity score refers to the semantic matching degree of the equipment based on semantic vector similarity; standardized semantic-level similarity score refers to converting the semantic-level similarity score to... The score is formed after taking values ​​within the same range as the character-level similarity score; weighted fusion refers to the process of merging different types of similarity scores into a unified evaluation result according to preset weights; the comprehensive matching score refers to the overall matching degree obtained after fusing the character-level similarity score and the standardized semantic-level similarity score; the candidate standard device record refers to the standard device record with the highest comprehensive matching score that is awaiting automatic confirmation or further confirmation; the preset matching conditions refer to the score conditions used to determine whether the candidate standard device record can be directly used as the matching result; the confirmation result refers to the data received by the lock control management server for confirming or adjusting the candidate standard device record; the target standard device record refers to the standard device record that finally establishes a corresponding relationship with the target device identifier after automatic matching or confirmation.

[0042] First, each standard equipment record in the equipment ledger is read sequentially, and the standard equipment name is extracted. The target equipment identifier is then paired with each standard equipment name to form a name pair for comparison. For each name pair, the target equipment identifier and the standard equipment name are compared character by character to determine the number of character insertions, deletions, and replacements required to convert the target equipment identifier into a standard equipment name, thus obtaining the corresponding edit distance. The edit distance is then converted to match degree based on the character length of the two names, ensuring that standard equipment records with smaller character differences have higher character-level similarity scores. A correlation is established between each character-level similarity score and its corresponding standard equipment record. Next, the target equipment identifier and each standard equipment name are input into the same semantic representation model. Semantic vectors are obtained through semantic feature extraction and vector encoding. The semantic vector similarity of each standard equipment record is determined based on the direction and proximity between the semantic vector of the target equipment identifier and the semantic vector of each standard equipment name. The semantic-level similarity scores are then converted according to a preset mapping range, ensuring that the converted scores are within the same range as the character-level similarity scores, while maintaining the original semantic matching order between the standard equipment records, resulting in a standardized semantic-level similarity score.

[0043] Secondly, character-level similarity scores and standardized semantic-level similarity scores are combined according to the standard device records, and preset weights are assigned to each type of score. The weighted scores are then fused to obtain a comprehensive matching score for each standard device record. The comprehensive matching scores are sorted, and the standard device record with the highest comprehensive matching score is identified as a candidate standard device record. This candidate standard device record's comprehensive matching score is then compared with preset matching conditions. When a candidate standard device record meets the preset matching conditions, a mapping relationship between the target device identifier and the candidate standard device record is directly established. When a candidate standard device record does not meet the preset matching conditions, the corresponding target device identifier is marked as pending confirmation, and the candidate standard device record and its matching information are output. After receiving the confirmation result, the target standard device record is determined based on the confirmation result. Finally, the corresponding device code is extracted from the automatically determined or confirmed target standard device record to obtain the standard device code.

[0044] By calculating the edit distance between the target device identifier and each standard device name, we can identify device abbreviations, missing characters, and differences in numbering at the character level. By performing semantic vector conversion and similarity judgment on the target device identifier and standard device names, we can identify names that have different literal expressions but point to similar devices at the semantic level. After mapping the semantic similarity score to a value range consistent with the character similarity score, we perform weighted fusion so that the character matching results and semantic matching results can participate in device judgment under a unified scale, reducing the probability of incorrect mapping based on a single matching method. Furthermore, by screening candidate standard device records through comprehensive matching scores and confirming results that do not meet the preset matching conditions, we can restrict the direct adoption of low-matching records, thereby improving the accuracy and reliability of matching between the target device identifier and standard device records, and providing a standardized data foundation for subsequent topology traversal and lock association based on standard device codes.

[0045] This embodiment acquires operation ticket text data, performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions; matches the target device identifier with the standard device records in the device ledger to obtain the standard device code; based on the standard device code and action category, performs a restricted traversal of the target device nodes in the electrical main wiring topology data to determine the topology-associated devices, and associates the standard device code and the device codes corresponding to the topology-associated devices with the smart lock registration data to obtain the lock list; based on the preconditions and the correspondence between devices and locks in the lock list, determines the precondition dependencies between lock entries, and performs topological sorting on the lock list to obtain the lock control task execution sequence; performs a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and if the check passes, sends the lock control task execution sequence to the smart key. This embodiment performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions, converting the unstructured description in the operation ticket into structured information that can be used for device matching, topology traversal, and sequence determination. By matching the target device identifier with standard device records in the device ledger, the target device is uniformly represented by a standard device code, reducing the interference caused by inconsistencies between the device description in the operation ticket and the device ledger record on the lock association. Furthermore, by combining the standard device code and action category, a restricted traversal is performed on the target device node, so that the determined topology-associated devices correspond to the current target device and operation action, and the device codes of both the target device and the topology-associated devices are associated with the smart lock. The registration data is linked to ensure that the lock list covers both the target devices explicitly recorded in the operation ticket and the associated devices determined by the electrical main wiring topology, thereby improving the accuracy and completeness of the device-lock association. Based on this, the prerequisite dependencies between lock entries are determined according to the preconditions and the correspondence between devices and locks, and a lock control task execution sequence is formed through topological sorting, ensuring that the lock association results are organized in an orderly manner according to the dependencies between devices. Finally, a bidirectional consistency check is performed between the lock control task execution sequence and the operation ticket text data, and only the lock control task execution sequence that passes the check is sent to the smart key, thereby further improving the consistency between the lock control task content and the operation ticket, as well as the reliability of the lock control task issuance.

