Wind turbine fault blades detection using CWT analysis in low speeds

Jose R. Razo Hernandez, Juan P. Razon Gonzalez, Gustavo Adolfo Evangelista Ventura, David Granados Lieberman, C. Perez-Ramirez, Jesus A. Basurto-Hurtado
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Abstract

The recent increase of renewable energy sources can be explained due to the necessity to reduce the pollution generated by the usage of oil-derived power supplies. In this sense, aerogenerators are one of the active power supplies most used since they can be rapidly connected or disconnected according the power demand. Since they have some mobile parts that can be damaged, it is important to generate methodologies that can detect damages at the earliest possible stage. While the failures generated by bearings, misalignment or unbalance are widely studied, blade damages are barely analyzed since they are difficult to detect; yet, it should be considered that since blades are constantly moving, any damage might cause either an excessive vibration or inducing an increase current consumption. Considering the aforementioned facts, this work presents a methodology using the continuous wavelet transform for studying this type of failure when the aerogenerator is operating at a low speed.
基于CWT分析的风电机组低速故障叶片检测
最近可再生能源的增加可以解释为减少使用石油衍生电源所产生的污染的必要性。从这个意义上说,航空发电机是最常用的有源电源之一,因为它可以根据电力需求快速连接或断开。由于它们有一些可能损坏的移动部件,因此产生能够在尽可能早的阶段检测损坏的方法非常重要。由于轴承、不对中或不平衡引起的故障被广泛研究,而叶片损伤由于其难以检测而很少被分析;然而,应该考虑到,由于叶片是不断移动的,任何损坏都可能导致过度振动或诱导电流消耗增加。考虑到上述事实,本工作提出了一种使用连续小波变换来研究风力发电机在低速运行时这种类型的故障的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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