摘要
海量实时监测数据为缆机实际运行效率分析和工程现场调度优化提供了直接和可靠的研究基础。如何从庞杂的海量数据中准确快速地识别缆机的工作状态和吊运任务,从而提取吊运工作循环,是分析缆机吊运混凝土工作效率的关键问题。本文提出一种基于缆机吊重时序特征的吊运混凝土模式识别方法,以吊重的时序变化特征和状态区间平均吊重值定义缆机起吊、重载运行等工作状态,以工作状态的时序变化特征定义吊运混凝土模式;提取吊重参数的统计规律,定义模式识别标准模板,提出了“状态相似判别加状态罚函数”的吊运混凝土模式识别模型。针对两种特殊情况,即受大风或加速度影响造成缆索摆动时的吊重监测数据“假波动”,和缆机提升或卸料过程中意外停顿造成吊重的“假稳定”,本文构建了一种“孤点判别+多次迭代”的方法,修正状态识别结果。模型应用及工程实测数据分析表明,该模型能够快速准确地识别缆机工作模式、判别缆机吊运混凝土各工作状态的起止点、状态值和平均吊重,为缆机实际运行效率分析和调度优化等提供重要支撑。
Massive real-time monitoring data of a concrete liftingcable crane providesasa direct,reliable research basis for analysis of its practical operation efficiency.How to identify accurately and quickly its working cycle and extract useful information from these data is a key issueforefficiency analysis.Therefore,we develop a pattern recognition method.The working state of a cable crane is defined by the rates of changesinthe lifting weight and its average;its concrete lifting modes defined by a time series of its characteristic changes.Then,we extractthe statistical law of weightlifting parameters and definea set of pattern recognition standard templates;a pattern recognition model of lifting concrete featured with state similarity recognition plus state penalty functionisdeveloped.Especially,in view of the false fluctuationinthe monitoring data of the load caused by the wind or cable acceleration,and the false stability of the load caused by accidental pauses in weight lifting or unloading,we construct a method of discrimination of isolated points plus multiple iterations to identify and correct aworking state.Application of this model and measured dataanalysis show that it identifiesaccurately and quickly the working modes of a cable crane,thestart and end points of each working state,and itsinstant andaverage lifting weights,thus providing important support for practical operation efficiency analysis and scheduling optimization of cable cranes.
作者
赵春菊
资瑛
周宜红
刘全
赵可欣
ZHAO Chunju;ZI Ying;ZHOU Yihong;LIU Quan;ZHAO Kexin(College of Hydraulic&Environmental Engineering,China Three Gorges University,Yichang,Hubei 443002;Hubei Key Laboratory of Hydropower Engineering Construction and Management,Yichang,Hubei 443002;School of Water Resources and Hydropower Engineering,Wuhan University,Wuhan 430072;GuizhouSurvey&Design Research Institute for Water Resources&Hydropower,Guiyang 550001)
出处
《水力发电学报》
CSCD
北大核心
2021年第12期119-128,共10页
Journal of Hydroelectric Engineering
基金
国家自然科学基金面上项目(51779131)。
关键词
水利工程施工
海量监测数据
缆机
吊运混凝土
模式识别
construction for hydraulic works
massive monitoring data
cable crane
lifting concrete
pattern recognition