[0046] Based on the second embodiment described above, a third embodiment of the intelligent lock control management method for hydropower stations according to this application is proposed. Please refer to... Figure 3 , Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the intelligent lock control management method for hydropower stations in this application.

[0047] In this embodiment, step S3 includes: S31: Based on the standard equipment code, determine the target equipment node in the electrical main wiring topology data, and query the preset topology association rules according to the action category to determine the corresponding traversal depth and the range of associated equipment types, thereby obtaining topology traversal constraint data; S32: Starting from the target device node, visit adjacent device nodes layer by layer according to the topology traversal constraint data, retain device nodes whose device type belongs to the range of the associated device type, and stop traversing when the traversal depth is reached, and determine the device corresponding to the retained device node as the topology associated device. S33: Extract the device code corresponding to the topology-associated device, perform an association query between the standard device code and the device code corresponding to the topology-associated device and the smart lock registration data, generate a lock missing mark for device codes that are not associated with lock registration records, and obtain the lock list based on the association query results and the lock missing mark.

[0048] It should be noted that: the preset topology association rule refers to the pre-established correspondence rule between action categories and topology traversal requirements; traversal depth refers to the maximum number of topology layers accessed outward from the target device node along the device connection relationship; the associated device type range refers to the set of device types allowed to be identified as topology-associated devices; topology traversal constraint data refers to traversal control data composed of the target device node, traversal depth, and associated device type range; adjacent device nodes refer to other device nodes directly connected to the current device node in the electrical main wiring topology; layer-by-layer access refers to the processing method of accessing device nodes sequentially from near to far according to the topology distance from the target device node; association query refers to the process of retrieving corresponding lock information from smart lock registration data using the device code as the query condition; lock registration record refers to a single registration data entry used to record the lock code and its associated device codes; lock missing flag refers to the abnormal status flag configured for the device code when no corresponding lock registration record is found.

[0049] First, based on the standard equipment code, the node attributes of each device node in the electrical main wiring topology data are queried. Device nodes whose device codes match the standard equipment codes are identified as target device nodes, and their node identifiers and adjacency relationships are obtained. Using action categories as rule query conditions, the corresponding traversal depth and associated device type range are read from the preset topology association rules, and the target device node, traversal depth, and associated device type range are associated to form topology traversal constraint data. During traversal, the target device node is first added to the set of nodes to be visited, and its level is set as the starting level. The directly connected adjacent device nodes of the target device node are read, and unvisited adjacent device nodes are added to the next level's set of nodes to be visited, while the access level corresponding to each adjacent device node is recorded. The adjacency relationships of device nodes in each level are read sequentially in the same way, and the device nodes that are visited repeatedly are excluded based on the already visited node record.

[0050] During the layer-by-layer traversal, the device type of each accessed device node is read, and device nodes whose device types fall within the range of associated device types are added to the associated node set, while those whose device types do not fall within the range are excluded. When the current access level reaches the traversal depth, or no new adjacent device nodes exist, outward traversal stops, and the devices corresponding to the device nodes in the associated node set are identified as topology-associated devices. Subsequently, the device codes corresponding to each topology-associated device are extracted, merged with the standard device codes of the target device, and duplicate codes are removed to obtain the set of device codes to be queried. Smart lock registration data is retrieved sequentially using each device code to be queried as the query condition: when a corresponding lock registration record is found, the lock code and its associated device code are extracted, and the corresponding lock is marked as either a target device lock or a topology-associated device lock based on the device's origin; when no corresponding lock registration record is found, the corresponding device code is retained, and a lock missing mark is generated. Finally, the retrieved lock registration records and device records carrying lock missing marks are organized according to their corresponding device codes to obtain a lock list.

[0051] By locating target device nodes in the electrical main wiring topology data using standard device codes, topology traversal can have a clear starting position. Determining the traversal depth and associated device type range based on action category allows the search range for topology-associated devices to be limited according to the current operation type, reducing the inclusion of irrelevant devices in the association results. Through layer-by-layer access, accessing hierarchical records, and excluding duplicate nodes, device nodes around the target device can be systematically checked within a specified depth, reducing the probability of missing or duplicate associated devices. Furthermore, unifying the device codes of the target device and topology-associated devices with the smart lock registration data for association queries, and generating a lock missing mark for devices without lock registration records, prevents devices without locks from being directly ignored during list generation, thereby improving the accuracy of topology-associated device determination, the coverage completeness of the lock list, and data reliability.

