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Hyper-Heuristic Capacitance Array Method for Multi-Metal Wear Debris Detection.


ABSTRACT: Online detection of fatigued wear debris in the lubricants of aero-engines can provide warning of engine failure during flight, thus having great economic and social benefits. In this paper, we propose a capacitance array sensor and a hyper-heuristic partial differential equation (PDE) inversion method for detecting multiple micro-scale metal debris, combined with self-adaptive cellular genetic (SA-CGA) and morphological algorithms. Firstly, different from the traditional methods, which are limited in multi-induction-Dirac-boundary-inversion, a mathematical model with non-local boundary conditions is established. Furthermore, a hyper-heuristic method based on prior knowledge is also proposed to extract the wear character. Moreover, a 12-plate array circulating sensor and corresponding detection system are designed. The experimental results were compared with the optical microscopy. The results show that under the conditions of 1~3 wear debris with diameters of between 250?900 ?m, the accuracy of the proposed method is 10?38% higher than those of the traditional methods. The recognition error of the wear debris counts decreases to 0.

SUBMITTER: Sun Y 

PROVIDER: S-EPMC6387040 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Hyper-Heuristic Capacitance Array Method for Multi-Metal Wear Debris Detection.

Sun Yanshan Y   Jia Lecheng L   Zeng Zhoumo Z  

Sensors (Basel, Switzerland) 20190126 3


Online detection of fatigued wear debris in the lubricants of aero-engines can provide warning of engine failure during flight, thus having great economic and social benefits. In this paper, we propose a capacitance array sensor and a hyper-heuristic partial differential equation (PDE) inversion method for detecting multiple micro-scale metal debris, combined with self-adaptive cellular genetic (SA-CGA) and morphological algorithms. Firstly, different from the traditional methods, which are limi  ...[more]

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