Pipeline Inspection and Health Monitoring Technology: The Key to Integrity Management

295 Pages·2023·8.346 MB·English

by  Hongfang Lu, Zhao-Dong Xu, Tom Iseley, Haoyan Peng, Lingdi Fu

Hongfang Lu · Zhao-Dong Xu ·
Tom Iseley · Haoyan Peng · Lingdi Fu
Pipeline
Inspection
and Health
Monitoring
Technology
The Key to Integrity Management
Pipeline Inspection and Health Monitoring
Technology
· · ·
Hongfang Lu Zhao-Dong Xu Tom Iseley
·
Haoyan Peng Lingdi Fu
Pipeline Inspection
and Health Monitoring
Technology
The Key to Integrity Management
Hongfang Lu Zhao-Dong Xu
China-Pakistan Belt and Road Joint China-Pakistan Belt and Road Joint
Laboratory on Smart Disaster Prevention Laboratory on Smart Disaster Prevention
of Major Infrastructures of Major Infrastructures
School of Civil Engineering School of Civil Engineering
Southeast University Southeast University
Nanjing, China Nanjing, China
Tom Iseley Haoyan Peng
Construction and Engineering Management China-Pakistan Belt and Road Joint
Purdue University Laboratory on Smart Disaster Prevention
West Lafayette, IN, USA of Major Infrastructures
School of Civil Engineering
Lingdi Fu Southeast University
Safety, Environment and Technology Nanjing, China
Supervision Research Institute
PetroChina Southwest Oil and Gasfield
Company
Chengdu, China
ISBN 978-981-19-6797-9 ISBN 978-981-19-6798-6 (eBook)
https://doi.org/10.1007/978-981-19-6798-6
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature
Singapore Pte Ltd. 2023
This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether
the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse
of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and
transmission or information storage and retrieval, electronic adaptation, computer software, or by similar
or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors, and the editors are safe to assume that the advice and information in this book
are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or
the editors give a warranty, expressed or implied, with respect to the material contained herein or for any
errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional
claims in published maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.
The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721,
Singapore
Preface
The pipeline is a crucial lifeline project that can transport oil, gas, water, and other
resources. It is often called the blood vessel of the energy system. Thus, pipeline
engineering is essential in ensuring national energy security, promoting economic
development, and ensuring social stability.
After many years of service, the pipeline gradually enters the aging stage. This
will inevitably lead to accidents and serious economic losses. In addition, accidents
in the city may lead to casualties, traffic paralysis, and other consequences. Using
advanced technology to understand the health status of pipelines is a very challenging
task in pipeline engineering.
In recent decades, many inspection and monitoring technologies have emerged
worldwide to assess pipelines’ conditions accurately. These technologies involve
acoustics, optics, and electromagnetism. Not only that, in the context of big data and
artificial intelligence, people use advanced computer and information techniques to
cooperate with inspection and monitoring to solve the problems encountered.
This book deals with interdisciplinary knowledge. It can let readers know about
the existing pipeline inspection and monitoring methods. This book is written for
managers, technicians, and researchers engaged in pipeline safety and can also
provide a reference for some graduate students engaged in relevant research. In
this book, a reader who wants to understand the background and health status of
global pipelines should read Chap. 1. In Chap. 2, pipeline inspection techniques
are described in detail, including visual, electromagnetic, acoustic, optical, and
chemical inspections, and the applicability of each method is indicated. Chapter 3
presents distributed fiber-optic and signal-based monitoring techniques for pipelines.
In Chaps. 4 and 5, some artificial intelligence-based methods and data processing
methods are presented. These contents mainly provide a reference for the post-
processing part of inspection or monitoring. In addition, we set up Chapter 6. By
providing several practical engineering cases, readers can have a more in-depth
understanding of the application of related technologies.
The first author, Dr. Hongfang Lu, would like to express his sincere gratitude to
his research advisor, Dr. Tom Iseley, for his support over the years. He would like
to thank his family members for their love and support. Moreover, he also would
v
vi Preface
like to thank his friends for their friendship and support. The second author, Dr.
Zhao-Dong Xu, would like to thank the Major Project of Fundamental Research
on Frontier Leading Technology of Jiangsu Province (Grant No. BK20222006) and
the National Key Research and Development Program of China (2019YFE0121900)
for their funding. The third author, Dr. Tom Iseley, would like to thank the Buried
Asset Management Institute-International (BAMI-I) for their support during the work
on this book. The fourth author, Mr. Haoyan Peng, would like to thank his family
members for their support. The fifth author, Ms. Lingdi Fu, would like to thank her
family members for their support.
The authors of this book would like to thank the editors for their effective
cooperation and great care in making possible the publication of this book.
Nanjing, China Hongfang Lu
Nanjing, China Zhao-Dong Xu
West Lafayette, USA Tom Iseley
Nanjing, China Haoyan Peng
Chengdu, China Lingdi Fu
Acknowledgements
This book was financially supported by the Major Project of Fundamental Research
on Frontier Leading Technology of Jiangsu Province (Grant No. BK20222006);
Natural Science Foundation of Jiangsu Province (Grant No. BK20220848), the
National Key Research and Development Program of China (2019YFE0121900); the
2022 Open Project of Failure Mechanics and Engineering Disaster Prevention, Key
Lab of Sichuan Province (Grant No. FMEDP202212); and the Zhejiang Engineering
Research Center of Intelligent Urban Infrastructure (Grant No. IUI2022-YB-02). We
also would like to thank the following people for their help:
Chapter 1:
