TY - GEN
T1 - Improved JPDA for fast fault detection
AU - Guo, Yangming
AU - Cai, Xiaobin
AU - Ma, Jiezhong
PY - 2011
Y1 - 2011
N2 - Regarding faults as dynamic modes which observe through the multi-sensors, with probabilistic data association based on multi-sensor, we obtain the fast fault detection results according to the association probability and threshold values. Joint Probabilistic Data Association (JPDA) algorithm is one of the effective ways for single-sensor multi-target tracking. Based on the analysis of JPDA algorithm, we improve the JPDA algorithm: first, we propose an approximation method for constructing the confirmation matrix through removing the small probability events using the right threshold values, and then, we present the mathematical division of the confirmation matrix according to the intersection area of the association gate of fault targets to be tracked; lastly, we compute the association probability of fault targets through attenuating the value of the public measurement. The simulation results show preliminarily that our improved JPDA algorithm saves the computing time greatly, and effectively meet the requirements of fast and real-time fault detection.
AB - Regarding faults as dynamic modes which observe through the multi-sensors, with probabilistic data association based on multi-sensor, we obtain the fast fault detection results according to the association probability and threshold values. Joint Probabilistic Data Association (JPDA) algorithm is one of the effective ways for single-sensor multi-target tracking. Based on the analysis of JPDA algorithm, we improve the JPDA algorithm: first, we propose an approximation method for constructing the confirmation matrix through removing the small probability events using the right threshold values, and then, we present the mathematical division of the confirmation matrix according to the intersection area of the association gate of fault targets to be tracked; lastly, we compute the association probability of fault targets through attenuating the value of the public measurement. The simulation results show preliminarily that our improved JPDA algorithm saves the computing time greatly, and effectively meet the requirements of fast and real-time fault detection.
KW - Association Probability
KW - Confirmation Matrix
KW - Fault Detection
KW - JOINT Probabilistic Data Association (JPDA)
UR - https://www.scopus.com/pages/publications/80053075465
M3 - 会议稿件
AN - SCOPUS:80053075465
SN - 9789881725592
T3 - Proceedings of the 30th Chinese Control Conference, CCC 2011
SP - 4167
EP - 4169
BT - Proceedings of the 30th Chinese Control Conference, CCC 2011
T2 - 30th Chinese Control Conference, CCC 2011
Y2 - 22 July 2011 through 24 July 2011
ER -