Eddy current-based techniques have been investigated for the inspection of embedded cracks under fastener heads in riveted structures. However, these techniques are limited in their ability to detect cracks that are not perpendicular to induced current flows. Further, the presence of a steel fastener of high permeability produces a strong signal that masks relatively smaller indication from a crack. In this paper, a rotating electromagnetic field is designed to rotate the applied magnetic fields and related eddy currents electrically so that the sensor shows uniform sensitivity in detecting cracks in all radial directions around fastener sites. Giant magnetoresistive sensors are employed to image the normal component of this rotating field, to detect different crack orientations at aluminum and ferromagnetic fastener sites. Numerical model-based studies and experimental validation are presented.Index Terms-Eddy current, giant magnetoresistive sensor, rotating electromagnetic field, fastener hole inspection, NDE.

This milestone report presents an update on the state-of-the-art review and research being conducted to identify key indicators of cable aging at nuclear power plants (NPPs), and devise in-situ measurement techniques that are sensitive to these key indicators. The motivation for this study stems from the need to address open questions related to nondestructive evaluation (NDE) of aging cables for degradation detection and estimation of condition-based remaining service life. These questions arise within the context of a second round of license extension for NPPs that would extend the operating license from 60 to 80 years. Within the introduction, a review of recent published U.S. and international research and guidance for cable aging management programs including NDE technologies is provided. As with any "state-of-the-art" report, the observations are deemed accurate as of the publication date but cannot anticipate evolution of the technology. Moreover, readers are advised that research and development of cable NDE technology is an ongoing issue of global concern.Cable safety factors offer significant margin for normal operation and consequently most cables can be expected to perform satisfactorily under normal loads. Cables are inherently tested as part of the regular system tests that are periodically performed on nuclear plant systems and active components. As emphasized in Regulatory Guide 1.128, the cable aging management program focuses on the ability of a cable to withstand extreme stresses such as in a design-basis event (DBE) that may not be addressed with normal system tests. Degradation of the electrical insulation and other cable components are key issues that are likely to affect the ability of the currently installed cables to operate safely and reliably under a DBE for another 20 to 40 years beyond the initial qualified operating life. With more than 1000 km of power, control, instrumentation, and other cables typically found in a NPP, it would be a daunting undertaking to inspect all of the cables. Practical guidelines, however, have been developed and are evolving that offer a manageable approach to sampling and screening cables based on accessibility, risk, history, and other factors. Moreover, the range of cables and conditions plus today's state of the art does not support a single test to assure the cable's function. Rather, a range of testing tools must be applied to manage the cable aging concerns and assure that degraded cables are repaired or replaced prior to the end of their safe operating life. Cable aging management program recommendations include a database of cables selected for test and trending including the required appropriate cable test based on accessibility, risk, and environment. Such tests include bulk electrical characteristic measurements that can be made from the cable ends and, in some cases, locate the weak portion of the cable as well as local tests to confirm insulation condition and provide guidance to predict remaining available safe life.The Pacific Northwest Nat...

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Guided wave structural health monitoring uses sparse sensor networks embedded in sophisticated structures for defect detection and characterization. The biggest challenge of those sensor networks is developing robust techniques for reliable damage detection under changing environmental and operating conditions (EOC). To address this challenge, we develop a novelty classifier for damage detection based on one class support vector machines. We identify appropriate features for damage detection and introduce a feature aggregation method which quadratically increases the number of available training observations. We adopt a two-level voting scheme by using an ensemble of classifiers and predictions. Each classifier is trained on a different segment of the guided wave signal, and each classifier makes an ensemble of predictions based on a single observation. Using this approach, the classifier can be trained using a small number of baseline signals. We study the performance using Monte-Carlo simulations of an analytical model and data from impact damage experiments on a glass fiber composite plate. We also demonstrate the classifier performance using two types of baseline signals: fixed and rolling baseline training set. The former requires prior knowledge of baseline signals from all EOC, while the latter does not and leverages the fact that EOC vary slowly over time and can be modeled as a Gaussian process.

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