Online and Remote Motor Energy Monitoring and Fault Diagnostics Using Wireless Sensor Networks

This paper identifies the synergies between wireless sensor networks (WSNs) and nonintrusive electrical-signal-based motor signature analysis and proposes a scheme of applying WSNs in online and remote energy monitoring and fault diagnostics for industrial motor systems. The main scope is to provide a system overview where the nonintrusive nature of the electrical-signal-based motor signature analysis enables its applications in a WSN architecture. Special considerations in designing nonintrusive motor energy monitoring and fault diagnostic methods in such systems are discussed. This paper also provides detailed analyses to address the real-world challenges in designing and deploying WSNs in practice, including wireless-link-quality dynamics, noise and interference, and environmental impact on communication range and reliability. The overall system feasibility is investigated through a series of laboratory experiments and field tests. First, the concept of a remote and online energy monitoring and fault diagnostic system is demonstrated using a simplified star-type IEEE 802.15.4 compliant WSN in the laboratory. Two well-established nonintrusive motor diagnostic algorithms are intentionally used to prove the feasibility. Next, the challenges of applying the proposed WSN scheme in real industrial environments are analyzed experimentally using field test results.