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Minimum entropy deconvolution based on simulation-determined band pass filter to detect faults in axial piston pump bearings
- Source :
- ISA transactions. 88
- Publication Year :
- 2018
-
Abstract
- The fault diagnosis of axial piston pumps is of significance for enhancing the reliability and security of hydraulic systems. Most of the faults occurring in the mechanical components of piston pumps are exhibited as fault-excited impulses. However, the strong impact-induced natural periodic impulses under the common working conditions (i.e. reciprocating motion of pistons) inevitably cause interference that considerably affects the fault detection performance. In this study, a simulation-determined band pass filter is employed to improve the performance of minimum entropy deconvolution (MED) for the fault diagnosis of axial piston pump bearings. First, a finite element method (FEM) simulation is performed to determine the possible carrier frequency. Second, the carrier frequency is used as the center frequency in association with a fixed bandwidth to determine the band pass filter parameters. Finally, the MED technique is applied to enhance weak fault-excited impulses by means of kurtosis maximization. Thereafter, envelope spectrum analysis is applied to the enhanced signals to obtain faulty feature frequencies. Two case studies are conducted, using bearings with faults in the outer and inner races of an axial piston pumps under common working conditions. The case studies confirm the necessity and effectiveness of the proposed method for detecting bearings faults in axial piston pumps.
- Subjects :
- Physics
0209 industrial biotechnology
Piston pump
Applied Mathematics
Acoustics
020208 electrical & electronic engineering
Bandwidth (signal processing)
Axial piston pump
02 engineering and technology
Fault detection and isolation
Finite element method
Computer Science Applications
Reciprocating motion
020901 industrial engineering & automation
Band-pass filter
Control and Systems Engineering
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Center frequency
Instrumentation
Subjects
Details
- ISSN :
- 18792022
- Volume :
- 88
- Database :
- OpenAIRE
- Journal :
- ISA transactions
- Accession number :
- edsair.doi.dedup.....ac5d03146a37d62fab9459c579ce108e