TY - GEN
T1 - Automatic baseline-sample-selection scheme for baseline predictive maintenance
AU - Chen, Chun Fang
AU - Hsieh, Yao Sheng
AU - Cheng, Fan Tien
AU - Huang, Hsien Cheng
AU - Wang, Saint Chi
PY - 2013/12/1
Y1 - 2013/12/1
N2 - A virtual-metrology-based (VM-based) baseline-predictive-maintenance (BPM) scheme was proposed by the authors recently. By applying the BPM scheme, fault diagnosis and prognosis can be accomplished and the requirement of massive historical failure data can also be released. The accuracy of the BPM scheme highly depends on the correctness of the baseline models in the BPM scheme. The samples of creating the target-device (TD) baseline model consist of the concise and healthy (C&H) historical samples and the fresh samples just after maintenance. Originally, each one of the C&H samples was checked manually to ensure that the sample was generated under healthy status and its data quality is good. However, this health-&-quality check process is so tedious and may also neglect deleting contradictory samples, which may deteriorate the BPM results and prohibit the usage of the BPM scheme. The purpose of this paper is to develop an automatic baseline-sample-selection (ABSS) scheme for selecting the C&H samples and deleting the contradictory samples automatically.
AB - A virtual-metrology-based (VM-based) baseline-predictive-maintenance (BPM) scheme was proposed by the authors recently. By applying the BPM scheme, fault diagnosis and prognosis can be accomplished and the requirement of massive historical failure data can also be released. The accuracy of the BPM scheme highly depends on the correctness of the baseline models in the BPM scheme. The samples of creating the target-device (TD) baseline model consist of the concise and healthy (C&H) historical samples and the fresh samples just after maintenance. Originally, each one of the C&H samples was checked manually to ensure that the sample was generated under healthy status and its data quality is good. However, this health-&-quality check process is so tedious and may also neglect deleting contradictory samples, which may deteriorate the BPM results and prohibit the usage of the BPM scheme. The purpose of this paper is to develop an automatic baseline-sample-selection (ABSS) scheme for selecting the C&H samples and deleting the contradictory samples automatically.
UR - http://www.scopus.com/inward/record.url?scp=84891534648&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891534648&partnerID=8YFLogxK
U2 - 10.1109/CoASE.2013.6653934
DO - 10.1109/CoASE.2013.6653934
M3 - Conference contribution
AN - SCOPUS:84891534648
SN - 9781479915156
T3 - IEEE International Conference on Automation Science and Engineering
SP - 183
EP - 188
BT - 2013 IEEE International Conference on Automation Science and Engineering, CASE 2013
T2 - 2013 IEEE International Conference on Automation Science and Engineering, CASE 2013
Y2 - 17 August 2013 through 20 August 2013
ER -