Electromagnetic Noise Classification and Novelty Detection Using Machine Learning for Frequency Sharing among Various Communications in the Manufacturing Field

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  • 製造現場における多用途周波数共用のための電磁ノイズの機械学習による分類と新規性検出

Abstract

The time waveform and spectral pattern of electromagnetic noise generated from industrial equipment in the manufacturing site differ depending on the equipment that is the source. Therefore, there is a high possibility that unknown patterns will occur when classifying by machine learning. Novelty detection can be used to detect unknown patterns. However, limited computational resources on the shop floor limit the parallel execution of electromagnetic noise classification and novelty detection. In this paper, we propose a method to detect unknown noise from posterior probability values obtained during classification, and demonstrate it using actual measurement data.

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