[0052] Based on the second embodiment described above, in this embodiment, step S4 includes: S41: Determine the corresponding prerequisite devices based on the prerequisites for each target device, and based on the correspondence between devices and locks, determine the lock entries corresponding to the target devices and the prerequisite devices respectively, and establish the prerequisite dependency relationship between the lock entries corresponding to the prerequisite devices and the lock entries corresponding to the target devices. S42: Using the lock entries in the lock list as nodes and the preceding dependencies as directed edges, construct a lock dependency directed graph, and perform loop detection on the lock dependency directed graph. If no loop is detected, determine the lock dependency directed graph as a lock dependency graph to be sorted. S43: Perform topological sorting on the lock dependency graph to be sorted, determine the execution level corresponding to each lock entry, mark lock entries with prerequisite dependencies as serial execution, mark lock entries at the same execution level but without mutual dependencies as parallel execution, and arrange each lock entry according to the execution level to obtain the lock control task execution sequence.

[0053] It should be noted that: a prerequisite device refers to a device whose operation can only be executed after its operation is completed or its state is satisfied; a node refers to a graph data unit in a lock dependency directed graph used to represent a single lock item; a directed edge refers to a data connection from a prerequisite lock item to a subsequent lock item, used to represent the execution direction between the two; a lock dependency directed graph refers to a graph structure composed of lock items as nodes and the prerequisite dependencies between lock items as directed edges; a cycle refers to a closed dependency path formed by connecting the first and last prerequisite dependencies of multiple lock items; cycle detection refers to the process of checking whether there are closed dependency paths in the lock dependency directed graph; a lock dependency graph to be sorted refers to a lock dependency directed graph that has passed cycle detection and has not found any cycles, and can continue to be topologically sorted; execution level refers to the task execution stage divided according to the number and order of prerequisite dependencies of lock items; serial execution means that related lock items need to be executed sequentially according to the order of prerequisite dependencies; parallel execution means that lock items without mutual dependencies can be executed separately at the same execution level.

[0054] First, following the operation steps, read the preconditions corresponding to each target device one by one. Extract the devices that need to meet the preconditions or complete the operation in advance to obtain the precondition devices. Based on the device codes of the target devices and precondition devices, query the correspondence between device codes and lock codes in the lock list to determine the target lock entries corresponding to the target devices and the precondition lock entries corresponding to the precondition devices. When the same target device corresponds to multiple precondition devices, establish dependency records for each precondition lock entry pointing to the target lock entry; when the same device corresponds to multiple lock entries, establish corresponding dependency records according to the device source and operation steps corresponding to each lock entry. Merge duplicate relationships in the generated dependency records and exclude invalid dependencies where the same lock entry points to itself to obtain the precondition dependencies between lock entries. Convert each lock entry in the lock list into a graph node, and record the lock code, associated device code, and operation steps in the graph node. Based on each precondition dependency, establish directed edges from the precondition lock nodes to the target lock nodes to form a directed graph of lock dependencies.

[0055] When performing loop detection on a directed graph of lock dependencies, lock nodes that have not yet been detected are selected as the starting point for detection. Subsequent lock nodes are traced level by level along the directed edges of that lock node, and the current tracing path is recorded. When a subsequent lock node reappears in the current tracing path, a loop is determined, and conflict information is generated based on the lock entries in the loop and their associated operation steps. When no closed path is formed among all lock nodes, the directed graph of lock dependencies is determined as a lock dependency graph to be sorted. For the lock dependency graph to be sorted, the preceding directed edges corresponding to each lock node are counted. Lock nodes without preceding directed edges are assigned to the first execution level. After removing nodes and their outward directed edges from this level, newly appearing nodes without preceding directed edges are assigned to the next execution level, until the hierarchical division of all lock nodes is completed. Lock entries with pre-dependent relationships between different execution levels are marked as serial execution, and lock entries without mutual dependencies within the same execution level are marked as parallel execution. Then, the lock entries are arranged in order from front to back according to the execution level to obtain the lock control task execution sequence.

[0056] By converting the device-level constraints between the target device and the prerequisite devices into prerequisite dependencies between corresponding lock items, the prerequisites in the operation ticket can be reflected in the lock control task. By constructing a directed graph of lock dependencies based on lock items and prerequisite dependencies, the scattered lock execution constraints can be transformed into a detectable and sortable graph structure. Furthermore, by identifying conflicting closed dependencies through loop detection, lock tasks with cyclic constraints can be prevented from directly entering the sorting process. In the absence of loop detection, the execution order of lock items is determined layer by layer through topological sorting, and serial execution and parallel execution are marked respectively. This clarifies the execution method of each lock item based on satisfying the prerequisite dependencies, thereby improving the sequential accuracy, structural rationality, and executability of the lock control task execution sequence.

