Title :
An Automated Aero-Engine Thrust Detecting Method Based on Sound Recognition
Author :
Teng Teng;Zhao Zhihua
Author_Institution :
Nat. Key Lab. of Sci. &
Abstract :
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.
Keywords :
"Neural networks","Aircraft","Engines","Training","Aircraft propulsion","Software","Aerospace simulation"
Conference_Titel :
Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015 IEEE 12th Intl Conf on
DOI :
10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.113