FAULTS DETECTION VIA MOBILE SAFETY INSPECTION SYSTEM

Authors

  • Chew Sue Ping Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia
  • Anis Shahida Niza Mokhtar Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia
  • Chi Zhi Ren Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia
  • Wan Ariff Fadhil Wan Abdullah Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia
  • Shee Hui Chien Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia
  • Tee kai Wen Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia
  • Muhd Asran Turan Department of Electrical & Electronics Engineering, National Defence University of Malaysia, Sungai Besi, Malaysia

Keywords:

Cable detection, damaged wiring, Deep learning, Gas leaking, Safety inspection

Abstract

Fire accidents due to damaged wiring cables have claimed many buildings and lives. Refrigerant leakage might cause fire and it is poisonous if inhaled in large amount. Regular inspection and maintenance works are compulsory to have early detection to prevent such tragedies. However, the inspection works are tedious and incurring ineffective costs. In this paper, we present a robot CABtec with artificial intelligence capability to conduct close range inspection and detection missions in wiring systems of buildings. This robot will continuously navigate the entire area for damaged cables and gas leakages. If any fault is detected, CABtec is able to conduct thorough inspection suing multi-sensing feature. Users can then utilise the front robot arm to have a closer inspection on the suspected faults. Should any damages to be found, technicians will have to carry out maintenance job using the GPS location sent by the robot as a guide.

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Published

23-01-2022

How to Cite

Chew Sue Ping, Anis Shahida Niza Mokhtar, Chi Zhi Ren, Wan Ariff Fadhil Wan Abdullah, Shee Hui Chien, Tee kai Wen, & Muhd Asran Turan. (2022). FAULTS DETECTION VIA MOBILE SAFETY INSPECTION SYSTEM. Zulfaqar Journal of Defence Science, Engineering & Technology, 4(2). Retrieved from https://zulfaqarjdset.upnm.edu.my/index.php/zjdset/article/view/52

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Articles