Abstract
Manufacturing system is becoming larger and more complicated. Global manufacturing chains have become common in the new millennium. Internet and intranet integrate the advanced manufacturing system. To perform remote monitoring and diagnosis in such chains and systems, real-time data compression has become a core factor in the efficient and effective exchange of information exchange via computer networks. This paper presents a new technique for compressing data using a kernel-based method. Overcoming the drawbacks of support vector techniques — that is, fast decompression but slow compression — the new method exhibits high speed in both phases. In addition, the new method can also be applied for pattern classification. Based on strain signal example tests derived from sheet metal stamping operations, the new method is very effective. The proposed technology has enormous potential in the application of advanced manufacturing system monitoring and control through internet or intranet.
Sign-in/Register to access full text options 
Free) 
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 call
