A hybrid approach to hydraulic vane pump condition monitoring and fault detection

Transactions of the ASABE

Volumn 49, Issue 4, 2006, Pages 1203-1211

  Hancock, K Monette ^a   Zhang, Qin ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

Adaptive neuro fuzzy inference; Condition based monitoring; Fault detection; Hydraulic vane pump; Wavelet analysis

Indexed keywords

ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS); FAULT DETECTION; HYDRAULIC VANE PUMPS; OIL ANALYSIS; WAVELET PACKET ANALYSIS;

CONDITION MONITORING; FUZZY SETS; INFERENCE ENGINES; REAL TIME SYSTEMS; VIBRATIONS (MECHANICAL);

VANE PUMPS;

DETECTION METHOD; FAULT DISPLACEMENT; HEALTH MONITORING; HYBRID; HYDRAULIC PROPERTY; OIL; PUMP; RESEARCH WORK; VIBRATION; WAVELET ANALYSIS;

EID: 33750585063     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (29)

1. Boller, C. 2000. Next-generation structural health monitoring and its integration into aircraft design. International J. Systems Science 31(11): 1333-1349.
2. Caterpillar 1999. Understanding the S.O.S. Oil Analysis Tests. PEHP7076-01. Peoria, Ill.: Caterpillar, Inc.
3. Deere. 2005. PowerGard protection plan. Moline, Ill.: Deere & Company. Available at: www.deere.com/en_US/ag/servicesupport/powegard. Accessed 9 March 2005.
4. Edwards, D. J., G. D. Holt, and F. C. Harris. 1998. Predictive maintenance techniques and their relevance to construction plant. J. Quality Maintenance 4(1): 25-37.
5. Fitch, J. C. 2001. Advancements in fluid analysis technologies and strategies for hydraulic system condition-based maintenance. In Hydraulic Failure Analysis: Fluids, Components, and System Effects, 225-247. Philadelphia, Pa.: ASTM.
6. Gao, Y., Q. Zhang, and X. Kong. 2003. Wavelet-based pressure analysis for hydraulic pump diagnosis. Trans. ASAE 46(4): 969-976.
7. Hancock, K. M., and Q. Zhang. 2005. Maintenance and fault diagnostic tools for hydraulic pumps. In Proc. 50th National Conference on Fluid Power, 363-369. Milwaukee, Wisc.: NFPA.
8. He, D., X. Wang, A. Babayan, and Q. Zhang. 2002a. Intelligent equipment health diagnosis and prognosis using wavelets: The status of research and industrial applications. In Proc. Automation Technology for Off-Road Equipment, 77-88. St. Joseph, Mich.: ASAE.
9. He, Y., Q. Zhang, and L. Feng, 2002b. Engine real-time fault diagnosis using neural networks. In Proc. Automation Technology for Off-Road Equipment, 89-95. St. Joseph, Mich.: ASAE.
10. Jardine, A. K. S., D. Banjevic, M. Wiseman, S. Buck, and T. Joseph. 2001. Optimizing a mine haul truck wheel motors' condition monitoring program: Use of proportional hazards modeling. J. Quality Maintenance Eng. 7(4): 286-301.
11. Koppen-Seliger, B., and P. M. Frank. 1999. Fuzzy logic and neural networks in fault detection. In Fusion of Neural Networks, Fuzzy Sets, and Genetic Algorithms: Industrial Applications, 171-109. L. C. Jain and N. M. Martin, eds. New York, N.Y.: CRC Press.
12. Liberatore, S., J. L. Speyer, and A. C. Hsu. 2003. Fault detection filter applied to structural health monitoring. In Proc. 42nd IEEE Conference on Decision and Control, 1944-1949. Piscataway, N.J.: IEEE
13. Ludema, K. C. 2001. Tribological design: A real-world approach. In Hydraulic Failure Analysis: Fluids, Components, and System Effects, 3-12. Philadelphia, Pa.: ASTM.
14. Lurette, C., and S. Lecoeuche. 2003. Unsupervised and auto-adaptive neural architecture for on-line monitoring: Application to a hydraulic process. Eng. Applications Artificial Int. 16(5-6): 441-451.
15. Macian, V., B. Tormos, P. Olmeda, and L. Montoro. 2003. Analytical approach to wear rate determination for internal combustion engine condition monitoring based on oil analysis. Tribology International 36(10): 771-776.
16. Martin, K. F. 1994. A review by discussion of condition monitoring and fault diagnosis in machine tools. Int. J. Mach. Tools Manufact. 34(4): 527-551.
17. Mathworks. 2005. Fuzzy Logic Toolbox User's Guide. Version 2. Natick, Mass.: Mathworks, Inc.
18. Misti, M., Y. Misti, G. Oppenheim, and J. Poggi. 1997. Wavelet Toolbox User's Guide. Version 3. Natick, Mass.: Mathworks, Inc.
19. Mitchell, J. S. 1999. The history of condition monitoring and condition-based maintenance. Sound and Vibration 33(11): 21-28.
20. Momoh, J., and D. T. Rizy. 1996. Application of wavelet theory to power distribution systems for fault detection. In Proc. International Conference on Intelligent Systems Applications to Power Systems, 345-350, Piscataway, N.J.:IEEE.
21. Saadat, S., G. D. Bucknera, T. Furukawab, and M. N. Nooria. 2004. An intelligent parameter varying (IPV) approach for non-linear system identification of base excited structures. Int. J. Non-Linear Mechanics 39(6): 993-1004.
22. Sculthorpe, B. R. 2002. Maintenance for the millennium: Another approach. In Proc. ICONE 10th International Conference on Nuclear Engineering, 25-28. New York, N.Y.: ASME.
23. Song, R., and N. Sepehri. 2002. Fault detection and isolation in fluid power systems using a parametric estimation method.In Proc. 2002 Canadian Conference on Electrical and Computer Engineering, 144-149. Piscataway, N.J.: IEEE.
24. Tanaka, M. 1999. Application of the neural network and fuzzy logic to the rotating machine diagnosis. In Fusion of Neural Networks, Fuzzy Sets, and Genetic Algorithms: Industrial Applications, 213-228. L. C. Jain and N. M. Martin, eds. New York, N.Y.: CRC Press.
25. Viall, A. 2005. Fault diagnosis of a hydraulic vane pump. MS thesis. Urbana, Ill.: University of Illinois at Urbana Champaign, Department of Agricultural and Biological Engineering.
26. Vickers. 2002. The systemic approach to contamination control: A complete guide for maximum system performance. Document 561. Eden Prairie, Minn.: Eaton Fluid Power. Available at: http://hydraulics.eaton.com/products/pdfs/561.pdf. Accessed 3 September 2004.
27. Wetzer, J. M., G. J. Cliteur, W. R. Rutgers, and H. F. A. Verhaart. 2000. Diagnostic and condition assessment techniques for condition based maintenance. In 2000 Annual Report: Conference on Electrical Insulation and Dielectric Phenomena 1: 47-51. Piscataway, N.J.: IEEE.
28. Wolfram, A., D. Fussel, T. Brune, and R. Isermann. 2001. Component-based multi-model approach for fault detection and diagnosis of a centrifugal pump. In Proc. 2001 American Control Conference, 4443-4448. American Automatic Control Council.
29. Yu, D. 1997. Fault diagnosis for a hydraulic drive system using a parameter-estimation method. Control Eng. Practice 5(9): 1283-1291.