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Understanding effect and diagnosis of internal leakage in hydrostatic actuation systemsThakur, Amit 27 January 2012 (has links)
This research presents implementation of the Wavelet transform for detecting internal leakages occurring within an Electro-Hydrostatic Actuation (EHA) system. Simulation studies are carried out in order to investigate the feasibility of a particular approach and to determine the level of accuracy that can be expected in the experimental system. The effect of friction, orifices and the dynamics of motor/pump are considered during the simulation study. Experimental analysis based on Wavelet transform is conducted for detecting internal leakage. The original pressure signals at either side of the cylinder are decomposed using Wavelet transform to detect internal leakage which is clearly identified.
Results obtained through the use of Wavelet transform prove that this method is fast and easily-implementable for leakage detection in EHA on the basis of the pressure data obtained. Internal leakages as low as 0.0042 lit/min are shown to be detectable 85% of the time using a structured input signal.
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Understanding effect and diagnosis of internal leakage in hydrostatic actuation systemsThakur, Amit 27 January 2012 (has links)
This research presents implementation of the Wavelet transform for detecting internal leakages occurring within an Electro-Hydrostatic Actuation (EHA) system. Simulation studies are carried out in order to investigate the feasibility of a particular approach and to determine the level of accuracy that can be expected in the experimental system. The effect of friction, orifices and the dynamics of motor/pump are considered during the simulation study. Experimental analysis based on Wavelet transform is conducted for detecting internal leakage. The original pressure signals at either side of the cylinder are decomposed using Wavelet transform to detect internal leakage which is clearly identified.
Results obtained through the use of Wavelet transform prove that this method is fast and easily-implementable for leakage detection in EHA on the basis of the pressure data obtained. Internal leakages as low as 0.0042 lit/min are shown to be detectable 85% of the time using a structured input signal.
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