[0057] In this embodiment, step S5 includes: S51: Using each operation step in the operation ticket text data as a verification benchmark, detect whether the device involved in each operation step has a corresponding lock entry in the lock control task execution sequence, and mark the operation steps that do not have a corresponding lock entry as uncovered abnormal entries to obtain the first verification result; S52: Using each lock item in the lock control task execution sequence as a verification benchmark, based on the device and lock source corresponding to each lock item, detect whether each lock item can be associated with the operation steps in the operation ticket text data, and mark the lock items that cannot be associated with the corresponding operation steps as isolated abnormal items to obtain the second verification result; S53: If the first verification result does not contain any uncovered abnormal entries and the second verification result does not contain any isolated abnormal entries, the bidirectional consistency verification is determined to be successful. The lock control task execution sequence is encapsulated into a lock control task data packet and sent to the smart key through a preset communication channel.

[0058] It should be noted that the verification baseline refers to the set of data used as a reference when performing consistency checks; uncovered anomaly entries refer to anomaly records formed when the device involved in the operation steps does not find the corresponding lock entry in the lock control task execution sequence; the first verification result refers to the data formed after performing a forward coverage check with the operation steps as the verification baseline; the lock source refers to the source attribute of the lock entry, which is directly associated with the target device or extended by the topology-associated device; the isolated anomaly entry refers to anomaly records formed when the lock entry cannot be traced directly or through the lock source to the corresponding operation step; the second verification result refers to the data formed after performing a reverse tracing check with the lock entry as the verification baseline; the lock control task data packet refers to the transmission data formed after encapsulating the lock control task execution sequence and its associated information according to a preset data structure; and the preset communication channel refers to the pre-configured communication link used for transmitting lock control task data between the lock control management server and the smart key.

[0059] First, each operation step in the operation ticket text data is read sequentially according to the operation step number. The equipment involved in each operation step and its corresponding standard equipment code are determined, and a step query condition is established based on the operation step number, standard equipment code, and lock code. The lock control task execution sequence is retrieved using the step query condition, and it is checked whether the equipment involved in each operation step has a corresponding lock entry. When the same operation step involves multiple devices, the lock entries corresponding to each device are checked one by one, and the equipment codes for which no lock entries are found are recorded. If any device in the operation step does not have a corresponding lock entry, the operation step number, the uncovered device code, and the exception type are associated to form an uncovered exception entry; if all devices have corresponding lock entries, the operation step is recorded as covered normally. The check results of each operation step are summarized to obtain the first verification result. Subsequently, each lock entry in the lock control task execution sequence is read sequentially, and the lock code, associated device code, lock source, and the corresponding operation step number are extracted. When the lock originates from the target device, check if its associated device code exists in the corresponding operation step. When the lock originates from a topology-related device, check whether it can be traced back to the operation step in the operation ticket through the corresponding target device and operation step number, based on the associated source recorded in the lock entry. For lock entries that cannot be traced back to the operation step directly or through the associated source, their lock code, associated device code, and lock source are associated to form isolated abnormal entries, which are then summarized to obtain the second verification result.

[0060] Next, the set of uncovered anomaly entries in the first verification result and the set of isolated anomaly entries in the second verification result are read respectively. When either set is not empty, the bidirectional consistency verification is deemed to have failed. Anomaly information is generated based on the operation step sequence number, device code, and lock code corresponding to the anomaly entry, and the issuance of the lock control task is paused. After the anomaly information is processed, the bidirectional consistency verification is re-executed. When both the set of uncovered anomaly entries and the set of isolated anomaly entries are empty, the bidirectional consistency verification is deemed to have passed. The lock code, associated device code, execution order, and serial or parallel execution marker in the lock control task execution sequence are extracted sequentially according to the execution level. The extracted information is associated with the target smart key identifier and encapsulated into a lock control task data packet according to a preset data structure. The corresponding preset communication channel is determined based on the target smart key identifier, and the lock control task execution sequence is issued to the smart key by sending the lock control task data packet.

[0061] By performing forward coverage checks using each operation step in the operation ticket as the verification benchmark, it is possible to identify situations where the equipment involved in the operation steps is not configured with the corresponding lock task, reducing the probability of missing lock tasks. By using each lock entry in the lock control task execution sequence as the verification benchmark, and combining it with the associated equipment and lock source for reverse tracing, it is possible to identify lock entries that lack the source of the operation step, while avoiding misjudging lock entries with clear topological association sources as abnormal. Furthermore, by encapsulating and issuing the lock control task execution sequence only when neither uncovered abnormal entries nor isolated abnormal entries exist, it is possible to restrict lock control tasks with incomplete coverage or unclear sources from entering the smart key, thereby improving the consistency between lock control tasks and operation tickets, the coverage integrity of lock tasks, and the reliability of task issuance.

