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Title: Using the Villari effect to detect anomalies in steel materials
Author: Staples, Stephen George Henry
ISNI:       0000 0004 6497 3151
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2017
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Magnetostriction in various metals has been known since 1842. Recently the focus has shifted away from ferrous metals, towards materials with a straightforward or exaggerated stress magnetostriction relationship. However, there is an increasing interest in understanding ferrous metal relationships, especially steels, because of its widespread use in building structures, transport and equipment and pipelines. The purpose of this PhD is to develop the relationship between stress and magnetisation for commercial steel, such that experimental determination and theoretical modelling will allow prediction and location of stress concentration zones, which can in turn be identified as defects within the material. Such defects are either expected, such as weld joints, or unexpected such as damage caused by pipeline corrosion or dents. This will serve to support a magnetic field measurement instrument, developed in University of Leeds Electrical Engineering, to allow non- invasive inspection of underground pipelines, and the detection of any defects using the technique of measuring Self Magnetic Flux Leakage (SMFL) from the pipe material. Extensive trials show reliable field performance, basic algorithms can estimate pipeline integrity. The prototype is being used commercially by the project sponsor, and is the subject of a patent. Experimental measurement of magnetic fields around stress concentration zones supports the development of a theoretical model which will enhance the operation of the prototype exploiting this magnetic technique. The hypothesis proposed is that the magnetic flux observed from SCZ (Stress Concentration Zone) in steel objects is because of a flux leakage mechanism from a SCZ, which could be due to a defect or anomaly. A simple magnetic model is proposed, where a pipeline is represented as a series of connected bar magnets, the joints or welds in the pipeline are discontinuities which create a magnetic field pattern in the pipe sections and at the weld joints. These areas can be modelled and located by characterizing each region as a dipole, with resulting characteristic magnetic field patterns, particularly when they are resolved into orthogonal components. Pipeline defects can be similarly modelled, and given this characteristic magnetic pattern, the SCZ area can be located by magnetometry. Analysis of the forward problem, predicting magnetic field from a given steel material stress state, has indicated that observed magnetic field from flux leakage is of the same magnitude as that calculated from the bulk flux of the steel object. This has led to the solution for the inverse problem of estimating material stress from the measured magnetic field from flux leakage of SCZ. Algorithms have been developed that allow the calculation of pipeline stress, the estimation of pipeline depth and correction for the direction of the pipeline. A simple depth algorithm is required to estimate the distance from the magnetic field measurement, to the SCZ, in this case the depth algorithm has been shown, by field trials, to have a standard error of +/- 40 cm with a 70 % confidence level. In addition, a stress algorithm has been developed, with an estimated standard error of +/- 15 MPa, and the algorithm is judged to be capable of estimating pipeline stress to +/- 20 % of the absolute value, whilst this is insufficient for a detailed determination of pipeline integrity, it is sufficient to indicate potential problem areas, which then can be evaluated with established techniques. Field trials carried out on industrial underground pipelines show the technique can locate welds in the pipeline and that 81\% of welds are located within +/- 3m of ILI (in line inspection) reference data with a POD (probability of Detection) of 75%. Unexpected defects were located, 83% being found < 2m compared to ILI data, with a mean error of +/- 1m. These features are demonstrated in surveys carried out in conjunction with National Grid. Work on the location of weld position has also demonstrated that there is a capability for this system to be used in this mode, which is of importance to pipeline operators, as they use weld positions to find pipeline sections that have defects. This then leads to the conclusions that the prototype system developed, can in principle identify and locate SCZ, the aspect to be developed is the characterisation and the determination of the severity of either a defect in the pipeline or an expected SCZ such as a weld, which is the subject of further work, beyond this PhD.
Supervisor: Varcoe, Ben ; Freear, Steven Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available