Mfcc- Lstm Framework for Leak Detection and Leak Size Identification in Gas-Liquid Two-Phase Flow Pipelines Based on Acoustic Emission

[1]  Weiliang Wang,et al.  Pipeline leak detection method based on acoustic-pressure information fusion , 2023, Measurement.

[2]  Shang Gao,et al.  Metric Mutation Anomaly Detection Method of the Power Grid Dispatching Automatic System Based on Machine Learning and Statistics , 2023, Journal of Physics: Conference Series.

[3]  Zahoor Ahmad,et al.  Leak detection and size identification in fluid pipelines using a novel vulnerability index and 1-D convolutional neural network , 2023, Engineering Applications of Computational Fluid Mechanics.

[4]  Pedro J. Lee,et al.  Transient Wave-Leak Interaction Analysis for Improved Leak Detection in Viscoelastic Pipelines , 2023, SSRN Electronic Journal.

[5]  Changhang Xu,et al.  A CNN-based transfer learning method for leakage detection of pipeline under multiple working conditions with AE signals , 2022, Process Safety and Environmental Protection.

[6]  Yuan Xue,et al.  Investigation on leakage detection and localization in gas-liquid stratified flow pipelines based on acoustic method , 2022, Journal of Pipeline Science and Engineering.

[7]  Christos C. Spandonidis,et al.  Evaluation of deep learning approaches for oil & gas pipeline leak detection using wireless sensor networks , 2022, Eng. Appl. Artif. Intell..

[8]  Cuiping Wang,et al.  High-speed train wheel set bearing fault diagnosis and prognostics: Fingerprint feature recognition method based on acoustic emission , 2022, Mechanical Systems and Signal Processing.

[9]  Ali Asghar Heidari,et al.  Apple leaf disease recognition method with improved residual network , 2022, Multimedia Tools and Applications.

[10]  Zhijing Yang,et al.  CNN-LSTM network-based damage detection approach for copper pipeline using laser ultrasonic scanning. , 2022, Ultrasonics.

[11]  Jingyi Lu,et al.  Novel leakage detection by ensemble 1DCNN-VAPSO-SVM in oil and gas pipeline systems , 2021, Appl. Soft Comput..

[12]  Fangli Ning,et al.  A framework combining acoustic features extraction method and random forest algorithm for gas pipeline leak detection and classification , 2021 .

[13]  Fan Liping,et al.  Experimental study on the amplitude characteristics and propagation velocity of dynamic pressure wave for the leakage of gas-liquid two-phase intermittent flow in pipelines , 2021 .

[14]  Simon S. Park,et al.  Pipeline Leak and Volume Rate Detections Through Artificial Intelligence and Vibration Analysis , 2021, Measurement.

[15]  T. N. Ofei,et al.  Developments of Leak Detection, Diagnostics, and Prediction Algorithms in Multiphase Flows , 2021, Chemical Engineering Science.

[16]  Zhoumo Zeng,et al.  Pipeline leak detection based on variational mode decomposition and support vector machine using an interior spherical detector , 2021 .

[17]  Tamiru Alemu Lemma,et al.  Determination and analysis of leak estimation parameters in two-phase flow pipelines using OLGA multiphase software , 2021, Sustain. Comput. Informatics Syst..

[18]  F. Khan,et al.  Offshore pipeline integrity assessment considering material and parametric uncertainty , 2021, Journal of Pipeline Science and Engineering.

[19]  Chan-Wook Lee,et al.  Development of Leakage Detection Model and Its Application for Water Distribution Networks Using RNN-LSTM , 2021, Sustainability.

[20]  Somtochukwu Godfrey Nnabuife,et al.  Development of Gas–Liquid Flow Regimes Identification Using a Noninvasive Ultrasonic Sensor, Belt-Shape Features, and Convolutional Neural Network in an S-Shaped Riser , 2021, IEEE Transactions on Cybernetics.

[21]  Simon S. Park,et al.  The development of leak detection model in subsea gas pipeline using machine learning , 2021 .

[22]  Fachun Liang,et al.  Identification of gas-liquid two-phase flow patterns in a horizontal pipe based on ultrasonic echoes and RBF neural network , 2021 .

[23]  Lide Fang,et al.  Acoustic emission-based flow noise detection and mechanism analysis for gas-liquid two-phase flow , 2021, Measurement.

[24]  J. Ribeiro,et al.  Characteristics of horizontal gas-liquid two-phase flow measurement in a medium-sized pipe using gamma densitometry , 2020, Scientific African.

