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Magneto-Optic Imaging for Aircraft Skins Inspection: A Probability of Detection Study of Simulated and Experimental Image Data

机译:用于飞机蒙皮检查的磁光成像:模拟和实验图像数据检测研究的可能性

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摘要

The increasing fleet of aging aircrafts has resulted in an increasing demand for cost effective nondestructive evaluation (NDE) techniques that are accurate, reliable, and easy to use. Magneto-Optic Imaging (MOI) is such a technique, which has gained wide acceptance for detection of both surface and subsurface defects in multi-layer aircraft structures. The main advantage of MOI is rapid inspection and ease of interpreting image data in contrast to complex impedance signals from conventional eddy current instruments. One missing piece of the puzzle for advanced MOI systems is how to quantitatively analyse the MO images, and understand the detectability limits when image data are acquired under varying operational conditions. This paper presents a probability of detection (POD) study that is conducted using both simulation model-predicted and experimental MO image data. Simulated panels from a 3-D FEM model and experimental panels with machined defects are used to generate data for interpretation by human inspectors or automated systems, and subsequently for POD studies. The POD curves demonstrate the merits in optimizing inspection parameters that maximized the performance of current MOI systems. Parameters quantifying the detectability of MO image data using skewness functions are also presented and discussed.
机译:日益老化的飞机机队不断增长,导致对准确,可靠且易于使用的经济高效的无损评估(NDE)技术的需求日益增长。磁光成像(MOI)是一种这样的技术,它已被广泛用于检测多层飞机结构中的表面和亚表面缺陷。与来自传统涡流仪器的复杂阻抗信号相比,MOI的主要优点是快速检查和易于解释图像数据。对于高级MOI系统,难题之一是如何定量分析MO图像,并了解在变化的操作条件下获取图像数据时的可检测性限制。本文介绍了使用模拟模型预测和实验MO图像数据进行的检测概率(POD)研究。来自3-D FEM模型的模拟面板和具有机加工缺陷的实验面板用于生成数据,以供人工检查员或自动化系统进行解释,然后用于POD研究。 POD曲线展示了优化检查参数的优点,该参数可最大化当前MOI系统的性能。还介绍和讨论了使用偏度函数量化MO图像数据可检测性的参数。

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