[0062] This embodiment acquires operation ticket text data, performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions; matches the target device identifier with the standard device records in the device ledger to obtain the standard device code; based on the standard device code and action category, performs a restricted traversal of the target device nodes in the electrical main wiring topology data to determine the topology-associated devices, and associates the standard device code and the device codes corresponding to the topology-associated devices with the smart lock registration data to obtain the lock list; based on the preconditions and the correspondence between devices and locks in the lock list, determines the precondition dependencies between lock entries, and performs topological sorting on the lock list to obtain the lock control task execution sequence; performs a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and if the check passes, sends the lock control task execution sequence to the smart key. This embodiment performs semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions, converting the unstructured description in the operation ticket into structured information that can be used for device matching, topology traversal, and sequence determination. By matching the target device identifier with standard device records in the device ledger, the target device is uniformly represented by a standard device code, reducing the interference caused by inconsistencies between the device description in the operation ticket and the device ledger record on the lock association. Furthermore, by combining the standard device code and action category, a restricted traversal is performed on the target device node, so that the determined topology-associated devices correspond to the current target device and operation action, and the device codes of both the target device and the topology-associated devices are associated with the smart lock. The registration data is linked to ensure that the lock list covers both the target devices explicitly recorded in the operation ticket and the associated devices determined by the electrical main wiring topology, thereby improving the accuracy and completeness of the device-lock association. Based on this, the prerequisite dependencies between lock entries are determined according to the preconditions and the correspondence between devices and locks, and a lock control task execution sequence is formed through topological sorting, ensuring that the lock association results are organized in an orderly manner according to the dependencies between devices. Finally, a bidirectional consistency check is performed between the lock control task execution sequence and the operation ticket text data, and only the lock control task execution sequence that passes the check is sent to the smart key, thereby further improving the consistency between the lock control task content and the operation ticket, as well as the reliability of the lock control task issuance.

[0063] In one embodiment, taking a hydropower station (code name: Station A) as an example, preventative maintenance of Unit 2 is planned for 20XX. The dispatch center issues a switching operation ticket to the Station A maintenance team, involving the shutdown operation of the No. 2 turbine generator unit's outlet circuit breaker, main transformer, related disconnect switches, and grounding switch. The operation ticket is described in semi-structured text form, containing four operation steps, with abbreviations and number variations in the equipment names involved. Maintenance personnel B possess a registered smart key (terminal number: KEY-021). The lock control management server connects to the equipment ledger database and the smart lock registration database via a local area network and maintains communication with KEY-021 via a 5G network channel.

[0064] The system acquires the operation ticket text and extracts equipment semantic information. The lock control management server receives the operation ticket text issued by the dispatcher, calls the named entity recognition model (which has been fine-tuned based on the hydropower station domain corpus), and processes each of the four operation steps one by one. It identifies the equipment entity name, action type, and constraints, generating a sequence of semantic triplets for each operation step. The text "Confirm that both disconnect switches QS21 and QS22 at the No. 2 unit outlet are in position, then open the high-voltage side disconnect switch of the No. 2 main transformer" contains two equipment entities. The model generates independent triplets for QS21 and QS22 respectively, and both share step number 3.

[0065] Table 1. Operational Steps and Semantic Triple Sequences

[0066] For each target device identifier in Table 1, calculate its character-level similarity score with the standard device name in the device ledger database. and semantic similarity score (mapped to via linear transformation) After the interval), according to the preset weight , Perform weighted fusion to obtain a comprehensive matching score. :

[0067] Taking "Unit 2 Output Switch" as an example, its comprehensive matching score with the standard name "Unit 2 Output Circuit Breaker CB201" in the ledger is... If the score is higher than the preset threshold of 0.75, mapping will be completed automatically. The overall matching score between "QS21" and "Outlet Isolation Switch QS21 of Unit 2" is 0.93, and mapping will also be completed automatically.

[0068] Table 2 Standardized Equipment Identification Mapping Table

[0069] In Table 2, the comprehensive matching score of "No. 2 main transformer high voltage side grounding switch" is 0.70, which is lower than the preset threshold of 0.75. The system triggers a prompt message on the lock control management interface. After the maintenance team leader confirms, it is mapped to DEV-QEA201 and written back to the mapping table.

[0070] Taking the target device DEV-CB201 (action type: tripping) corresponding to step number 1 as an example, the topology traversal process is illustrated. The system queries the predefined topology association rule table and finds that the traversal depth corresponding to the "tripping" type circuit breaker operation is 2 levels, and the associated device type range is disconnecting switches and grounding switches. Then, starting with DEV-CB201 as the starting node, a restricted breadth-first traversal is performed in the electrical main wiring topology diagram data. The first level obtains DEV-QS21 and DEV-QS22, and the second level obtains DEV-QEA201. Nodes outside the type range are filtered out during the traversal process.

[0071] During the cross-comparison, it was found that DEV-QS21, DEV-QS22, and DEV-QEA201 had all appeared as independent operation targets in steps 3 and 4. An associated source mark was added to them, and they were retained in the subsequent lock list but not repeatedly generated as independent lock control task entries.

[0072] Table 3. Set of devices associated with each target device's topology.

[0073] The system performs a correlation query between the codes of each target device and its associated topology devices and the smart lock registration database. DEV-QEA202 has no lock registration record in the database. The system generates a missing entry and triggers an alarm. After the maintenance team confirms that no smart lock has been installed on this grounding switch, the missing entry is retained in the list for manual processing.

