Abstract detail

247 / 2021-04-14 17:15:24
Howling abnormal sound diagnosis of aircraft based on spectrum visibility graph
Aircraft howling abnormal sound,Diagnosis,Visibility graph
Special Sessions > Applications of machine learning in vibration and noise problems
Final Paper
Xin Wen / Shanghai Jiao Tong University
Haijun Wu / Shanghai Jiaotong University
Chenyi Zhao / Shanghai Aircraft Design and Research Institute
Huayong Zhao / Shanghai Aircraft Design and Research Institute
The howling abnormal sound of aircraft can affect the reliability of aircraft and the comfort of passengers. Identifying the fault types of the howling abnormal sound in time can provide an important reference for taking operation and making later maintenance. This paper presents a new method for this purpose. In this method, the frequency spectrum of the sound signal obtained by FFT is divided to the several sub-bands. The visibility graph is then constructed from the resulting sub-bands, where the considers the structural information of the spectrum. The KNN classifier is used to locate the aircraft howling abnormal sound, where the metric distance is calculated between graphs. The proposed method is investigated based on a real dataset collected by a certain type of aircraft, and experimental results demonstrate the priority and the great potential of the proposed method in real applications.

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Important Dates

Abstract Submission Deadline:

 31st March 2021 15th April 2021

Extended Deadline: 1st Aug. 2022

 

Abstract Acceptance:

30th April  2021 Rollover

 

Full Paper Submission Deadline:

30th June 2021  14th July 2021

Extended Deadline: 15th Aug. 2022 

 

Notification of Acceptance:

15th August 2021 1st Sept. 2021

1st Sept. 2022

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