摘要
本文旨在研究和应用大数据技术设计热轧辊道电机监测模型,以提高热轧辊道电机的运行效率和可靠性。通过借助大数据处理平台和相关算法提取有用的特征和模式,以及对热轧辊道电机数据的分析,并使用数据挖掘和机器学习算法来设计预测模型,设计了基于大数据技术的热轧辊道电机监测模型,为热轧板带企业提供了一个可靠的监测和预测工具。
In order to improve their operational efficiency and reliability,big data technology is researched and applied to design a monitoring model for hot rolling roller table motors.By utilizing big data processing platforms and related algorithms to extract useful features and patterns,as well as analyzing hot rolling roller motor data,and using data mining and machine learning algorithms to design prediction models,a monitoring model for hot rolling roller table motors based on big data technology has been designed,and a reliable monitoring and prediction tool for hot rolling plate and strip production enterprises is provided.
作者
赵庆浩
荆丰伟
刘恒文
Zhao Qinghao;Jing Fengwei;Liu Hengwen(National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing,University of Science and Technology Beijing,Beijing 100083)
出处
《中国仪器仪表》
2024年第1期35-39,共5页
China Instrumentation
基金
国家重点研发计划重点专项(2022YFB3304002-02)
广西重点研发计划(桂科AB21196025)。
关键词
大数据
状态监测
机器学习
智慧运维
Big data
Condition monitoring
Machine learning
Intelligent maintenance and operation
