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دسته بندی:
یادگیری عمیق - deep learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Deep learning and its applications to machine health monitoring
ترجمه فارسی عنوان مقاله:
یادگیری عمیق و کاربردهای آن برای نظارت بر سلامت دستگاه
منبع:
Sciencedirect - Elsevier - Mechanical Systems and Signal Processing, 115 (2019) 213-237: doi:10:1016/j:ymssp:2018:05:050
نویسنده:
Rui Zhao a, Ruqiang Yan a,⇑, Zhenghua Chen b, Kezhi Mao b, Peng Wang c, Robert X. Gao c
چکیده انگلیسی:
Since 2006, deep learning (DL) has become a rapidly growing research direction, redefining
state-of-the-art performances in a wide range of areas such as object recognition, image
segmentation, speech recognition and machine translation. In modern manufacturing systems,
data-driven machine health monitoring is gaining in popularity due to the widespread
deployment of low-cost sensors and their connection to the Internet. Meanwhile,
deep learning provides useful tools for processing and analyzing these big machinery data.
The main purpose of this paper is to review and summarize the emerging research work of
deep learning on machine health monitoring. After the brief introduction of deep learning
techniques, the applications of deep learning in machine health monitoring systems are
reviewed mainly from the following aspects: Auto-encoder (AE) and its variants,
Restricted Boltzmann Machines and its variants including Deep Belief Network (DBN)
and Deep Boltzmann Machines (DBM), Convolutional Neural Networks (CNN) and
Recurrent Neural Networks (RNN). In addition, an experimental study on the performances
of these approaches has been conducted, in which the data and code have been online.
Finally, some new trends of DL-based machine health monitoring methods are discussed
Keywords: Deep learning | Machine health monitoring | Big data
قیمت: رایگان
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