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We propose a new approach, namely Optimized Embedded Signature Monitoring (OESM) to perform on-line control-flow fault detection. The underlined advantage of this approach is the ability to perform a profiling algorithm that analyses the control-flow graph of user program in order to optimize the number of checkpoints (i.e., signatures) to be inserted along with the application code. By optimization,...
This paper focuses on one stage of a research project concerning online surveillance of the knitting process, which intends to detect faults as soon as possible. The objective of the paper is focused on the pattern recognition stage, i.e, distinguishing faults. For that purpose, discriminant analysis is proposed as the approach to be explored. The general problem is discussed, followed by the prototype...
This paper reports the recent developments in the pursuit to correctly locate, identify and distinguish faults during production of weft knitted fabrics. For this purpose a major textile parameter - yarn input tension (YIT) - is analyzed by means of signal processing techniques. An overview of the entire process of gathering the information and fault detection is presented. For the purpose of distinguishing...
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