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Detection and Classification of Wear Fault in Axial Piston Pumps: Using ANNs and Pressure Signals
Abstract
Variable displacement axial piston hydraulic pumps (VDAP) are the heart of any hydraulic system and are commonly used in the industrial sector for its high load capacity, efficiency, and good performance in the handling of high pressures and speeds. Due to this configuration, the most common faults are related to the wear and tear of internal components, which decrease the operational performance of the hydraulic system and increase maintenance costs. So, through data acquisition such as signals of pressure and the digital processing of them, it is possible to detect, classify, and identify faults or symptoms in hydraulic machinery. These activities form the basis of a condition-based maintenance (CBM) program. This chapter shows the developed methodology to detect and classify a wear fault of valve plate taking into account six conditions and the facilities providing by wavelet analysis and ANNs.
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