RESEARCH ARTICLE
A Study on Oil Pipeline Risk Assessment Technique Based on Fuzzy Analytic Hierarchy Process
Hang Dong*, Lixin Wei, Qiannan Wang
Article Information
Identifiers and Pagination:
Year: 2014Volume: 7
First Page: 125
Last Page: 129
Publisher Id: TOPEJ-7-125
DOI: 10.2174/1874834101407010125
Article History:
Received Date: 16/09/2014Revision Received Date: 23/12/2014
Acceptance Date: 31/12/2014
Electronic publication date: 31/12/2014
Collection year: 2014
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Risk assessment of oil pipeline is the core content in the pipeline integrity management. Through risk assessment of oil pipelines, we could know the comprehensive operating condition of the pipelines, identify the dangerous factors of the pipeline and find out the risk section of the pipeline, so as to work out the risk mitigation measures and provide a theoretical basis for integrity assessment of the pipeline. However, the commonly used Kent risk assessment method does not have a very reasonable distribution of the failure indicator values. Therefore, this paper establishes a failure indicator value adjustment model for oil pipeline risk assessment based on the fuzzy analytic hierarchy process. Risk assessment of Qingha Oil Pipeline has been carried out based on the foundation data and real condition of the pipeline, and the established model was used for weighting adjustment of the various failure risk factors of the pipeline. Thus, a risk assessment model which is more suitable for Qingha Oil Pipeline was obtained. This laid a very solid foundation for proposal of suggestions on mitigation of risk of damage by the third party and the implementation of protective measures of the pipeline.