TY - JFULL AU - M. Khatami Rad and N. Jamali and M. Torabizadeh and A. Noshadi PY - 2011/1/ TI - Performance Analysis of Expert Systems Incorporating Neural Network for Fault Detection of an Electric Motor T2 - International Journal of Mechanical and Mechatronics Engineering SP - 2562 EP - 2567 VL - 5 SN - 1307-6892 UR - https://publications.waset.org/pdf/9552 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 60, 2011 N2 - In this paper, an artificial neural network simulator is employed to carry out diagnosis and prognosis on electric motor as rotating machinery based on predictive maintenance. Vibration data of the primary failed motor including unbalance, misalignment and bearing fault were collected for training the neural network. Neural network training was performed for a variety of inputs and the motor condition was used as the expert training information. The main purpose of applying the neural network as an expert system was to detect the type of failure and applying preventive maintenance. The advantage of this study is for machinery Industries by providing appropriate maintenance that has an essential activity to keep the production process going at all processes in the machinery industry. Proper maintenance is pivotal in order to prevent the possible failures in operating system and increase the availability and effectiveness of a system by analyzing vibration monitoring and developing expert system. ER -