Analyses of the most influential factors for vibration monitoring of planetary power transmissions in pellet mills by adaptive neuro-fuzzy technique

Milovančević, Miloš; Nikolić, Vlastimir; Anđelković, Boban

doi:10.1016/j.ymssp.2016.05.028

Cited by 11 publications

(5 citation statements)

References 38 publications

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“…We have the sensors of acceleration, velocity and displacement. The principle of a vibration sensor function is the motion of seismic matter of mass m toward an object of mass M whose vibrations are measured (Milovančević et al , 2017b; Milovančević et al , 2017a; Milovančević et al , 2015).…”

Section: Methodsmentioning

confidence: 99%

Analyzing of micro-electro-mechanical systems (MEMS) sensor for pumping aggregates

Milovančević

Tijan

2018

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Purpose The purpose of this research paper is to develop and analyze micro-electro-mechanical systems sensor for vibration monitoring of pumping aggregate. Design/methodology/approach The system is based on smart sensor and smart mobile phone. Findings The numerous measurements on a wide range of turbo aggregates were performed to establish the operating condition of pumping aggregates. Originality/value Afterwards, the influence of vibration at different positions on the output vibration of the pumping aggregate was analyzed by adaptive neuro fuzzy inference system method.

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Section: Methodsmentioning

confidence: 99%

Analyzing of micro-electro-mechanical systems (MEMS) sensor for pumping aggregates

Milovančević

Tijan

2018

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“…ANFIS'in doğruluğu; yapılarını ve öğrenmelerini etkileyen parametrelerin doğru belirlenmesi ile ilişkilidir [30]. Literatürde yapılan çalışmaların çoğunda [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35], bu parametreler rastgele veya deneme yanılma yöntemiyle seçilmiştir. Ancak bu durumda daha iyi sonuç verecek parametre kombinasyonunun belirlenememesi söz konusudur.…”

Section: Amaçlanan Model (Proposed Model)unclassified

PCA Esaslı Hibrit ANFIS-Taguchi Yöntemi ile Kan Bankası için Talep Tahmini

Gökler

Boran

2020

Bilişim Teknolojileri Dergisi

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Özet-Kan; hastalıklar, ameliyatlar veya yaralanmalar nedeniyle her gün binlerce insan tarafından ihtiyaç duyulan hayati bir üründür. Bu nedenle hastanelerin kan ihtiyacını karşılayan kan bankalarının stoklarında yeterli miktarda kan bulundurması gereklidir. Gereğinden az miktarda kan elde bulundurulması ihtiyacın karşılanamaması ve can kaybı gibi önemli sorunlar oluştururken, fazla miktarda kanın stoklanması ise kanın bozulmasına ve kan ihtiyacı olan farklı hastanelerin stoksuz kalmasına neden olmaktadır.

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“…Based on the literature overview, one can conclude that there is gap in the vibration monitoring of the pellet mills systems in regard to application of advances control techniques. However, this study is based on articles Milovančević et al (2017, 2015 and 2010), where the embedded condition monitoring systems of power transmission of a pellet mill was developed, and the main contribution of the study should be developed advanced prediction technique for condition monitoring.…”

Section: Frameworkmentioning

confidence: 99%

“…Vibration monitoring is a method of technical diagnostics which could be used for monitoring of a technical state of a device by observing the level of a mechanical oscillation in a real time (Milovančević et al , 2017, 2015, 2010). Systems failures could be detected by the vibration diagnostics (Centobelli et al , 2015; Yang et al , 2013).…”

Section: Introductionmentioning

confidence: 99%

Vibration prediction of pellet mills power transmission by artificial neural network

Milovančević

Nikolić

Pavlović

et al. 2017

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Purpose The purpose of this study is to establish a vibration prediction of pellet mills power transmission by artificial neural network. Vibration monitoring is an important task for any system to ensure safe operations. Improvement of control strategies is crucial for the vibration monitoring. Design/methodology/approach As predictive control is one of the options for the vibration monitoring in this paper, the predictive model for vibration monitoring was created. Findings Although the achieved prediction results were acceptable, there is need for more work to apply and test these results in real environment. Originality/value Artificial neural network (ANN) was implemented as the predictive model while extreme learning machine (ELM) and back propagation (BP) learning schemes were used as training algorithms for the ANN. BP learning algorithm minimizes the error function by using the gradient descent method. ELM training algorithm is based on selecting of the input weights randomly of the ANN network and the output weight of the network are determined analytically.

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Analyses of the most influential factors for vibration monitoring of planetary power transmissions in pellet mills by adaptive neuro-fuzzy technique

Cited by 11 publications

References 38 publications

Analyzing of micro-electro-mechanical systems (MEMS) sensor for pumping aggregates

Analyzing of micro-electro-mechanical systems (MEMS) sensor for pumping aggregates

PCA Esaslı Hibrit ANFIS-Taguchi Yöntemi ile Kan Bankası için Talep Tahmini

Vibration prediction of pellet mills power transmission by artificial neural network

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