PSO-aided fuzzy inference of material elastic constants with resonant ultrasound spectroscopy

IF 1.1 4区工程技术 Q3 ENGINEERING, MULTIDISCIPLINARY Inverse Problems in Science and Engineering Pub Date : 2020-12-10 DOI:10.1080/17415977.2020.1856102

Kai Yang, Jinbo Liu, T. Zhu, Hui Wang, Xinxin Zhu

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Abstract

ABSTRACT Fuzzy inference method is applied to formulate an algorithm capable of estimating material elastic constants (ECs) of a specimen by solving an inverse problem with a group of measured resonance frequencies obtained via Resonant Ultrasound Spectroscopy (RUS). The algorithm is validated with RUS data from a specimen of polycrystalline aluminium alloy. Then the algorithm is found to be sensitive to the initial ECs by processing RUS data from a specimen of fine-grain polycrystalline Ti–6Al–4V, the same as the Levenberg–Marquardt (L–M) method popularly used in solving inverse problems. To overcome such a drawback, a hybrid method of Particle Swarm Optimization (PSO) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is proposed. And it is used to generate several groups of initial ECs for the fuzzy inference method. There is a trade-off between computational time and accurately estimated ECs, since the hybrid method needs more time to directly find out accurate ECs.

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PSO辅助共振超声谱模糊推理材料弹性常数

摘要采用模糊推理方法，通过求解共振超声光谱(RUS)测量的一组共振频率的反问题，建立了一种能够估计试样材料弹性常数(ECs)的算法。用多晶铝合金试样的RUS数据对算法进行了验证。然后，通过处理来自细晶粒多晶Ti-6Al-4V样品的RUS数据，发现该算法对初始ECs敏感，与求解反问题中常用的Levenberg-Marquardt (L-M)方法相同。为了克服这一缺点，提出了一种粒子群优化(PSO)和基于密度的带噪声应用空间聚类(DBSCAN)的混合方法。并利用模糊推理方法生成多组初始ec。由于混合方法需要更多的时间来直接找到准确的ECs，因此在计算时间和准确估计的ECs之间存在权衡。

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来源期刊

Inverse Problems in Science and Engineering 工程技术-工程：综合

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0.00%

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审稿时长

6 months

期刊介绍： Inverse Problems in Science and Engineering provides an international forum for the discussion of conceptual ideas and methods for the practical solution of applied inverse problems. The Journal aims to address the needs of practising engineers, mathematicians and researchers and to serve as a focal point for the quick communication of ideas. Papers must provide several non-trivial examples of practical applications. Multidisciplinary applied papers are particularly welcome. Topics include: -Shape design: determination of shape, size and location of domains (shape identification or optimization in acoustics, aerodynamics, electromagnets, etc; detection of voids and cracks). -Material properties: determination of physical properties of media. -Boundary values/initial values: identification of the proper boundary conditions and/or initial conditions (tomographic problems involving X-rays, ultrasonics, optics, thermal sources etc; determination of thermal, stress/strain, electromagnetic, fluid flow etc. boundary conditions on inaccessible boundaries; determination of initial chemical composition, etc.). -Forces and sources: determination of the unknown external forces or inputs acting on a domain (structural dynamic modification and reconstruction) and internal concentrated and distributed sources/sinks (sources of heat, noise, electromagnetic radiation, etc.). -Governing equations: inference of analytic forms of partial and/or integral equations governing the variation of measured field quantities.