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Öğe A neural based position controller for an electrohydraulic servo system(2011) Yildirim, Şahin; Erkaya, Selçuk; Uzmay, Ibrahim; Kalkat, MenderesThis paper proposes a neural network based controller for controlling the position of an electrohydraulic servo system. Feedforward network structure, which consists of an input and output layer with one linear neuron, a hidden layer with two nonlinear neurons, is used for the related controlling, and backpropagation algorithm (BP) is implemented for the learning process. Du to the adaptability and robustness, the neural network based model reference adaptive control scheme gives very successful control results. The simulation gives that the proposed adaptive neural controller has better control performance than that of the standard PID controller. This kind of neural controllers could be utilized in experimental investigation of electrohydraulic servo systems.Öğe DALGIÇ POMPALARDA YAPAY SİNİR AĞLARI KULLANILARAK DENEYSEL AKIŞ ANALİZİ(2019) Kalkat, Menderes; Tom, VeliMakale kapsamında, derin kuyu su pompalarının su debisinin deneysel akış analizi, yapay sinirağları kullanılarak gerçekleştirilmiştir. Pompanın en önemli parametresi olan debi verisi debimetre ileelde edildi. Elde edilen veriler kullanılarak yapay sinir ağı modeli ile yeni modeller oluşturuldu.Aktarılan veriler ve programın oluşturduğu grafikler gerçekte oluşturulan veriler ile birbirlerine uyumluolduğu gözlemlenmektedir. Sonuç olarak, pompaların arızası yapay sinir ağı ile yapılan debi girişleri iletespit edilebilir ve sonrasında pompanın, de-montajı gerçekleştirilip direk arızalı kısma müdahaleedilebilecek seviyeye gelinebilir.Öğe Design of artificial neural networks for rotor dynamics analysis of rotating machine systems (Retraction of vol 15, pg 573, 2005)(PERGAMON-ELSEVIER SCIENCE LTD, 2013) Kalkat, Menderes; Yildirim, Sahin; Uzmay, Ibrahim[Abstract Not Available]Öğe Experimentally vibration and noise analysis of two types of washing machines with a proposed neural network predictor(ELSEVIER SCI LTD, 2014) Kalkat, MenderesDue to unpredictable noises, there are plenty of health problems on human. This paper is focused on neural networks (NNs) based prediction analyzer for two types drive schemes of washing machines that are direct drive and belt-pulley drive, for vibration and fault diagnosis of motors bearings. Furthermore, eight different cases including, during washing with direct drive and belt-pulley, squeezing during washing with direct drive and belt-pulley for noises and acceleration of the washing machines systems are investigated using the proposed algorithm of NNs. An Intelligent Data Acquisition (IDA), a microphone and PC are used to measure the system noise. For the case of different working conditions of the system, three types of NN are used to investigate the noise levels. The results show that NN with quick propagation algorithm gives superior performance for predicting and evaluating the noise of washing machine systems. (C) 2013 Elsevier Ltd. All rights reserved.Öğe Force analysis of bearings on a modified mechanism using proposed recurrent hybrid neural networks(KOREAN SOC MECHANICAL ENGINEERS, 2008) Yildirim, Sahin; Eski, Ikbal; Kalkat, MenderesDue to different load conditions on four-bar mechanisms, it is necessary to analyze force distribution on the bearing systems of mechanisms. A proposed neural network was developed and designed to analyze force distribution on the bearings of a four bar mechanism. The proposed neural network has three layers: input layer, output layer and hidden layer. The hidden layer consists of a recurrent structure to keep dynamic memory for later use. The mechanism is an extended version of a four-bar mechanism. Two elements, spring and viscous, are employed to overcome big force problem on the bearings of the mechanism. The results of the proposed neural network give superior performance for analyzing the forces on the bearings of the four-bar mechanism undergoing big forces and high repetitive motion tracking. This continuation of simulation analysis of bearings should be a benefit to bearing designers and researchers of such mechanisms.Öğe Installation of Test Setup and Measurement Procedures in Fir Wood Hydraulic Conductance Measurement(Zagreb Univ, Fac Forestry, 2021) Koksal, Suheyla Esin; Gunduz, Gokhan; Kalkat, MenderesFor a hydraulic conductor, through which liquid flows, hydraulic conductance (K, ml.s(-1).MPa-1) is defined as the ratio of pressure difference at the inlet and outlet to the fluid amount passing through the hydraulic conductor in a unit time period. This property is one of the key functions of the wood, and is obtained by the flow rate (F - Flow, ml.s(-1)) along the wood sample divided by the pressure difference driving the flow (Delta P MPa). This study aimed to establish a test setup to determine the hydraulic conductance values of Uludag Fir (Abies bornmulleriana Hattf). A test setup was established to measure the amount of water that flows in samples and pressure difference in characterized capillary tubes. In addition, calibration of the test apparatus is explained in detail. Fir wood samples taken from Yedigoller, which is affiliated to Kale Operation Chieftainship and Bolu Forest Regional Directorate, of 4 mm in diameter and 3 cm in length were prepared and hydraulic conductance measurements were performed, and the results are presented in this article. The installed test setup was used to obtain the following information about frees: operation of the hydraulic conduction system, the amount of needed water, seasonal effects and stress-related changes.