Nuclear energy operation and maintenance optimization method based on graph driving

By using a graph-driven nuclear energy operation and maintenance optimization method, a list of equipment health status assessments and fault mode identification are constructed, which solves the problems of uneven resource allocation and insufficient anomaly identification in traditional nuclear energy operation and maintenance, and realizes refined management of equipment status and optimized resource allocation.

CN120875688AActive Publication Date: 2025-10-31HANGZHOU WANCHENG INTELLIGENT TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202511374351.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-25
Publication Date
2025-10-31
Estimated Expiration
2045-09-25

AI Technical Summary

Technical Problem

Traditional nuclear power operation and maintenance methods rely on manual inspections and periodic maintenance, which makes it difficult to accurately predict the time and cause of equipment failures. This results in maintenance strategies that are difficult to match with actual operating conditions, uneven resource allocation, and an inability to capture abnormal signs in a timely manner, which can easily lead to task overlap and resource waste.

Method used

The graph-driven nuclear energy operation and maintenance optimization method acquires equipment operation data and maintenance records, constructs a knowledge graph, generates an equipment health status assessment list, selects suitable maintenance strategies, identifies fault modes by combining semantic reasoning algorithms, identifies abnormal impact areas by using sensor data, and optimizes task allocation and resource configuration.

Benefits of technology

It enables a refined characterization of equipment health status, improves the accuracy of maintenance strategy adaptation, accurately locates potential risk points, optimizes task coordination efficiency and resource allocation, and improves fault prediction accuracy and resource utilization efficiency.

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Abstract

The invention relates to the technical field of intelligent operation and maintenance, in particular to a nuclear energy operation and maintenance optimization method based on atlas driving, which comprises the following steps: acquiring equipment data and maintenance records, marking state matching, screening a maintenance strategy and combining semantic reasoning to extract a fault path, and classifying deviations to generate adaptability labels. Uninterfered tasks are screened, work order mapping distribution is extracted, execution imbalance is judged, resource and task ratio recording period differences are calculated, and operation and maintenance progress monitoring structure indexes are generated. According to the method, the mapping relation between equipment and working conditions is constructed through operation data and maintenance records, accurate evaluation of the health state is achieved, the fault path and deviation degree are recognized in combination with semantic reasoning, the adaptability of a maintenance strategy and the working conditions is improved, task interference risks are avoided, load fluctuation is recognized by means of work order execution data, and resource and task quantity comparison is combined. And a resource investment benefit evaluation mechanism is constructed, so that the fault prediction accuracy, the task execution coordination and the resource configuration rationality are improved.
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