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Development of indicators for the detection of equipment malfunctions and degradation estimation based on digital signals (alarms and events) from operation SCADA

机译:根据来自SCADA操作的数字信号(警报和事件),开发用于检测设备故障和退化估计的指标

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Certain mechanical and electrical components, such as generators, exhibit degradation phenomena, which may develop slowly over time or suddenly. The current trend in this field of research is to develop malfunction detection indicators from analog signals recorded by operation supervisory control and data acquisition (SCADA), creating behavioral models of the equipment and the development of a series of status indicators. These models and indicators are used to detect malfunctions when operation SCADA are unable to detect an abnormality, thus determining that the component is beginning to degrade when certain normal limits are exceeded. However, the digital signals from operation SCADA have great potential for providing additional information that could be used to detect possible malfunction. Detection must be accompanied by a study of the remaining life of a component so that the remaining useful life of the component before failure can be estimated before losing its functionality. If SCADA can detect a malfunction and determine when the component will break, the operator will have valuable time to intervene prior to failure at an optimum time. This is particularly important in installations with difficult access, such as offshore wind farms. (C) 2016 Elsevier Ltd. All rights reserved.
机译:某些机械和电气组件(例如发电机)会表现出退化现象,这种现象可能会随着时间的流逝而缓慢发展或突然发展。该研究领域的当前趋势是从操作监控和数据采集(SCADA)记录的模拟信号中开发故障检测指示器,创建设备的行为模型并开发一系列状态指示器。这些模型和指示器用于在操作SCADA无法检测到异常时检测故障,从而确定在超出某些正常限制时组件开始退化。但是,来自操作SCADA的数字信号具有提供可用于检测可能的故障的附加信息的巨大潜力。检测必须伴随着对组件剩余寿命的研究,以便可以在失去功能之前估算出组件在故障之前的剩余使用寿命。如果SCADA能够检测到故障并确定何时损坏组件,则操作员将有宝贵的时间进行干预,以在最佳时间进行故障诊断。这对于难以接近的设施(例如海上风电场)尤其重要。 (C)2016 Elsevier Ltd.保留所有权利。

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