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首页> 外文会议>The 2001 International Congress and Exhibition on Noise Control Engineering Vol.5, 2001, Aug 27-30, 2001, The Hague, the Netherlands >Recognition of selected helicopter types based on the generated acoustic signal with application of artificial intelligence methods
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Recognition of selected helicopter types based on the generated acoustic signal with application of artificial intelligence methods

机译：应用人工智能方法，基于生成的声音信号识别选定的直升机类型

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摘要

In the paper selected parts of conducted research are presented, concerning the application of artificial intelligence methods, in particular the neural networks technique, in the task of helicopter type identification based on the generated acoustic signal. In the design of helicopters produced in recent years (passenger and transport as well as multipurpose ones) certain trends can be noticed, oriented towards increase of the take-off mass, decrease of the lift-off speed, definite increase of the climbing speed and achieved accelerations (steeper take-off profiles). These trends considerably affect the emitted outside noise level (during the initial lift-off phase the engines of the power unit work at their maximum power levels). In this presentation results are discussed, which has been obtained in the laboratories of University of Mining and Metallurgy by application of advanced acoustic signal analysis techniques and by referring to learning neural networks in the task of recognition of selected helicopter types based on their generated noise.
机译：在本文中，介绍了一些进行研究的部分，涉及人工智能方法（特别是神经网络技术）在基于生成的声信号的直升机类型识别任务中的应用。在近几年生产的直升机（客运和多用途直升机）的设计中，可以注意到某些趋势，即起飞质量的增加，起飞速度的降低，爬升速度的明显提高以及实现了加速（更陡峭的起飞轮廓）。这些趋势会严重影响发出的外部噪声水平（在初始提起阶段，动力装置的发动机将以其最大功率水平工作）。在本演示中，将讨论结果，这些结果是在采矿和冶金大学的实验室中通过应用先进的声信号分析技术并在参考基于所选神经网络的噪声识别所选直升机类型的任务中参考学习神经网络而获得的。

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