风力发电机动态检测的神经网络模型

G. Iannace, Giuseppe Ciaburro, A. Trematerra
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引用次数: 0

摘要

自古以来,风一直是人类的一种能源,主要是因为它在世界各地都可以广泛利用。几家公司正在投入巨额资金建设风力发电场,目的是获得最大可能的经济回报。因此,为了恰当地定义一个充分利用风能的系统,有必要对涡轮机的运行动力学进行精确定义。在本研究中,通过测量不同风力涡轮机发出的噪声来获得有关其运行动力学的信息。在1/3倍频程范围内提取了选定的平均光谱水平范围。建立了一种基于神经网络的检测模型,并将其应用于风力发电机组的工况识别。预测和识别模型返回了很高的精度,这表明在其他几个应用中可以采用该工具。
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Neural Networks Model to Detect Wind Turbine Dynamics
: The wind has been a source of energy for the human being since ancient times, mainly because it is widely available in different areas of the world. Several companies are investing huge capital to build wind farms with the aim of obtaining the maximum possible economic return. Therefore, a precise definition of the dynamics of operation of the turbines is necessary in order to appropriately define a system that takes full advantage of the wind energy. In this study, the measurements of the noise emitted by different wind turbines were used to obtain information on the dynamics of operation. A selected range of average spectral levels was extracted in a 1/3 octave band. A model based on the neural network for detection has been developed and applied to identify the operating conditions of wind turbines. The prediction and identification model have returned a high precision that suggests the adoption of this tool for several other applications.
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来源期刊
International Journal of Automation and Smart Technology
International Journal of Automation and Smart Technology Engineering-Electrical and Electronic Engineering
CiteScore
0.70
自引率
0.00%
发文量
0
审稿时长
16 weeks
期刊介绍: International Journal of Automation and Smart Technology (AUSMT) is a peer-reviewed, open-access journal devoted to publishing research papers in the fields of automation and smart technology. Currently, the journal is abstracted in Scopus, INSPEC and DOAJ (Directory of Open Access Journals). The research areas of the journal include but are not limited to the fields of mechatronics, automation, ambient Intelligence, sensor networks, human-computer interfaces, and robotics. These technologies should be developed with the major purpose to increase the quality of life as well as to work towards environmental, economic and social sustainability for future generations. AUSMT endeavors to provide a worldwide forum for the dynamic exchange of ideas and findings from research of different disciplines from around the world. Also, AUSMT actively seeks to encourage interaction and cooperation between academia and industry along the fields of automation and smart technology. For the aforementioned purposes, AUSMT maps out 5 areas of interests. Each of them represents a pillar for better future life: - Intelligent Automation Technology. - Ambient Intelligence, Context Awareness, and Sensor Networks. - Human-Computer Interface. - Optomechatronic Modules and Systems. - Robotics, Intelligent Devices and Systems.
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