Fault diagnosis using an enhanced relevance vector machine (RVM) for partially diagnosable multistation assembly processes

IEEE Transactions on Automation Science and Engineering

Volumn 10, Issue 1, 2013, Pages 124-136

  Bastani, Kaveh ^a   Kong, Zhenyu ^a   Huang, Wenzhen ^b   Huo, Xiaoming ^c   Zhou, Yingqing ^d  

^a Oklahoma State University   (United States)

^b Department of Electrical and Computer Engineering   (United States)

^c Georgia Institute of Technology   (United States)

^d Dimensional Control Systems Inc   (United States)

Author keywords

Enhanced relevance vector machine (RVM); fault diagnosis; multistation assembly processes; partially diagnosable; sparse solution

Indexed keywords

DIMENSIONAL INTEGRITY; DIMENSIONAL MEASUREMENTS; DIMENSIONAL VARIATIONS; LINEAR RELATIONSHIPS; MULTISTATION ASSEMBLY PROCESS; PARTIALLY DIAGNOSABLE; PROCESS ERRORS; PROCESS FAULTS; RELEVANCE VECTOR MACHINE; ROOT CAUSE; SIGNIFICANT IMPACTS; SPARSE SOLUTIONS; STATE SPACE MODEL;

FAILURE ANALYSIS; STATE SPACE METHODS;

ERRORS;

EID: 84871773196     PISSN: 15455955     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASE.2012.2214383     Document Type: Article

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