Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization

The completeness of oil goods activates the barriers of lack of goods, inequality in the society, and surroundings impoverishment. Avoiding their use overnight and switching to clean electric motors are a challenge. Under all these conditions, researchers can launch their research on alternative fue...

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Main Authors: P. Nirmala, G. Ramkumar, Satyajeet Sahoo, G. Anitha, S. Ramesh, S. Agnes Shifani, Agegnehu Shara Shata
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2021/7663348
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author P. Nirmala
G. Ramkumar
Satyajeet Sahoo
G. Anitha
S. Ramesh
S. Agnes Shifani
Agegnehu Shara Shata
author_facet P. Nirmala
G. Ramkumar
Satyajeet Sahoo
G. Anitha
S. Ramesh
S. Agnes Shifani
Agegnehu Shara Shata
author_sort P. Nirmala
collection DOAJ
description The completeness of oil goods activates the barriers of lack of goods, inequality in the society, and surroundings impoverishment. Avoiding their use overnight and switching to clean electric motors are a challenge. Under all these conditions, researchers can launch their research on alternative fuels for a preeminent solution. Oxygenated fuel additives and thermal barrier coating (TBC) applications are essential to decrease the emission levels of exhaust and improve the performance of the vehicle. The main objective of this research is to analyze the performance of the ceramic-coated diesel engine. The ceramic particles use polymer coating to enhance the functionality and durability. Optimum outcomes are determined using Taguchi method. The impacts of various casting parameters of composites have been examined in detail. PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. Using an artificial neural network (ANN), the performance of diesel engine is examined to reduce time, cost, and experimental repetition. Thus, by using the artificial intelligence, the performance of the ceramic-coated diesel engine is analyzed and the polymeric substance and condition in coating ceramic engine is discussed.
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institution OA Journals
issn 1687-8434
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language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Advances in Materials Science and Engineering
spelling doaj-art-6e3e1eddc19d45bab6301157123f46fc2025-08-20T02:06:28ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422021-01-01202110.1155/2021/76633487663348Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter OptimizationP. Nirmala0G. Ramkumar1Satyajeet Sahoo2G. Anitha3S. Ramesh4S. Agnes Shifani5Agegnehu Shara Shata6Department of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai 602 105, Tamil Nadu, IndiaDepartment of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai 602 105, Tamil Nadu, IndiaDepartment of Electronics and Communication Engineering, Vignan’s Foundation for Science, Technology and Research (Deemed to be University), Vadlamudi Guntur, Andra Pradesh-522213, IndiaDepartment of Electronics and Communication Engineering, Saveetha School of Engineering, SIMATS, Chennai 602 105, Tamil Nadu, IndiaDepartment of Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore-641062, Tamilnadu, IndiaDepartment of Electronics and Communication Engineering, Jeppiaar Maamallan Engineering College, Chennai, Tamilnadu, IndiaFaculty of Mechanical Engineering, Arba Minch Institute of Technology, Arba Minch, EthiopiaThe completeness of oil goods activates the barriers of lack of goods, inequality in the society, and surroundings impoverishment. Avoiding their use overnight and switching to clean electric motors are a challenge. Under all these conditions, researchers can launch their research on alternative fuels for a preeminent solution. Oxygenated fuel additives and thermal barrier coating (TBC) applications are essential to decrease the emission levels of exhaust and improve the performance of the vehicle. The main objective of this research is to analyze the performance of the ceramic-coated diesel engine. The ceramic particles use polymer coating to enhance the functionality and durability. Optimum outcomes are determined using Taguchi method. The impacts of various casting parameters of composites have been examined in detail. PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. Using an artificial neural network (ANN), the performance of diesel engine is examined to reduce time, cost, and experimental repetition. Thus, by using the artificial intelligence, the performance of the ceramic-coated diesel engine is analyzed and the polymeric substance and condition in coating ceramic engine is discussed.http://dx.doi.org/10.1155/2021/7663348
spellingShingle P. Nirmala
G. Ramkumar
Satyajeet Sahoo
G. Anitha
S. Ramesh
S. Agnes Shifani
Agegnehu Shara Shata
Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
Advances in Materials Science and Engineering
title Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
title_full Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
title_fullStr Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
title_full_unstemmed Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
title_short Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization
title_sort artificial intelligence to analyze the performance of the ceramic coated diesel engine using digital filter optimization
url http://dx.doi.org/10.1155/2021/7663348
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