某电厂发电设备可靠性建模及状态预测
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摘要
结合电厂巡点检数据处理的发展现状和某热电厂的实际情况,以发电设备状态参数为研究对象,建立了基于灰色理论的数学模型,进行了状态参数的预测和评价;使用"改进灰色模型"通过引入m点均算因子,对具有波动性的原始发电设备运行参数序列进行m点均值处理,使原始数据满足灰色模型光滑性的要求。结果表明,使用改进的灰色模型能更加准确地预测和评价该电厂发电设备的运行状态,最终实现了对点检数据处理分析的目的。
Combining the development status of power plants spot check and actual situation of a thermal power plant,taking the state parameters of generation equipment as research object,a mathematical model based on Gray Theory is established,which can be used for state parameters prediction and evaluation.By introducing m-point factor,the improved Gray Model can make m point average process on volatile operating parameters sequences of generation equipment,which makes the original data meet the the smoothness requirements of Grey Model.The results show that the improved Gray Model can predict and evaluate the operation status of power plants more accurately and achieve the purpose of processing of spot check data.
Combining the development status of power plants spot check and actual situation of a thermal power plant,taking the state parameters of generation equipment as research object,a mathematical model based on Gray Theory is established,which can be used for state parameters prediction and evaluation.By introducing m-point factor,the improved Gray Model can make m point average process on volatile operating parameters sequences of generation equipment,which makes the original data meet the the smoothness requirements of Grey Model.The results show that the improved Gray Model can predict and evaluate the operation status of power plants more accurately and achieve the purpose of processing of spot check data.
引文
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[2]肖进华.电厂设备点检管理决策系统研究与开发[D].武汉:华中科技大学,2005.
[3]杨永会.电厂发电设备可靠性分析[J].建筑工程技术与设计,2016(22):2182.
[4]张中东.点检制在发电企业中的应用研究[D].保定:华北电力大学,2006.
[5]李耀君,于新颖.火电厂设备状态检修技术[J].中国电力,2005,38(4):9-15.
[6]耿红杰.设备点检管理与预知性维修的简要分析[J].中国高新技企业,2009(10):71-72.
[7]韩红彩.灰色系统预测的研究与分析[J].中国科技信息,2010(14):29-30.
[8]RAMIN M,LABENCKI T,BOYD D,et al.A Bayesian synthesis of predictions from different models for setting water quality criteria[J].Ecological Modelling,2012,242:127-145.
[9]芦森.基于组合模型的中国能源需求预测[D].成都:成都理工大学,2010.
[10]田红霞.基于两次改进灰色加权马尔可夫模型的CPI预测[J].中北大学学报(自然科学版),2015(2):113-117.
[11]江长征.电动给水泵润滑油压低缺陷的消除[J].湖北电力,2009(6):70-71,74.