Identification of filter management strategy in fluid power systems under uncertainty: an interval-fuzzy parameter integer nonlinear programming method

Abstract

An interval-fuzzy integer nonlinear programming (IFINP) method is developed for the identification of filter allocation and replacement strategies in a fluid power system (FPS) under uncertainty. It can handle uncertainties expressed as interval-fuzzy values that exist in the left- and right-hand sides of constraints as well as in the objective function. The developed method is applied to a case of planning filter allocation and replacement strategies under uncertainty for a FPS with a single circuit. A piecewise linearisation approach is used to convert the nonlinear problem of FPS into a linear one. The generated fuzzy solutions will be used to analyse and interpret the multiple decision alternatives under various system conditions, and thus help decision-makers to make a compromise among the system contamination level, system cost, satisfaction degrees and system-failure risks under different contaminant ingression/generation rates. The results demonstrate that the suction and return filters can effectively reduce the contamination level associated with a low system cost, but the FPS will take lots of failure risk when the contaminant ingression/generation rate is high; and the combination of suction and pressure filters can bring the lowest system cost with more security instead. Furthermore, comparisons for the optimised solutions are made among IFINP, interval-parameter integer nonlinear programming and deterministic linear programming also. Generally, the IFINP method can effectively reduce the total design and operation cost of the filtration system when contaminants ingression/generation rate is high, and it could be extended to the lubricating system.

Keywords:

• contamination control
• decision-making
• hydraulic system
• interval-fuzzy optimisation
• integer programming
• uncertainty

Acknowledgements

This research was funded by the Natural Science Foundations of China (Nos 50675074 and 50775081), National High-tech R&D (863) Programme (No. 2006AA09Z238), NCET of State Education Ministry (No. NCET-07-0330) and PHR (IHLB) 20090203. The authors are grateful to the editor and the anonymous reviewers for their insightful and helpful comments and suggestions.