S. Thirunavukkarasu

Flexible GMR Sensor Array for Magnetic Flux Leakage Testing of Steel Track Ropes

This paper presents design and development of a flexible GMR sensor array for nondestructive detection of service-induced defects on the outer surface of 64 mm diameter steel track rope. The number of GMR elements and their locations within saddle-type magnetizing coils are optimized using a three dimensional finite element model. The performance of the sensor array has been evaluated by measuring the axial component of leakage flux from localized flaw (LF) and loss of metallic cross-sectional area (LMA) type defects introduced on the track rope. Studies reveal that the GMR sensor array can reliably detect both LF and LMA type defects in the track rope. The sensor array has a fast detection speed along the length of the track rope and does not require circumferential scanning. It is also possible to image defects using the array sensor for obtaining their spatial information.

Three-Dimensional Finite Element Modeling of Remote Field Eddy Current Technique for Detection of Localized Defects

Three-dimensional finite element (FE) modeling of remote field eddy current (RFEC) technique has been performed to detect localized defects in ferromagnetic steam generator tubes. The excitation frequency, intercoil spacing, and the design of localized receiver coil have been optimized using this model. Amplitude and phase of RFEC signals of radial and axial receiver coils have been predicted for a through hole and two flat bottom holes (FBH). The detection sensitivity of the receiver coils has been compared, and the model has been validated for a few cases.

Eigenvalue-Based Approach for Enhancement of Eddy Current Images of Shallow Defects

An eigenvalue-based approach is proposed for enhancement of eddy current images. The images are obtained by raster scanning an absolute eddy current probe over defects in a ferromagnetic carbon steel plate and by measuring the changes in probe impedance. During eddy current testing of ferromagnetic materials, variations in local magnetic permeability produce incoherent noise as compared to systematic impedance changes due to defects. In the proposed approach, eigen pairs of image covariance matrix are determined, and only the significant eigen pairs that have maximum information of the impedance changes due to defects are utilized to reconstruct images free from noise attributable to permeability variations. The capability of the proposed approach is assessed using eddy current images of a hole and a machined notch in a carbon steel plate.

Enhancement of magnetic flux leakage images of defects in carbon steel using Eigen vector based approach

Magnetic flux leakage images of defects are affected by incoherent noise due to non-linear permeability, surface roughness, stresses and lift-off variations. In this paper, an approach that utilizes the energy packing property of the Eigen values is used to process the tangential component images of machined notches in carbon steel plates. These images are obtained by scanning Giant-magneto resistive (GMR) sensor. In this approach, Eigen values and vectors of image covariance matrix are determined and images are reconstructed after considering the most significant Eigen pair that has the information of defects. The quality of reconstruction is assessed using signal to noise ratio and a new factor called noise reduction factor. Significant enhancement in image quality is observed enabling reliable detection of sub-surface notch located 8.6 mm below surface and a 1.1 mm deep surface-breaking notch.

MAGNETIC FLUX LEAKAGE NDE USING GIANT MAGNETO‐RESISTIVE (GMR) SENSORS

Giant magneto‐resistive (GMR) sensors are used in this study for detection of tangential component of magnetic field leakage (MFL) from sub‐surface notches in 12 mm thick carbon steel plates. The sensor output is amplified selectively for reliable detection of notches located at 8.68 mm below the scanning surface. In order to suppress variations in magnetic permeability, surface roughness and stresses that produced incoherent noise in MFL images, an Eigen value based approach has been applied.

Methodology for non‐destructive assessment of integrity of steam generator shell welds

Purpose – Development of non‐destructive methodology for detection of arc strike, spatter and fusion type of welding defects which may form on steam generator (SG) tubes that are in close proximity to the circumferential shell welds. Such defects, especially fusion‐type defects, are detrimental to the structural integrity of the SG. This paper aims to focus on this problem.Design/methodology/approach – This paper presents a new methodology for non‐destructive detection of arc strike, spatter and fusion type of welding defects. This methodology uses remote field eddy current (RFEC) ultrasonic non‐destructive techniques and K‐means clustering.Findings – Distinctly different RFEC signals have been observed for the three types of defects and this information has been effectively utilized for automated identification of weld fusion which produces two back‐wall echoes in ultrasonic A‐scan signals. The methodology can readily distinguish fusion‐type defect from arc strike and spatter type of defects.Originality/...