Empirical mode decomposition: A review on mode selection method for rotating machinery diagnosis

Abstract

Rotating machinery diagnosis is very important to ensure safe operation and avoid fatalities. Failure of rotating machinery causes production loss, equipment loss and financial loss. Therefore, condition monitoring and fault diagnosis are very crucial to most critical engineering application such as helicopter, aircraft and gas turbine. Empirical mode decomposition (EMD) method is a well-known method that has been widely and successfully used for rotating machinery diagnosis over decades. Selection of IMF is very important to have most information extracted from vibration signal and avoiding misled interpretation. This review paper aims to review and summarise the selection method used to select most significance IMF for rotating machinery diagnosis. Besides that, this review paper also has proposed some fruitful research direction for future consideration.