Smart Fault Diagnostics using Convolutional Neural Network and Adam Stochastic Optimization

IF 1 4区 心理学 Q3 PSYCHOLOGY, CLINICAL
S. Shakya
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引用次数: 0

Abstract

Navigation, aviation and several other fields of engineering extensively make use of rotating machinery. The stability and safety of the equipment as well as the personnel are affected by this machinery. Use of deep learning as the basis of intelligent fault diagnosis schemes has and investigation of other relevant fault diagnosis schemes has a large scope for development. Thorough exploration needs to be performed in deep neural network (DNN) based schemes as shallow layer network structure based fault diagnosis schemes that are currently available has several considerable limitations. The nonlinear problems may be processed during intelligent fault diagnosis using deep convolutional neural network, which is a special structure DNN. The convolutional neural network (CNN) based scheme is emphasized in this paper. The principle and basic structure of the model are introduced. In rotating machinery, the fault diagnosis schemes using CNN are analyzed and summarized. Various CNN schemes, the potential mechanisms and performance diagnosis are analyzed. A novel smart fault diagnosis strategy is proposed while highlighting the potential aspects of existing schemes and reviewing the challenges.
基于卷积神经网络和Adam随机优化的智能故障诊断
航海、航空和其他几个工程领域广泛使用旋转机械。设备的稳定性和安全性以及人员的安全都受到这些机器的影响。利用深度学习作为智能故障诊断方案的基础,对其他相关故障诊断方案的研究具有很大的发展空间。由于现有的基于浅层网络结构的故障诊断方案存在一些相当大的局限性,因此基于深度神经网络(DNN)的故障诊断方案需要进行深入的探索。作为一种特殊结构的深度卷积神经网络,深度卷积神经网络可以处理智能故障诊断中的非线性问题。本文重点介绍了基于卷积神经网络(CNN)的方案。介绍了该模型的原理和基本结构。在旋转机械中,对基于CNN的故障诊断方案进行了分析和总结。分析了各种CNN方案、潜在机制和性能诊断。提出了一种新的智能故障诊断策略,强调了现有方案的潜在方面,并回顾了面临的挑战。
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来源期刊
CiteScore
2.90
自引率
0.00%
发文量
20
期刊介绍: This journal is devoted to the application of theory and research from social psychology toward the better understanding of human adaptation and adjustment, including both the alleviation of psychological problems and distress (e.g., psychopathology) and the enhancement of psychological well-being among the psychologically healthy. Topics of interest include (but are not limited to) traditionally defined psychopathology (e.g., depression), common emotional and behavioral problems in living (e.g., conflicts in close relationships), the enhancement of subjective well-being, and the processes of psychological change in everyday life (e.g., self-regulation) and professional settings (e.g., psychotherapy and counseling). Articles reporting the results of theory-driven empirical research are given priority, but theoretical articles, review articles, clinical case studies, and essays on professional issues are also welcome. Articles describing the development of new scales (personality or otherwise) or the revision of existing scales are not appropriate for this journal.
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