Journal
IEEE SENSORS JOURNAL
Volume 17, Issue 19, Pages 6418-6430Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2017.2738028
Keywords
Transformer winding; RFID; self-powered; fault diagnosis and prognosis
Funding
- National Natural Science Foundation of China [51577046, 51607004]
- State Key Program of National Natural Science Foundation of China [51637004]
- national key research and development plan important scientific instruments and equipment development [2016YFF0102200]
- Ph.D. special research fund of HFUT [JZ2016HGBZ1030]
Ask authors/readers for more resources
This paper presents a transformer winding fault diagnosis and prognosis method based on self-powered radio frequency identification (RFID) sensor tag. The proposed RFID sensor tag, which consists of RFID tag, power management circuit, MCU, and accelerometer, can acquire the vibration signals of transformer winding from the tank by accelerometer, and then wirelessly transmit the signals to the RFID reader. An inductive energy harvester utilizing surrounding magnetic field is optimized as power supply for the proposed sensor tag, including the MCU and the accelerometer. A customized ac-dc converter together with a low-dropout voltage regulator is designed to provide stable dc voltage for the proposed sensor tag. The RFID reader compiles the data from all the RFID sensor tags and then transmits them to the remote monitoring software which is developed to display the diagnosis results and alert messages. The experimental results show that the proposed energy harvester can provide 197-mu w power in a 50-Hz magnetic field, and the ac-dc converter is capable of providing 2.5-V dc voltage to power the circuitry. The measured maximum power consumption of the proposed sensor tag is 147 mu w. Furthermore, the achieved reliable communication distance is 13 m in the test scenario. The experimental results show that the proposed method is effective in term of the diagnosis and prognosis of transformer winding.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available