Development of a simple force prediction model and consistency assessment of knee movements in ten-pin bowling

The aim of this research is to use LabVIEW to help bowlers understand theirjoint movements, forces acting on their joints, and the consistency of their knee movements while competing in ten-pin bowling. Kinetic and kinematic data relating to the lower limbs were derived from bowlers’ joint angles and the joint forces were calculated from the Euler angles using the inverse dynamics method with Newton-Euler equations. An artificial-neural-network (ANN)-based data-driven model for predicting knee forces using the Euler angles was developed. This approach allows for the collection of data inbowling alleys without the use of force plates. Correlation coefficients were computed after ANN training and all values exceeded 0.9. This result implies a strong correlation between the joint angles and forces. Furthermore, the predicted 3D forces (obtained from ANN simulations) and the measured forces (obtained from force plates via the inverse dynamics method) are strongly correlated. The agreement between the predicted andmeasured forces was evaluated by the coefficient of determination (R2), which reflects the bowler’s consistency and steadiness of the bowling motion at the knee. The R2 value was beneficial in assessing the consistency of the bowling motion. An R2 value close to 1 implies a more consistent sliding motion. This research enables the prediction of the forceson the knee during ten-pin bowling by ANN simulations using the measured knee angles. Consequently, coaches and bowlers can use the developed ANN model and the analysis module to improve bowling motion

Control of MacPherson active suspension system using sliding mode control with composite nonlinear feedback technique

The MacPherson active suspension system is able to support the weight of vehicle and vibration isolation from road profile, and is also able to maintain the traction between tyre and road surface. It also provides both additional stability and maneuverability by performing active roll and pitch control during cornering and braking, and the most significant are ride comfort and road handling performance. However, a drawback of MacPherson model is the self-steer phenomenon in the active suspension system. The problem might be solved by controlling the actuator force and control arm of the system. The MacPherson model has a similar layout to a real vehicle active suspension system. The mathematical model of the system produces a nonlinear mathematical model with uncertainties. Therefore, the proposed control strategy must be able to cater the uncertainties in mathematical model and simultaneously provide a fast response to the system. The control strategy combines Composite Nonlinear Feedback (CNF) algorithm and Proportional Integral Sliding Mode Control (PISMC) algorithm to achieve quick response and to reduce uncertainties. Optimisation of parameters in the CNF was performed using Evolutionary Strategy (ES) algorithm for fast transient performance. Thus, the controller is called Proportional Integral Sliding Mode Control – Evolutionary Strategy – Composite Nonlinear Feedback (PISMC-ES-CNF). To validate the proposed controller, the conventional Sliding Mode Control (SMC) and CNF were utilised to control the system under various road profiles. The ISO 2631-1, 1997 was used as a reference of ride comfort level for the acceleration of sprung mass. Results show that the proposed controller, PISMC-ES-CNF achieved the best control performance under various road profiles. The results obtained also prove that the PISMC-ES-CNF managed to improve ride comfort quality and road handling quality and has also delivered better control performance in terms of transient response of acceleration of sprung mass, reducing overshoot and chattering problem compared to conventional SMC and CNF

Intelligent active torque control for vibration reduction of a sprayer boom suspension system

The most usual way of protecting crop from diseases is by using chemical method whereby mixture of chemicals and water are sprayed onto crop via nozzles. These nozzles are located consistently along a boom structure oriented perpendicular to the direction of motion to cover large areas. The most important factor on spray distribution pattern is spray boom vibration. Thus, suspension control aims to attenuate the unwanted vibration and should provide improvements in term of distribution uniformity. In this study, a combination of passive and active suspension was considered to create superior performance. A passive suspension was employed to control undesired vertical motion of sprayer boom structure while the roll movement of spray boom was reduced via active suspension. The active suspension system of sprayer was implemented by applying robust active torque control (ATC) scheme that integrates artificial intelligence (AI) methods plus another feedback control technique utilizing proportional-integral-derivative (PID) control. The proposed control system basically comprises of two feedback control loops; an innermost loop for compensation of the disturbances using ATC strategy and an outermost loop for the computation of the desired torque for the actuator using a PID controller. Two AI methods employing artificial neural network (ANN) and iterative learning (IL) were proposed and utilized to compute the estimated inertial parameter of the system through the ATC loop. The research proposes two main control schemes; the first is a combination of ATC and ANN (ATCANN) while the other is ATC and IL (ATCAIL). The suspension system was first modeled and a number of farmland terrains were simulated as the main disturbance components to verify the robustness of the system and sprayer boom dynamic performance related to distribution uniformity. The simulation results both in frequency and time domains show the effectiveness of the proposed ATC schemes in reducing the disturbances and other loading conditions. The control schemes were further implemented experimentally on a developed laboratory spray boom suspension test rig

