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An Automated Aero-Engine Thrust Detecting Method Based on Sound Recognition

机译:基于声音识别的航空发动机自动推力检测方法

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摘要

In order to confirm the aero-engine thrust before a carrier aircraft is launched, an automated aero-engine thrust detecting method based on sound recognition has been presented. Using the flight simulation software, it is possible to obtain an aero-engine's sound signal which can be divided into sections and put into the frequency domain by using FFT (Fast Fourier Transform). A 3-layer BP (Back Propagation) neural network is introduced to classify the spectrum of sound signal sections. In training the network, the L-BFGS algorithm is used to optimize the network parameters to make the accuracy of the network up to 99% in terms of test data. The result proves the algorithm to be effective. In practical application, the decision logic for 3 continuous sections is used to make the misjudgment rate for the launching thrust less than one millionth. The automated aero-engine thrust detecting method based on sound recognition can be adopted for a real-time detection of the aero-engine thrust, thereby replacing the current artificial confirmation methods of engine thrust to increase the efficiency and reliability of carrier aircraft launch.
机译:为了在航空母舰发射前确定航空发动机推力,提出了一种基于声音识别的自动航空发动机推力检测方法。使用飞行模拟软件,可以使用FFT(快速傅立叶变换)获得航空发动机的声音信号,该声音信号可以分为多个部分并进入频域。引入了3层BP(反向传播)神经网络对声音信号部分的频谱进行分类。在训练网络时,L-BFGS算法用于优化网络参数,以使测试数据方面的网络精度高达99%。结果证明了该算法的有效性。在实际应用中,使用3个连续断面的决策逻辑使发射推力的误判率小于百万分之一。可以采用基于声音识别的自动航空发动机推力检测方法对航空发动机推力进行实时检测,从而代替了目前人工推力的发动机推力确认方法,以提高舰载机发射的效率和可靠性。

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