基于油液在线监测系统的智能诊断模块

Intelligent Diagnosis Module Based on Oil Online Monitoring System

目前广泛部署的油液在线监测系统在应用过程中,企业用户对于实时采集的大量油液理化指标数据缺乏有效的分析手段,从而导致数据所蕴含的信息无法及时得到挖掘和利用,无法有效指导润滑管理工作。为解决现场对于油液大量数据分析的滞后性,并增加企业润滑管理工作的时效性,提出以油液在线监测系统作为研究基础,以Python3作为开发语言,结合PyQt5等技术库进行软件模块构建,将机器学习和神经网络等算法模型进行封装开发,最终开发实现基于油液在线监测系统的智能诊断模块。结果表明:该模块能够在油液在线监测系统的基础上,新增提供对大量油液指标数据的智能化诊断服务,并对油液的健康状况进行分析。

In the application process of the widely deployed oil online monitoring system,enterprise users lack effective analysis methods for the real-time collection of a large amount of oil physical and chemical index data,resulting in the information contained in the data being unable to be excavated and utilized in a timely manner,and unable to effectively guide lubrication management work.In order to solve the lag in analyzing a large amount of oil data on site and increase the timeliness of enterprise lubrication management work,it is proposed to use the oil online monitoring system as the research foundation,use Python3 as the development language,and combine PyQt5 and other technical libraries to construct software modules.Machine learning and neural network algorithm models are encapsulated and developed,and ultimately an intelligent diagnosis module based on the oil online monitoring system is developed.The results indicate that this module can provide intelligent diagnostic services for a large amount of oil indicator data and analyze the health status of the oil based on the online oil monitoring system.