Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 508
Design of an Optimal Linear Quadratic Regulator (LQR) Controller for the Ball-On-Sphere System
Статья научная
Linear Quadratic Regulator (LQR) is one of the optimal control methods that continue to gain popularity. This paper designed an optimal LQR controller to control the system of the ball-on-sphere. System equations were derived and due to the nonlinearity of the system, the equations were linearized. After that, the coefficient matrices of the system dynamics were derived. Given some initial conditions, the response was simulated and controlled close to the desired values. An improvement of about 87% was achieved and the performance of the controller was observed to be good based on the simulation results. The results showed that LQR controller is one of the best optimal control methods because of its high performance improvement.
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Design of the Wing of a Medium Altitude Long Endurance UAV
Статья научная
Over time, the need to extend the endurance of fixed-wing UAVs has been a challenge and requirement for the aviation industry. As a result, there are many ongoing researches on how to address this challenge while developing new concepts for an aircraft wing. This paper presents the methodology applied in the design of the wing of a lightweight unmanned aerial vehicle (UAV) that is intended for intelligence and surveillance (ISR) missions. A conceptual design was developed with the aircraft having a hybrid wing for the purpose of improving its structural design. The wing has two spars and thirteen ribs a side with an all-composite structure. Initial calculations were performed theoretically, thereafter, analyzed using the finite element analysis tool.
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Detection and classification of tumour in brain MRI
Статья научная
Brain Tumour is an abnormal cell formation inside the brain. They are mainly classified as benign and malignant tumours. Magnetic Resonance Imaging (MRI) is used for effective diagnosis of brain tumour. An automated method for detection and classification of brain tumour is preferred as analysis of MRI manually is a difficult task for medical experts. The proposed method uses Adaptive Regularized Kernel based Fuzzy C-Means Clustering (ARKFCM) for segmentation. A combination of Support Vector Machine (SVM) and Artificial Neural Network (ANN) is proposed for detection and classification of brain tumour based on the extracted features. A dataset of 94 images is considered for validation of the proposed method which resulted in an accuracy of 91.4%, Sensitivity of 98%, Specificity of 78% and Bit Error Rate (BER) of 0.12. Comparison of the proposed method is carried out with other conventional methods and the results are tabulated.
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Development and Evaluation of BOD–DO Model for River Ghataprabha near Mudhol (India), using QUAL2K
Статья научная
The present study involves the application of a water quality model QUAL2K for developing the BOD-DO model and evaluation of the results for a 50 km stretch of river Ghataprabha near Mudhol town of Bagalkot district, Karnataka. QUAL2K is a modeling framework for simulating river and stream water quality. Arc-GIS technique is used to obtain some hydro-geometric data of the river for input to model QUAL2K. For calibration and validation of the model, the BOD and DO values were monitored at six different locations. The calibrated model was validated to predict water quality using a different set of data under different conditions. The performance of the model was evaluated using statistics based on Standard errors (SE), Normalized Mean Errors (NME) and Mean Multiplicative errors (MME). The SE and MME values for BOD and DO during calibration are, 1.41 (1.12) and1.28 (0.90), respectively. The values in the bracket show MME. Corresponding values for the validation are 1.27 (1.09) and 1.10 (0.96). These results show that the values predicted by the model are in close agreement with measured values.
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Development of a 120kg Load Lifting Capacity Scissor Elevator Platform
Статья научная
This work focused on the development of a 120kg load lifting capacity scissor elevator platform (SEP) with a horizontally positioned rack and pinion gear actuating mechanism which is driven by a DC motor. The time of lift to an elevated height of 0.9m is 30s. Simulation of a typical SEP structure in the 3D workspace of a Computer Aided Design (CAD) software package was carried out to investigate the balance of the SEP structure, the stresses experienced, the efficiency, and safety of operations. A prototype was also fabricated for the physical demonstration of SEP. The SEP can be used for a range of engineering applications such as making an adjustable workbench for workshop use, solving the problem of table adjustment for height-challenged personnel, or used as a load-transferring device if mobile to transfer loads between two or more elevated locations during construction or maintenance work. Calculated results give the platform weight as 136.693N, the scissor arms weight as 188.205N, the total structure weight as 1502.098N, the stress in the scissor arm at maximum platform elevation as 1.702MPa, the stress in the scissor arm at minimum platform elevation as 4.928MPa, the maximum actuation force as 4126.980N, and the power required to drive the mechanism as 26.963W. Autodesk Inventor Pro simulation results show that a wide range of data can be sourced when one considers the real-time behavior of SEP. The results also indicated the values of the reaction forces, reaction moments, stresses, strains, and displacements developed at every joint, link, hinged support, and every other point in a 3D workspace.
