TY - JOUR A2 - Petrov, Evgeny AU - Wang, JiaQing AU - Xiao, Han AU - Lv, Yong AU - Wang, Tao AU - Xu, Zengbing PY - 2016 DA - 2016/01/06 TI - Detrended Fluctuation Analysis and Hough Transform Based Self-Adaptation Double-Scale Feature Extraction of Gear Vibration Signals SP - 3409897 VL - 2016 AB - This paper presents the analysis of the vibration time series of a gear system acquired by piezoelectric acceleration transducer using the detrended fluctuation analysis (DFA). The experimental results show that gear vibration signals behave as double-scale characteristics, which means that the signals exhibit the self-similarity characteristics in two different time scales. For further understanding, the simulation analysis is performed to investigate the reasons for double-scale of gear’s fault vibration signal. According to the analysis results, a DFA double logarithmic plot based feature vector combined with scale exponent and intercept of the small time scale is utilized to achieve a better performance of fault identification. Furthermore, to detect the crossover point of two time scales automatically, a new approach based on the Hough transform is proposed and validated by a group of experimental tests. The results indicate that, comparing with the traditional DFA, the faulty gear conditions can be identified better by analyzing the double-scale characteristics of DFA. In addition, the influence of trend order of DFA on recognition rate of fault gears is discussed. SN - 1070-9622 UR - https://doi.org/10.1155/2016/3409897 DO - 10.1155/2016/3409897 JF - Shock and Vibration PB - Hindawi Publishing Corporation KW - ER -