In this study, analysis and classification of audio data collected from faulty air disc brakes has been carried out by Fourier Transform (FT). The sound data have been recorded by 2 identical Norsonic Type 1228 microphones in the laboratory of Ege Fren A.S. on a vehicle. The recorded data set which has been transferred into computer by a data acquisition board has been analyzed in Matlab. Number of zero crossings; mean, variance, entropy, and spectral rolloff of Fourier coefficients have been used as features in order to distinguish normal and faulty brakes. These features have been classified with 10x10 crossvalidation by using kth nearest neighbour algorithm with a success rate of 96.23
Time-frequency imaging provides a straightforward means to understanding machinery conditions. The m...
Abstract The interaction between bladed wheels and the fluid distributed by the stator vanes results...
[[abstract]]A scooter fault diagnostic system that makes use of feature extraction and intelligent c...
In this study, analysis and classification of audio data collected from faulty air disc brakes has b...
An acoustic analysis in the investigation of brake noise shows the severity of the noise and its cha...
Abstract: This paper presents an analysis of braking noise and vibration measurements using the shor...
AbstractThe paper deals with frequency analysis of acoustic signals using the Fast Fourier Transform...
This paper presents the application of wavelet transforms in the analysis of high frequency squeal i...
This research aims to identify misalignment of the rotor dynamics based on sound spectrum characteri...
Noise and vibration characterization is an important benchmark to reduce brake noise. Brake noise an...
This study aims to identify the outer race bearing needed to protect an induction motor from severe ...
The scope of this thesis is to investigate methods of recording, processing and analysing sound data...
This master’s thesis deals with signal evaluation using Fourier transform. In the theoretical sectio...
The paper discusses means to predict sound source position emitted by fault machine components based...
The paper discusses means to predict sound source position emitted by fault machine components based...
Time-frequency imaging provides a straightforward means to understanding machinery conditions. The m...
Abstract The interaction between bladed wheels and the fluid distributed by the stator vanes results...
[[abstract]]A scooter fault diagnostic system that makes use of feature extraction and intelligent c...
In this study, analysis and classification of audio data collected from faulty air disc brakes has b...
An acoustic analysis in the investigation of brake noise shows the severity of the noise and its cha...
Abstract: This paper presents an analysis of braking noise and vibration measurements using the shor...
AbstractThe paper deals with frequency analysis of acoustic signals using the Fast Fourier Transform...
This paper presents the application of wavelet transforms in the analysis of high frequency squeal i...
This research aims to identify misalignment of the rotor dynamics based on sound spectrum characteri...
Noise and vibration characterization is an important benchmark to reduce brake noise. Brake noise an...
This study aims to identify the outer race bearing needed to protect an induction motor from severe ...
The scope of this thesis is to investigate methods of recording, processing and analysing sound data...
This master’s thesis deals with signal evaluation using Fourier transform. In the theoretical sectio...
The paper discusses means to predict sound source position emitted by fault machine components based...
The paper discusses means to predict sound source position emitted by fault machine components based...
Time-frequency imaging provides a straightforward means to understanding machinery conditions. The m...
Abstract The interaction between bladed wheels and the fluid distributed by the stator vanes results...
[[abstract]]A scooter fault diagnostic system that makes use of feature extraction and intelligent c...