Öğe Investigations on the effect of oil quality on gearboxes using neural network predictors(EMERALD GROUP PUBLISHING LTD, 2015) Kalkat, MenderesPurpose - The purpose of this paper was to perform an experimental investigation to analyze vibration and noise of unloaded gearbox with different oil quality. All motor-driven machinery used in the modern world can develop faults. The maintenance plans include analyzing the external relevant information of critical components, in order to evaluate its internal state. From the beginning of the twentieth century, different technologies have been used to process signals of dynamical systems. Design/methodology/approach - A proposed neural network (NN) is also employed to predict vibration parameters of the experimental test rig. Moreover, four types of oils are used for gearbox to predict reliable oil. Vibration signals extracted from rotating parts of machineries carry lot many information within them about the condition of the operating machine. Further processing of these raw vibration signatures measured at a convenient location of the machine unravels the condition of the component or the assembly under study. The experimental stand for testing an unloaded gearbox is composed by actuated direct current (DC) driving system. Findings - This paper deals with the effectiveness of wavelet-based features for fault diagnosis of a gearbox using two types of artificial neural networks (ANNs) and stress analyzed with computer-based software ANNs. The results improved that the proposed NN has superior performance to adapt experimental results. Practical implications - This paper is one such attempt to apply machine learning methods like ANN. This work deals with extraction of wavelet features from the vibration data of a gearbox system and classification of gear faults using ANNs. Originality/value - These kind of NN-based approaches are novel approaches to predict real-time vibration and acceleration parameters of unloaded gearbox with five types of oils. Also, the investigation contains new information about studied process, containing elements of novelty.Öğe NEURAL PREDICTOR DESIGN FOR COVID-19 CASES IN DIFFERENT REGIONS(Cefin Publishing House, 2023) Yildirim, Sahin; Durmusoglu, Aslı; Sevim, Caglar; Bingol, Mehmet Safa; Kalkat, MenderesCOVID-19, which emerged in the past years, has affected human life in many different ways. The COVID-19 virus has spread very quickly around the world and has become a pandemic. In many applications, artificial neural networks are used to estimate system parameters in real-time or simulation-based methods. In this study, the daily and total number of cases in Turkey, Italy and India are predicted. Three alternative areas, with or without following rules, are chosen for the COVID-19 cases. For this prediction process, 3 different neural network methods are used: Nonlinear autoregressive neural network (NAR-NN), Adaptive-Network Based Fuzzy Inference Systems (ANFIS) and Autoregressive integrated moving average (ARIMA). The results obtained for 3 different neural networks are given with graphs and tables. The conclusion of this study may be used to improve the precaution for the pandemic. © 2023, Cefin Publishing House. All rights reserved.Öğe Oils quality and performance analysis of vehicle's engines using radial basis neural networks(EMERALD GROUP PUBLISHING LTD, 2009) Kalkat, Menderes; Yildirim, Sahin; Erkaya, SelcukPurpose - The purpose of this paper is to improve the application of neural networks on vehicle engine systems for fault detecting and analysing engine oils. Design/methodology/approach - Three types of neural networks are employed to find exact neural network predictor of vehicle engine oil performance and quality. Nevertheless, two oil types are analysed for predicting performance in the engine. These oils are used and unused oils. In experimental work, two accelerometers are located at the bottom of the car engine to measure related vibrations for analysing oil quality of both cases. Findings - The results of both computer simulation and experimental work show that the radial basis neural network predictor gives good performance at adapting different cases. Research limitations/implications - The results of the proposed neural network analyser follow the desired results of the vehicle engine's vibration variation. However, this kind of neural network scheme can be used to analyse oil quality of the car in experimental applications. Practical implications - As theoretical and practical studies are evaluated together, it is hoped that oil analysers and interested researchers will obtain significant results in this application area. Originality/value - This paper is an original contribution on vehicle oil quality analysis using a proposed artificial neural network and it should be helpful for industrial applications of vehicle oil quality analysis and fault detection.Öğe Power and performance analysis of light bicycle on different road profiles(Akademiai Kiado ZRt., 2021) Kalkat, MenderesNowadays, digital technology and measurement are improving to measure some systems in accurate conditions without errors. From these improvements and developments, it is necessary to analyse performances and condition of bicycle and biker before high level computations. In this experimental investigation, a high quality and very light bicycle and a well-equipped trained biker were trained to test the system with different road and region conditions. The purpose of this investigation is to predict unwanted conditions of bicycle before computations and activity. Otherwise, this kind of experimental trained testing will give some information from unwanted bicycle accidents. Moreover, in this experimental work, a power meter and measurement instrument with sensors are used to measure real time parameters. As can be concluded from experimental results and the analysis, the proposed work has a good design and analysis for good material bicycles. The displacement analysis is also outlined with load of a 63 kg biker. © 2020 The Author(s)Öğe The determination of the working life of backhoe-loader bucket teeth showing abrasive wear under the effect of dynamic loads(2023) Kalkat, Menderes; Bahadır, Mehmet; Yılmaz, FurkanEspecially in developing countries, the rise of infrastructure works increases the demand for heavy machines. Backhoe loaders: These are small tonnage work machines consisting of a bucket group at the front and a bucket set at the back, which are used in many areas such as infrastructure, road construction, maintenance, and repair in the construction industry. The teeth, which are bolted or welded to the front of the buckets, protect the bucket against the abrasive effects of soil and rocks. The rapid wear of the teeth under great loads is an important cost item in construction equipment. In this study, the stresses under the effect of dynamic loads were tried to be determined in the teeth in the backhoe loader buckets. In this context, it is aimed to determine the wear conditions of two different models of teeth, which are frequently used in the sector, with the help of the discrete element and finite element methods.
