物联网设备故障数据定位优化仿真研究

Lot Device Failure Data Location Optimization Simulation Research

对物联网环境下的不同设备故障数据进行检测定位,可提高物联网的可靠性、可修复性和安全性。由于物联网环境下存在大量硬件设备,在对设备进行故障检测时,无法统一故障阀值标准,导致传统方法无法用统一标准对差异化的设备进行故障检测,存在鲁棒性较差的问题。为解决上述问题,提出采用粗糙集算法的物联网环境下的不同设备故障数据挖掘定位方法。针对物联网设备运行数据连续性的特点,对采集到的初始数据进行离散化处理,针对冗余的数据特征属性进行约简,并依据相关原理构建故障数据挖掘定位的基本模型,采用模糊粗糙集算法对模型求解,实现了故障数据的有效分类,完成对设备具体故障元件的准确定位。实验结果表明,采用改进算法进行物联网环境下的不同设备故障数据挖掘定位,能够提高故障数据挖掘定位的准确性。

In this paper, we proposed a mining location method of different equipment failure data in Intemet of things. Firstly, aiming at the continuity characteristic of equipment operation data in Internet of things, discretization process of collected initial data was conducted, and feature attribute reduction was carried out with the redundancy data. Then we built a mining location basic model of failure data according to the correlation theory. We also used fuzzy rough set algorithm to solve the model. Finally, we achieved the effective classification of failure data and completed the accurate location of specific equipment fault component. The simulation results show that it can improve the mining location accuracy using the modified algorithm to make mining location to different equipment fault data in Internet of things.