NoC AI Chip Integration for Industrial IoT Fault Diagnosis and Notification System

This work has developed a wireless smart machine box for industrial IoT fault detection and notification with the advantage of the Internet of Thing (IoT). The edge artificial intelligence (Edge AI) has been used in this design to simplify the operation and automatically extract the features from the collected signals from the machinery for fault diagnosis, so the industries can carry out the fault detection even if the experts lack. With the help of it, the operational conditions of machinery are under control and the staff can fix or maintain the machines according to the classification of fault diagnosis. In addition, accuracy fault classification significantly improves the quality of mechanical maintenance. In this demonstration, we will show a powerful motor diagnosis platform integrated into PYNQ-ZU with a NoC AI chip, which supports fault diagnosis to multiple types of machinery simultaneously, wireless sensing diagnosis technology, and real-time fault diagnosis notification in an Industrial IoT (IIoT) environment.

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Publication Details

Published
2024-11-07
DOI
https://doi.org/10.1109/apccas62602.2024.10808976
Citations
2
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.66
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article

NoC AI Chip Integration for Industrial IoT Fault Diagnosis and Notification System

Yingyu Wang, Kun-Chih Chen, H.-M. Chen, Pengbo Shen et al.
2 citations
Fault Detection and Control Systems
0.66
article

NoC AI Chip Integration for Industrial IoT Fault Diagnosis and Notification System

Yingyu Wang, Kun-Chih Chen, H.-M. Chen, Pengbo Shen, Yen-Chen Yen
article en
2 citations

Abstract

This work has developed a wireless smart machine box for industrial IoT fault detection and notification with the advantage of the Internet of Thing (IoT). The edge artificial intelligence (Edge AI) has been used in this design to simplify the operation and automatically extract the features from the collected signals from the machinery for fault diagnosis, so the industries can carry out the fault detection even if the experts lack. With the help of it, the operational conditions of machinery are under control and the staff can fix or maintain the machines according to the classification of fault diagnosis. In addition, accuracy fault classification significantly improves the quality of mechanical maintenance. In this demonstration, we will show a powerful motor diagnosis platform integrated into PYNQ-ZU with a NoC AI chip, which supports fault diagnosis to multiple types of machinery simultaneously, wireless sensing diagnosis technology, and real-time fault diagnosis notification in an Industrial IoT (IIoT) environment.

National Yang Ming Chiao Tung University (TW)
Openalex Percentile: Top 28%
Fault Detection and Control Systems
0.66
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