| Summary: | ObjectivesIn view of the difficulty of collecting the full life cycle performance degradation data of a marine diesel turbocharger, a life prediction model based on the Weiner process is proposed to predict the residual life of the turbocharger. MethodsFirst, the K-Means model is used to cluster the actual operating conditions of the turbocharger and extract the typical operating condition data, then the Bayesian change-point detection model is used to identify the defect points of the turbocharger, and finally, the residual life of a certain type of turbocharger is predicted by the Weiner process degradation model. ResultsThe results prove that the proposed method can predict the residual lifetime of the turbocharger without the historical degradation data of similar equipment. Conclusions The method proposed herein is valuable for marine diesel turbochargers without fault samples.
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