STATISTICAL CALIBRATION OF PIPELINE IN-LINE INSPECTION DATA
This paper describes a statistical methodology for the calibration of in-line inspection (ILI) tools which is based on the comparison of the ILI readings with field-measurements results. The systematic and random errors that affect the ILI and the field tools are estimated and from this information, an unbiased estimation of the true depth of the defects detected by the ILI tool is produced. The influence of the number of field verifications on the reliability of the calibration process is addressed. The methodology is tested through Monte Carlo simulations and illustrated using a real-life ILI dataset produced by an UT tool. Introduction: Today in-line inspection (ILI) tools used to detect, locate and size pipeline anomalies such as dents, cracks and corrosion metal loss are based on the magnetic flux leakage (MFL) and ultrasonic (UT) principles [1]. The information provided by ILI tools consists of geometrical data describing each detected anomaly, e.g. its length, depth, width and orientation. This information is affected by built-in measurement errors, both systematic and random, that have to be considered when the ILI data is used to conduct integrity studies and fitness-forpurpose investigations. Pipeline integrity analysts and ILI vendors are now aware of the fact that in assessing the severity of a defect, the key issue is how accurately its geometry has been measured. In this sense, the two important parameters that ILI vendors provide are the probability of detection (POD) and the sizing accuracy of the tool. The sizing accuracy associated with an ILI tool is quoted as an accuracy level and a percent confidence. The depth sizing accuracy associated with corrosion metal loss of today high resolution (HR) MFL tools is typically claimed to be ±10% of the pipe wall thickness (wt) with a confidence level of 80%. In the case of extra high resolution (XHR) MFL tools, the sizing accuracy is ±5% wt at 80% confidence. On the other hand, today HR and XHR UT tools are claimed to have a sizing accuracy of ±0.6 mm and ±0.3 mm at a confidence level of 80%, respectively [1]. Pipeline operators assess the accuracy of a pipeline inspection through the statistical comparison of the metal loss sizes predicted by the ILI tool with the sizes obtained through field inspections. (a) 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100
Error-reduction approach for corrosion measurements of pipeline inline inspection tools
Inline inspection tools that are used to scan the interior defects of gas and oil pipelines tend to suffer from measuring error due to their sizing accuracy. This error often causes an over- or under-estimation of the operating conditions of the pipeline, which might lead to a system failure. While parametric calibration models provide a simple method to reduce the measuring error, it is limited to datasets that follow the normal distribution only. Thus, in this paper, a non-parametric calibration model based on k-nearest neighbor interpolation was proposed to improve the measurements recorded by the scanning tools. Corrosion data collected using an ultrasonic scan device and the magnetic flux leakage intelligent pig are considered in the research. The k-nearest neighbor interpolation is studied based on the effect of using six kernel functions with two different positioning approaches on the interpolation behavior. The results have shown enhancement in the accuracy of the readings obtained from the intelligent pig from ±20% of the pipeline wall thickness to only ±8%. This enhancement in the sizing accuracy is meant to prevent a possible system failure for using the corroded part of the studied pipeline for an extra 4.6 years instead of replacing it.
Neutron Residual Stress Measurements on Rail Sections for Different Production Conditions
Rail sectioning with subsequent neutron diffraction experiments has been used to assess residual stresses in the rails. In this study we present the results of neutron stress measurements performed at the NIST Center for Neutron Research (NCNR) on rail sections from rails that were produced under various conditions. Specifically, these are air-cooled, air-cooled and roller-straightened, head-hardened and head-hardened and roller-straightened. More significantly, a head-hardened and roller-straightened rail was also studied after service to elucidate evolution of the service-induced residual stresses. In the latter case both a transverse-cut slice and the central region of a 0.53 m long piece were studied. Measurements on this piece are the first in which triaxial stresses have been determined for an intact rail. Neutron strain measurements with 3×3×3 mm3 spatial resolution were successfully employed for transversally cut slices to verify the difference in the stress state depending on the production process. Although examination of slices allows determination of only two-dimensional stresses in the plane of the slice, additional measurements on obliquely-cut slices, which were also carried out, and utilization of FEM gives the possibility of reconstructing the full triaxial stress distribution. Together, these approaches provide a better understanding of rail fabrication and the possibility of improving the durability and safety of rails in the future.Copyright © 2004 by ASME