CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK

A neural network is used to calibrate a load cell that was built using strain gages. The inputs to the neural networkare the reference voltage applied to the Wheatstone bridge formed by the strain gages, the amplification value appliedto the Wheatstone bridge's output voltage, and the 8-bit dig...

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Autor principal: Vásquez Céspedes, Horacio
Formato: Online
Lenguaje:spa
Publicado: Universidad de Costa Rica 2011
Acceso en línea:https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/6438
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author Vásquez Céspedes, Horacio
author_facet Vásquez Céspedes, Horacio
author_sort Vásquez Céspedes, Horacio
collection Revista Ingeniería (RI)
description A neural network is used to calibrate a load cell that was built using strain gages. The inputs to the neural networkare the reference voltage applied to the Wheatstone bridge formed by the strain gages, the amplification value appliedto the Wheatstone bridge's output voltage, and the 8-bit digitized voltage value acquired by a microprocessor. Theoutput of the network is the estimated value of the weight being applied to the load cell. The network's main objectivewas to learn an accurate input-output relationship of the variables in the load cell system. The backpropagationLevenberg-Marquardt algorithm was used to train the network, and satisfactory results were obtained with a 5-3-1neural network. This project could be used as an example to design similar neural networks for other applications.
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spelling INII-RI-article-64382021-06-10T04:10:48Z CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK Vásquez Céspedes, Horacio A neural network is used to calibrate a load cell that was built using strain gages. The inputs to the neural networkare the reference voltage applied to the Wheatstone bridge formed by the strain gages, the amplification value appliedto the Wheatstone bridge's output voltage, and the 8-bit digitized voltage value acquired by a microprocessor. Theoutput of the network is the estimated value of the weight being applied to the load cell. The network's main objectivewas to learn an accurate input-output relationship of the variables in the load cell system. The backpropagationLevenberg-Marquardt algorithm was used to train the network, and satisfactory results were obtained with a 5-3-1neural network. This project could be used as an example to design similar neural networks for other applications. Universidad de Costa Rica 2011-07-19 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Article Artículo application/pdf https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/6438 Ingeniería; Vol. 12 No. 1-2 (2002); 105-114 Ingeniería; Vol. 12 Núm. 1-2 (2002); 105-114 Ingeniería; Vol. 12 N.º 1-2 (2002); 105-114 2215-2652 1409-2441 spa https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/6438/6143 Derechos de autor 2014 Revista Ingeniería
spellingShingle Vásquez Céspedes, Horacio
CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK
title CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK
title_full CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK
title_fullStr CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK
title_full_unstemmed CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK
title_short CALIBRATION OF A LOAD CELL USING A NEURAL NETWORK
title_sort calibration of a load cell using a neural network
url https://revistas.ucr.ac.cr/index.php/ingenieria/article/view/6438
work_keys_str_mv AT vasquezcespedeshoracio calibrationofaloadcellusinganeuralnetwork