KPCA-Based Multisensor Data Fusion for Machine Fault Diagnosis
(0) This paper examines the application of KPCA (kernel principal component analysis) to multisensor data fusion for machine fault diagnosis. After a concise review of KPCA is given. The proposed multisensor data fusion method based on KPCA is presented. The effect of the KPCA-based multisensor data fusion method for machine fault diagnosis is tested in combination with DT CWT-based HMT (dual tree complex wavelet transform-based hidden Markov tree) model for a gearbox fault diagnosis. The efficiency of KPCA-based multisensor data fusion technique is illustrated by case study.
KPCA HMT multisensor data fusion machine fault diagnosis
GUI Lin WU Xiaoyue
School of Information System and Management, National University of Defence Technology, China
国际会议
The First International Conference on Maintenance Engineering(首届维修工程国际学术会议)
成都
英文
473-478
2006-10-15（万方平台首次上网日期，不代表论文的发表时间）