| Signal feature extraction for sewing analysis using non-linear tecniques (2003) | |||||||||||
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| Signal Feature Extraction for Sewing Analysis using Non Linear Techniques CARVALHO Member IEEE FERREIRA ROCHA and MONTEIRO Member IEEE DET Campus Azur Guimar Portugal mail helder det uminho amrocha det uminho DEI Campus Azur Guimar Portugal mail pedro celestino sapo monteiro dei uminho Abstract This paper describes the measurement process variable industrial sewing machines using piezoelectric sensing system and non linear filtering and processing techniques The objective obtain measure the needle penetration and withdrawal forces fabric which can used detect faulty processing conditions causing second rate quality products Aimed for future real time applications currently the measurement process has been optimised for laboratory use provides the means for experimentation leading the development further processing techniques able detect fault conditions automatically completely innovative industrial application The signal acquired piezoelectric sensor introduced the needle support bar With this set the sensor provides not only the forces related needle fabric interaction but also other undesired components that are reduced with specifically developed techniques This paper presents the advantages and drawbacks the measurement set and describes the optimization the complex processing techniques used extract the relevant information from the signals Index Terms sewing monitoring sensors filtering neural processing Related stitch formation Thread tensions and thread consumption d. This paper describes the measurement of a proc-ess variable in industrial sewing machines using a piezoelectric sensing system and non-linear filtering and processing tech-niques. The objective is to obtain a measure of the needle pene-tration and withdrawal forces in a fabric, which can be used to detect faulty processing conditions causing second-rate quality products. Aimed for future real-time applications, currently the measurement process has been optimised for laboratory use. It provides the means for experimentation leading to the development of further processing techniques able to detect fault conditions automatically, a completely innovative indus-trial application. The signal is acquired by a piezoelectric sensor introduced in the needle support bar. With this set-up, the sensor provides not only the forces related to needle-fabric interaction, but also other, undesired components, that are reduced with specifi-cally developed techniques. This paper presents the advantages and drawbacks of the measurement set-up and describes the optimization of the complex processing techniques used to ex-tract the relevant information from the signals.. Fundação para a Ciência e Tecnologia - POSI/SRI/38944/2001. | |||||||||||
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