Abstract
In this paper a Fault Detection and Isolation (FDI) procedure is applied for the defects detection and analysis of electrical motors at the end of production line in hood factories. The objective consists of developing a fast and robust methodology to detect defective motors and to identify defects for quality analysis on production line. Using a signal based FDI procedure, an end of a line bench system is designed, which is able to analyze the defects of produced motors. Multi-Scale Principal Component Analysis (MSPCA) is used for defect detection and a Kernel Density Estimation (KDE) algorithm is used for fault isolation on the PCA residual contributions. Also a method to choose the WT levels is adopted. MSPCA with KDE thresholding advantage is demonstrated by experimentations on test bench, using vibration measurements. Experiments show that the stochastic method used to compute thresholds on PCA residuals is robust and at the same time accurate.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
