Bearings represent the most important part in rotating machinery. For any machine problems bearing suffers the consequences. It is therefore necessarily to monitor and diagnose the bearing health condition in order to avoid serious problems that can lead to catastrophic machine failure. Various condition monitoring techniques are used for detection of rotating machine faults. This paper demonstrates a method based on time analysis of an acoustic emission signals and bursts captured from bearing assembly. The capability of AE technique for detection of bearing abnormalities and defects at incipient stages is conducted. A real time AE measurement system is developed. It allows AE signals to be processed and analyzed using LabVIEW. ©2008 IEEE.