cbmLAD-using Logical Analysis of Data in Condition Based Maintenance
Condition Based Maintenance (CBM) software, called cbmLAD, under development at Ecole Polytechnique de Montreal is presented in this paper. The backbone of the software is a supervised learning data mining approach called Logical Analysis of Data (LAD). LAD possesses distinctive advantages that are useful in Condition Based Maintenance (CBM), namely its independence from statistical processes and its ability to generate interpretable patterns. The latter property serves to reinforce the theoretical knowledge and uncover new knowledge about a certain diagnostic problem in CBM. cbmLAD has been tested in two maintenance scenarios. Expert knowledge was elicited in each scenario to train the diagnostic decision models obtained through cbmLAD. This paper describes the methodology applied in each scenario and highlights the advantages of using LAD for fault diagnosis.
Logical Analysis of Data Condition Based Maintenance Data Mining Expert Elicitatioin
Mohamad-Ali Mortada Soumaya Yacout
Department of Mathematics and Industrial Engineering Ecole Polytechnique de Montreal Montreal,Canada
国际会议
上海
英文
30-34
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）