A method for predictive maintenance of a steam turbine rotor

CN122928009APending Publication Date: 2026-10-16CEIC BOILER & PRESSURE VESSEL INSPECTION CO LTD
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Patent Information

Application Number
CN202611112379.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-07-24
Publication Date
2026-10-16

AI Technical Summary

Technical Problem

[0005]本申请提供一种汽轮机转子预知性检修方法,以解决定期检修模式下的过度检修或检修不足的问题,提升转子运行可靠性、降低故障风险并优化检修资源配置

Benefits of technology

[0005] This application provides a predictive maintenance method for steam turbine rotors to address the problems of over-maintenance or under-maintenance under the periodic maintenance mode, thereby improving rotor operational reliability, reducing failure risks, and optimizing maintenance resource allocation.

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Abstract

The application relates to a steam turbine rotor predictive maintenance method, which comprises the following steps: collecting full-life cycle basic data of a steam turbine rotor, performing function analysis and equipment classification on components of the steam turbine rotor based on the full-life cycle basic data of the steam turbine rotor, performing failure mode and effect analysis according to the results of the function analysis and the equipment classification to obtain a failure mode of a to-be-maintained component in the steam turbine rotor and a risk priority number of the failure mode; evaluating a state level of the to-be-maintained component in the steam turbine rotor, evaluating an overall state of the steam turbine rotor and predicting an actual residual life of the to-be-maintained component based on the state level of the to-be-maintained component; matching a corresponding maintenance decision result according to the risk priority number of the failure mode of the to-be-maintained component and the overall state of the steam turbine rotor, performing maintenance on the to-be-maintained component according to the maintenance decision result, and performing maintenance effect evaluation on the components after the maintenance is performed, so that the maintenance decision in the subsequent step is optimized according to the maintenance effect evaluation.
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