基于信息融合的球磨机料位分级与检测研究

陈蔚;贾民平;王恒

振动与冲击 ›› 2010, Vol. 29 ›› Issue (6) : 142-143.

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PDF(1123 KB)
振动与冲击 ›› 2010, Vol. 29 ›› Issue (6) : 142-143.
论文

基于信息融合的球磨机料位分级与检测研究


  • 陈蔚; 贾民平; 王恒
作者信息 +

A study on the mill fill level grading theory and soft-sensing of mill fill level based on information fusion

  • Chen Wei Jia Minping Wang Heng
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摘要



火力发电厂锅炉制粉系统的主要设备之一—球磨机的运行状况优劣在一定程度上决定了电厂的经济运行好坏。分析了球磨机磨筒内料位的各种影响因素及影响特性,提出了料位分级理论,将料位分为非经济区、优化区与危险区三个区域,解决了数据融合测料位时无法获得大量料位样本的问题。在此基础上,提出了基于BP人工神经网络测量球磨机料位的软测量方法,对球磨机现场数据分析进一步验证了所提方法的有效性。该方法确定了球磨机最佳运行工况的范围,为实现球磨机系统的优化运行和自动控制奠定了基础。

Abstract

Abstract:A ball mill is one of the most often used milling equipments in power plants. The efficiency of ball mill operation is an important aspect to improve economization of the plants. Factors those effect the mill fill level and their relationships are analyzed. Mill fill level grading theory is proposed which classifies the coal amount into three areas: uneconomical area, optimal area and dangerous area. The difficulty to obtain plenty of fill level samples is solved so that the data fusion method can be properly used to measure the fill level. A soft-sensing method of mill fill level based on BP neural network is proposed and is validity by analyzing the data from the operation field. This method gives the optimal operation range for ball mill and forms the basis for the optimum operation and automatic control of the ball mill system.

关键词

球磨机 / 料位检测 / 料位分级理论 / BP神经网络

Key words

ball mill / measurement of mill fill level / fill level grading theory / BP neural network

引用本文

导出引用
陈蔚;贾民平;王恒. 基于信息融合的球磨机料位分级与检测研究 [J]. 振动与冲击, 2010, 29(6): 142-143
Chen Wei Jia Minping Wang Heng. A study on the mill fill level grading theory and soft-sensing of mill fill level based on information fusion[J]. Journal of Vibration and Shock, 2010, 29(6): 142-143

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