Due the complexity of control and automation networks in modern industries, sensor-based systems stand out as effective approaches for failure detection in electrical and mechanical machines. This kind of intervention has a high operational value in industrial scenarios, once it can avoid corrective maintenance stops, i.e., before the failure reaches a high level of severity and compromises the machine. Consequently, the development of sensors applied to non-destructive techniques (NDT) for failure monitoring in electrical machines has become a recurrent theme in recent studies. In this context, this paper investigates the application of low-cost piezoelectric sensors for vibration analysis, which is an NDT that has already proved to be efficient for the detection of many structural anomalies in induction motors. Further, the proposed work presents a low-cost alternative approach for expensive commercial sensors, which will make this NDT more attractive for industrial applications. To describe the piezoelectric sensor frequency response, a pencil lead break (PLB) test was performed. After this validation, the Root Mean Square (RMS) value from the voltage samples obtained in the test bench was used as a signal processing method. A comparison between the results for different levels of mechanical load attached to the machine shaft indicated not only the successful performance of the low-cost sensors for load estimation purposes, but also showed that oversized motors may present higher vibration levels in some components that could cause mechanical wearing.
FPGA based Signal Prefiltering System for Vibration Analysis of Induction Motor Failure Detection
