Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin

In this study, NFTOOL with Levenberg-Marquardt (trainlm) algorithm has been used to detect the presence of backlash in a vehicle driveline system model. The database consists of data with and without backlash that was collected from ECP Model 220 industrial plant emulator. The same data was first fi...

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Main Author: Khairudin, Muhammad Amier Rizal
Format: Thesis
Language:English
Published: 2018
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Online Access:https://ir.uitm.edu.my/id/eprint/98465/1/98465.PDF
https://ir.uitm.edu.my/id/eprint/98465/
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spelling my.uitm.ir.984652024-08-07T15:02:00Z https://ir.uitm.edu.my/id/eprint/98465/ Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin Khairudin, Muhammad Amier Rizal T Technology (General) In this study, NFTOOL with Levenberg-Marquardt (trainlm) algorithm has been used to detect the presence of backlash in a vehicle driveline system model. The database consists of data with and without backlash that was collected from ECP Model 220 industrial plant emulator. The same data was first filtered using a Butterworth filter then was used as input and target to develop ANN models. The model was trained, tested and validated using MATLAB R2013a software. The result was analyzed based on the mean square error (MSE) and regression (R) values. MSE and R value is obtained for different sampling time and compared. It was found that MSE value for dataset without backlash is smaller than dataset with backlash. While R value for dataset without backlash is better than dataset with backlash. 2018 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/98465/1/98465.PDF Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin. (2018) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Khairudin, Muhammad Amier Rizal
Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin
description In this study, NFTOOL with Levenberg-Marquardt (trainlm) algorithm has been used to detect the presence of backlash in a vehicle driveline system model. The database consists of data with and without backlash that was collected from ECP Model 220 industrial plant emulator. The same data was first filtered using a Butterworth filter then was used as input and target to develop ANN models. The model was trained, tested and validated using MATLAB R2013a software. The result was analyzed based on the mean square error (MSE) and regression (R) values. MSE and R value is obtained for different sampling time and compared. It was found that MSE value for dataset without backlash is smaller than dataset with backlash. While R value for dataset without backlash is better than dataset with backlash.
format Thesis
author Khairudin, Muhammad Amier Rizal
author_facet Khairudin, Muhammad Amier Rizal
author_sort Khairudin, Muhammad Amier Rizal
title Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin
title_short Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin
title_full Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin
title_fullStr Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin
title_full_unstemmed Backlash detection of two-mass rotation system using Artificial Neural Network (AAN) / Muhammad Amier Rizal Khairudin
title_sort backlash detection of two-mass rotation system using artificial neural network (aan) / muhammad amier rizal khairudin
publishDate 2018
url https://ir.uitm.edu.my/id/eprint/98465/1/98465.PDF
https://ir.uitm.edu.my/id/eprint/98465/
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