Current Issue : April - June Volume : 2016 Issue Number : 2 Articles : 6 Articles
This paper studies the use of adaptive neuro-fuzzy inference system (ANFIS) to\npredict the performance parameters and exhaust emissions of a diesel engine operating on\nnanodiesel blended fuels. In order to predict the engine parameters, the whole experimental\ndata were randomly divided into training and testing data. For ANFIS modelling, Gaussian\ncurve membership function (gaussmf) and 200 training epochs (iteration) were found to be\noptimum choices for training process. The results demonstrate that ANFIS is capable of\npredicting the diesel engine performance and emissions. In the experimental step, Carbon nano\ntubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure\nwere prepared and added as additive to the diesel fuel. Six cylinders, four-stroke\ndiesel engine was fuelled with these new blended fuels and operated at different engine speeds.\nExperimental test results indicated the fact that adding nano particles to diesel fuel, increased\ndiesel engine power and torque output. For nano-diesel it was found that the brake specific fuel\nconsumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with\nincrease of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2\nemission increased. CO emission in diesel fuel with nano-particles was lower significantly\ncompared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased\nwhile with fuels that contains CNT nano particles increased. The trend of NOx emission was\ninverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx\nincreased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles\ncan be used as additive in diesel fuel to improve combustion of the fuel and reduce the exhaust\nemissions significantly....
This article shows that the L-R method introduced in this work is one of valid methods for computing performance\nmeasures of fuzzy queues. Using this calculation technique, we find the number of customers and the waiting time of\na simple queue M/M/1 in fuzzy environment. L-R method has the advantage of being short, convenient and flexible\ncompared to the well-known and called alpha-cuts method....
In this article, we propose an audio equalizer of musical genres\nbased on fuzzy logic. Widely used audio playback software,\nsuch as VLC or iTunes, propose genre-specific equalization\ncurves to be applied for the whole duration of the music.\nThese curves are the same for all songs belonging to a\nspecific genre, and they do not take into account the specifics\nand diversity of each song. We propose a different strategy.\nResearch in music information retrieval has revealed a significant\nnumber of audio descriptors that allow for the recognition\nand description of diverse musical genres. We use some\nof these descriptors to feed a fuzzy logic inference system,\nwhose outputs are the required equalization levels for each\nfrequency band. The rules of the system are derived from the\nanalysis of a well known music database encompassing ten\ndifferent musical genres. Our results indicate that our approach\nworks for songs that exhibit multiple genre characteristics,\nthat are difficult to classify into one category, or that\nmix genres....
The design of civil engineering floors is increasingly being governed by their vibration serviceability\nperformance. This trend is the result of advancements in design technologies offering designers greater flexibilities in\nrealising more lightweight, longer span and more open-plan layouts. These floors are prone to excitation from human\nactivities. The present research work looks at analytical studies of active vibration control on a case study floor\nprototype that has been specifically designed to be representative of a real office floor structure. Specifically, it looks\nat tuning fuzzy control gains with the aim of adapting them to measured structural responses under human excitation.\nVibration mitigation performances are compared with those of a general velocity feedback controller, and these are\nfound to be identical in these sets of studies. It is also found that slightly less control force is required for the fuzzy\ncontroller scheme at moderate to low response levels and as a result of the adaptive gain, at very low responses the\ncontrol force is close to zero, which is a desirable control feature. There is also saturation in the peak gain with the\nfuzzy controller scheme, with this gain tending towards the optimal feedback gain of the direct velocity feedback\n(DVF) at high response levels for this fuzzy design....
This paper presents a method using multiobjective particle swarm optimization (PSO) approach to improve the consistency matrix\nin analytic hierarchy process (AHP), called PSOM OF. The purpose of this method is to optimize two objectives which conflict each\nother, while improving the consistency matrix. They are minimizing consistent ratio (CR) and deviation matrix. This study focuses\non fuzzy preference matrix as one model comparison matrix in AHP. Some inconsistent matrices are repaired successfully to be\nconsistent by this method. This proposed method offers some alternative consistent matrices as solutions....
Rolling bearing is of great importance in rotating machinery, so the fault diagnosis of rolling bearing is essential to ensure\nsafe operations. The traditional diagnosis approach based on characteristic frequency was shown to be not consistent\nwith experimental data in some cases. Furthermore, two data sets measured under the same circumstance gave different\ncharacteristic frequency results, and the harmonic frequency was not linearly proportional to the fundamental frequency.\nThese indicate that existing fault diagnosis is inaccurate and not reliable. This work introduced a new method based on\ndata-driven random fuzzy evidence acquisition and Dempsterââ?¬â??Shafer evidence theory, which first compared fault sample\ndata with fuzzy expert system, followed by the determination of random likelihood value and finally obtained diagnosis\nconclusion based on the data fusion rule. This method was proved to have high accuracy and reliability with a good\nagreement with experimental data, thus providing a new theoretical approach to fuzzy information processing in complicated\nnumerically controlled equipments....
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