Decision Making for Condition‐Based Maintenance of Rotating Machinery

ABSTRACT As critical rotating machinery at gas transmission stations, air compressors suffer from limitations of fixed‐interval maintenance during long‐term operation, which fails to reflect actual equipment health, while maintenance threshold setting and rapid degradation identification remain highly experience‐dependent. This paper proposes a condition‐based maintenance (CBM) decision method based on the Weibull proportional hazards model (WPHM). A baseline life model is established using historical failure times, and high/low‐pressure discharge temperatures are adopted as condition covariates to evaluate failure risk. Under availability constraints, maintenance timing is optimized to minimize unit time maintenance costs, with upper and lower thresholds derived for graded condition decision‐making. An early warning mechanism based on the decision index change rate is further introduced to identify potential rapid degradation risks. Case results show that the method balances long‐term maintenance optimization and short‐term anomaly identification, providing a quantitative basis for preventive maintenance of air compressors at gas transmission stations.