Seyed Ali Niknam - Departments of Mechanical Engineering, ETS, University of Québec, ۱۱۰۰ Notre-Dame west street , Montréal, Qc, Canada H۳C ۱K۳
Seyed Mehdi Rezaei - Professor, Department of Mechanical Engineering, Amir Kabir university of technogly,Tehran, Iran
Victor Songmene

With ever growing competition in industry, the need to automate machine condition monitoringcondition monitoring (CM) (CM) has became more and more accuraterequired. CM is known as a method to track the failures in the machines and machine elements and it comprises different kinds of techniques. Bearings are perhaps the most omnipresent machine elements and their condition is often critical to the success of an operation or process. Consequently, there is a great need for a timely knowledge of the health status of bearings. The The One of the most popular condition monitoringCM techniques for bearing fault detection is s are based on vibration and AE signals analysesAcoustic Emission (AE). AE is a technique that can be applied to detect the failure of bearing under various applied operational conditions. The term acoustic emission, often abbreviated to AE, is used to describe both a technique and the phenomenon upon which the technique is based [3]. AE is transient elastic waves generated by rapid release of energy from localised sources within material, which can be applied to detect the failure of bearing under various applied operational conditions. This paper reviews fundamental principles of CM and applications of AE sensing technique in bearing CM and describes applied signal processing techniques in bearing CM using AE. The paper concludes with a brief discussion the advantages of AE to vibration monitoring technique in bearing CM techniques. AE is a technique that can be applied to detect the failure of bearing under various applied operational conditions

Bearing, Condition monitoring, Condition based maintenance, Signal processing, Acoustic Emission