Primary-Auxiliary Statistical Local Kernel Principal Component Analysis and Its Application to Incipient Fault Detection of Nonlinear Industrial Processes

Primary-Auxiliary Statistical Local Kernel Principal Component Analysis and Its Application to Incipient Fault Detection of Nonlinear Industrial Processes

Statistical local kernel principal component analysis (SLKPCA) has demonstrated its success in incipient fault detection of nonlinear industrial processes by incorporating the statistical local analysis (SLA) technology. However, the basic SLKPCA method builds the statistical model only based on the...

Full description

Bibliographic Details
Main Authors: Xiaogang Deng, Peipei Cai, Jiawei Deng, Yuping Cao, Zhihuan Song
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Incipient fault
fault detection
kernel principal component analysis
statistical local analysis
prior fault information
Online Access:https://ieeexplore.ieee.org/document/8815719/

Similar Items

Similar Items