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Development of a Mobile Liquid Spraying Machine for Small and Medium Scale Crop Production
Статья научная
This article presents the design, simulation, fabrication and performance evaluation of a liquid spraying machine for application of pesticides in a small and medium scale crop plantation. In this article, components of the conceptualized spraying machine were modelled and assembled in SolidWorks CAD environment. The modelled components were designed in order to obtain design parameters for simulation. An extensive simulation on the stress and strain analysis was carried out on the designed components. The significance of the simulation is to predict the structural integrity and performance of the component parts of the machine before fabrication. The components were fabricated from locally sourced material in order to ensure a lower cost of production. The fabricated spraying machine was tested and the performance indicated that a field efficiency of 79% is obtainable in an average time of 1374 s to spray a maize crop field area of 1813 m2 having an average crop height of 0.52m. Further observations from the performance analysis also show that the field efficiency of the spraying machine drops to a value of 75% when used in a crop field area of 2206.3 m2. This is an indication that the spraying machine’s efficiency will reduce as the field area increases. In essence, the significance of the approach presented in this article is to ensure that the simulation predicts the performance of the design and the fabrication of the spraying machine using locally sourced material will ensure lower cost of fabrication.
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Development of a Multi Degree-of-Freedom Vibration Exciter for Laboratory Applications
Статья научная
Introduction of vibration to manufacturing operations such as casting and welding has proved to improve the physical and mechanical properties of manufactured parts. A vibration exciter is developed for the purpose of generating and inducing vibration, along different degrees of freedom, on objects placed on its surface. The equipment applies an eccentric mass drive system which gives the equipment an overall advantage in varying the vibration parameters. The acceleration of the vibratory motion of the equipment was measured using an accelerometer and oscilloscope set-up. The natural frequencies of the different vibration modes are also obtained from a developed mathematical model executed using the MATLAB Simulink software. The developed equipment successfully generated random sinusoidal vibrations of accelerations ranging from −5 m/s^2 to 8 m/s^2 along the principal axes and angular accelerations ranging from −40 rad/s to 40 rad/s about the pitch and roll axes. Natural frequencies of f_x = 3.78 Hz, f_θ = 7.94 Hz and f_φ = 9.89 Hz are obtained along the vertical, pitch and roll directions respectively. The presented results indicate that the developed machine successfully satisfied the proposed hypothesis of being able to measure vibrational characteristics along different degrees of freedom.
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Development of a low-cost air quality data acquisition IoT-based system using arduino leonardo
Статья научная
Air pollution is responsible for an estimated 5.5 million deaths in 2013 which costed the global economy approximately US$225 billion in lost labor income. To address the problems caused by air pollution, this study aims to develop a low-cost and portable air quality monitoring system that detects the levels of CO, PM2.5, PM10, temperature, and humidity. Using Internet of Things (IoT), the data that the system gathers can be accessed through the internet. Moreover, the system assesses the obtained data through a comparative analysis with the AQI. The Iterative Design Loop method was used in the development of the air quality monitoring system. Furthermore, the sensors were programmed using the Arduino Integrated Development Environment (IDE). Using the Welch’s t-test, it was found that the obtained data of the system is not significantly different to that of the standard air quality monitoring systems. To achieve more accurate data from the developed system, the raw data of the developed and standard system were calibrated through an equation from the trendline. Through the use of Acer CloudProfessor, the study successfully developed an air quality monitoring system that can be accessed through the internet.
