Fuzzy Expert System for Defect Classification for Non-Destructive Evaluation of Petroleum Pipes

U. Qidwai, M. Maqbool
{"title":"Fuzzy Expert System for Defect Classification for Non-Destructive Evaluation of Petroleum Pipes","authors":"U. Qidwai, M. Maqbool","doi":"10.1109/IBCAST.2007.4379912","DOIUrl":null,"url":null,"abstract":"In this paper, an expert system has been outlined to classify the defects in metallic petroleum pipelines using acoustic techniques with non-destructive evaluation (NDE) protocols, the proposed system maps the quantitative defect data through a novel perception-based kernel that has its roots in multidimensional fuzzy set theory to map the relative weights given to various features; mathematical or statistical, to the decision surface to deduce the type of the defect. The system has a centralized database which holds the defect information in the form of known and calculated features. The known features and their quantitative representations are used to initialize the database. Then experiments are conducted on known defects and the collected experimental data is then modeled into autoregressive process models using state of the art ltinfin deconvolution algorithm. With each feature set, a classifier tag is associated that assigns a class number to that defect. The classifier tag is then used to classify any new data using the fuzzy classifier.","PeriodicalId":259890,"journal":{"name":"2007 International Bhurban Conference on Applied Sciences & Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Bhurban Conference on Applied Sciences & Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBCAST.2007.4379912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In this paper, an expert system has been outlined to classify the defects in metallic petroleum pipelines using acoustic techniques with non-destructive evaluation (NDE) protocols, the proposed system maps the quantitative defect data through a novel perception-based kernel that has its roots in multidimensional fuzzy set theory to map the relative weights given to various features; mathematical or statistical, to the decision surface to deduce the type of the defect. The system has a centralized database which holds the defect information in the form of known and calculated features. The known features and their quantitative representations are used to initialize the database. Then experiments are conducted on known defects and the collected experimental data is then modeled into autoregressive process models using state of the art ltinfin deconvolution algorithm. With each feature set, a classifier tag is associated that assigns a class number to that defect. The classifier tag is then used to classify any new data using the fuzzy classifier.
石油管道无损评价缺陷分类模糊专家系统
本文提出了一种基于无损评价(NDE)协议的声学技术对金属石油管道缺陷进行分类的专家系统,该系统通过一种新颖的基于感知的核来映射定量缺陷数据,该核基于多维模糊集理论来映射赋予各种特征的相对权重;数学的或统计的,到决策面来推断缺陷的类型。该系统有一个集中的数据库,以已知和计算特征的形式保存缺陷信息。已知特征及其定量表示用于初始化数据库。然后对已知缺陷进行实验,并利用最先进的ltinfin反卷积算法将收集到的实验数据建模为自回归过程模型。对于每个特征集,一个分类器标签被关联起来,它为该缺陷分配一个类号。然后使用分类器标签对使用模糊分类器的任何新数据进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信