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长输管道高后果区识别及统计受人为因素影响较大,导致识别过程冗长,人力与物力消耗大,识别结果查询不便、通用性差、后处理困难,不能在次年识别过程中有效应用。根据 Q/SY 1180.2-2009 的相关规定,利用 Microsoft Visual Studio 2010 设计了一套完整的软件组织架构,完成了管道风险评价、管道完整性评价、数据库表结构及效能评价软件开发。该软件建立了完整的高后果因素数据库,能够杜绝工作人员在识别过程中对高后果因素的识别误差、等级划分误差、打分误差等人为错误;利用计算机软件系统整合全部数据,形成完整、规范的高后果区识别报告,可有效避免统计误差,形成完全一致的电子和书面报告,大大减少了工作时间,节约资金,形成统一的完整性管理工作信息平台,进一步提高了管道完整性管理水平。
High consequence area (HCA) identification and statistics of long-distance pipeline are greatly influenced by human factors, which result in lengthy identification process and large consumption of labor and material.The identification results exhibit features of inconvenient query, poor versatility and inconvenient post treatment, and they cannot be effectively applied in the identification process in the following year.According to Q/SY 1180.2-2009, a China standard, a complete set of software framework is designed with Microsoft Visual Studio 2010.The software can be used for risk assessment, integrity assessment and database structure/performance evaluation of pipelines.It incorporates a complete database of high consequence factors and can eliminate the identification error, classification error, scoring error and other human errors of the operators during high consequence factors identification.Complete and standardized HCA identification reports are formed to avoid statistical errors by using the software to integrate all the data.Consistent electronic and written reports are generated in cost and time-effective manner.Thus, a unified integrity management platform is formed to further improve the pipeline integrity.
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收稿日期:2013-7-17;改回日期:2014-3-19。
作者简介:马廷霞,副教授,在读博士生,1974 年生,2002 年硕士毕业于兰州交通大学工程力学专业,现主要从事油气储运、过程装备与控制、管道状态检测与远程监控等相关技术的研究工作。Tel: 13982251188, Email: hh_mtx@163.com