Smart Motor Fault Detection Leveraging LabVIEW and IoT Integration

The most common primary movers in modern industries, induction machines are typically strong and long-lasting, although they can malfunction due to ageing, vibration, environmental variables, and regular use. A combined approach of fault detection techniques is essential to improve motor performance and reliability while lowering the chance of unanticipated failures. The article presents a real-time remote monitoring and identification of induction motor faults with LabVIEW. The method proposed makes use of the Internet of Things (IoT) to remotely regulate motor operation and LabVIEW to categories motor or generator faults. By addressing these problems, motor efficiency will increase and their use in industrial settings will increase. The motor's sensors record voltage, current, and temperature in real time. LabVIEW simulation software is then used to analyze the data. Each parameter has threshold values that are established, and an alert is provided to indicate the level with of fault with alarm when real-time values routinely exceed these limits. A LabVIEW dashboard tailored for monitoring motor faults serves as a centralized platform for real-time observation and analysis of critical motor parameters. Leveraging IoT in this work enable remote access, empowering users to monitor motor status and adjust settings from anywhere. The work is validated with the prototype connected to single phase induction motor and fault is analyzed at different load conditions and fault conditions. This Fault identification in motors is critical across a wide range of applications and industries where motor-driven systems are employed such as manufacturing industry, power generation and utilities, transportation sector, water and waste water treatments.