Low Frequency Analysis of Acoustic and Vibration Data of a Remote Control Electronic Helicopter

The acoustic and vibration data of the tail rotor of a remote control unmanned electrical helicopter are simultaneously collected by sound and image data acquisition systems. To inspect the pure vibration spectrum in the extreme low frequency region, an image system containing a Web camera and having a sampling rate of 20 frames per second is proposed to collect the data of the tail boom. The total gray levels within a specified square of a frame are considered as a single image data at the corresponding instance. The image data string always involves the non-sinusoidal part which will introduce the Direct Current (DC) contamination to the spectrum. In order to exclude the contamination, the iterative Gaussian smoothing method is employed to remove the non-sinusoidal part. Then, both sound and image data strings are examined in terms of the Fourier sine spectrum. In order to capture information of minor modes, the Fourier sine spectrum of a sinusoidal data string is obtained through the following procedure: search zero points around the two ends, redistribute data so that the data size is an integer power of 2, perform odd function mapping, and apply the Fast Fourier Transform (FFT). A ball belling data is first employed to show that the Fourier sine spectrum can capture information of both the sub-harmonic and side band modes. With the help of the image data, many sub-harmonics and side-band modes embedded in the acoustic data of the tail rotor were identified by the Fourier sine spectrum.