FAULT DETECTION IN GEARBOX USING IoT-BASED MONITORING SYSTEM

Abstract: Gearboxes are critical components in industrial machinery, and their unexpected failure can result in significant operational downtime, elevated maintenance costs, and serious safety hazards. Conventional gearbox maintenance relies on periodic manual inspections that are incapable of detecting developing faults in real time. This paper presents the design and implementation of a low-cost, IoT-based fault detection system for gearboxes that integrates DS18B20 digital temperature sensors and an SW-420 vibration sensor with a NodeMCU (ESP8266/ESP32) microcontroller. The system continuously acquires temperature and vibration data, displays readings on a 16×2 LCD screen for on-site visualization, and transmits the data wirelessly to the Blynk IoT cloud platform, enabling remote monitoring via a smartphone application. Fault conditions such as overheating, excessive vibration, gear misalignment, and lubrication failure are automatically detected when sensor readings exceed predefined safety thresholds, triggering instant mobile alerts. Experimental validation confirms that the system reliably identifies abnormal operating conditions within seconds, enabling proactive maintenance intervention. The proposed system achieves a fault detection accuracy exceeding 94%, reduces manual inspection dependency, and provides a scalable and cost-effective solution for predictive maintenance in industrial environments. The total hardware and software implementation cost is estimated at ₹12,000, making it accessible for small and medium-scale industries.

Keywords: IoT, Gearbox Fault Detection, DS18B20, SW-420, NodeMCU, ESP32, Vibration Monitoring, Predictive Maintenance, Blynk, Condition Monitoring.