Abstract
In order to effectively monitor the wear and predict the life of cylinder liner, a nonlinear degradation model with multi-source uncertainty based on Wiener process is established to evaluate the remaining useful life (RUL) of cylinder liner wear. Due to complex service performance of cylinder liner, the uncertainty of operational environment and working conditions of cylinder liner wear are considered into the model by a random function. The probability density function (PDF) formula of RUL is derived, and the maximum likelihood estimation method is adopted to estimate the unknown parameters of PDF. Considering the evaluated parameters as the initial values, the model parameters are updated adaptively, and an adaptive PDF is obtained. Furthermore, the proposed model is compared with two classical degradation models. The results show that the proposed model has a good performance for predicting the life, and the error is within 5%. The method can provide a reference for condition monitoring of cylinder liner wear.
Highlights
Failure analysis methods are widely used in aviation, navigation, wind power and other industries
The above literatures analyzed the cylinder liner wear from different factors, and the results provide a reference for wear evaluation
The reliability of internal combustion engines (ICEs) is an important indicator of safe operation, and the cylinder liner wear directly affects the reliability of ICEs
Summary
Failure analysis methods are widely used in aviation, navigation, wind power and other industries. Based on nonlinear-drift-driven Wiener process model, the multi-source uncertainties were built by an age-dependent state-space model for the RUL estimation of degrading systems [30]. It can be seen from the above analysis that the degradation model based on Wiener process is widely used in PHM of equipment. In order to predict RUL of cylinder liner more accurately, an adaptive nonlinear degradation with multi-source uncertainty model based on Wiener process is proposed. Different from the existing degradation models, the proposed model considers the adaptive process and stochastic effects of drift coefficient, and the Bayesian method is used to update the model parameters On this basis, RUL of the cylinder liner wear is predicted, and the comparison of the proposed model with two classical degradation model is conducted
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