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自激式除尘器在线监测系统设计 被引量:2

Design of on-line monitoring system for self-excited deduster
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摘要 自激式除尘器内气液混合状态因运行环境密闭而难于实时观测,无法及时避免气液耦合过程中液面波动和捕集体间歇性激发引起的粉尘逃逸,造成除尘器运行参数液位、风速等的确定缺乏科学依据,除尘效率难以保证。针对上述问题,设计了一套自激式除尘器在线监测系统,该系统将除尘器压力信号所具有的阻力参数、液位参数、功率谱密度值、相对功率谱密度值及频率特征段5种特征参数作为气液两相流流型变化识别依据,对除尘器内部气液流动形态进行定量识别,并对其各项运行参数进行调节,实现了自激式除尘器内气液混合状态的在线监测。试验结果表明,在线监测系统能够对除尘器气液流动形态进行实时精准判别,整体识别率为95.6%。 Due to unobservable operating environment,gas-liquid mixing state of self-excited deduster can not be observed in real time,so it is difficult to avoid dust escape caused by fluctuation of liquid surface and intermittent excitation of traps in gas fluid coupling process,and determining of operating parameters(liquid level,wind speed,etc)of the deduster lacks of scientific basis,so it is difficult to guarantee removal efficiency of the deduster.In order to solve the above problems,an on-line monitoring system for self-excited deduster was designed.The system uses five characteristics parameters as the important identification basis of flow pattern to identify the gas-liquid flow pattern inside the deduster quantitatively,including resistance parameter,liquid level parameter,power spectral density value,relative power spectral density value and frequency characteristic segment of pressure signal.The system can adjust operating parameters of the deduster,and realizes on-line monitoring of gas-liquid mixing state in the selfexcited deduster.Test results show that the system can realize real-time and precise recognition for gasliquid flow pattern of deduster with 95.6% recognition rate.
出处 《工矿自动化》 北大核心 2017年第10期7-13,共7页 Journal Of Mine Automation
基金 国家自然科学基金资助项目(51404252) 中国博士后科学基金面上资助项目(2016M590522) 江苏省大学生创新训练计划项目(201610290084X) 中国矿业大学大学生创新创业基金资助大学生创新项目(DC201622)
关键词 自激式除尘器 在线监测 流型识别 气液流动模式 功率谱密度 阻力参数 液位参数 self-excited deduster on-line monitoring flow pattern recognition gas-liquid flow pattern power spectral density resistance parameter liquid level parameter
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