[25]  Hazem Nounou,et al.  Chronic leak detection for single and multiphase flow: A critical review on onshore and offshore subsea and arctic conditions , 2020 .

[26]  Lei Ni,et al.  An improved variational mode decomposition method based on particle swarm optimization for leak detection of liquid pipelines , 2020 .

[27]  Hongfang Lu,et al.  Leakage detection techniques for oil and gas pipelines: State-of-the-art , 2020 .

[28]  Mohammadamin Azimi,et al.  Carbon trading volume and price forecasting in China using multiple machine learning models , 2020 .

[29]  Mohammadamin Azimi,et al.  US natural gas consumption prediction using an improved kernel-based nonlinear extension of the Arps decline model , 2020 .

[30]  Jong-Myon Kim,et al.  Leak detection in a gas pipeline using spectral portrait of acoustic emission signals , 2020 .

[31]  Peng Xu,et al.  Predicting pipeline leakage in petrochemical system through GAN and LSTM , 2019, Knowl. Based Syst..

[32]  Jie Li,et al.  Leak detection of gas pipelines using acoustic signals based on wavelet transform and Support Vector Machine , 2019, Measurement.

[33]  Jian Li,et al.  A small leakage detection approach for oil pipeline using an inner spherical ball , 2019, Process Safety and Environmental Protection.

[34]  Cuiwei Liu,et al.  New leak-localization approaches for gas pipelines using acoustic waves , 2019, Measurement.

[35]  Yuxing Li,et al.  Application of EMD Technology in Leakage Acoustic Characteristic Extraction of Gas-Liquid, Two-Phase Flow Pipelines , 2018, Shock and Vibration.

[36]  Jiheon Kang,et al.  Novel Leakage Detection by Ensemble CNN-SVM and Graph-Based Localization in Water Distribution Systems , 2018, IEEE Transactions on Industrial Electronics.

[37]  Hengshan Hu,et al.  An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS , 2018 .

[38]  Paulo J. Waltrich,et al.  Evaluation of Software-based Early Leak Warning System in Gulf-of-Mexico Subsea Flowlines , 2017 .

[39]  Gangbing Song,et al.  An acoustic emission based multi-level approach to buried gas pipeline leakage localization , 2016 .

[40]  Deendarlianto,et al.  Pipeline Leak Detection in Two Phase Flow Based on Fluctuation Pressure Difference and Artificial Neural Network (ANN) , 2014 .

[41]  Lide Fang,et al.  Flow noise characterization of gas–liquid two-phase flow based on acoustic emission , 2013 .

[42]  Ioan Silea,et al.  A survey on gas leak detection and localization techniques , 2012 .

[43]  Rainer Hoffmann,et al.  Estimation of volume fractions and flow regime identification in multiphase flow based on gamma measurements and multivariate calibration , 2012 .

[44]  Yinfeng Wu,et al.  Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks , 2011, Sensors.

[45]  Hongli Hu,et al.  Identification of gas/solid two-phase flow regimes using electrostatic sensors and neural-network techniques , 2011 .

[46]  D. Mba,et al.  Acoustic Emission and Gas-Phase Measurements in Two-Phase Flow , 2010 .

[47]  Seung Ihl Kam,et al.  Mechanistic modeling of pipeline leak detection at fixed inlet rate , 2010 .

[48]  H.A. Toliyat,et al.  Rail defect diagnosis using wavelet packet decomposition , 2002, Conference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344).

[49]  Andrew K. Wojtanowicz,et al.  Leak Detection in Liquid Subsea Flowlines With no Recorded Feed Rate , 1999 .

[50]  Pascal Stouffs,et al.  Pipeline leak detection based on mass balance: Importance of the packing term , 1993 .

[51]  Stan Davis,et al.  Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Se , 1980 .

[52]  K. Aziz,et al.  A flow pattern map for gas—liquid flow in horizontal pipes , 1974 .

[53]  Deguo Wang,et al.  Prediction model of natural gas pipeline crack evolution based on optimized DCNN-LSTM , 2022, Mechanical Systems and Signal Processing.

[54]  Jong-Myon Kim,et al.  A novel pipeline leak detection approach independent of prior failure information , 2021 .

[55]  Hongjun Zhu,et al.  A CFD (computational fluid dynamic) simulation for oil leakage from damaged submarine pipeline , 2014 .

[56]  Paulo Seleghim,et al.  Assessment of the Performance of Acoustic and Mass Balance Methods for Leak Detection in Pipelines for Transporting Liquids , 2010 .