A survey of approaches for fault diagnosis in axial piston pumps

Jessica Gissella Maradey Lázaro, Carlos Borrás Pinilla, Sebastian Roa Prada

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Axial piston variable displacement pumps (VDAP) are the heart of every hydraulic system, and are they commonly used in the industry for its high capacity, efficiency (volume and total), and good performance in the handling of high pressures and speeds. Faults are usually associated with wear and leakage processes, which cause significant decreases in performance. This paper discusses about the advantages to implement a Condition-based Maintenance (CBM) and the use of techniques of fault diagnosis in axial variable displacement piston pumps (VDAP), as they are: Neural Networks (NN), Support Vector Machine (SVM) and Fuzzy Logic (FL) and other hybrid models. The results of this investigation provide guidelines for the selection of the most suitable technique to prevent faults in VDAP in order to help reducing down time, increase productivity and competitiveness of companies that requires the use of fluid power systems by enabling the implementation of a non-intrusive fault diagnosis management system, which must be reliable, economical and easily accessible to the industry.

Original languageEnglish
Title of host publicationDynamics, Vibration, and Control
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791850541
DOIs
StatePublished - 2016
EventASME 2016 International Mechanical Engineering Congress and Exposition, IMECE 2016 - Phoenix, United States
Duration: 11 Nov 201617 Nov 2016

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume4A-2016

Conference

ConferenceASME 2016 International Mechanical Engineering Congress and Exposition, IMECE 2016
Country/TerritoryUnited States
CityPhoenix
Period11/11/1617/11/16

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