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Applying Bayesian networks in making intelligent applications for static and dynamic unbalance diagnosis

IAES International Journal of Artificial Intelligence · Vol. 13 No. 1 (2024) · hlm. 174–184

DOI
10.11591/ijai.v13.i1.pp174-184
ISSN
2252-8938, 2089-4872
Terbit
2024-03-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

One of the problems often encountered in vibration analysis is unbalanced or imbalanced, namely the occurrence of a shift in the center of mass from the center of rotation to cause high vibrations. Unbalance itself is divided into two, namely static and dynamic unbalance. Identification of the right type of unbalance must be done because each type of unbalance requires different handling. Therefore, this study aims to design a system to identify the type of unbalance based on the required parameters. The system design determines the input and then builds an algorithm by combining vibration analysis methods and Bayesian networks (BN). Systems and applications are built using MATLAB. After the application is finished, testing is carried out using vibration measurement data obtained from a demo machine that has previously been conditioned for damage. The BN method has been successfully applied to the unbalance diagnosis system. When there is evidence of large amplitude in 1X the frequency spectrum and the value of the static phase range, the percentage of static unbalance from 26.8% increases to 75%. The system can predict all testing data quickly and precisely for the six experiments.

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  • Mercu Buana University
  • Beijing Institute of Technology
  • Tun Hussein Onn University of Malaysia
  • Ungku Omar Polytechnic
  • Nanjing University of Science and Technology
  • National University of Malaysia
  • Kyushu University
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Rekan penulisOrganisasiArtikel bersama
Hadi PranotoMercu Buana University9
Aberham Genetu FelekeBeijing Institute of Technology7
Nurato NuratoMercu Buana University7
Fajar AnggaraMercu Buana University6
Supaat ZakariaUngku Omar Polytechnic6
Rikko Putra YouliaMercu Buana University5
Wiwit SuprihatiningsihMercu Buana University3
Alief Avicenna LuthfieMercu Buana University3
Hui XiongBeijing Institute of Technology3
Nur IndahNational University of Malaysia3
Rachmat MuwardiMercu Buana University3
Imam HidayatMercu Buana University3
L. B. Desti DorionNanjing University of Science and Technology2
Andi AdriansyahMercu Buana University2
Abdi WahabMercu Buana University2
Andi Firdaus SudarmaMercu Buana University2
Shahruddin MahzanTun Hussein Onn University of Malaysia2
Fathoni Putra WijayaAfiliasi tidak diketahui2
Dong WangBeijing Institute of Technology2
Agung Wahyudi BiantoroMercu Buana University2
Tri Wahyu AdinartoMercu Buana University2
Fatkur RachmanuPoliteknik Enjinering Indorama2
S.S. AbdulmalikAfiliasi tidak diketahui2
Nanang RuhyatMercu Buana University1
Solli Dwi MurtyasKyushu University1
Hanif GhufronMercu Buana University1
Abdul Mutalib LemanTun Hussein Onn University of Malaysia1
Yosua Heru IrawanNational Taiwan University of Science and Technology1
Hifdzul Luthfan HabibullahMercu Buana University1
Diah UtamiMercu Buana University1
Yang XiaweiNorthwestern Polytechnical University1
Yudha Aji PramonoMercu Buana University1
Muhammad ImranBeijing Institute of Technology1
Himawan S. WibisonoMercu Buana University1
Mohamad Ardy FirmansyahMercu Buana University1

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Applying Bayesian networks in making intelligent applications for static and dynamic unbalance diagnosis</dc:title>
	<dc:creator>Romahadi, Dedik</dc:creator>
	<dc:creator>Fitri, Muhamad</dc:creator>
	<dc:creator>Feriyanto, Dafit</dc:creator>
	<dc:creator>Hidayat, Imam</dc:creator>
	<dc:creator>Imran, Muhammad</dc:creator>
	<dc:subject xml:lang="en-US">Mechanical Engineering</dc:subject>
	<dc:subject xml:lang="en-US">Bayesian networks; Intelligent system; Rotating equipment; Unbalance; Vibration analysis;</dc:subject>
	<dc:description xml:lang="en-US">One of the problems often encountered in vibration analysis is unbalanced or imbalanced, namely the occurrence of a shift in the center of mass from the center of rotation to cause high vibrations. Unbalance itself is divided into two, namely static and dynamic unbalance. Identification of the right type of unbalance must be done because each type of unbalance requires different handling. Therefore, this study aims to design a system to identify the type of unbalance based on the required parameters. The system design determines the input and then builds an algorithm by combining vibration analysis methods and Bayesian networks (BN). Systems and applications are built using MATLAB. After the application is finished, testing is carried out using vibration measurement data obtained from a demo machine that has previously been conditioned for damage. The BN method has been successfully applied to the unbalance diagnosis system. When there is evidence of large amplitude in 1X the frequency spectrum and the value of the static phase range, the percentage of static unbalance from 26.8% increases to 75%. The system can predict all testing data quickly and precisely for the six experiments.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2024-03-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/22260</dc:identifier>
	<dc:identifier>10.11591/ijai.v13.i1.pp174-184</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 13, No 1: March 2024; 174-184</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v13.i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/22260/13813</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>