This book includes six chapters aiming to introduce global pipeline inspection and health monitoring technologies comprehensively. The pipeline is the blood vessel of the energy system and a vital lifeline project. After many years of service, the pipeline gradually enters the aging stage. Pipeline inspection and health monitoring can effectively reduce the failure and accident risks of the pipeline, and it is conducive to integrity management. Through case analysis, practitioners can have a deeper understanding of the application of related technologies.
Author(s): Hongfang Lu, Zhao-Dong Xu, Tom Iseley, Haoyan Peng, Lingdi Fu
Publisher: Springer
Year: 2023
Language: English
Pages: 294
City: Singapore
Preface
Acknowledgements
Contents
1 Background and Health Problems of Pipelines
1.1 Introduction
1.2 Pipeline Classification and Construction Status
1.3 Pipeline Health Status Globally
1.4 Pipeline Inspection Technology System
1.5 Technical System of Pipeline Health Monitoring
1.6 Global Pipeline Inspection and Monitoring Standards and Specifications
References
2 Pipeline Inspection Technology
2.1 Introduction
2.2 Visual Inspection Technology
2.3 Electromagnetic Inspection Technology
2.3.1 Magnetic Flux Leakage
2.3.2 Remote Field Eddy Current
2.3.3 Broadband Electromagnetic
2.3.4 Pulsed Eddy Current System
2.3.5 Ground Penetrating Radar
2.4 Acoustic Inspection Technology
2.4.1 Acoustic Emission Method
2.4.2 Ultrasonic Method
2.4.3 Ultrasonic Guided Wave Method
2.4.4 Echo Impact
2.4.5 SmartBall
2.4.6 Sonar System Method
2.4.7 Leakfinder
2.4.8 Sahara
2.5 Optical Inspection Technology
2.5.1 Lidar System
2.5.2 Diode Laser Absorption Method
2.5.3 Thermal Imaging
2.5.4 Spectral Imaging Method
2.6 Chemical Composition Analysis-Based Method
2.6.1 Sniffer Method
2.6.2 Vapor Sampling Method
2.7 Technology Selection Considerations
References
3 Pipeline Health Monitoring Technology
3.1 Introduction
3.2 Optical Fiber Sensing
3.2.1 Optical Time Domain Reflection (OTDR)
3.2.2 Fiber Bragg Grating (FBG)
3.2.3 Interferometric Optical Fiber Sensor
3.3 Signal-Based Method
3.3.1 Volume/Mass Balance Method
3.3.2 Negative Pressure Wave Method
3.3.3 GPS Time Label Method
3.3.4 Pressure Point Analysis Method
3.3.5 Cross Correlation Analysis
3.3.6 Transient Test-Based Technique
3.3.7 State Estimation Method
3.4 Technology Selection Considerations
References
4 Health Monitoring Technology Based on Artificial Intelligence
4.1 Introduction
4.2 Classic Models
4.2.1 Linear Regression
4.2.2 Naive Bayes
4.2.3 Artificial Neural Network
4.2.4 Kernel-Based Model
4.2.5 Decision Tree Method
4.2.6 Deep Learning
4.3 Optimizers
4.3.1 Fruit Fly Optimizer
4.3.2 Grey Wolf Optimizer
4.3.3 Whale Optimization Algorithm
4.3.4 Nondominated Sorting Genetic Algorithm II
4.3.5 Multi-objective Grey Wolf Optimizer
4.3.6 Multi-objective Salp Swarm Algorithm
4.4 Application Scenarios
4.4.1 Fault Diagnosis
4.4.2 Risk Prediction
4.4.3 Condition-Related Parameter Prediction
4.4.4 Visual Defect Recognition
4.5 Application Summary
4.5.1 Model Category
4.5.2 Model Framework
4.5.3 Data Size and Data Division
4.5.4 Input Variable
4.5.5 Error (Accuracy) Indicator
4.5.6 Real-World Applications
4.6 Specific Applications
4.6.1 Burst Pressure Prediction [236]
4.6.2 Pullback Force Prediction [229]
References
5 Data Preprocessing Technology in Pipeline Health Monitoring
5.1 Introduction
5.2 Advantages of Big Data
5.3 Data Correlation Theory
5.3.1 Chi-Square Test
5.3.2 Information Gain and Information Gain Ratio
5.3.3 Covariance
5.3.4 Correlation Coefficient
5.4 Data Dimensionality Reduction Method
5.4.1 Principal Component Analysis
5.4.2 Linear Discriminant Analysis
5.4.3 Locally Linear Embedding
5.4.4 Laplacian Eigenmaps
5.4.5 High Correlation Filtering
5.4.6 Factor Analysis
5.4.7 Independent Component Analysis
5.5 Data Noise Reduction Method
5.5.1 Wavelet Transform
5.5.2 Empirical Mode Decomposition
5.5.3 Variational Mode Decomposition
5.5.4 Singular Spectrum Analysis
5.6 Data Exception Elimination and Missing Supplement Methods
5.6.1 K-nearest Neighbor Substitution Method
5.6.2 Regression Filling Method
5.7 Multi-source Heterogeneous Data Fusion Method
References
6 Application and Cases of Pipeline Inspection and Monitoring
6.1 Introduction
6.2 Closed-Circuit Television (CCTV) Inspection
6.2.1 Considerations Before an Inspection
6.2.2 Project Description
6.2.3 Evaluation Results
6.3 Magnetic Flux Leakage Inspection
6.3.1 Project Description
6.3.2 Inspector Description
6.3.3 Inspection Process
6.4 Remote Field Eddy Current
6.4.1 Project Description
6.4.2 Inspector Description
6.4.3 Inspection Details
6.4.4 Inspection Results
6.5 Pipeline Monitoring in the Landslide Section
6.5.1 Project Description
6.5.2 Monitoring Details
6.5.3 Monitoring Results
References
