TY - GEN
T1 - Research of fault diagnosis method for a electric component based on immune neural network and Pspice
AU - Huang, Ji Chuan
AU - Zhou, De Yun
AU - Jing, Xian Yong
AU - Hou, Man Yi
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/20
Y1 - 2017/1/20
N2 - Fault diagnosis systems based on computational intelligence have prominent advantages such as rapid reasoning, accurate judgment and so on. A certain type of electronic component has complex structure and mass elements, so it is difficult to determine fault points. Aimed at the problem, a intelligent fault diagnosis method based on immune neural network and Pspice is researched. Fault knowledge acquisition and learning is the key to establish reasoning machine, circuit simulation of the component is carried out based on Pspice, then fault knowledge is obtained by setting elements in the circuit with fault conditions. According to generated rules, training samples for reasoning machine can be obtained based on fault knowledge. Based on immune algorithm and training samples, accuracy reasoning machine for fault diagnosis is established. Simulation results based on Matlab prove the effectiveness of the proposed method.
AB - Fault diagnosis systems based on computational intelligence have prominent advantages such as rapid reasoning, accurate judgment and so on. A certain type of electronic component has complex structure and mass elements, so it is difficult to determine fault points. Aimed at the problem, a intelligent fault diagnosis method based on immune neural network and Pspice is researched. Fault knowledge acquisition and learning is the key to establish reasoning machine, circuit simulation of the component is carried out based on Pspice, then fault knowledge is obtained by setting elements in the circuit with fault conditions. According to generated rules, training samples for reasoning machine can be obtained based on fault knowledge. Based on immune algorithm and training samples, accuracy reasoning machine for fault diagnosis is established. Simulation results based on Matlab prove the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=85015210634&partnerID=8YFLogxK
U2 - 10.1109/CGNCC.2016.7828788
DO - 10.1109/CGNCC.2016.7828788
M3 - 会议稿件
AN - SCOPUS:85015210634
T3 - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
SP - 227
EP - 231
BT - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Y2 - 12 August 2016 through 14 August 2016
ER -