[0074] The unlocking priority field is assigned a value according to the following rules: the priority value of the lock corresponding to the topology-related device is lower than the priority value of the lock corresponding to the target device itself. The smaller the value, the higher the priority.

[0075] Table 4 Complete Lock List

[0076] Based on the prerequisite device set field, the prerequisite dependencies between the lock entries in Table 4 are represented as a directed acyclic graph: LK-3011 and LK-3012 have no prerequisite dependencies; LK-3021 depends on LK-3011 and LK-3012; LK-4031 depends on LK-3021, LK-3013 depends on LK-3021; ​​LK-5041 depends on LK-3013. After performing loop detection, no loops were found, and the process proceeds to topology sorting.

[0077] The sorting results are divided into four levels: In the first level, LK-3011 and LK-3012 have no dependency on each other and are marked as parallel executable; in the second level, LK-3021 depends on all entries in the first level and is marked as a serial execution constraint; in the third level, LK-4031 and LK-3013 both depend on LK-3021, but they have no mutual dependency and are marked as parallel executable; in the fourth level, LK-5041 depends on LK-3013 and is marked as a serial execution constraint.

[0078] Table 5 Locking Task Execution Sequence

[0079] Step S602 checks each of the four original operation steps on the operation ticket step by step to confirm that each step has a corresponding lock entry in the complete lock list, and any uncovered abnormal entries are empty. Step S602 checks each lock entry in the lock control task execution sequence step by step to confirm that each lock entry can be found in the operation ticket, and any isolated abnormal entries are empty. Once the two-way verification is passed, the execution sequence is encapsulated into a lock control task data packet and sent to KEY-021 via the 5G network channel.

[0080] The unlocking audit data returned by KEY-021 during the execution process is recorded. Table 6 shows the first 4 execution records.

[0081] Table 6. Audit Feedback Records of Smart Key Unlocking (Partial)

[0082] Once the execution status of all lock entries is updated to "completed", the lock control management server generates a lock control task execution completion record and archives it.

[0083] Throughout the process, data starts with the original text of the operation ticket, is converted into a structured sequence of semantic triples representing operation steps, then mapped to standardized device codes, and expanded through topological traversal into a complete set of devices containing implicitly related devices. This set is then transformed into a complete list of locks with priority fields (including lock missing alarm entries). Based on pre-dependencies, the lock list is topologically sorted and divided into four execution levels, with timing constraints annotated. Finally, after bidirectional verification, the data is encapsulated, distributed, and archived for auditing. The output of each step serves as direct input for the next step. Key identifiers such as device codes, step numbers, and lock codes maintain consistent correspondence throughout the entire process, ensuring a complete data flow from the operation ticket to the lock control task execution sequence.

[0084] This application also provides an intelligent lock control management device for hydropower stations. Please refer to... Figure 4 , Figure 4 This is a schematic diagram of the module structure of the intelligent lock control management device for hydropower stations according to an embodiment of this application. The intelligent lock control management device for hydropower stations includes: The semantic recognition module 401 is used to acquire operation ticket text data, perform semantic recognition on the operation steps in the operation ticket text data, and obtain the target device identifier, action category and preconditions. The equipment coding module 402 is used to match the target equipment identifier with the standard equipment record in the equipment ledger to obtain the standard equipment code; The lock list module 403 is used to perform a restricted traversal of the target device node in the electrical main wiring topology data based on the standard device code and the action category, determine the topology-associated device, and associate the standard device code and the device code corresponding to the topology-associated device with the smart lock registration data to obtain the lock list; The execution sequence module 404 is used to determine the pre-dependencies between lock entries based on the preconditions and the correspondence between devices and locks in the lock list, and to perform topological sorting on the lock list to obtain the lock control task execution sequence; The verification and distribution module 405 is used to perform bidirectional consistency verification between the lock control task execution sequence and the operation ticket text data, and if the verification passes, distribute the lock control task execution sequence to the smart key.

[0085] The intelligent lock control management device for hydropower stations provided in this application, employing the intelligent lock control management method for hydropower stations described in the above embodiments, can solve the technical problem of how to improve the accuracy and completeness of the association between the operating ticket equipment and the intelligent lock. Compared with the prior art, the beneficial effects of the intelligent lock control management device for hydropower stations provided in this application are the same as those of the intelligent lock control management method for hydropower stations provided in the above embodiments, and other technical features in the intelligent lock control management device for hydropower stations are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0086] This application provides a smart lock control management device for a hydropower station. The smart lock control management device for a hydropower station includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the smart lock control management method for a hydropower station described in the above embodiments.

