TY - GEN
T1 - Equipment Working State Recognition Based on Broadband Spectral Features in Electromagnetic Noise Environment
AU - Zhang, Fan
AU - Ren, Dexin
AU - Zhang, Dongrong
AU - Xu, Hui
AU - Sang, Weihan
AU - Lu, Xiaozhu
AU - Su, Donglin
N1 - Publisher Copyright:
© 2023 International Union of Radio Science.
PY - 2023
Y1 - 2023
N2 - In the electromagnetic compatibility experiments and troubleshooting experiments, there are not only the electromagnetic signals emitted by the equipment under test (EUT) that need to be identified, but also a large number of electromagnetic signals emitted by other equipment in the tested electromagnetic environment, which poses a huge challenge to identify the working state of the EUTs. Inspired by basic emission waveform theory (BEWT), this paper extracts spectral features from the unintentional emission of the EUT when it worked alone, and then determines the working state of the EUT that we focus on by comparing similarity of the spectral features of the electromagnetic environment tested of the environment and EUT. The experiments show the effectiveness of the method. The correct rate of judging the working state of the equipment is 96.7%.
AB - In the electromagnetic compatibility experiments and troubleshooting experiments, there are not only the electromagnetic signals emitted by the equipment under test (EUT) that need to be identified, but also a large number of electromagnetic signals emitted by other equipment in the tested electromagnetic environment, which poses a huge challenge to identify the working state of the EUTs. Inspired by basic emission waveform theory (BEWT), this paper extracts spectral features from the unintentional emission of the EUT when it worked alone, and then determines the working state of the EUT that we focus on by comparing similarity of the spectral features of the electromagnetic environment tested of the environment and EUT. The experiments show the effectiveness of the method. The correct rate of judging the working state of the equipment is 96.7%.
UR - https://www.scopus.com/pages/publications/85175147686
U2 - 10.23919/URSIGASS57860.2023.10265499
DO - 10.23919/URSIGASS57860.2023.10265499
M3 - 会议稿件
AN - SCOPUS:85175147686
T3 - 2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
BT - 2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
Y2 - 19 August 2023 through 26 August 2023
ER -