【作者】 李龙江；

【导师】 陶文亮；

【作者基本信息】 贵州大学 ， 材料学， 2006， 硕士

【摘要】 埋地燃气管线是城市“生命线工程”的重要组成部分，具有点多，面广，线长，易受环境腐蚀，各种人为破坏及自然灾害的影响。随着城市埋地燃气管道数量的增多和运行时间的增加，埋地燃气管道在设计，元件制造，安装及运行管理中的问题逐渐暴露出来，而地下燃气管道铺设在地下，工作环境相当复杂，给检修和维护又带来极大的困难，致使城市煤气管道事故时有发生。管道一旦失效将引发灾难性事故，对人民生命财产造成损失。因此，为确保埋地燃气管线的安全运行，挖掘管线潜力，减少因管线失效而引起的停气和不必要的管道更换带来的经济损失，对地埋燃气管线的故障树分析研究和风险分析研究就具有重要的意义。 本研究在广泛收集国内外资料和在地下燃气管道调研的基础上，针对我国地下燃气管道的实际工作情况，对地下燃气管网的定量的风险分析进行了探索性研究。本课题根据现场采集的数据，用补偿模糊神经网络建模计算得出管线的失效风险。为了更有效的分析和改进评估中出现的问题，采用先建立数学模型，然后在计算机上进行假设模拟计算，最后通过做实验来验证，这样可以节约较多的人力，物力和财力，避免盲目的去做实验，实验层次分明，目的明确。本课题只对管道的衰老期进行风险分析研究。完成了以下9个方面的研究工作。 1．收集并整理有关埋地燃气管线的腐蚀与防护资料、历史事故记录、操作失误记录、检测技术、评价标准及操作管理的文献资料，并查找国内外相关标准，明确课题研究的方向及技术路线，了解了贵阳市煤气输送管道的运行情况，埋设施工工艺，腐蚀现状及防护措施，公司管理状况等。 2．全面细致地分析管道的失效原因，通过现有的科学方法全面细致地找出埋地燃气管道的失效机理。把影响埋地燃气管线的失效原因分为五大类(腐蚀影响因素、第三方影响因素、设计影响因素、操作影响因素和人因可靠性)130个底事件。本文在管道失效分析中，第一次提出了人因可靠性并参与了故障树影响因素的计算。 3．确定补偿模糊神经网络模型为本课题计算模糊故障树及模糊风险的首选数学模型。并确定故障树补偿模糊神经网络的输入因素权重。用改进的层次分析法和CR一致判据来确定各底事件的因素权重，为补偿模糊神经网络模型计算故障树模糊重要度的训练数据对构造提供了依据。 4．构造并计算模糊故障树。用补偿模糊神经网络进行故障树顶事件失效的可能性计算以及运用补偿模糊神经网络计算故障树模糊重要度，找出影响埋地燃气管线失效的主要原因，对底事件的影响程度进行排序，分析因素间的独立性和相互作用性，全面细致地分析每一段管道的着重影响因素。 5．进行管道风险分析。根据风险的定义，管线的风险是指管网系统在设计的工作条件下和设计的工作时间内，其不能完成预定功能的可能性及由此而产生的影响后果，管道风险可表示为管道失效的可能性和失效后果的函数。根据故障树对管道顶事件失效的可能性的计算和僮祥英同学对管网失效后果的计算，建立了风险分析的两因素的补偿模糊神经网络模型，对管道模糊风险进行了分析和计算，计算风险量和风险发生的可能性区间。并取贵阳市的部分管段分析计算，得出了管道的风险矩阵。 6．实验。做实验找出在杂散电流和其它因素共同作用下的土壤腐蚀情况。杂散电流有直流杂散电流，交流扎散电流和交直流交叉作用下的杂散电流，分别做实验来看其对土壤腐蚀的影响。实验模拟了贵阳市贵黄公路旁的高寨段土壤环境，分别给定不同环境条件下的杂散电流，看其对埋地管道的腐蚀影响，并自行设计了一套阴极保护系统，对在存在杂散电流的情况下如何用强制电流保护的方法保护管道进行了深入的研究。 7．对管道风险的分析后果进行评价。研究模型的可行性，提出相应的地埋燃气管道的减小风险的措施，进一步提出其预防措施。提出埋地燃气管道风险的可接受准则。更多还原

【Abstract】 The underground gas pipeline is the significant parts of the " life blood project " in city , the underground gas pipeline not only the surface is vast ,the line is long, but also that apting to affect by the environment , different man-made damage and natural calamitys. With the underground gas pipeline quantity increasing and the operating time longth, the underground gas pipeline is living with lots of questions such as pipeline design , element manufacture , the problem which fixed and administration reveals out one by one,but the underground gas pipeline is builded under the sbterranean , the work environment is considerably complex , gives maintenance and protection to bring extremely great hardship once more , resuling in the gas piping mishap more frequently in town. The gas piping once lose the effectiveness will bring the calamity ,affect people’s existence and wealth. Hence in order to make sure the underground gas pipeline secure, unearth pipelines-latent capacity, decreases gas pipelines failure to brought ceases gas and the economy decrease, it is very significant to underway the fault tree analysis and risk analysis on underground gas pipeline.On the base of gathering home and abroad datum widely and living up the underground gas pipeline researches, and combining our country gas pipeline actual work situation, This research has been carried on the quality risk analysis research. This research according to collect the underground gas pipeling data in field,use compensation fuzzy neural network to establish mathematical model and calculate and anilyle and obtaine the gas pipeline failure risk.For the sake of more valid analysis and modification the questions that ariseed in assessing, we adopts establishing the mathematical model earlier , afterwards assumes the analog computation in the computer, finally by means of the experiment to certificate , that may thrift more labours power , resource and financial, and avert the test blindly , the test step clearly , the aim is clear. This task merely analyses the underground gas pipeline death stage and carries on risk analysis research. Complete 9 respects research work as the following below.1. Gathering the literature datum , evaluation criterion and operation that is administerd and keeping the minutes and examine in gas pipeline corruption datum , history mishap and manipulate miss, and correlation criterion in searching home and abroad , subject study orientation and make sure the technique course, and comprehend the Guiyang gas pipeline operation situation that was exploted at present, and covers up building technology that etcing present situation and guard arrangement, the corporation administers and so on.2. Carefully analysing underground gas pipeline failure cause completely. The underground gas pipeline failure effect is divided into five types( Corruption effect element and third side effect element, design effect element and manipulate effect element and man as a result of the dependability) 130 base events with covering up . In fault tree analysis hostiry,man as a result of the dependability is the first to join the concluate and analysis.3.This research first choose compensation fuzzy neural network model pattern as calculation and analysis mathematical model, and determinate fault tree compensates fuzzy neural network input element weight. Use progress step analytic approach and CR unanimousle evidence to bring to fix the base event element weight , offering the compensation fuzzy neural network calculation flaut tree fuzzy importance degree that supplyd the foundation of training data structure.4. Structure and calculation fuzzy fault tree . use compensation fuzzy neural network calculate fault tree top event fuzzy effectiveness prc bability and calculation fault tree fuzzy important degree , finds out the main reason that lose effectiveness with underground gas pipeline, and carries on the更多还原