Kaynak dikiş formunun yapay sinir ağı ve vokselleme yöntemleriyle modellenmesi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Bu çalışmada, kaynakçı adaylarının eğitimi amacıyla geliştirilen düşük maliyetli sanal kaynak simülatörü için gerçek zamanlı ve üç boyutlu bir kaynak dikiş formu modellenmiştir. Adaylar bu simülatör vasıtasıyla kaynak tekniklerini herhangi bir iş kazasına neden olmadan güvenli bir ortamda öğrenebilir ve kısa sürede normalden daha fazla uygulama yaparak becerilerini geliştirebilirler. Geliştirilen simülatörde, Flock of Birds konum ve oryantasyon sensörü ile başa takılan ekran gibi özel sanal gerçeklik aygıtları kullanılmıştır. Simülasyon, torcun konumunu izleyen Flock of Birds sensör cihazından gelen verilere dayanarak, kaynak dolgu şeklini ve nufuziyet miktarını belirler. Kaynak dolgu şekli oluşturulurken, kaynak dikiş kesitinin parabol ile benzerliği nedeniyle bu şekil temel dolgu birimi olarak kullanılmıştır. Kaynak dikişimizi oluşturacak temel dolgu şeklinin yükseklik, genişlik ve nufuziyet parametrelerine ait değerler literatürdeki kaynak dikişi deneylerinden elde edilmiştir. Sanal kaynak işlemi esnasında, kaynak dolgu şekli parametre değerleri belirli zaman aralıklarında, ileri beslemeli geri yayılımlı yapay sinir ağı kullanılarak hesaplanır. Ağ kurgusu yapılırken eğitim fonksiyonu olarak TrainLM (Levenberg-Marquardt) referans alınmıştır. En uygun transfer fonksiyonu belirlenirken de en iyi sonucu LogSig() fonksiyonunun verdiği saptanmıştır. Ara katman sayısı ve her ara katmandaki proses elemanı (nöron) sayısının kaç olacağına deneme/yanılma yöntemiyle karar verilmiştir. Aynı zaman aralığında voksel haritası ve buna karşılık gelen hash tabanlı sekizli ağaç veri yapısı gerçek zamanlı olarak oluşturulur. Voksellenen veriler kullanılarak, kaynak dolgusunun üçgenlerden oluşan eş yüzeyleri, yürüyen küpler algoritması ile yeniden oluşturulur. Bu sayede daha gerçekçi bir kaynak dikiş görüntüsü elde edilir. Bu görüntü ve sanal sahne devamlı olarak başa takılan ekrana yollanarak sanal ortam içindeki gerçeklik hissi devam ettirilir. Vokselleme ve eş yüzey oluşturma işlemleri için yüksek çözünürlüklü sanal sahnelerde işlem süresini kısaltmak için de çok iş parçacıklı programlama tekniği kullanılmıştır. Farklı iş parçacığı sayıları için eş yüzey oluşturma süreleri de gösterilmiştir.In this study, a real time and three dimensional weld seam form was modeled for a low cost virtual welding simulator developed for training welder candidates. Through this simulator, candidates can learn welding techniques in a safe environment without causing any work accidents and improve their skills by performing more applications than usual in a short time. In the developed simulator, special virtual reality devices such as Flock of Birds position and orientation sensor and head mounted display are used. The simulation determines the weld bead shape and amount of penetration based on data from the Flock of Birds sensor device monitoring the position of the torch. When forming the weld bead shape, parabola was used as the basic bead shape unit due to the similarity of the weld bead slice with the parabola. The values of the height, width and penetration parameters of the basic weld bead shape that will form our weld seam were obtained from the weld seam experiments in the literature. During the virtual welding process, the weld bead shape parameter values are calculated at specified time intervals using the feed-forward back-propagation artificial neural network. TrainLM (Levenberg-Marquardt) was used as the training function for network design. While determining the most appropriate transfer function, it was found that LogSig () function gave the best result. The number of hidden layers and the number of process elements (neurons) in each hidden layer were determined by trial and error method. In the same time interval, the voxel map and the corresponding hash-based octree data structure are generated in real time. By using voxelized data, the triangular isosurfaces of the weld bead are reconstructed using the marching cubes algorithm. This results a more realistic weld seam appearance. This image and virtual scene are continuously sent to the head mounted display to maintain the sense of reality in the virtual environment. Multi-threaded programming technique is also used to shorten the processing time in high resolution virtual scenes for voxelization and isosurface extraction processes. The isosurface extraction times for different number of threads are also shown

