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Rolling element bearings are critical components of rotating machines, and fault in the bearing can cause the machine to fail. Bearing failure is one of the leading causes of failure in various rotating machines used in industry at high and low speeds. Fault diagnosis of various rotating equipment plays a significant role in industries as it guarantees safety, reliability and prevents breakdown and loss of any source of energy. Early identification is an essential element in the diagnosis of defects that saves time and expenses and avoids dangerous conditions. Investigations are being carried out for intelligent fault diagnosis using machine learning approaches. This article gives a short overview of recent trends in the use of machine learning for fault detection. Finally, Deep Learning techniques were recently developed to monitor the health of the intelligent machine are discussed.

A Recent Machine Learning Techniques for Failure Diagnosis of Rolling Element Bearing