APPLICATION OF CONVOLUTIONAL NEURAL NETWORKS IN WALL MOISTURE IDENTIFICATION BY EIT METHOD
Grzegorz Kłosowski
g.klosowski@pollub.plLublin University of Technology, Faculty of Management (Poland)
https://orcid.org/0000-0001-7927-3674
Tomasz Rymarczyk
University of Economics and Innovation in Lublin, Institute of Computer Science and Innovative Technologies (Poland)
https://orcid.org/0000-0002-3524-9151
Abstract
The article presents the results of research in the area of using deep neural networks to identify moisture inside the walls of buildings using electrical impedance tomography. Two deep neural networks were used to transform the input measurements into images of damp places - convolutional neural networks (CNN) and recurrent long short-term memory networks LSTM. After training both models, a comparative assessment of the results obtained thanks to them was made. The conclusions show that both models are highly utilitarian in the analyzed problem. However, slightly better results were obtained with the LSTM method.
Keywords:
machine learning, deep learning, electrical impedance tomography, moisture detection in wallsReferences
Fabijańska A., Banasiak R.: Graph Convolutional Networks for Enhanced Resolution 3D Electrical Capacitance Tomography Image Reconstruction. Applied Soft Computing 110, 2021, 107608, [http://doi.org/10.1016/J.ASOC.2021.107608].
DOI: https://doi.org/10.1016/j.asoc.2021.107608
Google Scholar
Hola A.: Measuring of the Moisture Content in Brick Walls of Historical Buildings-the Overview of Methods. IOP Conference Series: Materials Science and Engineering 251(1), 2017, [http://doi.org/10.1088/1757-899X/251/1/012067].
DOI: https://doi.org/10.1088/1757-899X/251/1/012067
Google Scholar
Kłosowski G. et al.: Quality Assessment of the Neural Algorithms on the Example of EIT-UST Hybrid Tomography. Sensors 20(11), 2020, [http://doi.org/10.3390/s20113324].
DOI: https://doi.org/10.3390/s20113324
Google Scholar
Kłosowski G. et al.: The Concept of Using Lstm to Detect Moisture in Brick Walls by Means of Electrical Impedance Tomography. Energies 14(22), 2021, [http://doi.org/10.3390/en14227617].
DOI: https://doi.org/10.3390/en14227617
Google Scholar
Litti G. et al.: Hygrothermal Performance Evaluation of Traditional Brick Masonry in Historic Buildings. Energy and Buildings 105, 2015, 393–411, [http://doi.org/10.1016/j.enbuild.2015.07.049].
DOI: https://doi.org/10.1016/j.enbuild.2015.07.049
Google Scholar
Porzuczek J.: Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography. Sensors 19(12), 2019, 2807, [http://doi.org/10.3390/s19122807].
DOI: https://doi.org/10.3390/s19122807
Google Scholar
Romanowski A. et al.: X-Ray Imaging Analysis of Silo Flow Parameters Based on Trace Particles Using Targeted Crowdsourcing. Sensors 19(15), 2019, 3317, [http://doi.org/10.3390/s19153317].
DOI: https://doi.org/10.3390/s19153317
Google Scholar
Rymarczyk T. et al.: Area Monitoring Using the ERT Method with Multisensor Electrodes. Przegląd Elektrotechniczny 95(1), 2019, [http://doi.org/10.15199/48.2019.01.39].
DOI: https://doi.org/10.15199/48.2019.01.39
Google Scholar
Rymarczyk T., Adamkiewicz P.: Nondestructive Method to Determine Moisture Area in Historical Building. Informatics Control Measurement in Economy and Environment Protection 7(1), 2017, [http://doi.org/10.5604/01.3001.0010.4586].
DOI: https://doi.org/10.5604/01.3001.0010.4586
Google Scholar
Authors
Grzegorz Kłosowskig.klosowski@pollub.pl
Lublin University of Technology, Faculty of Management Poland
https://orcid.org/0000-0001-7927-3674
Authors
Tomasz RymarczykUniversity of Economics and Innovation in Lublin, Institute of Computer Science and Innovative Technologies Poland
https://orcid.org/0000-0002-3524-9151
Statistics
Abstract views: 285PDF downloads: 193
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Most read articles by the same author(s)
- Grzegorz Kłosowski, Tomasz Rymarczyk, USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 7 No. 3 (2017)
- Tomasz Rymarczyk, Tomasz Cieplak, Grzegorz Kłosowski, Paweł Rymarczyk, DESIGN OF DATA ANALYSIS SYSTEMS FOR BUSINESS PROCESS AUTOMATION , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 8 No. 3 (2018)
- Tomasz Rymarczyk, Michał Gołąbek, Piotr Lesiak, Andrzej Marciniak, Mirosław Guzik, CONSTRUCTION OF AN ULTRASONIC TOMOGRAPH FOR ANALYSIS OF TECHNOLOGICAL PROCESSES IN THE FIELD OF REFLECTION AND TRANSMISSION WAVES , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 4 (2019)
- Tomasz Rymarczyk, Grzegorz Kłosowski, THE USE OF ARTIFICIAL INTELLIGENCE IN AUTOMATED IN-HOUSE LOGISTICS CENTRES , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 8 No. 1 (2018)
- Tomasz Rymarczyk, Bartek Przysucha, Marcin Kowalski, Piotr Bednarczuk, ANALYSIS OF DATA FROM MEASURING SENSORS FOR PREDICTION IN PRODUCTION PROCESS CONTROL SYSTEMS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 4 (2019)
- Tomasz Rymarczyk, Krzysztof Polakowski, Jan Sikora, A NEW CONCEPT OF DISCRETIZATION MODEL FOR IMAGING IMPROVING IN ULTRASOUND TRANSMISSION TOMOGRAPHY , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 4 (2019)
- Konrad Niderla, Tomasz Rymarczyk, Jan Sikora, MANUFACTURING PLANNING AND CONTROL SYSTEM USING TOMOGRAPHIC SENSORS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 8 No. 3 (2018)
- Tomasz Rymarczyk, Jan Sikora, SINGULAR INTEGRATION IN BOUNDARY ELEMENT METHOD FOR HELMHOLTZ EQUATION FORMULATED IN FREQUENCY DOMAIN , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 11 No. 4 (2021)
- Tomasz Rymarczyk, Jan Sikora, SOME MORE ON LOGARITHMIC SINGULARITY INTEGRATION IN BOUNDARY ELEMENT METOD , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 14 No. 1 (2024)
- Tomasz Rymarczyk, Grzegorz Kłosowski, SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 7 No. 4 (2017)
