Thermal equipment fault analysis method and system

Through the combination of data classification, labeling and simulation model, the problem of low accuracy in extracting fault characteristics of thermal equipment is solved, more accurate fault analysis and processing is achieved, and operation and maintenance efficiency is improved.

CN119669809APending Publication Date: 2025-03-21INNER MONGOLIA SHANGDU SECOND POWER GENERATION CO LTD
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Patent Information

Application Number
CN202411437868.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-14
Publication Date
2025-03-21

AI Technical Summary

Technical Problem

Due to differences in equipment types, fault types and operating environment, the accuracy of extraction of fault characteristics of thermal equipment is low.

Method used

The preset data classification model classifies the operating data of thermal equipment, and compares the classified data to obtain data category differences information. The data category distinction information is marked and matched with the thermal equipment fault analysis process information. The thermal equipment operation data corresponding to the process node with the marked data difference information is retrieved, and the thermal equipment operation data is substituted into the thermal equipment fault analysis simulation model to obtain the fault analysis simulation results, and the data of unidentified fault types are processed through the data detection and correction model.

Benefits of technology

It improves the accuracy of fault feature extraction, ensures that each process node has accurate data support, can accurately predict and identify fault types, reduces manual intervention, and improves the efficiency of fault processing.

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Abstract

The invention relates to the technical field of power plant equipment operation and maintenance, provides a thermal equipment fault analysis method and system, and aims to solve the problem of low accuracy of thermal equipment fault feature extraction. The method comprises the steps of obtaining thermal equipment operation data and fault analysis process information, analyzing faults and classifying the data through a preset model, comparing classification results to mark data distinguishing information, then matching the marked information with process nodes, calling related data to carry out fault simulation analysis, recognizing recognizable and unrecognizable fault types, and finally, carrying out fault analysis. And for unrecognizable faults, detecting errors by using the data detection model, and matching a repair strategy in the data correction knowledge base for correction. According to the method, the accuracy of fault feature extraction is improved, the pertinence and comprehensiveness of fault analysis are enhanced, automatic detection and correction of error data are realized, the operation and maintenance cost is reduced, and the intelligent level of the system is improved.
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