涡流微传感器与RBF神经网络用于表面小缺陷的检测与表征

IF 1 4区 工程技术 Q4 INSTRUMENTS & INSTRUMENTATION
Chifaa ABER, Azzedine Hamid, M. Elchikh, T. Lebey
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引用次数: 1

摘要

工业过程和制造零件的日益复杂,对服务安全性的需求日益增长,以及对零件寿命优化的愿望,要求实施越来越复杂的质量评估。在要考虑的各种异常中,亚毫米表面缺陷必须特别注意。这些缺陷是非常危险的,因为它们往往是更大缺陷的起点,如疲劳裂纹,这可能导致零件的破坏。由于渗透检测具有良好的性能,目前已广泛应用于此类缺陷的检测。然而,考虑到环境标准,最终还是应该放弃。在可能的替代方案中,涡流(EC)用于导电材料是一种可靠、快速和廉价的替代方案。研究了用于无损检测的微传感器涡流探头结构的设计和建模。为此采用了考虑传感器运动的动带有限元法,并在镍基合金试样上进行了实验验证。通过实验和仿真计算得到传感器各位置阻抗的实部和虚部符合较好。利用设计并实现的径向基函数神经网络(RBF NN)对裂纹检测质量进行量化,并对缺陷的几何特征进行估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eddy Current Microsensor and RBF Neural Networks for Detection and Characterization of Small Surface Defects
Abstract The growing complexity of industrial processes and manufactured parts, the growing need for safety in service and the desire to optimize the life of parts, require the implementation of increasingly complex quality assessments. Among the various anomalies to consider, sub-millimeter surface defects must be the subject of particular care. These defects are extremely dangerous as they are often the starting point for larger defects such as fatigue cracks, which can lead to the destruction of the parts. Penetrant testing is now widely used for this type of defect, due to its good performance. Nevertheless, it should be abandoned eventually due to environmental standards. Among the possible alternatives, the use of eddy currents (EC) for conductive materials is a reliable, fast, and inexpensive alternative. The study concerns the design and modeling of eddy current probe structures comprising micro-sensors for non-destructive testing. The moving band finite element method is implemented for this purpose to take into account the movement of the sensor, experimental validations were conducted on a nickel-based alloy specimen. The real and imaginary parts of the impedance at every position of the sensor computed by experiments and simulations were in good agreement. The crack detection quality was quantified and the geometric characteristics of the defects were estimated using RBF NN (Radial Basis Function Neural Networks) that were designed and implemented on the acquired signals.
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来源期刊
Measurement Science Review
Measurement Science Review INSTRUMENTS & INSTRUMENTATION-
CiteScore
2.00
自引率
11.10%
发文量
37
审稿时长
4.8 months
期刊介绍: - theory of measurement - mathematical processing of measured data - measurement uncertainty minimisation - statistical methods in data evaluation and modelling - measurement as an interdisciplinary activity - measurement science in education - medical imaging methods, image processing - biosignal measurement, processing and analysis - model based biomeasurements - neural networks in biomeasurement - telemeasurement in biomedicine - measurement in nanomedicine - measurement of basic physical quantities - magnetic and electric fields measurements - measurement of geometrical and mechanical quantities - optical measuring methods - electromagnetic compatibility - measurement in material science
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