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The safety, reliability, efficiency and performance of rotating machinery are major concerns in industry. Induction motors with many important advantages such as high reliability and performance have a critical role in many industries. The failure of rolling element bearings is one of the foremost causes of breakdown in induction motors. Accordingly, a reliable bearing health condition monitoring system is very useful in industries to detect incipient defects in bearings, so as to prevent motor performance degradation and malfunction.The objective of this study is to develop an intelligent system for more reliable bearing fault diagnostics. This system involves two sequential processes: feature extraction and fault diagnosis. The strategy is to develop advanced and robust techniques at each processing stage so as to improve the reliability of bearing condition monitoring.