Determination of vibrations properties of a wire rope H-type wind turbine with artificial neural network method
سال انتشار: 1402
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 16
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شناسه ملی سند علمی:
AEROSPACE22_060
تاریخ نمایه سازی: 31 مرداد 1403
چکیده مقاله:
This research examines the determination of vibrations characteristics and power calculation of a H-type cable wind turbine based on Artificial Neural Network or ANN. The considered hypotheses include the structure of the wind turbine in the form of a cable under tension and its type is a vertical axis and H-type cable. The type of analysis is non-linear due to the geometry and loading as well as the material used in the structure, and the Dynamic Stiffness Matrix or DSM method is used to calculate the vibrations and natural frequency and the Double Multiple Stream Tube or DMST model is used to calculate the production power of wind turbine. Here, ANN method is used with the aim of reducing the amount of computations time and minimizing design and analysis costs, as well as achieving a method for analyzing aerospace structures with the ability to generalize. The innovations carried out in this research include the extraction of relationships vibrations analysis and production power for the cable structure of a H-type cable wind turbine as well as the prediction of vibrations analysis along with the amount of production power using ANN without the need to perform modeling and spending time running analytical software in the least time with the highest level of accuracy and minimum error. Also, a design code for H- type cable vertical axis wind turbine was created based on the determination of natural frequencies in this research. Finally, the analysis time comparison for the three methods FEM, DSM and ANN shows that the ANN method has a higher analysis speed than the other two methods.
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نویسندگان
Shahrokh Shams
Associate Professor, Faculty of Aerospace Engineering, college of interdisciplinary sciences and technologies,University of Tehran, Tehran, Iran, Postal Code:۱۴۳۹۹۵۷۱۳۱
Mohammad Hassan Khoshnevis
MSc, Faculty of Aerospace Engineering, college of interdisciplinary sciences and technologies, University of Tehran, Tehran, Iran