Defect detection and classification using a SQUID based multiple frequency eddy current NDE system

Kreutzbruck, Marc; Allweins, K.; Ruhl, T.; Heiden, C.; Krause, Hans‐Joachim; Hohmann, R.

doi:10.1109/77.919525

Cited by 27 publications

(8 citation statements)

References 11 publications

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“…SQUID sensor known to have an outstanding sensitivity in detecting signal frequency between near DC and low MHz range [41][42][43]. An experiment done by Faley et al [44] analysed a spectral density of the SQUID signal which shows a significant decrease of noise value especially in a strong magnetic field as illustrated in Figure 1.…”

Section: Superconducting Quantum Interference Device (Squid)mentioning

confidence: 99%

Theory and development of magnetic flux leakage sensor for flaws detection: A review

Sharif¹,

Ramli²,

Mohamed³

et al. 2019

IJAAS

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<p>This paper presents a review of state-of-art in the Magnetic Flux Leakage (MFL) sensor technology, which plays an important role in Nondestructive Testing (NDT) to detect crack and corrosion in ferromagnetic material. The demand of more reliable MFL tools and signal acquisition increase as it has a direct impact on structure integrity and can lead to be major catastrophic upon questionable signal analysis. This is because the size, cost, efficiency, and reliability of the extensive MFL system for NDT applications primarily depend on signal acquisition as a qualitative measure in producing a trustworthy analysis. Therefore, the selection of appropriate tools and methodology plays a major role in determining the comprehensive performance of the system. This paper also reviews an Artificial Neural Network (ANN) and Finite Element Method (FEM) in developing an optimum permeability standard on the test piece. </p>

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Section: Superconducting Quantum Interference Device (Squid)mentioning

confidence: 99%

Theory and development of magnetic flux leakage sensor for flaws detection: A review

Sharif¹,

Ramli²,

Mohamed³

et al. 2019

IJAAS

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“…So far, neural networks have been applied to various topics from fatigue prediction to wear simulation, and to monitoring of the manufacturing process and analysis of composite curing [18]. This technique was also applied to pattern classification in nondestructive detection by SQUIDs in the case of flaws in metals [19,20] and only recently in the case of impact damage in composite materials [21]. The structure used in [21] is a multilayered feed-forward network constructed with three layers of neurons: input, output and hidden layers (Fig.…”

Section: Neural Network System Applied To Cfrpmentioning

confidence: 99%

Nondestructive detection of damage in carbon fibre composites by SQUID magnetometry

Ruosi

2005

phys. stat. sol. (c)

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Monitoring of structural integrity is an essential issue in enhancing the affordability as well the safety of modern aircraft and spacecraft structures. Increasingly, metallic parts of aircrafts are being replaced by carbon fibre composite components due to their high strength and stiffness combined with low density. This paper reviews of the use of superconducting quantum interference devices (SQUIDs) in the detection of different types of damage in carbon fibre panels. The results presented here on impact damage on carbon fibre reinforced polymer and cracks induced by tensile loads on carbon fibre reinforced carbon matrix show that this method is sensitive not only to the presence but also the severity of damage. Indeed, it enables one to distinguish between the different failure mechanisms as the damage process evolves. SQUIDs response to artificial delaminations, flaws and deep-lying defects are also presented. The application of a neural network system for the detection of impact damage in a noisy environment is discussed. Experimental results demonstrate that nondestructive evaluation using SQUID magnetometers is a suitable technique to investigate composites to improve their mechanical properties

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“…The detection of deep, embedded cracks in multilayer riveted structures [ 1 , 2 , 3 , 4 ] is a major challenge in eddy-current (EC) non-destructive testing (NDT). Ultra-low frequency excitation along with giant magnetoresistive (GMR) sensor [ 5 ] to measure the induced magnetic field directly (EC-GMR) have been used to increase penetration depth as well as guarantee a good signal to noise ratio [ 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted Structures Inspection

Удпа

2016

Sensors

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In eddy current non-destructive testing of a multi-layered riveted structure, rotating current excitation, generated by orthogonal coils, is advantageous in providing sensitivity to defects of all orientations. However, when used with linear array sensors, the exciting magnetic flux density (Bx) of the orthogonal coils is not uniform over the sensor region, resulting in an output signal magnitude that depends on the relative location of the defect to the sensor array. In this paper, the rotating excitation coil is optimized to achieve a uniform Bx field in the sensor array area and minimize the probe size. The current density distribution of the coil is optimized using the polynomial approximation method. A non-uniform coil design is derived from the optimized current density distribution. Simulation results, using both an optimized coil and a conventional coil, are generated using the finite element method (FEM) model. The signal magnitude for an optimized coil is seen to be more robust with respect to offset of defects from the coil center. A novel multilayer coil structure, fabricated on a multi-layer printed circuit board, is used to build the optimized coil. A prototype probe with the optimized coil and 32 giant magnetoresistive (GMR) sensors is built and tested on a two-layer riveted aluminum sample. Experimental results show that the optimized probe has better defect detection capability compared with a conventional non-optimized coil.

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Defect detection and classification using a SQUID based multiple frequency eddy current NDE system

Cited by 27 publications

References 11 publications

Theory and development of magnetic flux leakage sensor for flaws detection: A review

Theory and development of magnetic flux leakage sensor for flaws detection: A review

Nondestructive detection of damage in carbon fibre composites by SQUID magnetometry

Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted Structures Inspection

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