Assessing the Probability of Detecting Crack Features using Ultrasonic In-line Inspection Tool Run Results and Excavation Data

At the 10th annual International Pipeline Conference in Calgary, Alberta, C-FER co-presented a paper with Enbridge which summarizes an investigation into the stress corrosion cracking (SCC) detection performance of ultrasonic in-line inspection tool that was evalulated using excavation data.  To request a free copy of this paper, complete the form at the bottom of the page.

Abstract

The probability of detection (POD) describes the ability of an in-line inspection (ILI) tool to detect cracks and is one of the key performance indicators for ILI system qualification. The POD of an ILI tool is often specified by the vendor as the probability of a feature above a certain threshold size being detected by the tool. To verify the POD performance of ILI tools, selected pipeline sections from the ILI runs are excavated and inspected. The excavation data provide valuable information that can be used to assess the performance that the ILI tool achieved in a field environment.

This paper analyzes the performance of an ultrasonic testing (UT) tool in detecting stress corrosion cracking (SCC) features using the ILI run results and excavation data from several operating pipelines. Analysis of the excavation data shows that the POD for SCC features is dependent on both the maximum depth and the longest interacting length of the feature. As the SCC becomes deeper and longer, the POD increases. An analytical POD model is described in which the POD of the UT tool for SCC features is modeled as a function of the maximum depth and the longest interacting length. Parameters of the POD model are estimated using a maximum likelihood method based on the ILI and excavation data. The analytical POD model provides refined means to evaluate the POD performance for SCC features of the tool. The methodology described in this paper can be used for similar analyses of POD performance of other tools or for other types of features.

Author: 

Lu, D., Skow, J. and Keane, S.

Publisher: 

10th International Pipeline Conference, Calgary, Alberta, September 29 – October 3

Year: 

2014

 

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