TY - JOUR
T1 - Sensor placement method based on bond graph models
AU - Ling, Mu
AU - Yuan, Haiwen
N1 - Publisher Copyright:
© 2016, Editorial Board of JBUAA. All right reserved.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - In order to study the influence of sensor placement on fault diagnosis, a new sensor placement method based on bond graph model was proposed. A group of virtual sensor test points were set in bond graph model, then the information of bond graph structure and causality constraints were used to deduce a set of analytical redundancy relations, namely system residuals. The relationships among residuals, faults and sensor placement configuration were analysed, and this sensor placement method can meet the requirements of system fault detection and isolation performance. The sensor placement configuration with the minimum number of sensors was chosen under the premise of maximizing system diagnosis performance. Finally, the synchronous generator was used as an example to establish the sensor placement algorithm. Residual analysis was used to derive the structure fault feature matrix and the sensor feature matrix. The proposed sensor placement optimization algorithm was verified by this example, and the experimental results show that the final sensor placement configuration can meet the requirements of maximum parameter fault detection and isolation performance.
AB - In order to study the influence of sensor placement on fault diagnosis, a new sensor placement method based on bond graph model was proposed. A group of virtual sensor test points were set in bond graph model, then the information of bond graph structure and causality constraints were used to deduce a set of analytical redundancy relations, namely system residuals. The relationships among residuals, faults and sensor placement configuration were analysed, and this sensor placement method can meet the requirements of system fault detection and isolation performance. The sensor placement configuration with the minimum number of sensors was chosen under the premise of maximizing system diagnosis performance. Finally, the synchronous generator was used as an example to establish the sensor placement algorithm. Residual analysis was used to derive the structure fault feature matrix and the sensor feature matrix. The proposed sensor placement optimization algorithm was verified by this example, and the experimental results show that the final sensor placement configuration can meet the requirements of maximum parameter fault detection and isolation performance.
KW - Bond graph
KW - Fault detection and isolation
KW - Parametric fault
KW - Sensor placement
KW - Synchronous generator
UR - https://www.scopus.com/pages/publications/84977647945
U2 - 10.13700/j.bh.1001-5965.2015.0400
DO - 10.13700/j.bh.1001-5965.2015.0400
M3 - 文章
AN - SCOPUS:84977647945
SN - 1001-5965
VL - 42
SP - 1142
EP - 1148
JO - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
JF - Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
IS - 6
ER -