Title :
On-line monitoring and diagnosis of tapping process using Neuro Fuzzy Systems
Author :
Liu, Tien-I ; Lee, Junyi ; Singh Gill, Gurinder
Author_Institution :
Coll. of Eng. & Comput. Sci., California State Univ., Sacramento, CA
Abstract :
Tapping has been widely used throughout industry, and its proper operation is paramount in ensuring product quality. Therefore, monitoring and diagnosis is needed to detect the tapping process conditions. In this work, a combination of ten indices of the tapping process was extracted from tapping torque, thrust force, and lateral forces. The Sequential Forward Search (SFS) algorithm has been used to select the best feature sets. Adaptive Neuro Fuzzy Inference Systems (ANFIS) were used for the monitoring and diagnosis of tapping process. A 3times2 ANFIS structure can distinguish normal tapping process from abnormal tapping process with 100% reliability. The tapping process conditions can be further classified into five categories with over 95% success rate using a 10times2 ANFIS structure. In simple words, monitoring and diagnosis of tapping process can be carried out successfully using SFS and ANFIS.
Keywords :
computerised monitoring; cutting; fuzzy neural nets; inference mechanisms; production engineering computing; adaptive neuro fuzzy inference systems; lateral forces; online diagnosis; online monitoring; sequential forward search algorithm; tapping process conditions; tapping torque; thrust force; Computerized monitoring; Condition monitoring; Feedforward neural networks; Feeds; Fuzzy sets; Fuzzy systems; Multi-layer neural network; Neural networks; Torque; Yarn;
Conference_Titel :
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1717-9
Electronic_ISBN :
978-1-4244-1718-6
DOI :
10.1109/ICIEA.2008.4582469