John C. Matthews, Trenchless Technology Center, Louisiana Tech University,
Ruston, LA 71270, United States
Saleh Behbahani, Construction Engineering and Management, Purdue University,
West Lafayette, IN 47907, United States
Mohammadamin Azimi, GeoEngineers, Inc., San Diego, CA 92128, United States
Chapter 2:
John C. Matthews, Trenchless Technology Center, Louisiana Tech University,
Ruston, LA 71270, United States
Chapter 3:
Dongmin Xi, China-Pakistan Belt and Road Joint Laboratory on Smart Disaster
Prevention of Major Infrastructures, School of Civil Engineering, Southeast Univer-
sity, Nanjing, China
Chapter 4:
John C. Matthews, Trenchless Technology Center, Louisiana Tech University,
Ruston, LA 71270, United States
Chapter 6:
Houming Ni, Asoe Hose Manufacturing Inc., Taizhou 225319, China
Jing Li, Safety, Environment and Technology Supervision Research Institute of
PetroChina Southwest Oil and Gasfield Company, Chengdu, Sichuan, 610041, China
vii
viii Acknowledgements
Dong Lin, Safety, Environment and Technology Supervision Research Institute of
PetroChina Southwest Oil and Gasfield Company, Chengdu, Sichuan, 610041, China
Jian Gao, Safety, Environment and Technology Supervision Research Institute of
PetroChina Southwest Oil and Gasfield Company, Chengdu, Sichuan, 610041, China
Chaolang Li, Safety, Environment and Technology Supervision Research Institute
of PetroChina Southwest Oil and Gasfield Company, Chengdu, Sichuan, 610041,
China
Kebing Shi, Asoe Hose Manufacturing Inc., Taizhou 225319, China
Contents
1 Background and Health Problems of Pipelines .................... 1
1.1 Introduction ............................................... 1
1.2 Pipeline Classification and Construction Status ................. 1
1.3 Pipeline Health Status Globally ............................... 5
1.4 Pipeline Inspection Technology System ........................ 10
1.5 Technical System of Pipeline Health Monitoring ................ 10
1.6 Global Pipeline Inspection and Monitoring Standards
and Specifications .......................................... 11
References ..................................................... 18
2 Pipeline Inspection Technology .................................. 21
2.1 Introduction ............................................... 21
2.2 Visual Inspection Technology ................................ 21
2.3 Electromagnetic Inspection Technology ....................... 25
2.3.1 Magnetic Flux Leakage ............................... 25
2.3.2 Remote Field Eddy Current ............................ 28
2.3.3 Broadband Electromagnetic ........................... 31
2.3.4 Pulsed Eddy Current System ........................... 32
2.3.5 Ground Penetrating Radar ............................. 35
2.4 Acoustic Inspection Technology .............................. 37
2.4.1 Acoustic Emission Method ............................ 37
2.4.2 Ultrasonic Method ................................... 39
2.4.3 Ultrasonic Guided Wave Method ....................... 41
2.4.4 Echo Impact ......................................... 47
2.4.5 SmartBall ........................................... 48
2.4.6 Sonar System Method ................................ 51
2.4.7 Leakfinder .......................................... 53
2.4.8 Sahara .............................................. 54
2.5 Optical Inspection Technology ............................... 54
2.5.1 Lidar System ........................................ 54
2.5.2 Diode Laser Absorption Method ....................... 56
ix
x Contents
2.5.3 Thermal Imaging .................................... 57
2.5.4 Spectral Imaging Method ............................. 59
2.6 Chemical Composition Analysis-Based Method ................. 60
2.6.1 Sniffer Method ...................................... 60
2.6.2 Vapor Sampling Method .............................. 60
2.7 Technology Selection Considerations .......................... 61
References ..................................................... 70
3 Pipeline Health Monitoring Technology .......................... 81
3.1 Introduction ............................................... 81
3.2 Optical Fiber Sensing ....................................... 81
3.2.1 Optical Time Domain Reflection (OTDR) ............... 83
3.2.2 Fiber Bragg Grating (FBG) ............................ 87
3.2.3 Interferometric Optical Fiber Sensor .................... 89
3.3 Signal-Based Method ....................................... 93
3.3.1 Volume/Mass Balance Method ......................... 93
3.3.2 Negative Pressure Wave Method ....................... 94
3.3.3 GPS Time Label Method .............................. 96
3.3.4 Pressure Point Analysis Method ........................ 96
3.3.5 Cross Correlation Analysis ............................ 97
3.3.6 Transient Test-Based Technique ........................ 98
3.3.7 State Estimation Method .............................. 104
3.4 Technology Selection Considerations .......................... 106
References ..................................................... 111
4 Health Monitoring Technology Based on Artificial Intelligence ..... 117
4.1 Introduction ............................................... 117
4.2 Classic Models ............................................. 117
4.2.1 Linear Regression .................................... 117
4.2.2 Naive Bayes ......................................... 118
4.2.3 Artificial Neural Network ............................. 118
4.2.4 Kernel-Based Model ................................. 119
4.2.5 Decision Tree Method ................................ 124
4.2.6 Deep Learning ....................................... 127
4.3 Optimizers ................................................ 128
4.3.1 Fruit Fly Optimizer ................................... 128
4.3.2 Grey Wolf Optimizer ................................. 131
4.3.3 Whale Optimization Algorithm ........................ 133
4.3.4 Nondominated Sorting Genetic Algorithm II ............. 134
4.3.5 Multi-objective Grey Wolf Optimizer ................... 136
4.3.6 Multi-objective Salp Swarm Algorithm .................. 136
4.4 Application Scenarios ....................................... 138
4.4.1 Fault Diagnosis ...................................... 138
4.4.2 Risk Prediction ...................................... 139
4.4.3 Condition-Related Parameter Prediction ................. 140