[0087] The following is for reference. Figure 5 , Figure 5 This is a schematic diagram of the hardware operating environment of the intelligent lock control management method for hydropower stations in the embodiments of this application. It shows a schematic diagram of the structure of the intelligent lock control management equipment for hydropower stations suitable for implementing the embodiments of this application. Figure 5 The intelligent lock control management device for hydropower stations shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0088] like Figure 5 As shown, the intelligent lock control management device for a hydropower station may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to programs stored in read-only memory (ROM) 1002 or programs loaded from storage device 1003 into random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the intelligent lock control management device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the hydropower station intelligent lock control management equipment to exchange data wirelessly or via wired communication with other devices. Although the figure shows a hydropower station intelligent lock control management equipment with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0089] In particular, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. When the computer program is executed by the processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0090] The intelligent lock control management device for hydropower stations provided in this application, employing the intelligent lock control management method for hydropower stations described in the above embodiments, can solve the technical problem of how to improve the accuracy and completeness of the association between the operation ticket device and the intelligent lock. Compared with the prior art, the beneficial effects of the intelligent lock control management device for hydropower stations provided in this application are the same as those of the intelligent lock control management method for hydropower stations provided in the above embodiments, and other technical features in this intelligent lock control management device are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0091] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0092] The above description is merely a specific embodiment 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.

[0093] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the intelligent lock control management method for hydropower stations described in the above embodiments.

[0094] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the hydropower station's intelligent lock control management device, the device performs the following actions: acquires operation ticket text data; performs semantic recognition on the operation steps in the operation ticket text data to obtain the target equipment identifier, action category, and preconditions; matches the target equipment identifier with the standard equipment record in the equipment ledger to obtain the standard equipment code; based on the standard equipment code and action category, performs a restricted traversal of the target equipment node in the electrical main wiring topology data to determine the topology-associated equipment, and associates the standard equipment code and the equipment code corresponding to the topology-associated equipment with the intelligent lock registration data to obtain a lock list; based on the preconditions and the correspondence between equipment and locks in the lock list, determines the precondition dependencies between lock entries, and performs topological sorting on the lock list to obtain a lock control task execution sequence; performs a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and, if the check passes, sends the lock control task execution sequence to the smart key. Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0095] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0096] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0097] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., computer programs) for executing the above-described intelligent lock control management method for hydropower stations. This addresses the technical problem of improving the accuracy and integrity of the association between the ticketing device and the intelligent lock. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the intelligent lock control management method for hydropower stations provided in the above embodiments, and will not be elaborated upon here.

[0098] This application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described intelligent lock control management method for hydropower stations.

[0099] The computer program product provided in this application can solve the technical problem of how to improve the accuracy and integrity of the association between the ticketing device and the smart lock. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the hydropower station smart lock control management method provided in the above embodiments, and will not be repeated here.

[0100] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A method for intelligent interlock control management of a hydropower station, characterized in that, The method includes: Obtain operation ticket text data, perform semantic recognition on the operation steps in the operation ticket text data, and obtain the target device identifier, action category and prerequisite conditions; The target device identifier is matched with the standard device record in the equipment ledger to obtain the standard device code; Based on the standard device code and the action category, a restricted traversal is performed on the target device node in the electrical main wiring topology data to determine the topology-associated device. The standard device code and the device code corresponding to the topology-associated device are then associated with the smart lock registration data to obtain a lock list. Based on the aforementioned preconditions and the correspondence between devices and locks in the lock list, the preconditions between lock entries are determined, and the lock list is topologically sorted to obtain the lock control task execution sequence. A two-way consistency check is performed between the lock control task execution sequence and the operation ticket text data, and if the check passes, the lock control task execution sequence is sent to the smart key.

2. The method as described in claim 1, characterized in that, The steps of acquiring operation ticket text data and performing semantic recognition on the operation steps in the operation ticket text data to obtain the target device identifier, action category, and preconditions include: The system receives operation ticket text data from the scheduling system, divides the operation ticket text data according to the operation step number and text boundary to obtain multiple operation step text fragments, and establishes the association between each operation step text fragment and the corresponding operation step number. Named entity recognition and semantic element extraction are performed on the text fragments of each operation step to identify the device entities, action descriptions and condition descriptions in each operation step text fragment, and obtain device entity data, action description data and condition description data. Based on the aforementioned association, the semantic association between the device entity data, the action description data, and the condition description data is parsed to determine the device entity as the operation object, the corresponding action type, and the device entity as the execution condition. The device entity as the operation object is identified as the target device identifier, the action type is identified as the action category, and the preconditions are generated based on the device entity as the execution condition.

3. The method as described in claim 1, characterized in that, The step of matching the target device identifier with the standard device record in the equipment ledger to obtain the standard device code includes: Extract the standard device name from each standard device record, determine the edit distance between the target device identifier and each standard device name, and determine the character-level similarity score corresponding to each standard device record based on the edit distance; Semantic vector transformation is performed on the target device identifier and each standard device name respectively to determine the semantic vector similarity between the target device identifier and each standard device name, and the corresponding semantic similarity score is mapped to a value range consistent with the character similarity score to obtain a standardized semantic similarity score; The character-level similarity score and the standardized semantic-level similarity score are weighted and fused to obtain the comprehensive matching score corresponding to each standard device record. The standard device record with the largest comprehensive matching score is determined as the candidate standard device record. When the candidate standard device record meets the preset matching conditions, the corresponding device code is extracted. Alternatively, when the preset matching conditions are not met, the target standard device record is determined based on the received confirmation result and the corresponding device code is extracted to obtain the standard device code.

