Health monitoring method and device for heavy gas turbine disc turning gear and storage medium

By synchronously collecting multi-dimensional status data and combining it with real-time operating condition identification and dynamic weight adjustment, the problems of low fault identification accuracy and life prediction deviating from actual operating conditions of heavy-duty gas turbine turning gears have been solved, thus achieving efficient operation and maintenance decision-making and fault management.

CN122149868APending Publication Date: 2026-06-05CHINA UNITED GAS TURBINE TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA UNITED GAS TURBINE TECH CO LTD
Filing Date
2026-05-09
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing health monitoring methods for heavy-duty gas turbine turning gears suffer from low fault identification accuracy, life prediction that deviates from actual operating conditions, and lack of executable strategies to support operation and maintenance decisions, thus affecting operational reliability.

Method used

By synchronously collecting multi-dimensional operating status data, including three-dimensional vibration signals, bearing temperature signals, lubrication circuit oil status signals, and torque and speed coordination signals of the drive shaft, and combining real-time operating condition identification and dynamic weight adjustment, adaptive fusion processing is performed to generate health status assessment results and operation and maintenance strategies.

Benefits of technology

It significantly improves the accuracy of fault identification and prediction, realizes closed-loop management from passive alarm to proactive decision-making, reduces the risk of unplanned downtime, and improves the efficiency of operation and maintenance response.

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Abstract

The present application relates to the technical field of gas turbine health monitoring, in particular to a heavy gas turbine turning gear health monitoring method, device and storage medium. The present application synchronously collects multi-dimensional running state data of the turning gear bearing; identifies the running working condition stage based on the rotation speed and torque signals, dynamically adjusts the weight coefficients of each dimension data; uses the adjusted weight coefficients for adaptive fusion processing, combines bearing fault characteristic frequency analysis and torque fluctuation characteristic analysis to generate health state evaluation results and residual life prediction values; generates operation and maintenance strategy instructions according to the evaluation results, prediction values, working condition emergency degree and spare parts inventory information. The present application solves the problem of single sensing dimension and disconnection from actual working conditions in the prior art through multi-dimensional synchronous sensing and working condition adaptive weight fusion, improves fault recognition accuracy and prediction accuracy, and realizes closed-loop management from passive alarm to active decision.
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