Hydraulic Pump Fault Diagnosis Control Research Based on PARD-BP Algorithm

¹ Anhui Communications Vocational and Technical College, Hefei 230051, China
² Institute of Mechanical and Automotive Engineering, Hefei University of Technology, Hefei 230009, China
¹ Tel.: 18019565911, fax: 0551-63440696

¹ E-mail: 13866120116@139.com

Received: 18 August 2014 /Accepted: 20 October 2014 /Published: 31 December 2014

Abstract: Combining working principle and failure mechanism of RZU2000HM hydraulic press, with its present fault cases being collected, the working principle of the oil pressure and faults phenomenon of the hydraulic power unit –swash-plate axial piston pump were studied with some emphasis, whose faults will directly affect the dynamic performance of the oil pressure and flow. In order to make hydraulic power unit work reliably, PARD-BP (Pruning Algorithm based Random Degree) neural network fault algorithm was introduced, with swash-plate axial piston pump’s vibration fault sample data regarded as input, and fault mode matrix regarded as target output, so that PARD-BP algorithm could be trained. In the end, the vibration results were verified by the vibration modal test, and it was shown that the biggest upward peaks of vacuum pump in X-direction, Y-direction and Z- direction have fallen by 30.49 %, 21.13 % and 18.73 % respectively, so that the reliability of the fact that PARD-BP algorithm could be used for the online fault detection and diagnosis of the hydraulic pump was verified.

Keywords: RZU2000HM hydraulic press, Swash-plate axial piston pump, Vacuum self-priming, FAULT diagnosis, Modal test.

Click <here> or title of paper to download the full pages article in pdf format

Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)

Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com

Download <here> the Library Journal Recommendation Form

Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn