Title: The design of enhanced online condition monitoring systems for turning processes
Authors: Abdulrahman Al-Azmi, Amin Al-Habaibeh
Addresses: Advanced Design and Manufacturing Engineering Centre, School of Architecture, Design and the Built Environment, Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, UK. ' Advanced Design and Manufacturing Engineering Centre, School of Architecture, Design and the Built Environment, Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, UK
Abstract: The increasing requirements of high quality and low cost of products have created an urgent need to implement new technologies in current automated manufacturing environments. Condition monitoring systems of manufacturing processes have been recognised in recent years as one of the essential technologies that provide the competitive advantage in many manufacturing environments. This paper aims to developing an effective sensor fusion model for turning processes for the detection of tool wear. Multi-sensors combined with a novelty detection algorithm are used to detect tool wear and provide diagnostic and prognostic information. A novel approach using dynamic threshold is utilised to improve the accuracy of the novelty detection system. The results found indicate that the suggested approach provides a responsive and effective solution in monitoring tool wear in turning.
Keywords: condition monitoring; turning; tool wear; vibration; acoustic emission; strain; signal processing; artificial intelligence; online monitoring; automated manufacturing; sensor fusion modelling; wear monitoring.
International Journal of Design Engineering, 2008 Vol.1 No.2, pp.208 - 222
Published online: 07 Nov 2008 *
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