Wear element analysis using neural networks of a DI diesel engine using biodiesel with exhaust gas recirculation

Manieniyan, V.; Vinodhini, G.; Senthilkumar, R.; Sivaprakasam, S.

doi:10.1016/j.energy.2016.08.040

Cited by 31 publications

(10 citation statements)

References 23 publications

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“…Exhaust gas recirculation systems have been used more and more extensively during the last decade both with stationary power plants [28,29] and marine power plants [30] to reduce concentration of NO х in exhausts of diesel engines. Such systems are developed for and installed on recently designed marine vessels.…”

Section: Materials and Methods / Materijali I Metodementioning

confidence: 99%

Exhaust Gas Recirculation as a Major Technique Designed to Reduce NOх Emissions from Marine Diesel Engines

Kuropyatnyk¹,

Sagin²

2019

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The study objective is to identify to what extent the recirculation of exhaust gas from a low-speed marine diesel engine affects environmental, economic and power-related parameters in engine operation. Concentration of nitrogen oxides in exhaust gases was assumed to be the environmental parameter of an engine, specific fuel consumption as its economic parameter while effective (brake) power as its power-related parameter. Content of nitrogen oxides in exhaust gases discharged by low-speed marine diesel engines shall remain within the range of 3.4…14.4 g/(kW•h) depending on the area of marine vessel operation as specified by requirements of Annex VI MARPOL. Exhaust gas recirculation (EGR) was reviewed as a way to provide for such values. It was proven experimentally that recirculation of exhaust gas in the range of 4.7…18.8 % provides for reduction in concentration of nitrogen oxide (NO х) in the exhaust gases respectively down to 13.3…3.3 g NO x /(kW•h) depending on the rotation speed and load of diesel engine. Drop of NO х concentration in exhaust gases (as compared to NO х concentration without any circulation system used) was shown to reach 37.9…53.5%. It is proposed to apply the EGR system as a major technique to reduce NO х-emissions and bring the aforesaid parameter in compliance with requirements of international agencies. Sažetak Cilj studije je identificirati: "Do koje mjere ponovno strujanje ispušnoga plina iz sporohodnog dizelskog stroja, utječe na okolišne, ekonomske i energetske parametre pri radu stroja?" Koncentracija nitrogen oksida pri ispušnim plinovima, smatra se energetskim parametrom stroja, a specifična potrošnja goriva, kao ekonomski parametar, dok je učinkovita (konjska) snaga energetski parametar. Sadržaj nitrogen oksida pri ispušnim plinovima koje ispušta sporohodni brodski dizelski stroj, ostat će unutar dometa od 3.4…14.4g/(kW•h) ovisno o području djelovanja broda na moru, kako je specificirano zahtjevima Annexa MARPOL Konvencije Ponovno strujanje plina (EGR) odabrano je za dokazivanje tih vrijednosti. Eksperimentalno je dokazano da ponovno strujanje ispušnoga plina u dometu od 4.7…18.8% osigurava smanjenje koncentracije nitrogen oksida (NO x) pri ispušnim plinovima, prema redosljedu navođenja sve do 13.3…3.3 g NO x /kW•h ovisno o rotacionoj brzini i opterećenju dizelskoga stroja. Pad koncentracije pri ispušnim plinovima (u usporedbi s NO x) koncentracijom bez ikakva sustava cirkulacije dostigao je 37.9…53.5%. Predlaže se da se primijeni EGR sustav kao glavna tehnika smanjenja NO x emisija i da se dovede spomenuti parametar u skladu sa zahtjevima međunarodnih agencija. KEY WORDS low-speed marine diesel engine environmental indicators of diesel engine operation concentration of nitrogen oxides in exhaust gases exhaust gas recirculation (EGR) system brake power specific fuel oil consumption KLJUČNE RIJEČI sporohodni dizelski motor okolišni pokazatelji djelovanja dizelskoga stroja koncentracija nitrogen oksida pri ispušnim plinovima sustav ponovnoga strujanja plina konjska snaga specifič...

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Section: Materials and Methods / Materijali I Metodementioning

confidence: 99%

Exhaust Gas Recirculation as a Major Technique Designed to Reduce NOх Emissions from Marine Diesel Engines

Kuropyatnyk¹,

Sagin²

2019

Naše more

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“…In Manieniyan et al [26], a model based on ANN to predict the engine performance such as wear of the DI diesel engine using B20 blend of MEOM and diesel is presented. The ANN model is based on probabilistic neural networks and radial basis function in order to predict the engine wear.…”

Section: Related Workmentioning

confidence: 99%

Using artificial neural networks to represent a diesel–biodiesel engine

Lage

Hanriot

Zárate

2020

J Braz. Soc. Mech. Sci. Eng.

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In this work, six computational models based on artificial neural networks were developed to simulate an operating diesel engine fuelled with 8% biodiesel in order to predict performance and emissions of a diesel-biodiesel engine in a group generator. The ANN models were used to simulate a diesel-biodiesel engine that has four cylinders with a volume of 3.9 l, a compression ratio of 17:1, direct injection, and a rated power of 49 kW. The models were validated against experimental data for 10 kW, 20 kW, and 30 kW loads. The models were capable of accurately predicting the output power, thermal efficiency, and emissions of CO 2 , CO, NO, and NOx. Their comparison with experimental results showed a satisfactory agreement and the reliability of their predicted results for new operating conditions.

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“…As for classifiers, artificial intelligence methods are commonly used. 4,10,11) Machine Learning methods such as pattern recognition method of fuzzy clustering, CART method and artificial neural networks have become the premier candidate as the modeling tool. The experimental results showed that those AI methods are sufficient enough in predicting the equipment wear.…”

Section: Wear Debris Classification Of Steel Production Equipment Usimentioning

confidence: 99%

Wear Debris Classification of Steel Production Equipment using Feature Fusion and Case-based Reasoning

et al. 2018

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Wear debris classification is of great significance for identifying machine wear states. In this paper, a method of wear debris classification using feature fusion and CBR is proposed. The method integrates local feature LBP, global feature FD and Tamura coarseness, and then the fused features are applied in CBR system with different weights and different similarity, which is adaptable, extendable, modular and fast. The results show that the subdivision of wear debris images into size 32*32 when calculating LBP is helpful for improving the classification, the combination of local features and global features can get better results. The comparative experimental results of different classification methods show that the CBR system has the shortest time-consuming while maintaining high classification accuracy.

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Wear element analysis using neural networks of a DI diesel engine using biodiesel with exhaust gas recirculation

Cited by 31 publications

References 23 publications

Exhaust Gas Recirculation as a Major Technique Designed to Reduce NOх Emissions from Marine Diesel Engines

Exhaust Gas Recirculation as a Major Technique Designed to Reduce NOх Emissions from Marine Diesel Engines

Using artificial neural networks to represent a diesel–biodiesel engine

Wear Debris Classification of Steel Production Equipment using Feature Fusion and Case-based Reasoning

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