A Model-Based Method for Remaining Useful Life Prediction of Machinery

Remaining useful life (RUL) prediction allows for predictive maintenance of machinery, thus reducing costly unscheduled maintenance. Therefore, RUL prediction of machinery appears to be a hot issue attracting more and more attention as well as being of great challenge. This paper proposes a model-based method for predicting RUL of machinery. The method includes two modules, i.e., indicator construction and RUL prediction. In the first module, a new health indicator named weighted minimum quantization error is constructed, which fuses mutual information from multiple features and properly correlates to the degradation processes of machinery. In the second module, model parameters are initialized using the…

• NN
  National Natural Science Foundation of China

  Awards: 51421004, 51475355
• FR
  Fundamental Research Funds for the Central Universities

  Awards: 2012jdgz01, CXTD2014001