Abstract

The twin-screw pump (TSP) is widely used in naval engineering for seawater transportation and treatment. However, the diverse composition of seawater, often containing impurities, poses a risk of screw corrosion and jamming of clearances. Detecting the compact internal structure's clearance between rotor and stator (GAPR) proves challenging. To address these challenges, a novel approach combining chaos theory's reconstructive phase space technique was proposed for processing pressure pulsation signals. The research found that only specific monitoring points displayed chaotic characteristics in pressure pulsation signals. The attractor structure complexity increased with GAPR changes, while the chaotic features decreased. Nonlinear analysis of pulsation signals at different GAPR values allowed determining reasonable ranges. Applying support vector classification algorithm based on chaotic dynamics achieved an impressive 89% accuracy in identifying GAPR values. This study offers practical insight for TSP fault detection and operational optimization, holding significance in both theory and practice.

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