Mechanical failure prevention and condition monitoring have been one of the mechanical engineers’ concerns in recent years due to the personal safety, reliability, failure cost, and equipment downtime issues. Proper system failure prevention process helps to reduce the possibility of the system malfunction, identification of source causes, and troubleshooting. The use of novel sensors such as an Air-coupled ultrasonic transducer, Eddy current, Piezoelectric ultrasonic transducer as diagnostic tools for detection of bearing faults has been investigated. A series of experiments were carried out in a laboratory environment. Localized defects with different sizes were created intentionally on the test bearing components simulating evolving cracks or other related faults. Four different signal processing techniques were applied to extract the signal features. The resulting data for different bearing speed and load showed that the sensors are capable of detecting different types of defects located on the bearing components.