建筑工程质量风险预测与控制方法研究

发布时间：2018-01-08 16:16

本文关键词：建筑工程质量风险预测与控制方法研究　出处：《东南大学》2017年硕士论文　论文类型：学位论文

【摘要】：建筑工程质量直接影响建筑工程自身全寿命期,关系到工程的适用性和社会效益,最终也会关系到人民财产与生命安全。经过大量的文献阅读,发现建筑工程风险管理的研究少有以工程对象系统的研究作为出发点进行动态评估和实时监控工程质量风险,且鲜有计算机技术的深入运用,因此确定"建筑工程质量风险预测和控制方法"为题。本文主要以理论分析为主,并结合863个建筑工程样本案例的实地调研、历史工程数据以及东南大学项目管理研究所多年重大科研项目部分成果,在以下几个方面进行研究:(1)本文研究的基础理论与方法,包括明确建筑工程质量风险定义、基于Domino理论和Reason理论与的建筑工程风险形成机理、工程系统结构分解方法(EBS)、贝叶斯网络和范例推理等方法,并构建建筑工程质量风险预测和控制体系。(2)在建筑工程分解结构基础上,结合案例工程调研结果,建立了基于EBS和建筑工程质量问题映射关系,有利于直接识别和获取建筑工程质量风险因素,并进行风险因素含义的解释和建筑工程质量风险结构分解。(3)建筑工程质量风险科学评估需要历史工程数据的仿真经验值,以弥补关键参数被主观赋值的数据缺失,利用灰色关联计量方法,并以贝叶斯准则的阈值作为建筑工程质量风险是否发生的临界点,实现风险动态预警。(4)根据风险识别和风险预测的研究结果,建立基于范例推理的建筑工程质量风险控制流程,包括对目标工程的数据采集、数据处理,在工程案例库中利用相似度寻求相似案例,构建建筑工程质量风险实时监控系统,满足目标工程现场与监控中心的数据实时交互需要,结合相似案例的经验数据,使用风险预测方法进行动态评估与监控,做到精准的风险事前控制;并详细论述当工程质量风险监控系统发出预警警报的时候,处于高危状态的风险由谁分担以及合理的分担比例,督促风险关联方主动采取针对性的风险应对措施而保障质量风险处于安全状态。
[Abstract]:The quality of construction works directly affects the whole life period of the construction project itself, relates to the applicability and social benefit of the project, and ultimately also relates to the people's property and life safety. It is found that the research on risk management of construction engineering seldom takes the research of engineering object system as the starting point to carry out dynamic evaluation and real-time monitoring of engineering quality risk, and seldom makes use of computer technology in depth. Therefore, "risk prediction and control method of construction engineering quality" is determined. This paper mainly focuses on theoretical analysis and field investigation of 863 construction engineering sample cases. Historical engineering data and some achievements of the major scientific research projects of the Institute of Project Management, Southeast University, are studied in the following aspects: 1) the basic theories and methods of this paper. Including clear definition of construction engineering quality risk, based on Domino theory and Reason theory and construction engineering risk formation mechanism, engineering system structure decomposition method. Bayesian network and Case-based reasoning (CBR) are used to construct the risk prediction and control system of construction engineering quality. Based on the decomposed structure of construction engineering, the research results of case engineering are combined. Based on EBS and the mapping relation of construction engineering quality problem, it is helpful to identify and obtain the risk factors of construction engineering quality directly. And the interpretation of the meaning of risk factors and the structural decomposition of construction quality risk. 3) the scientific evaluation of construction engineering quality risk needs the simulation experience value of historical engineering data. In order to make up for the lack of the data that the key parameters are assigned subjectively, the grey correlation measurement method is used, and the threshold of Bayesian criterion is used as the critical point of whether the quality risk of construction engineering occurs or not. According to the research results of risk identification and risk prediction, the paper establishes the construction engineering quality risk control flow based on case-based reasoning, including the data acquisition and data processing of the target engineering. In order to meet the need of real-time data interaction between the target project site and the monitoring center, a real-time monitoring system of construction engineering quality risk is constructed by using similarity to seek similar cases in the engineering case base. Combining with the experience data of similar cases, using the risk forecasting method to carry on the dynamic evaluation and monitoring, so as to achieve accurate risk control in advance; And discusses in detail when the project quality risk monitoring system sends out the early warning alarm, the risk in the high risk condition by who shares and the reasonable sharing proportion. Urge related parties to take targeted risk measures to ensure quality risk is in a safe state.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU712.3

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