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008 130613t2012 my da f m 000 0 eng d
020 _aTHE0005632(Local)
039 9 _a201905171157
_bhanafiah
_c201307051210
_dhuda
_y201306131506
_zhuda
040 _aUMP
090 _aTA355 .R53 2012 rs Bc.
100 0 _aRiduan Abdul Rahman
245 1 0 _aNoise extraction using frequency domain analysis /
_cRiduan bin Abdul Rahman
260 _aKuantan, Pahang :
_bUMP,
_c2012
300 _axv, 67 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD-ROM
502 _aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang - 2012
504 _aBibliography : p. 64-65
520 3 _aNoise is considered a hindrance in every vibrations signals including in an automotive suspension systems. Therefore methods of noise extraction were introduced in order to extract noise in the vibration signals. In this study noise are extracted from an automotive suspension system by frequency domain analysis. The vibrations frequency of the automotive spring is set to 8 Hz, 9 Hz and 10 Hz after that the automotive spring vibrations signals data were collected by using an accelerometer which connected to the suspension test rig which it functions were to measure the displacement of the spring, by using DASYLab® software. The vibrations signals it is then undergoes a low pass and high pass filter which is then interpreted in the form of power spectrum density which is done by fast-Fourier transforms which is then from the power spectrum density it is analyze to conduct noise extraction. The result is based on the ripple produce in power density spectrum of all the different frequency and also a different low-pass filter and high-pass filter. After that finding the most suitable frequency conditions for the low pass and high pass filter based on power spectrum density produce after filter process. The most optimum condition for noise extraction which achieved the most free noise vibration is when the low-pass filter is set to a frequency of 8 Hz and the high-pass filter is set to a frequency of 10 Hz.
650 0 _aVibration
_xMathematical models
650 0 _aNoise
_xMathematical models
650 0 _aSignal processing
999 _aVIRTUA40
_c3798
_d3804
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992