Investigation and Development of a Real-Time On-Site Condition Monitoring System for Induction Motors

Abstract

This thesis presents an investigation and development of a real-time on-site condition monitoring system for induction motors. Induction motors are employed in various industries as an essential machine. In order to prevent catastrophic faults during its serviceable life, condition monitoring of induction motors is commonly used in industrial applications to maintain safety and reliability of plant operation. The current practice in condition monitoring primarily involves using various forms of mobile or portable devices, usually with a single sensor input to perform tests at regular intervals. However, such devices and monitoring services can be expensive and require an experienced operator for reliable decisions. Therefore, this thesis investigates an alternative low-cost solution for continuous condition monitoring of induction machines using multiple sensors, which can be located next to a machine under test and can provide condition information using indicator lights for quick diagnosis. The thesis provides hardware and software implementation details using an FPGA based CompactRIO platform. The CompactRIO embedded reconfigurable platform incorporates an FPGA, an analog input module, a real-time host controller and a custom-made indicator module as an on-site monitoring system. The CompactRIO custom-made indicator module utilizes bi-colour LEDs and requirements of CompactRIO MDK to display each level fault. Furthermore, a data acquisition and monitoring system was developed under LabVIEW FPGA environment and LabVIEW Real Time software. The system that has been successfully designed has had its performances and capabilities evaluated through several tests. In addition, real faults are also introduced to demonstrate the system’s performance. The results show that the CompactRIO system is capable of being implemented as condition monitoring system, especially as an early warning unit. The early warning information obtained from this system can be used as valuable data for further detailed fault assessment.