Mechanical equipment fault diagnosis based on wireless sensor network data fusion technology

Fang Hao, Qiuping Yang, Anjali Sharma, V. Balyan
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Abstract

Abstract To save network energy consumption and prolong network life cycle in complex mechanical fault diagnosis, a research method of data fusion routing protocol algorithm based on wireless sensor network (WSN) is proposed. The specific content of the method is as follows: First, the low-energy adaptive clustering hierarchy algorithm is analyzed and discussed. On this basis, the prim route fusion algorithm is proposed to realize the effective utilization of energy and prolong the life of the network. Then, the WSN is abstracted as an undirected graph. From the perspective of saving the energy of the whole network, several current algorithms for building fusion trees are compared. The experimental results show that the prim algorithm consumes energy only after 700 rounds of clustering, while the leach clustering algorithm consumes energy only after 500 rounds. This shows that applying the prim algorithm can reduce the energy consumption of the whole network and prolong the life cycle of the network. However, the algorithm is carried out on the premise of uniform distribution of nodes, and there is a certain gap with the specific application of WSN in mechanical fault diagnosis. In the comparison of node energy consumption, it is found that compared with using the shortest path tree, using the central point of graph algorithm can greatly save the energy consumption of the node and has better performance. Practice has proved that this method can effectively remove redundant data information and solve the problem of unreliable data collected by a single sensor node. It is more suitable for the specific application of WSN in mechanical fault diagnosis.
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基于无线传感器网络数据融合技术的机械设备故障诊断
摘要为了在复杂机械故障诊断中节省网络能耗,延长网络生命周期,提出了一种基于无线传感器网络(WSN)的数据融合路由协议算法研究方法。该方法的具体内容如下:首先,对低能量自适应聚类层次算法进行了分析和讨论。在此基础上,提出prim路由融合算法,实现能量的有效利用,延长网络寿命。然后,将WSN抽象为无向图。从节约全网能量的角度出发,对目前几种构建融合树的算法进行了比较。实验结果表明,prim算法在700轮聚类后才消耗能量,而leach聚类算法在500轮聚类后才消耗能量。这表明,采用prim算法可以降低整个网络的能耗,延长网络的生命周期。但是,该算法是在节点均匀分布的前提下进行的,与WSN在机械故障诊断中的具体应用存在一定的差距。在节点能耗比较中发现,与使用最短路径树相比,使用图中心点算法可以大大节省节点的能耗,具有更好的性能。实践证明,该方法可以有效地去除冗余数据信息,解决单个传感器节点采集数据不可靠的问题。它更适合于WSN在机械故障诊断中的具体应用。
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