Vibration-based Fault Detection of Wind Turbine Gearbox using Empirical Mode Decomposition Method

Vibration based monitoring techniques are widely adopted for monitoring the condition of rotating machinery. However, in the case of wind turbines the measured vibration is complex due to the high number of vibration sources and modulation phenomenon. Signals are generated by tooth meshing, shaft rotation, gearbox resonance vibration signatures and a substantial amount of noise. Therefore, extracting condition related information of a specific element e.g. gears condition is very difficult. In this paper, a single stage gearbox and generator was manufactured to simulate a small horizontal-axis wind turbine that mounted with three blades. One accelerometer used to extract vibration data contains information about wind turbine gearbox health condition. Vibration signals were collected for healthy gears and gear suffering from a tooth breakage created by removing 30%, 60% 90% of gear tooth to simulate three faults at different rotational speeds; 100, 120 and 150 rpm. Gear fault detection method based on Empirical Mode Decomposition (EMD) that combined with Total energy calculation (TE) technique is presented. Healthy vibration signal has been used as baseline data and analyzed to be compared with faulty signals that may occur in gear to provide a comparison for assessing gear condition. The results showed that proposed method of vibration based condition monitoring is a promising technique for detecting the presence of the faults in gear. Moreover, it successfully differentiated the signals from healthy system and system containing damaged gear. KeywordsEmpirical mode decomposition method (EMD); Total Energy; Gearbox.