基于计算智能的机器状态监测系统

Vedant Bahel, Arunesh Mishra
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引用次数: 1

摘要

早在19世纪80年代左右,工业2.0标志着电力发明引起的社会变革。在当今时代,人工智能在定义工业4.0时代中扮演着至关重要的角色。在这项研究中,我们提出了基于计算智能的机器状态监测系统架构,用于确定工业机器的发展故障。目标是提高机器的效率并降低成本。该体系结构融合了机器敏感传感器、云计算、人工智能和数据库,开发了一个自主故障诊断系统。为了解释ci - mcm,我们将神经网络用于从液压系统获得的传感器数据。并与传统方法的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CI-MCMS: Computational Intelligence Based Machine Condition Monitoring System
Earlier around in year 1880’s, Industry 2.0 marked as change to the society caused by the invention of electricity. In today’s era, artificial intelligence plays a crucial role in defining the period of Industry 4.0. In this research study, we have presented Computational Intelligence based Machine Condition Monitoring system architecture for determination of developing faults in industrial machines. The goal is to increase efficiency of machines and reduce the cost. The architecture is fusion of machine sensitive sensors, cloud computing, artificial intelligence and databases, to develop an autonomous fault diagnostic system. To explain CI-MCMs, we have used neural networks on sensor data obtained from hydraulic system. The results obtained by neural network were compared with those obtained from traditional methods.
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