Adaptive extraction method for trend term of machinery signal based on extreme-point symmetric mode decomposition

In mechanical fault diagnosis and condition monitoring, extracting and eliminating the trend term of machinery signal are necessary. In this paper, an adaptive extraction method for trend term of machinery signal based on Extreme-point symmetric mode decomposition (ESMD) was proposed. This method fully utilized ESMD, including the self-adaptive decomposition feature and optimal fitting strategy. The effectiveness and practicability of this method are tested through simulation analysis and measured data validation. Results indicate that this method can adaptively extract various trend terms hidden in machinery signal, and has commendable self-adaptability. Moreover, the extraction results are better than those of empirical mode decomposition.