Chemical machining of advanced ceramics

Not until recently did we see an enormous surge of interest in the study of machining of advanced ceramics. This has resulted in significant advances lately in their development and usage. Machinable glass ceramics, boron nitride and silicon carbide are commonly used in the industry and their major features of attraction are their inherent properties. Previous studies on machining of these materials were mainly performed by other machining methods, such as electrode discharge machining, laser beam machining and abrasive jet machining. Although chemical machining is one of the oldest machining methods employed, the literature survey reveals a lack of knowledge in this particular aspect. Further understanding is required on the chemical machining characteristics of advanced ceramics as well as their performance and relationship between the variables and parameters involved in the process. Therefore, the aim of our study is to examine and establish the relationship between etching rate, surface roughness and dimensional accuracy with the relevant variables involved and at the same time to develop the predictive models for all outputs that we believe are beneficial to the manufacturing industries.A comprehensive review was written and published recently in a Journal on the current advanced ceramics machining techniques [1]. The chemical machining process was successfully conducted in this study with a variety of selected etchants. Using the RSM methodology the first and second order models were developed to study the chemical machining process and relationship between the outputs (etching rate, surface roughness and dimensional accuracy) with the selected variables, namely, etching temperature, etching duration, etchant and etchant’s concentration. A number of predictive models were developed followed by optimisation studies of chemical machining to obtain the best performance of chemical machining of advanced ceramics. Artificial neural network was also used as the analytical tool to evaluate the experimental data and validate the results generated by response surface roughness, and both results were found to be in good agreement with each other. Artificial neural network was performed by software of NeuroSolution 5.From the chemical etching studies both the etching temperature and etchant used have significant influence on the etch rate. Generally, the higher the etching temperature the greater the etch rates was observed for the substrates. The best etch rate was found in HBr etchant for MGC and BN, and the highest etch rate performance for SiC was found in H3PO4 etchant. For surface roughness, different substrates were found to be influenced by different variables. For MGC and BN, these substrates were affected by etching temperature and the best surface roughness occurred at high etching temperature of 90oC. Etching duration was also found to be critical in determining the quality of SiC surface roughness during chemical machining.Experimental data revealed that etching rate was closely correlated to surface roughness as well as the etching ratio. However, using the best etching rate it failed to yield the quality surface roughness, but produced the best etching ratio. Each variable presented different level of significance for each output of chemical machining. The results of etch rate and etch ratio also showed that etching temperature and etching duration imparted significant impact on the chemical machining of all substrates. In the analysis of surface roughness, etching temperature was found to be the critical variable in chemical machining of machinable glass ceramics. Etching temperature and etchant influenced the surface roughness of boron nitride whereas surface roughness of silicon carbide was more dependent on etching duration and etchant used.Predictive models were developed using DE 7 once the analysis of data was completed. A total of 27 predictive models were developed for each substrate and each output. This predictive model can be used directly in the industry with the selected substrate and etchant. Optimisation of chemical machining was also performed. For machinable glass ceramic, the optimum of chemical machining happened at 100oC in 10.5 molarity HCl etchant for 30 minutes. Results of chemical machining of machinable glass ceramics were obtained with optimal etching rate of 0.0008g/min, surface roughness improvement of 81.818nm (48% improvement) and etching ratio of 3.403. In chemical etching of boron nitride, the best result occurred at 40oC in 6 molarity HBr for 62 minutes. The etching rate obtained for BN is 0.00025g/min, with surface roughness improvement of 0.01nm (16% improvement) and etching ratio of 3.153. For the chemical etching of silicon carbide, the best performance occurred at 75oC in 8.5 molarity of HBr for 240 minutes. The optimal value of etching rate for silicon carbide is 0.0009g/min, with surface roughness improvement of 128.71um (35% improvement) and etching ratio of 10.004

