Monitoring the status of the facilities and detecting any faults are considered an important technology in a smart factory. Although the faults of machine can be analyzed in real time using collected data, it requires...
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Monitoring the status of the facilities and detecting any faults are considered an important technology in a smart factory. Although the faults of machine can be analyzed in real time using collected data, it requires a large amount of computing resources to handle the massive data. A cloud server can be used to analyze the collected data, but it is more efficient to adopt the edge computing concept that employs edge devices located close to the facilities. Edge devices can improve data processing and analysis speed and reduce network costs. In this paper, an edge device capable of collecting, processing, storing and analyzing data is constructed by using a single-board computer and a sensor. And, a faultdetection model for machine is developed based on the long short-term memory (LSTM) recurrent neural networks. The proposed system called LiReD was implemented for an industrial robot manipulator and the LSTM-based faultdetection model showed the best performance among six faultdetection models.
In this paper the telemetry data of Satellite TX-I are analyzed in order to have a better understanding of the satellite operating status,and to lay the foundation for faultdetection *** the high dimensional data,the...
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ISBN:
(纸本)9781479946983
In this paper the telemetry data of Satellite TX-I are analyzed in order to have a better understanding of the satellite operating status,and to lay the foundation for faultdetection *** the high dimensional data,the locally linear embedding (LLE),a kind of manifold learning schemes,is applied to perform dimensionality reduction and feature *** the data-driven fault detection can be effectively implemented by means of the statistic indexes T 2 and *** results presented in the paper demonstrate that not only the data processing,like feature extraction,but the faultdetection scheme is effective.
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