首页> 外文会议>Biennial International Pipeline Conference(IPC 2004) vol.3; 20041004-08; Calgary(CA) >BUILDING A LEAKAGE DETECTION SYSTEM USING ENSEMBLES: A NEW WAY
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BUILDING A LEAKAGE DETECTION SYSTEM USING ENSEMBLES: A NEW WAY

机译:使用封装构建泄漏检测系统:一种新方法

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Pipeline leakage is a demand from governmental and environmental associations that petroleum companies need to comply. Recent accidents with Petrobras pipelines increase local demand for leakage detection system. Due the high accuracy on detecting leakage required from that system is necessary to set a procedure that once applied will achieve the best performance considering the quality of the installed instrumentation. This paper describes a procedure to set such system in order to accomplish with the legal requirement keeping high reliability during normal and failure operations conditions. Nuisance alarms are kept at low value while minimum leakage detection is too small. To do that the described system uses a set of models acting as specialists each one observing and diagnosing pipeline leakage. This system also validates the operations according to the business rules. System uses a set of tools, fuzzy logic, neural network, genetic algorithm and statistic analysis, to execute its function. The usage of an optimization tool, genetic algorithm in this case, helps the designer to set a function alarm that uses a statistical approach to assure a reliable performance when detecting the leakage and keeping the nuisance alarm closes to zero. Both qualities make the system highly reliable since once it generates one alarm there is a likelihood of almost a 100% that the event is true. Instead of using the common two parameters alarm, threshold and timing, this system uses pattern recognition to verify the fault or leak condition. The detectable leakage value is function of the difference between the flow measurement at the inlet and the outlet of the pipeline. The minimum leakage detectable is constant and equal to 1.4 times the standard deviation of the error between this two meters for 0.2% of nuisance alarm. In the application it is able to alarm when a leakage of 2% of the total flow happens in a time bellow 5 minutes. If allowed a level of 5% of nuisance alarms the system is able to detect a leakage of one standard deviation of the error. That represents the mentioned amount of 1.4 times the standard deviation of the error. The system is in operation supervising pipeline in a Brazilian installation.
机译:管道泄漏是政府和环保协会要求石油公司必须遵守的要求。 Petrobras管道最近发生的事故增加了当地对泄漏检测系统的需求。由于检测该系统所需的泄漏的高精度是设置程序的必要条件,一旦应用该程序,考虑到已安装仪器的质量,将获得最佳性能。本文描述了设置此系统的过程,以在法律要求下完成,以在正常和故障操作条件下保持高可靠性。当最小泄漏检测量太小时,有害警报将保持在较低的值。为此,所描述的系统使用一组充当专家的模型,每个模型都观察和诊断管道泄漏。该系统还根据业务规则验证操作。系统使用一组工具,模糊逻辑,神经网络,遗传算法和统计分析来执行其功能。在这种情况下,使用优化工具(即遗传算法)可以帮助设计人员设置功能警报,该警报使用统计方法来确保在检测到泄漏时保持可靠的性能,并保持令人讨厌的警报接近零。两种质量都使系统具有高度的可靠性,因为一旦它生成一个警报,就几乎有100%的事件是真实的。该系统不使用通用的两个参数警报,阈值和定时,而是使用模式识别来验证故障或泄漏情况。可检测的泄漏值取决于管道入口和出口处的流量测量值之差。对于0.2%的滋扰警报,可检测到的最小泄漏量是恒定的,并且等于两米之间的误差标准偏差的1.4倍。在该应用中,它能够在5分钟以下的时间内发出总流量泄漏2%的警报。如果允许的干扰警报级别为5%,则系统能够检测到一个标准偏差的泄漏。这表示上述误差标准偏差的1.4倍。该系统正在运行中,以监视巴西安装中的管道。

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