FPGA based Signal Prefiltering System for Vibration Analysis of Induction Motor Failure Detection

Timely diagnosis of faults in industrial equipments is a concern to guarantee the overall production process efficiency. For instance, vibration analysis has been one of the few important approaches for motor failure detection. However, vibration sensory signals are often corrupted with random noise, processing of which leads to inaccurate results. Thus, there is a necessity of low cost instrumentation with proper filtering capabilities for online vibration measurement which can be permanently fixed to the machine under test (MUT) for continuous monitoring and reliable diagnosis. The present work compares three signal averaging based filtering techniques for the purpose of analysis. The filters have been implemented in Field Programmable Gate Arrays (FPGA) which are characterized by reduced power consumption and high operational speed for real time applications. To test the functionality of the proposed algorithms, case study of an accelerometer data attached to an Induction motor has been taken up and the results have been analyzed.