Dinamik kasılmalarda kas yorgunluğunun elektromiyogram ve mekanomiyogram ölçümleri ile analizi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Kas yorgunluğunu tanımlayabilecek indeksleri arttırmak ve çeşitli parametrelerle ilişkisini belirlemek, kişilere özel antrenman programlarının geliştirilmesine, kişinin günlük hayattaki aktivite programını düzenlenmesine ve olası kas hasarlarının engellenmesine destek olacaktır. Bu doğrultuda yapılan çalışmada, Bruce protokolü ve 100m sprint performans testi ile gönüllülerin kaslarında oluşturulan yorgunluğun, farklı parametreler kullanılarak belirlenmesi hedef alınmıştır. Ayrıca çalışmaya katılan gönüllülerin antrene olup olmamasının, kas yorgunluğu tespiti üzerine etkileri de incelenmiştir. Literatürde yer alan yorgunluk tespit çalışmalarından farklı olarak bu çalışmada, sadece EMG, sadece MMG ve EMG-MMG kombinasyonları karşılaştırmalı olarak değerlendirilmiştir. Analizler için ilk olarak, spor geçmişi olan fakat şuan aktif bir spor dalıyla uğraşmayan kişilerden oluşan bir gönüllü grubu oluşturulmuştur. Çalışmanın başında antrene olmayan bu gönüllü grubunun belirlenen prosedüre göre kayıtları alınmıştır. Daha sonra aynı grup 8 hafta boyunca eğim antrenmanlarına katılmış ve kasları anterene hale geldiğinde, gönüllülere aynı prosedür tekrar uygulanmıştır. Elde edilen kayıtlar önişleme, DPD tabanlı enerji değerlerinin hesaplanması ve sınıflandırma aşamalarından geçirilmiştir. DPD ayrışımı 8 seviyede gerçekleştirilmiş ve sınıflandırma yapmak için ÇKYSA kullanılmıştır. Çalışma sonucunda EMG ve MMG kayıtlarının kombine uygulamasının, antrene olmayan kişilerin kas yorgunluğunu belirlemede daha başarılı bir yöntem olduğu tespit edilmiştir. Antrene kişilerin kas yorgunluğunun belirlenmesinde ise sadece EMG kayıtlarının kullanılması durumunda en başarılı sonuçlara ulaşılmıştır. Yine antrene kişilerde MMG'nin, EMG ile kombinasyona girmesi sonucunda bu yüksek test başarı değerlerini düşürdüğü görülmüştür. Ayrıca kas yorgunluğunun belirlenmesinde kullanılacak parametrelerin sadece kendi başına değerlendirilemeyeceği, EMG ve MMG kayıtlarının alındığı kişilerin antrenman düzeyinin, yaptığı aktivite ya da sporun EMG ve MMG'nin kas yorgunluğu belirlemedeki etkinliğini tamamen değiştirdiği açıkça ortaya konulmuştur.Increasing the indexes that can define muscle fatigue and determining it's relationship with various parameters will help the development of personel training programs, the regulation of personel daily life activity program and the prevention of possible muscle impairment. Therefore, in this study carried out, determination of the fatigue, which occurs in the volunteers' muscles via Bruce protocol and 100 m sprint performance test, was aimed by using various parameters. Moreover, the effects of whether the volunteers being trained or not, over the determination of muscle fatigue were analysed as well. Differently from the fatigue determination studies that are present in the literature, the records of solely Electromyogram (EMG), solely Mechanomyogram (MMG) and the combination of EMG and MMG were evaluated comperatively. For the analysis, firstly, a volunteers group, made of people who had a suport background in the past but now does not engage in any sport branches were performed. At the beginning of the study, the records of this group of volunteers who were untrained were taken according to the determined procedure. Afterwards, the same group participated in the trainings for 8 weeks and once their muscles became trained, the same procedure was applied to the volunteers again. The obtained records were passed through the stages of pre-processing, calculation of energy values based Wavelet Packet Transform (WPT), and classification. Decomposition of WPT was carried out in 8 levels and the Multi-layer Perceptron Artificial Neural Network (MLPNN) was used for classification. As the result of the study, it was determined that the combined application of EMG and MMG records was a more successful method for determining the muscle fatigue of those who were untrained. As for the determination of fatigue levels of those who were trained, the most successful results were attained by the use of solely EMG records. Once again, it was clearly revealed that the parameters to be used for the determination of muscle fatigue should not be evaluated single-handedly, and the training level of the persons, whose EMG and MMG records were taken, the daily activities they do and the sport activities they take part in totaly changed the effectiveness of determination of muscle fatigue by using EMG and MMG

