Multiple Fault Detection and Analysis in Transmission Line Using IOT

The developed multiple fault detection system was tested under different simulated fault conditions to evaluate its detection capability, response time, communication, and stability. The system successfully detected low-voltage faults, cable faults at 2 km and 4 km, line-to-ground faults, line-to-line faults, short-circuit faults, and high-temperature conditions. During normal operation, the LCD displayed the measured temperature, humidity, voltage, and current values, while the corresponding fault message was displayed whenever an abnormal condition was detected. The system demonstrated a fault-detection response time of approximately 1–2 s, while SMS alerts were transmitted within approximately 3–4 s after fault detection. The GSM module successfully sent the fault type and GPS coordinates, and the generated Google Maps link assisted in identifying the fault location. The Arduino, sensors, GPS, and GSM modules also operated consistently during extended testing. Tests under varying voltage, temperature, humidity, and simulated cable-fault conditions demonstrated reliable operation of the prototype. The experimental results indicate that integrating sensor-based monitoring, Arduino processing, GPS localization, and GSM communication provides an effective approach for rapid fault identification and notification. The system reduces the need for continuous manual inspection and can help maintenance personnel respond more quickly to cable faults. However, the present prototype primarily demonstrates predefined fault locations such as 2 km and 4 km; therefore, future work can focus on continuous-distance fault localization and advanced intelligent fault-classification techniques.

[1] A. Bhatti and M. A. Abide, “Fault Detection in Three-Phase Systems Using Wavelet Transform and Neural Networks,” IEEE Transactions on Power Delivery, 2007, DOI: TPWRD.2006.884512. [2] V. Govindarajan, “Arduino Based Three-Phase Fault Detection and Protection System,” IEEE International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT), 2016, DOI: ICEEOT.2016.7755013. [3] M. H. Osman, “Fault Detection in Three-Phase Induction Motors Using Arduino and Sensors,” IEEE Journal of Telecommunication, Electronic and Computer Engineering, vol. 10, no. 2, 2018, DOI: JTEC.V10i2.354. [4] J. M. Santiago-Perez et al., “A Low-Cost Arduino-Based Three-Phase Multi-Fault Detection System Using Blynk,” IEEE Sensors, 2019, DOI: S19020274.