Symbolic dynamics based bearing fault detection

Abstract

Most of the time domain methods for bearing condition monitoring are machine and load dependent or involves complex mathematical calculations or need of training the algorithm. To overcome the above issues, symbolic dynamics based method is proposed. The time series vibration data is converted into symbolic series from which dictionary of the signal is constructed. Common Signal Index (CSI) a parameter is computed based on dictionary constructed from the reference signal and the test signal. Deviations of the computed CSI value from the CSI value of the healthy state serve as an indicator for the presence of bearing fault. No-load healthy vibration data is used as a reference signal to detect the bearing in healthy or faulty condition. The algorithm is tested with the experimental data obtained for different bearing fault of various sizes and at varying loads. Comparisons of the proposed method with existing time-domain and data based methods are made.