An adaptive inspection-method for industrial welding seam based on PCA algorithm and the modification of BP ANN
Yi-Fei Pu; Ke Liao; Ji-Liu Zhou; Ni Zhang
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Volume 6, Issue , 26-29 Aug. 2004 Page(s): 3412 - 3416 vol.6
Digital Object Identifier  
Summary: The paper adopts an adaptive momentum adjustments algorithm to standardize various lighting parameters, so as to improve its adaptive capacity for the environment. By PCA algorithm, the original data space is compressed into an eigenvalue pattern space, then the data will gather in a lesser effective eigenvalue space. Using the modification of BP ANN to classify the data pattern space, it can realize the system's self-teaching function, and improve the correct-inspection rate and real-time performance as well. This algorithm has been widely applied in the real-time inspection of industrial welding seam. It has strong ability of adaption and self-teaching, higher inspection rate and real-time performance.

» View citation and abstract

Log in by entering your IEEE Web Account Username and Password.

IEEE Communications Society members: If you subscribe to the IEEE Electronic Periodicals Package or IEEE Electronic Periodicals Package Plus, you must access your subscription at www.comsoc.org.

Check with your librarian, information professional, or system manager to determine if you need to log in. Please complete the online Technical Support Form if you need assistance.

Select the Purchase History link to access the document. You will have 5 Days after purchase to access the Full Text PDF. Please complete the online Technical Support Form if you need assistance.

• Search and access Abstract records free of charge
• Register for table of contents alerts
• Purchase Full Text PDF documents

» Learn more about subscription options or how to become an IEEE Member.