Diagnose Method Based on Spectral Analysis of Measured Parameters

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The paper presents a possible method to diagnose a mechanical fault of an automotive system. Starting from the point of view that every fault of a mechanical system should introduce an abnormal component within the signal that describes the time history of a mechanical parameter we tried to find a way to reveal it.We were performing some tests involving a military vehicle with respect to the performances of its braking system. The tests were aiming at identifying a way to bring up-to-date the old weapon system from the braking systems point of view. During these tests we observed some anomalies concerning the pressure evolution within the braking cylinders of the vehicle. Some unusual but also systematic noises occurred. As a main issue at this point, the source of the noise should have been identified and filtered if necessary. We had to decide whether the noisy component of the signal is just a noise that should be removed by filtering the signal or it is a physical component of the mechanical parameter itself (not noise but a useful information).These procedures take time and they also request accurate knowledge as well as fine expertise in automotive testing. Since our Dept. has a long and rich practice in this respect, we assumed to processing data and give them a thorough interpretation. So, the first thing we did was to perform a frequency analysis, using classical methods. Usually, a simple frequency analysis cant provide information about a time variation of the frequency spectra due to the Fourier Transforms behavior, since it freezes the signal in time. A much more accurate analysis is the time-frequency analysis. However, observing both the amplitude and power spectra can lead to a useful conclusion. We concluded that the noise we met within the signal is due to the brake drums loss of circular shape (they turned into an oval, the process being known as ovalization). Hence, we cant talk about a noise as it is usually defined.

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535-540

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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DOI: 10.4028/www.scientific.net/amr.837.434

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