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不同传感器在 Francis 涡轮机中水力现象的检测。

Detection of Hydraulic Phenomena in Francis Turbines with Different Sensors.

机构信息

Center for Industrial Diagnostics and Fluid Dynamics (CDIF), Universitat Politècnica de Catalunya (UPC), Av. Diagonal, 647, ETSEIB, 08028, Barcelona, Spain.

出版信息

Sensors (Basel). 2019 Sep 19;19(18):4053. doi: 10.3390/s19184053.

Abstract

Nowadays, hydropower is demanded to provide flexibility and fast response into the electrical grid in order to compensate the non-constant electricity generation of other renewable sources. Hydraulic turbines are therefore demanded to work under off-design conditions more frequently, where different complex hydraulic phenomena appear, affecting the machine stability as well as reducing the useful life of its components. Hence, it is desirable to detect in real-time these hydraulic phenomena to assess the operation of the machine. In this paper, a large medium-head Francis turbine was selected for this purpose. This prototype is instrumented with several sensors such as accelerometers, proximity probes, strain gauges, pressure sensors and a microphone. Results presented in this paper permit knowing which hydraulic phenomenon is detected with every sensor and which signal analysis technique is necessary to use. With this information, monitoring systems can be optimized with the most convenient sensors, locations and signal analysis techniques.

摘要

如今,为了使电网具有灵活性和快速响应能力,以补偿其他可再生能源的非恒定发电量,需要水力发电。因此,水力涡轮机需要更频繁地在非设计条件下运行,在这些条件下会出现不同的复杂水力现象,这会影响机器的稳定性并缩短其部件的使用寿命。因此,期望实时检测这些水力现象以评估机器的运行状况。为此,本文选择了一台大型中水头混流式水轮机。该原型机配备了多个传感器,如加速度计、接近探头、应变计、压力传感器和麦克风。本文介绍的结果可以了解每个传感器检测到的水力现象以及需要使用的信号分析技术。有了这些信息,就可以使用最方便的传感器、位置和信号分析技术来优化监控系统。

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