Accelerating the Levenberg-Marquardt method for the minimization of the square of functions with box constraints

Orientadores: Francisco de Assis Magalhães Gomes Neto, Jose Mario MartinezTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação CientificaResumo: Neste trabalho, apresentamos um algoritmo iterativo para a minimização de somas de quadrados de funções suaves, com restrições de caixa. O algoritmo é fortemente inspirado no trabalho de Birgin e Martínez [4]. A diferença principal está na escolha da direção de busca e na introdução de uma nova técnica de aceleração, usada para atualizar o passo. A cada iteração, definimos uma face ativa e resolvemos, nessa face, um subproblema quadrático irrestrito através do método evenberg-Marquardt (ver [26], [28] e [33]), obtendo uma direção de descida e uma aproximação x+ para a solução do problema. Ainda usando apenas as variáveis livres, tentamos acelerar o método definindo uma nova aproximaçaoo xa como combinação linear das últimas p - 1 aproximações da solução e do vetor x+. Os coeficientes desta combinação linear são calculados convenientemente através da resolução de um problema de Quadrados Mínimos com uma restrição de igualdade. O subproblema que determina o passo acelerado leva em conta as informações sobre a função objetivo nessas p soluções aproximadas. Como em [4], executamos uma busca linear ao longo da direção e usamos técnicas de projeção para adicionar novas restrições. Para deixar a face ativa, usamos a direção do gradiente espectral projetado [5]. Experimentos númericos são apresentados para confirmar a eficiência e robustez do novo algoritmo.Abstract: In this work, we present an active set algorithm for minimizing the sum of squares of smooth functions, with box constraints. The algorithm is highly inspired in the work of Birgin and Mart'inez [4]. The differences are concentrated on the chosen search direction and on the use of an acceleration technique to update the step. At each iteration, we define an active face and solve an unconstrained quadratic subproblem using the Levenberg-Marquardt method (see [26], [28] and [33]), obtaining a descent direction and an approximate solution x+. Using only the free variables, we try to accelerate the method defining a new solution xa as a linear combination of the last p-1 approximate solutions together with x+. The coefficients of this linear combination are conveniently computed solving a constrained least squares problem that takes into account the objective function values of these p approximate solutions. Like in [4], we compute a line search and use projection techniques to add new constraints to the active set. The spectral projected gradient [5] is used to leave the current active face. Numerical experiments confirm that the algorithm is both efficient and robust.DoutoradoMatematica AplicadaDoutor em Matemática Aplicad

Modelos no lineales de pronóstico de series temporales basados en inteligencia computacional para soporte en la toma de decisiones agrícolas

Tesis (DCI)--FCEFN-UNC, 2016Centra modelos predictivos basados en redes neuronales destinados a pronosticar datos históricos de lluvia observados para la toma de desiciones. Estos algoritmos de aprendizaje automático pueden mejorarse en numerosos aspectos y son una herramienta muy promisoria en el ámbito agropecuario