WeaveSense: IoT Infrastructure for Rapier Loom Condition Monitoring and Analysis

International Journal of Electrical and Electronics Engineering

© 2023 by SSRG - IJEEE Journal

Volume 10 Issue 12

Year of Publication : 2023

Authors : Ajit S. Gundale, Vaibhav M. Meshram

10.14445/23488379/IJEEE-V10I12P104

How to Cite?

Ajit S. Gundale, Vaibhav M. Meshram, "WeaveSense: IoT Infrastructure for Rapier Loom Condition Monitoring and Analysis," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 12, pp. 27-36, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I12P104

Abstract:

Various machines and equipment are involved at different stages of the textile manufacturing process. The rapier looms are used to produce high-quality fabrics and other traditional textiles. The rapier looms are exposed to mechanical and frequently occurring electronic problems, which disrupts their operation and production efficiency. The condition monitoring of the rapier loom is helpful to ensure optimal performance. The IoT infrastructure for condition monitoring is designed and implemented at the industrial level, and ground truth data is captured. Weavesense targets temporal analysis of Service-Oriented Architecture (SOA) based on an IoT framework implemented for condition monitoringof rapier loom. The study of captured streaming data involves pre-processing, feature extraction and behaviour pattern recognition. The supervised machine learning approach permits correlating extracted features and captured data. The application scenario of the rapier loom and sequence of observations clearly show the consequences on the performance of the rapier loom.

Keywords:

Rapier loom, Augmented framework, Filtering, Feature extraction, Data validation, Supervised learning, Correlation.

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