Silverwing UK Ltd

Swansea, United Kingdom

Silverwing UK Ltd

Swansea, United Kingdom
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Zhang L.,University of Swansea | Belblidia F.,University of Swansea | Cameron I.,University of Swansea | Sienz J.,University of Swansea | And 2 more authors.
Journal of Nondestructive Evaluation | Year: 2015

We investigate the influence of the specimen velocity on the magnetic flux leakage with the aim of selecting the optimum sensor locations. Parametric numerical simulations where the specimen velocity was in the range [0.1–20] m/s were carried out. As the specimen velocity is increased, the magnetic field varies from being symmetrical to being asymmetric. For the radial magnetic induction $$B_z$$Bz, the position at which the maximum difference between the minimum and maximum signal moves from the centre of the bridge towards the direction of the specimen movement. For the axial magnetic induction $$B_y$$By, the specimen velocity influence is dependent on the sensor location and a signal-velocity independent region was discussed. © 2015, Springer Science+Business Media New York.

Pearson N.R.,Silverwing UK Ltd. | Pearson N.R.,University of Swansea | Mason J.S.D.,University of Swansea | Priewald R.H.,University of Swansea
Insight: Non-Destructive Testing and Condition Monitoring | Year: 2012

In supply chains, such as those in the petrochemical industry, the above-ground storage tank (AST) plays an important role in ensuring a continuous flow of product and these, like other components, must undergo regular maintenance. While maintenance on the majority of surfaces of a typical AST can be conducted when in its normal operational condition, the AST floor presents a particular challenge because of its inaccessibility. As a consequence, the tank has to be periodically emptied and taken out of service to conduct inspections and the repair work deemed necessary. This is a costly activity, both in terms of loss of earnings and the maintenance operation itself. This paper addresses this situation and in particular looks at the operation of the AST together with the current limitations and possible enhancements to maintenance. The focus is on the AST floor as this is the primary component that characterises the out-of-service interval, an interval that needs to be minimal in terms of both duration and frequency. Strategies to achieve these goals are presented.

Priewald R.H.,University of Swansea | Magele C.,University of Graz | Ledger P.D.,University of Swansea | Pearson N.R.,Silverwing UK Ltd. | Mason J.S.D.,University of Swansea
IEEE Transactions on Magnetics | Year: 2013

This paper proposes a fast and effective method for reconstructing arbitrary defect profiles in steel plates from magnetic flux leakage (MFL) measurements widely used in nondestructive testing (NDT) of oil storage tanks and pipelines. The inverse reconstruction problem is formulated based on a nonlinear forward model using the finite element method (FEM) and is implemented in 2-D. A Gauss-Newton optimization is applied to reconstruct the defect geometry, using efficiently calculated Jacobian information directly derived from the FEM system matrix. © 1965-2012 IEEE.

Priewald R.H.,University of Swansea | Ledger P.D.,University of Swansea | Pearson N.R.,Silverwing UK Ltd | Mason J.S.D.,University of Swansea
Studies in Applied Electromagnetics and Mechanics | Year: 2014

The Magnetic flux leakage (MFL) method is commonly employed for the non-destructive evaluation (NDE) of steel plates used in the construction of oil storage tanks and pipelines, where large areas have to be covered within a short time. Due to fundamental characteristics of the MFL method, very narrow and deep pipe-type defects can produce very similar signals to wide and shallow lake-type defects. This inherent uncertainty of MFL can cause dangerous misinterpretations of the measurement data as crucially deep defects could remain unnoticed. This paper proposes a numerical method for the computation of the worst-case (WC) solution candidate to the inverse MFL problem in terms of defect depth, which produces MFL signals differing from the original data only within the limits of the measurement uncertainty. A fully nonlinear magnetostatic FEM model is used to create Taylor series expansions of the model error w.r.t. the multi-parametric surface profile in 2D, which is then iteratively changed into the WC estimate. The algorithm is explained and its effectiveness is illustrated for a particular simulation example, showing the resulting WC depths under different conditions. © 2014 The authors and IOS Press.

Boat M.,SilverwingUk Ltd. | Pearson N.,SilverwingUk Ltd. | Lieb R.,SilverwingUk Ltd. | Davies J.,SilverwingUk Ltd. | And 2 more authors.
NDT 2014 - 53rd Annual Conference of the British Institute of Non-Destructive Testing | Year: 2014

This paper is concerned with identifying the inherent Magnetic Flux Leakage (MFL) technology variables that affect the sizing of defects and the repeatability of results. External defect sizing factors such as operator competence and inspection environment are here assumed pacified and so not considered. With these extraneous variables removed saturation, calibration and defect geometry can be investigated, both globally and in the context of the technology employed herein. Under-saturation is revealed to be a major limiting factor in defect sizing. Consequently to overcome the limitations presented by under-saturation a new calibration procedure is proposed. Further suppositions pertaining to defect sizing are then verified empirically and in some cases confirmed via numerical simulation. The paper naturally concludes with a discussion of the results and where possible improvements could be made.

Silverwing U.K. Ltd | Date: 2012-10-03

The present invention discloses apparatus (2) and a method of inspecting plates or pipe walls of magnetisable material (8). The method comprises the steps of (i) creating a magnetic circuit that passes through a magnetising unit (6), a portion of the plate or pipe wall (8), and at least two air gaps between the magnetising unit (6) and the plate or pipe wall (8); (ii) measuring the magnetic reluctance of at least one of the air gaps at at least one position in the air gap; (iii) incorporating at least one of the measured magnetic reluctance values into one or more algorithms; and (iv) recording or displaying the result of the or each algorithm for each magnetic reluctance reading in association with information concerning the position of the or each magnetic reluctance reading on surface of plate or pipe wall (8).

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