Combining inertia and constriction technique in the PSO applied to fault identification in a hydraulic system

Abstract

A novel methodology for simultaneous parametric fault isolation and mode switching identification in the spool motion of a Directional Control Valve (DCV), under multi fault assumption, has been reported in this paper. The shape of the profile traversed by the DCV spool was assumed to be trapezoidal in both healthy and faulty condition, but the slope of trapezoidal may change due to fault. Under this assumption, the real valued fault parameter and binary mode switching were identified by real valued Particle Swarm Optimization (PSO) alone instead of a combined real and binary valued PSO (Hybrid PSO). A novel PSO algorithm by combining the concepts of varying inertia weight (both increasing and decreasing trend) and constriction factor has been proposed in the article to achieve more accurate identification. Its validity was examined using an existing heuristic formula and by conducting several tests on a benchmark function used for fault identification. Superior improvement was observed in the identification with increasing inertia weight than that of widely used decreasing inertia weight, when combined with the constriction coefficient. A high pressure hydraulic circuit used in dumper and several other lifting machines was used as a simulation example.

Keywords

Electro-hydraulic systems trapezoidal motion profile mode switching identification multiple fault particle swarm optimization inertia weight constriction coefficient

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