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.