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Статья научная
Wireless sensor networks (WSN), when applied to the field of water quality monitoring and management, has the potential to bring numerous benefits as compared to traditional methods since it is accurate, reliable in remote areas and in the tough condition such as during rainy seasons, and less costly. With the ever-growing application of Internet of Things (IoT) and technology in general, sensor devices have become less expensive and widely used in many applications that require remote monitoring. In this work, we present an innovative and secure water monitoring and management system using remote sensor prototype, which has been developed to monitor physiochemical parameters including pH, Turbidity, Temperature, and Dissolved Oxygen. Qualitative research methods were used for gathering system requirements through questionnaires and interviews conducted in Pangani water basin authority, in the United Republic of Tanzania. Documents were also reviewed to provide secondary knowledge. Furthermore, the system was developed using Dynamic System Development Methodology (DSDM). Firstly, the proposed system prototype is able to provide real-time measurements accurately. Secondly, the proposed system uses Advanced Encryption Standards to provide a secure transmission and storage of data transmitted from remote sensor nodes to a central database system. Thirdly, the web application was developed for data visualization using tabular and graphical formats. Lastly, the system prototype provides decisions support on quality of water present in Pangani river basin by evaluating sensor measurements and sends SMS alerts once the measured value is above the recommended standard values.
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Development of machine vision system for automatic inspection of vehicle identification number
Статья научная
The vision system is developed to reduce the human effort and improve productivity in the Vehicle Quality Assurance (VQA) shop for inspection of a car bearing a Vehicle Identification Number (VIN), assigned to it at the assembly shop. This project work is carried out in association with M/s Renault Nissan Automotive India Pvt Ltd, Chennai. The vision system consists of a camera fixed on a pan-tilt camera frame and an Optical Character Recognition (OCR) software. The camera frame is mounted on a belt conveyor with remote control of forward, backward and tilting motion. The image of VIN present at the car door is captured through a digital camera placed adjacent to the car. The characters in the VIN image thus obtained are extracted using MATLAB, with configurable OCR software. Template matching method is followed in the OCR process. The MATLAB code can overcome trivial issues in VIN image inspection at the quality shop. Development of a graphic user interface to the software is also described.
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Diffraction Tomography: It's Application in Ultrasound
Статья научная
Ultrasound Diffraction Tomography (UDT) is an important alternative to conventional B-mode imaging. Generally, in diffraction tomography, the most universal available computational strategies for reconstructing the object from its projections are interpolation in the frequency domain and interpolation in the space domain. They are analogous to the direct Fourier inversion and backprojection algorithms of straight ray tomography. In this paper two B-spline interpolation functions are introduced. Due to the computational expenses in the space domain interpolation, we apply the interpolation in the frequency domain to implement our new interpolation functions. We also compare our results with filtered backprojection algorithm result. The validity and feasibility of our method was tested using an agar phantom to mimic the human tissue, olive to mimic the cancer, and water to mimic the cyst. The experimental results show that this method has a promising impact in clinical applications.
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Статья научная
This paper presents a distribution network reconfiguration based on bacterial foraging optimization algorithm (BFOA) along with backward-forward sweep (BFS) load flow method and geographical information system (GIS). Distribution network reconfiguration (DNR) is a complex, non-linear, combinatorial, and non-differentiable constrained optimization process aimed at finding the radial structure that minimized network power loss while satisfying all operating constraints. BFOA is used to obtain the optimal switching configuration which results in a minimum loss, BFS is used to optimize the deviation in node voltages, and GIS is used for planning and easy analysis purposes. Simulation is performed on the 33-bus system and results are compared with the other approaches. The obtained results show that the proposed approach is better in terms of efficiency and having good convergence criteria.
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Driver Drowsiness Detection System
Статья научная
When you are driving a car and you are being responsible for your co-passenger and other innocent being on the road, you should be extra responsible. Many fatal and minor accidents happen on the road due to the drowsiness of drivers only. Hence, there is a need to detect drowsiness while driving a car. It has become an important requirement for everyone’s safety. The main objective of this study is to create a highly accurate drowsiness detection system using methods that are both affordable and easy for any car manufacturer to include in their cars. The ultimate objective is to increase road user’s protection by raising the level of safety for both drivers and their cars. This study's main contribution is the implementation of a bimodule method for drowsiness detection. The first module effectively detects signs of drowsiness by analyzing a constant stream of images of the driver in real time using a reinforcement learning model. Simultaneously, the car's second module, which is built into the steering wheel grip, keeps track of the driver's hand pressure when performing turns and emergency scenarios. The findings of the study highlight how well the proposed system works to reduce the risks associated with drowsy driving. It further highlights the value of cutting-edge technology in protecting other drivers and improving driving safety, which has the potential to save lives and avoid accidents.
