摘要
托辊是带式输送机重要运转部件,主要用于支撑输送带和承载及减小运行阻力。对异常托辊进行监测,早期发现故障前兆报警,对安全、高效生产具有重大意义。基于大数据技术,采用逻辑回归算法模型,对托辊故障进行前兆监测、准确识别和报警,有效预防带式输送机故障发生,在减少故障停机时间、降低设备运行成本、保障生产安全等方面具有重要的作用。
The rollers are the important parts of the belt conveyor,which mainly supporting the conveyor belt,carrying and reducing the running resistance.It is very important for safe and efficient production to monitor the abnormity of roller and find failure precursors and give alarms earlier.Based on big data technology,used a logistic regression algorithm model,precursory monitoring,accurate identification and alarming for the fault of roller.The failures of rollers will be effectively prevent.In reducing downtime,reducing equipment operating costs and ensuring production safety,it has important function.
作者
刘芬
Liu Fen(Chongqing Research Institute,China Coal Technology and Engineering Group,Chongqing 400039,China;State Key Laboratory of Gas Disaster Detecting,Preventing and Emergency Controlling,Chongqing 400037,China)
出处
《煤矿机械》
北大核心
2020年第8期177-179,共3页
Coal Mine Machinery
基金
国家重点研发计划资助项目(2018YFC0808300)。
关键词
托辊
大数据技术
故障诊断
回归算法
音频
roller
big data technology
fault diagnosis
regress algorithm
audio
