Fault Diagnosis of Electromotor by Using Fault probability Distribution Function and Support Vector Machine

Fault Diagnosis of Electromotor by Using Fault probability Distribution Function and Support Vector Machine

Because of many mechanical problems are initially recognized by a change in machinery vibration amplitudes; a maintenance process where the condition of equipment with regard to vibration is monitored for early signs of impending failure. In addition, type and severity of the problems can be recognized by the frequency of vibration, plus the location and direction of the vibratory motion. The objective of this research was condition monitoring of an Electromotor to investigate the correlation between vibration analysis, fault probability of data and fault prognosis. In this research Grms (Root- Mean-Square Acceleration) and the fault probability amount of an Electromotor at ١٤٥٠ RPM in different situations including health, unbalance, misalign and looseness were calculated. Probability Distribution Function is a mathematical function can be used to model the frequencies and their probabilities of occurrences over time. Exponential distribution function was used for calculating the Electromotor fault probability. In this research, the technique of Support Vector Machine(SVM) in the ١٤٥٠ RPM Electromotor faults are classified.