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Dynamic Modeling and H∞ Control of Offshore Wind Turbines
Статья научная
In this paper, vibration control problem in tension leg platform offshore wind turbines is investigated. First a non-linear model of the wind turbine is obtained. Six degrees of freedom are considered in the model including surge, heave and pitch of the platform, tower fore-aft vibrations, rotor rotation and drivetrain torsional vibration. Moreover all external loads acting on the offshore wind turbine such as aerodynamic loads, hydrodynamic loads and mooring line forces are taken into account. To achieve an accurate model of the wind turbine, tower and drivetrain are modelled as flexible components. The model output is compared with FAST simulator; a popular open source software for modeling wind turbines. Then, a robust controller is designed to regulate rotor speed and output power, increase wind turbine efficiency and attenuate tower fore-aft vibration. The controller is implemented on the non-linear dynamic model to investigate the closed loop performance.
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Dynamic Modelling and Control of Flapping Wing Micro Air Vehicle for Flap-Glide Flight Mode
Статья научная
Flapping wing micro-air-vehicles (FWMAV) are micro-air-vehicles that use biomimetic actuation (oscillatory flapping wing) for aerodynamic force generation. The realization of such bionic flight, which offers small size, low speed, and flexible maneuverability has significant military and civilian values. Thus the design of FWMAV (ESB-I) will be very important for security related sectors since they have all the right stuffs for surveillance and reconnaissance. Since everything about a bird is made for flight the kinematic and dynamic modeling as well as control algorithm of bird like FWMAVs is more complex than that of serial robots. Thus balancing the main requirements for the design of FWMAVs which includes excellent aerodynamic performance, high efficiency, and satisfactory maneuverability is very important. With the aim to improve the performance of a FWMAV this work incorporates an intermittent flapping and gliding flight mode. Flap-gliding flight mode, which is often used by large bird species, effectively combines the aerodynamic advantages of fixed and flapping wings. Inspired from it, a kind of flexible flap-gliding Micro Air Vehicle, named Ethio-Smart Bird-I (ESB-I), was successfully designed. An expression describing the mechanical energy cost of travelling of this flight mode in terms of work per range for one flap-glide flight cycle was presented. It is shown that there is an energy saving of flap-gliding flight compared to continuous flapping flight. However due to a system dynamic variation in this flight mode, it possesses difficulty in control surface design. To implement this specific flight mode, this thesis proposes a closed-loop active disturbance rejection control, ADRC, strategy to stabilize the attitude during the processes of flapping flight, transition and gliding flight. To verify the control effect, the unsteady aerodynamic estimation method of the flapping wing based on modified strip theory approach and the dynamics of the FWMAV in Lagrangian form were modelled in the MATLAB/SIMULINK platform and applied in the simulation. Using this model longitudinal stability of ESB-I was analyzed. Simulation results show that even if the FWMAV is in different flight modes, ADRC controller can track the target pitch signal effectively with tracking error less than 0.05rad. To further explain the effects of ADRC in this specific flight mode, the control effects of a PID controller is presented. As per the simulation result ESB-I with PID controller has a target pitch angle tracking error greater than 1rad. This shows that, in flap-gliding flight mode ADRC can track the target pitch signal better than PID controller.
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Early Detection of Dementia using Deep Learning and Image Processing
Статья научная
Dementia is the world's most deadly disease. A degenerative disorder that affects the thinking, memory, and communication abilities of the human brain. According to World Health Organization, more than 40 million people worldwide suffer from this illness. One of the most common methods for analyzing the human brain, including detecting dementia, is using MRI (Magnetic resonance imaging) data, which provides insight into the inner working of the human body. Using MRI images a deep Convolution neural network was designed to detect dementia, we are utilizing image processing to help doctors detect diseases and make decisions on observation, in an earlier stage of the disease. In this paper, we are going to get to the bottom of the DenseNet-169 model, to detect Dementia. There are approximately 6000 brain MRI images in the database for which the DenseNet-169 model has been used for classification purposes. It is a Convolution Neural Network (CNN) model that classifies Non-Dementia, Mild Dementia, Severe Dementia, and Moderate Dementia. The denseNet-169 model helps us determine Dementia disease. And also present the 97% accuracy for clarification of disease is present in the patient body. we are conducted this survey for providing effective disease prediction model for physicians to conclude that the disease stage is accurate and provide proper treatment for that.