4. The method as described in claim 1, characterized in that, The step of performing a restricted traversal of the target device node in the electrical main wiring topology data based on the standard device code and the action category to determine the topology-associated device, and associating the standard device code and the device code corresponding to the topology-associated device with the smart lock registration data to obtain the lock list includes: Based on the standard equipment code, the target equipment node is determined in the electrical main wiring topology data, and the preset topology association rules are queried according to the action category to determine the corresponding traversal depth and the range of associated equipment types, thereby obtaining the topology traversal constraint data. Starting with the target device node, the adjacent device nodes are visited layer by layer according to the topology traversal constraint data. Device nodes whose device type belongs to the range of the associated device types are retained. Traversal stops when the traversal depth is reached. The device corresponding to the retained device node is determined as the topology associated device. Extract the device code corresponding to the topology-associated device, perform an association query between the standard device code and the device code corresponding to the topology-associated device and the smart lock registration data, and generate a lock missing mark for device codes that are not associated with lock registration records. Based on the association query results and the lock missing mark, obtain the lock list.

5. The method as described in claim 1, characterized in that, The steps of determining the prerequisite dependencies between lock entries based on the preconditions and the correspondence between devices and locks in the lock list, and performing topological sorting on the lock list to obtain the lock control task execution sequence, include: Based on the preconditions corresponding to each target device, the corresponding precondition devices are determined, and based on the correspondence between devices and locks, the lock entries corresponding to the target devices and the precondition devices are determined respectively, and the precondition dependency relationship between the lock entries corresponding to the precondition devices and the lock entries corresponding to the target devices is established. Using the lock entries in the lock list as nodes and the preceding dependencies as directed edges, a lock dependency directed graph is constructed. Loop detection is performed on the lock dependency directed graph. If no loop is detected, the lock dependency directed graph is determined as a lock dependency graph to be sorted. The dependency graph of the locks to be sorted is topologically sorted to determine the execution level corresponding to each lock entry. Lock entries with prerequisite dependencies are marked as executed sequentially, and lock entries at the same execution level without mutual dependencies are marked as executed in parallel. The lock entries are then arranged according to the execution level to obtain the lock control task execution sequence.

6. The method as described in claim 1, characterized in that, The step of performing a bidirectional consistency check between the lock control task execution sequence and the operation ticket text data, and, if the check passes, sending the lock control task execution sequence to the smart key, includes: Using each operation step in the operation ticket text data as a verification benchmark, it is detected whether the device involved in each operation step has a corresponding lock entry in the lock control task execution sequence, and the operation steps that do not have a corresponding lock entry are marked as uncovered abnormal entries, thus obtaining the first verification result; Using each lock item in the lock control task execution sequence as the verification benchmark, based on the device and lock source corresponding to each lock item, it is detected whether each lock item can be associated with the operation steps in the operation ticket text data, and lock items that cannot be associated with the corresponding operation steps are marked as isolated abnormal items to obtain the second verification result; If the first verification result does not contain any uncovered abnormal entries and the second verification result does not contain any isolated abnormal entries, the bidirectional consistency verification is determined to be successful. The lock control task execution sequence is then encapsulated into a lock control task data packet and sent to the smart key through a preset communication channel.

7. A smart lock control management device for a hydropower station, characterized in that, The device includes: The semantic recognition module is used to acquire operation ticket text data, perform semantic recognition on the operation steps in the operation ticket text data, and obtain the target device identifier, action category and preconditions. The equipment coding module is used to match the target equipment identifier with the standard equipment record in the equipment ledger to obtain the standard equipment code; The lock list module is used to perform a restricted traversal of the target device node in the electrical main wiring topology data based on the standard device code and the action category, determine the topology-associated device, and associate the standard device code and the device code corresponding to the topology-associated device with the smart lock registration data to obtain the lock list; The execution sequence module is used to determine the pre-dependencies between lock entries based on the preconditions and the correspondence between devices and locks in the lock list, and to perform topological sorting on the lock list to obtain the lock control task execution sequence; The verification and distribution module is used to perform bidirectional consistency verification between the lock control task execution sequence and the operation ticket text data, and if the verification passes, distribute the lock control task execution sequence to the smart key.

8. A computer device, characterized in that, The device includes: a memory, a processor, and a hydropower station intelligent lock control management program stored in the memory and executable on the processor, the hydropower station intelligent lock control management program being configured to implement the steps of the hydropower station intelligent lock control management method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a hydropower station intelligent lock control management program, which, when executed by a processor, implements the steps of the hydropower station intelligent lock control management method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the intelligent lock control management method for hydropower stations as described in any one of claims 1 to 6.

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