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Ascertaining the integrity of large steel structures such as storage tanks, pipes and vessels is a complex task. Silverwing (UK) Ltd has developed an inspection solution that can inspect, manage, present and generate reports. The inspection data generated from these large assets can be large, requiring gigabytes to even terabytes of storage and meticulous analysis. And while it is normally accepted that more data is always better, the ability to handle, analyse and report findings with vast amounts of information efficiently becomes a challenge. In this paper, examples are given towards illustrating how volumes of information is technically handled and how it can improve the efficiency of the overall inspection process from the measurement gathering stage to the report and how this can benefit the inspection company, asset integrity engineer and asset owner.

Magnetic flux leakage (MFL) continues to be a widely used approach to detect defects caused by corrosion in applications with large areas. The principal merit of MFL is that large areas can be covered relatively quickly making it beneficial for example in the inspection of asset components that are costly to expose and in large area; two good examples are the floor of above ground storage tanks or exceedingly large surface areas such as pipelines. Though rapid, MFL is continually reported to have limitations when estimating the geometry of defects. In this paper we introduce and define the frequency response (FR) of MFL in an attempt to understand the relationship between MFL and defect geometry. This novel approach describes the relationship between MFL and defect shape using simulated sinusoidal defects to reveal important fundamental characteristics of MFL.

This paper focuses on state-of-the-art Magnetic Flux Leakage (MFL) technology for the inspection of storage tank floors. The primary advantage of the MFL approach is the ability to locate and estimate the size of defects over large areas in a quick and efficient manner. As with any inspection approach, there are limitations which can influence the consistency and reliability of reported defects. However, MFL sometimes appears to be considered as a simple technology screening approach where any competent inspector can interoperate their signals. However, there are misconceptions of the approach that might simply be due to a lack of awareness. Some perceived limitations will be outlined together with suggestions to reduce their effects. To assist with overcoming these parameters further, technological advancements such as a combination of high-resolution scanners and a complementary approach to top and bottom defect discrimination and lead more consistent and reliable inspections.

A primary reason for failure in above ground storage tanks (ASTs) is corrosion. The inability to accurately dene defects as a result of corrosion, particularly those located on the AST oor, can lead to erroneous repair strategies with costly outcomes. Therefore, accurately determining the geometry of defects is pivotal if an optimum repair strategy is to be formulated. Magnetic ux leakage (MFL) is a widely used and accepted technology for locating defects on a tank oor. While MFL signals are often linked to the volume of a defect, however its depth is perhaps the most dicult to estimate and the most critical dimension since it indicates the closeness of a potential leak. In this paper we look to establish a relationship between the defect and the corresponding MFL by analysing the inuence of two fundamental components of the defect geometry, namely the length and the depth. Keywords: Magnetic ux leakage (MFL), defect characteristics, defect normalisation, defect geometry.

Magnetic ux leakage (MFL) is a widely used approach to detect corrosion in applications where large areas are to be inspected in short time scales. A particularly good example is in above ground storage tanks (ASTs) within the petrochemical industry where tank oors are inspected periodically, calling for the AST to be taken out-of-service and emptied. This makes maintenance times that much more expensive and calls for techniques that are both reliable and fast. MFL is widely used in the context because of its inherent speed. Magnetic ux leakage (MFL) is a widely used and accepted technology for locating defects on a tank oor. While MFL signals are often linked to the volume of a defect, its depth is perhaps the most dicult to estimate and the most critical dimension since it indicates the closeness of a potential leak and if misinterpreted can lead to erroneous repair strategies with costly outcomes. Therefore, accurately determining the geometry of defects is pivotal if an optimum repair strategy is to be formulated. In this paper we look to understand why these relationships occur and attempt to minimise them by characterising the inuence of two fundamental components of the defect geometry, namely the length and depth. Analysis of the corresponding MFL signals leads to a novel, multi-valued reference map which is capable of reducing the depth error by around 40%. Keywords: Magnetic ux leakage (MFL), defect characteristics, defect normalisation, defect geometry.

INTRODUCTION
Magnetic Flux Leakage (MFL) and manual Ultrasonics (UT) have been used extensively for the detection and sizing of corrosion pits in ferrous plates and pipes. Users and providers of these inspection services may have different perceptions and expectations of the sensitivity and accuracy of the methods. This paper discusses the underlying principles of the methods and their effect on Probability of Detection (POD) and accuracy.
CORROSION PITTING
There are many types and mechanisms of corrosion but in this instance we deal exclusively with corrosion that is typical between the pad and the underside of tank bottoms or from water contamination inside the tank. The ultrasonic means of detecting erosion in pipework was so successful during the 1960's that it has given a false impression of the accuracy that will be obtained with pitting type corrosion. To help appreciate the difference we will illustrate erosion and some typical pit shapes. Figure 1 shows erosion whereas Figures 2 to 4 sketch corrosion shapes that have been given the terms "Lake Type", "Cone Type" and "Pipe Type".