The Application of Wireless Sensor Networks in Machinery Fault Diagnosis

Q1 Social Sciences
Baolu Gao, S. Xiong, Zhanwei Xu
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引用次数: 7

Abstract

Wireless sensor network is a thriving information collecting and processing technology, which is widely used in military field, industry and environmental monitoring, etc. In a wireless sensor network which is made up of tens of thousands battery-powered sensor nodes, data fusion technology can be used to reduce communication traffic in order to save energy. With respect to large mechanical equipment, traditional wired sensors are commonly used for fault detection and diagnosis. There will be no wiring problem if wireless sensor networks are used, which is favorable to detect potential problems in mechanical equipment without affecting normal production of enterprises. In this paper, the application of wireless sensor networks in machinery fault diagnosis is studied, a data fusion model for machinery fault diagnosis in wireless sensor networks and PCA neural data fusion algorithm are proposed, and the effectiveness of the method is demonstrated in an experiment.
无线传感器网络在机械故障诊断中的应用
无线传感器网络是一种蓬勃发展的信息采集和处理技术,广泛应用于军事、工业和环境监测等领域。在由数万个电池供电的传感器节点组成的无线传感器网络中,可以使用数据融合技术来减少通信流量以节省能源。对于大型机械设备,通常采用传统的有线传感器进行故障检测和诊断。如果使用无线传感器网络,就不会出现布线问题,有利于在不影响企业正常生产的情况下发现机械设备的潜在问题。本文研究了无线传感器网络在机械故障诊断中的应用,提出了无线传感器网络中机械故障诊断的数据融合模型和PCA神经数据融合算法,并通过实验验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.00
自引率
0.00%
发文量
10
审稿时长
8 weeks
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