首页> 外文会议>Proceedings of the ASME power conference 2009 >IMPROVING PLANT OPERATIONS WITH PERFORMANCE AND CONDITION MONITORING SYSTEMS
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IMPROVING PLANT OPERATIONS WITH PERFORMANCE AND CONDITION MONITORING SYSTEMS

机译:通过性能和状态监控系统改善工厂运营

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Business operations in the power industry, as with every other industry, require payback for the resolution of process problems. In order to achieve this payback many plant monitoring systems are used such as Performance and Condition Monitoring Systems. Performance Monitoring systems use first principles calculations for a baseline and test performance case, both of these calculations can then be reconciled to give a cost associated with off design operation. Condition Monitoring systems operate on the Advanced Pattern Recognition Algorithm (APR) and can be used to identify slight variations in the performance of a system largely independent of the quality of the inputs. The process to identify deviations is as follows: a predicted value is calculated for every modeled parameter, a difference between the predicted value and actual value is calculated, the difference is compared to an allowed threshold, and then problems are reported. The purpose of the following report is to identify the strengths and weaknesses of each monitoring system and show how they may be used together for a more thorough analysis of off design operation. Performance monitoring systems provide a reliable and actionable assessment of Heat Rate deviations when they occur in the field. The calculations provided by these systems can lead directly to the diagnosis of real performance problems as well as instrument inaccuracies and provide the financial implications of each issue. Performance monitoring systems, however, are highly dependent upon input quality as their results are found using first principles calculations. Condition Monitoring systems can be used to identify smaller deviations from normal at an earlier time. The major strength of the APR process is its ability to identify these deviations regardless of input quality. As with Performance Monitoring Systems the APR process will identify real problems as well as instrument problems. However, it will not provide a financially quantifiable result as to the effect of the deviation. Monitoring systems should be able to provide quantifiable results withrnminimal personnel use in order to achieve a payback for more operational problems. This paper will discuss how the use of Performance Monitoring Systems in conjunction with Condition Monitoring Systems will provide the complete analysis needed by the power industry today
机译:与其他所有行业一样,电力行业中的业务运营也需要回报以解决过程问题。为了实现这一回报,使用了许多工厂监控系统,例如性能和状态监控系统。性能监视系统将第一原理计算用于基准和测试性能案例,然后可以对这两个计算进行协调以提供与设计外操作相关的成本。状态监视系统在高级模式识别算法(APR)上运行,可用于识别系统性能的细微变化,而这些变化在很大程度上与输入的质量无关。识别偏差的过程如下:为每个建模参数计算一个预测值,计算该预测值和实际值之间的差异,将该差异与允许的阈值进行比较,然后报告问题。以下报告的目的是确定每个监视系统的优点和缺点,并说明如何将它们一起使用以更彻底地分析非设计操作。当在现场发生热效率偏差时,性能监控系统可提供可靠且可操作的评估。这些系统提供的计算结果可以直接导致对实际性能问题以及仪器错误的诊断,并提供每个问题的财务影响。然而,性能监控系统高度依赖于输入质量,因为其结果是使用第一原理计算得出的。状态监视系统可用于在较早的时间识别出与正常值的较小偏差。 APR流程的主要优势在于,无论输入质量如何,它都能识别这些偏差。与性能监控系统一样,APR流程将识别实际问题以及仪器问题。但是,它不会提供有关偏差影响的可财务量化的结果。监控系统应该能够在不减少人员使用的情况下提供可量化的结果,以便为更多的操作问题获得回报。本文将讨论如何结合使用性能监控系统和状态监控系统来提供当今电力行业所需的完整分析

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