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Edge Detection of Image Using Image Divergence and Downsampling Method
Статья научная
Classically, the points where digital image brightness transforms rapidly are ordered into a group of curved line segments termed as edges. Edge detection is an important feature and tool in digital image processing to analyze the significant changes in gray level image intensity. In this paper, an edge detection method is proposed. In the proposed method divergent operation is applied to the image to compute the Laplacian of the image. After then the sample rate of Laplacian of image is decreased by downsampling. A threshold value is yielded by computing the mean on the down sample value. Laplacian of image and threshold value is compared and pixel values are set according to the threshold value. Then the morphological operation is performed on the processed image to produce the final edge detection image. The significance and value of this research are reducing image noise by downsampling and searching vital edge information through divergence operation. The present study introduces a new method of edge detection. The finding of this research work is to detect the edges of objects. The proposed method is compared with other existing edge detection methods i.e., Canny, Sobel, Robert, Zero cross, and Frei-Chen. Quantitative evaluation is performed through various metrics i.e., Entropy, Edge-based contrast measure (EBCM), F-Measure, and Performance ratio. Experimental results obtained from MATLAB 2018a show that the proposed method performs better than other well-known edge detection methods.
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EduCloud: A Dynamic Three Stage Authentication Framework to Enhance Security in Public Cloud
Статья научная
Now-a-days, one of the most exciting technology is cloud computing. Accessing dynamically virtualized resources through internet is called as cloud computing. Security and confidentiality are the major concerns in public cloud. Though EduCloud (Educational Cloud) uses public cloud, moving data from one location to another location may lead to risk. Information related to staff, student and management or admin that can be shared in EduCloud, are to be secured in public educational cloud environment. In this scenario, data security is the most critical issue in cloud. But present authentication system available does not provide enough security in public EduCloud. Hence, we propose new authentication framework to enhance security in public educational cloud. The features of various authentication techniques are discussed in this paper and a novel framework is proposed for pubic EduCloud, which provides not only security but also increases the response time. The developed software tool is best suited and provably a secured solution to the public educational cloud environment.
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Effect of Thar Coal Fly Ash on Compressive and Tensile Strength of Concrete
Статья научная
This study's subject is the effectiveness of substituting Thar Coal Fly Ash (TCFA) for ordinary Portland cement, also known as OPC. Tharparkar, Pakistan, possesses the world’s third largest coal reserves, with deposited coal fuel of 175 billion tons and capable of providing energy for over 200 years. Thar Coal is a lignite type that produces 7-10% of by-products in ashes; among them, Fly Ash is a significant waste. Reusing this waste as a partial cement replacement offers an environmentally friendly solution. This study prepared concrete specimens with varying proportions of TCFA (0%, 10%, 20%, and 30% by mass) as cement substitutes. Compressive strength tests were conducted on 36 cubes (100mm x 100mm x 100mm) with different fly ash percentages at a proportion to water to cement of 0.52. Ages 7, 14, and 28 days for curing were considered. The findings demonstrate that a higher TCFA component enhances the workability of the concrete. At all curing ages, the strength in compression at a 20% TCFA replacement level was greater than that of standard concrete. However, as the cement replacement was increased to 30%, there was a slight decrease in the comparative compressive strength compared to regular concrete. The tensile strength of the splitting test, performed after twenty-eight days of curing age, reveals that it surpassed conventional concrete for all replacement levels. Considering the favorable outcomes in workability, constrictive strength, durability strength, and substantial economic and environmental benefits, there is much potential for using TCFA as a cement substitute in the construction sector.
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Статья научная
The main objective of the study was to investigate the effect of various filler materials on inter laminar shear properties of glass/epoxy composite materials. In this study three different filler materials were selected (SiO2, TiO2, Glass powder) for high strength and stiffness applications. The physical properties are also studied with the composites. The fiber volume fraction of material plays vital role in preparation of composite laminates. The fabrication method used was conventional hand lay-up process depending upon the resin system hot temperature cure and room temperature curing processes were selected. The short beam shear test was carried out to test inter laminar shear strength (ILSS). The short beam shear test results inter laminar shear strength and to find the significant influence of filler material on characterization of glass fiber reinforced plastic (GFRP) composite. The test results shown that high shear strength were observed with silicon dioxide(SiO2) filler material and with 10% of silicon dioxide filler material shows maximum ILSS value.
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