TY - GEN
T1 - Extracting relevant features for diagnosing machine tool faults in cloud architecture
AU - Li, Yu Yung
AU - Yang, Haw Ching
AU - Tieng, Hao
AU - Cheng, Fan Tien
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/7
Y1 - 2015/10/7
N2 - This paper presents a cloud diagnosis architecture to support diagnosis of different machine tool faults with similar abnormal events. Lacking the corresponding features of failure historical data, similar abnormal events are insufficient to be used for identifying the root causes of faults. On the basis of a novel event-oriented process monitoring and backtracking (EOPMB) method and the clustering non-dominated sorting genetic algorithm (CNSGA), this paper proposes a cloud diagnosis architecture for identifying failure causes by extracting relevant features of various faults from different machine tools. Results show that the proposed architecture can assist users in improving diagnosis performance.
AB - This paper presents a cloud diagnosis architecture to support diagnosis of different machine tool faults with similar abnormal events. Lacking the corresponding features of failure historical data, similar abnormal events are insufficient to be used for identifying the root causes of faults. On the basis of a novel event-oriented process monitoring and backtracking (EOPMB) method and the clustering non-dominated sorting genetic algorithm (CNSGA), this paper proposes a cloud diagnosis architecture for identifying failure causes by extracting relevant features of various faults from different machine tools. Results show that the proposed architecture can assist users in improving diagnosis performance.
UR - http://www.scopus.com/inward/record.url?scp=84952777871&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84952777871&partnerID=8YFLogxK
U2 - 10.1109/CoASE.2015.7294299
DO - 10.1109/CoASE.2015.7294299
M3 - Conference contribution
AN - SCOPUS:84952777871
T3 - IEEE International Conference on Automation Science and Engineering
SP - 1434
EP - 1439
BT - 2015 IEEE Conference on Automation Science and Engineering
PB - IEEE Computer Society
T2 - 11th IEEE International Conference on Automation Science and Engineering, CASE 2015
Y2 - 24 August 2015 through 28 August 2015
ER -