TY - GEN
T1 - Diagnostics of Magnetron Transmitter System using Thermal Camera and Neural Network
AU - Prinanto, Arsy Yudha
AU - Rivai, Muhammad
AU - Setiawan, Rachmad
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The magnetron transmitter system is one of the most important components of weather radar. Monitoring the condition of the system is crucial to ensure the radar is operating normally. In this study, the temperature monitoring of the magnetron transmitter system was carried out. Thermal camera MLX90640 accompanied by NodeMCU ESP32 microcontroller provides a temperature matrix, which can represent the overall temperature of the radar system. The diagnosis system is built based on a neural network consisting of a hidden layer, and an output layer that classifies six system conditions. The results of this study showed that the thermal camera can measure the temperature of the magnetron transmitter system. This system can obtain 100% accuracy in identifying the conditions of the magnetron transmitter system, namely magnetron on, magnetron off, radar off, modulator power supply overheat, switch array unit overheat, and signal processing faulty. This innovation is expected to be early detection of an anomaly that occurs in the magnetron transmitter system so that it can minimize downtime to make repairs due to the unpreparedness of spare parts.
AB - The magnetron transmitter system is one of the most important components of weather radar. Monitoring the condition of the system is crucial to ensure the radar is operating normally. In this study, the temperature monitoring of the magnetron transmitter system was carried out. Thermal camera MLX90640 accompanied by NodeMCU ESP32 microcontroller provides a temperature matrix, which can represent the overall temperature of the radar system. The diagnosis system is built based on a neural network consisting of a hidden layer, and an output layer that classifies six system conditions. The results of this study showed that the thermal camera can measure the temperature of the magnetron transmitter system. This system can obtain 100% accuracy in identifying the conditions of the magnetron transmitter system, namely magnetron on, magnetron off, radar off, modulator power supply overheat, switch array unit overheat, and signal processing faulty. This innovation is expected to be early detection of an anomaly that occurs in the magnetron transmitter system so that it can minimize downtime to make repairs due to the unpreparedness of spare parts.
KW - diagnostic
KW - magnetron transmitter system
KW - neural network
KW - thermal camera
UR - http://www.scopus.com/inward/record.url?scp=85138717165&partnerID=8YFLogxK
U2 - 10.1109/ICISIT54091.2022.9872884
DO - 10.1109/ICISIT54091.2022.9872884
M3 - Conference contribution
AN - SCOPUS:85138717165
T3 - 2022 1st International Conference on Information System and Information Technology, ICISIT 2022
SP - 73
EP - 78
BT - 2022 1st International Conference on Information System and Information Technology, ICISIT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Information System and Information Technology, ICISIT 2022
Y2 - 27 July 2022 through 28 July 2022
ER -