Analysis of electrochemical noise data by use of recurrence quantification analysis and machine learning methods

QR Code

Analysis of electrochemical noise data by use of recurrence quantification analysis and machine learning methods

© 2017 By use of recurrence quantification analysis (RQA), twelve features were extracted from the electrochemical noise signals generated by three types of corrosion: uniform, pitting and passivation. Machine learning methods, i.e. linear discriminant analysis (LDA) and random forests (RF), were us...

Full description

Bibliographic Details
Main Authors:	Hou, Y., Aldrich, Chris, Lepkova, Katerina, Machuca Suarez, Laura, Kinsella, Brian
Format:	Journal Article
Published:	Pergamon 2017
Online Access:	http://hdl.handle.net/20.500.11937/57708

Similar Items

Monitoring of carbon steel corrosion by use of electrochemical noise and recurrence quantification analysis
by: Hou, Y., et al.
Published: (2016)

Detection of under deposit corrosion in a CO2 environment by using electrochemical noise and recurrence quantification analysis
by: Hou, Y., et al.
Published: (2018)

Identifying corrosion of carbon steel buried in iron ore and coal cargoes based on recurrence quantification analysis of electrochemical noise
by: Hou, Y., et al.
Published: (2018)

Corrosion Monitoring Based on Recurrence Quantification Analysis of Electrochemical Noise and Machine Learning Methods
by: Hou, Yang
Published: (2018)

Application of electrochemical noise technique to monitor carbon steel corrosion under sand deposit
by: Hou, Y., et al.
Published: (2017)

Aggressive corrosion of steel by a thermophilic microbial consortium in the presence and absence of sand
by: Suarez, Erica, et al.
Published: (2019)

The role of bacteria in under-deposit corrosion in oil and gas facilities: A review of mechanisms, test methods and corrosion inhibition
by: Machuca Suarez, Laura, et al.
Published: (2019)

Analysis of electrochemical noise with phase space methods.
by: Aldrich, Chris, et al.
Published: (2006)

Early Detection of risk of autism spectrum disorder based on recurrence quantification analysis of electroencephalographic signals
by: Pistorius, T, et al.
Published: (2013)

Corrosion of carbon steel in the presence of oilfield deposit and thiosulphate-reducing bacteria in CO2 environment
by: Machuca Suarez, Laura, et al.
Published: (2017)

Electrochemical behaviour and surface analysis of chalcopyrite in alkaline glycine solutions
by: O'Connor, G., et al.
Published: (2018)

Recurrence quantification analysis of resting state EEG signals in autism spectrum disorder - a systematic methodological exploration of technical and demographic confounders in the search for biomarkers
by: Heunis, T., et al.
Published: (2018)

Electrochemical study of under-deposit carbon dioxide corrosion and its inhibition
by: Lepkova, Katerina, et al.
Published: (2009)

Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development
by: Curtin, P., et al.
Published: (2017)

Microbiologically Induced Corrosion Associated with the Wet Storage of Subsea Pipelines (Wet Parking)
by: Machuca Suarez, Laura
Published: (2017)

Microbiologically influenced corrosion: A review focused on hydrotest fluids in subsea pipelines
by: Machuca Suarez, Laura
Published: (2014)

Understanding and addressing Microbiologically Influenced Corrosion (MIC)
by: Machuca Suarez, Laura
Published: (2019)

Electrochemical behaviour of copper in alkaline glycine solutions
by: O'Connor, G., et al.
Published: (2018)

Sensing localised corrosion by means of electrochemical noise detection and analysis
by: Tan, Yong
Published: (2009)

Selection of electrode area for electrochemical noise measurements to monitor localized CO2 corrosion
by: Jiang, X., et al.
Published: (2012)

Microbiologically influenced corrosion of common alloys used for subsea applications
by: Machuca Suarez, Laura Lizeth
Published: (2012)

Estimation of electrochemical noise impedance and corrosion rates from electrochemical noise measurements.
by: Lowe, Alexander M.
Published: (2002)

Recurrence Analysis of Time Series
by: Chew, Kai Ye
Published: (2019)

Developing Real-time Corrosion Monitoring: A Cutting-Edge Fusion of Electrochemical Noise Data and Machine Learning Techniques
by: Abdulmutaali, Ahmed
Published: (2024)

Cancer recurrence prediction using machine learning
by: Shoon Lei, Win, et al.
Published: (2014)

Microbiologically Influenced Corrosion in Floating Productions Systems
by: Machuca Suarez, Laura, et al.
Published: (2018)

Effect of sample storage conditions on the molecular assessment of MIC
by: Machuca Suarez, Laura, et al.
Published: (2018)

Adsorption of corrosion inhibitor 1-dodecylpyridinium chloride on carbon steel studied by in situ AFM and electrochemical methods
by: Pandarinathan, Vedapriya, et al.
Published: (2014)

Root cause analysis of process fault conditions on an industrial concentrator circuit by use of causality maps and extreme learning machines
by: Groenewald, J., et al.
Published: (2015)

Complementary DNA/RNA-Based Profiling: Characterization of Corrosive Microbial Communities and Their Functional Profiles in an Oil Production Facility
by: Machuca Suarez, Laura, et al.
Published: (2019)

Science and the Sydney
by: Harvey, Euan, et al.
Published: (2016)

Industrial vibration and noise analysis of conventional drilling machine on different type of materials
by: Nur Afiq, Abu Bakar
Published: (2007)

Microorganisms associated with corrosion of structural steel in diverse atmospheres
by: Machuca Suarez, Laura, et al.
Published: (2016)

Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks
by: Solanka, Lukas, et al.
Published: (2015)

Froth image analysis by use of transfer learning and convolutional neural networks
by: Fu, Y., et al.
Published: (2018)

Flotation Froth Image Analysis by Use of a Dynamic Feature Extraction Algorithm
by: Fu, Y., et al.
Published: (2016)

Characterisation of Dynamic Process Systems by Use of Recurrence Texture Analysis
by: Bardinas, Jason
Published: (2018)

Emerging surface characterization techniques for carbon steel corrosion: A critical brief review
by: Dwivedi, D., et al.
Published: (2017)

A Machine Learning Classification Approach to Geotechnical Characterization Using Measure-While-Drilling Data
by: Goldstein, D., et al.
Published: (2025)

Unlocking Subsurface Geology: A Case Study with Measure-While-Drilling Data and Machine Learning
by: Goldstein, D., et al.
Published: (2025)