TY - GEN
T1 - Prediction method of dedicated power supply for tank commander panoramic based on grey Markov model optimized by PSO
AU - Li, Yingshun
AU - Xiao, Yu
AU - Yi, Xiaojian
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Electrical equipment failure is a monotonous process with a sudden change in performance due to its own life cycle and a sudden change in state deterioration. Taking the dedicated power supply for tank commander panoramic of a certain type tank as the research object. The concepts of grey prediction model and Markov model are introduced. The Markov model is used to classify the residuals of the grey GM(1, 1) prediction model, and the state transition matrix is determined. The particle swarm optimization algorithm is used to find the whitening coefficient of the Markov model residual state, and the grey Markov model of particle swarm optimization is established.The dedicated power supply for tank commander panoramic measurement values (highest value, lowest value, median value) are predicted. The results show that the optimized prediction results are better than the original gray GM (1, 1) and gray Markov prediction methods. With the increase of the working time of the dedicated power supply of the dedicated power supply for tank commander panoramic, the trend of relative error occurrence state transition is more stable, the accuracy of prediction will be further improved, and the equipment can predict and maintain a certain value for maintenance work.
AB - Electrical equipment failure is a monotonous process with a sudden change in performance due to its own life cycle and a sudden change in state deterioration. Taking the dedicated power supply for tank commander panoramic of a certain type tank as the research object. The concepts of grey prediction model and Markov model are introduced. The Markov model is used to classify the residuals of the grey GM(1, 1) prediction model, and the state transition matrix is determined. The particle swarm optimization algorithm is used to find the whitening coefficient of the Markov model residual state, and the grey Markov model of particle swarm optimization is established.The dedicated power supply for tank commander panoramic measurement values (highest value, lowest value, median value) are predicted. The results show that the optimized prediction results are better than the original gray GM (1, 1) and gray Markov prediction methods. With the increase of the working time of the dedicated power supply of the dedicated power supply for tank commander panoramic, the trend of relative error occurrence state transition is more stable, the accuracy of prediction will be further improved, and the equipment can predict and maintain a certain value for maintenance work.
KW - Grey prediction model
KW - Markov prediction model
KW - PSO
KW - The dedicated power supply
UR - http://www.scopus.com/inward/record.url?scp=85091522856&partnerID=8YFLogxK
U2 - 10.1109/SDPC.2019.00043
DO - 10.1109/SDPC.2019.00043
M3 - Conference contribution
AN - SCOPUS:85091522856
T3 - Proceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019
SP - 197
EP - 203
BT - Proceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019
A2 - Li, Chuan
A2 - Zhang, Shaohui
A2 - Long, Jianyu
A2 - Cabrera, Diego
A2 - Ding, Ping
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019
Y2 - 15 August 2019 through 17 August 2019
ER -