Faculty of Engineering

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Now showing 1 - 7 of 7
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    PublicationOpen Access
    Development of an underwater robotic arm using multibody dynamics approach
    (2022-02-05) Fernando, S; Perera, M
    Underwater robotic arms are important devices that enables workers to carry out tasks remotely from a safe distance reducing or eliminating the risks that are involved with the task. The primary objective of the robotic manipulator is to perform maintenance and cleaning activities of the hull of a ship. However, the control of these devices underwater is quite complicated due to the numerous factors that make these systems unstable and non-linear. The aim of this study is to develop a multibody dynamic robotic manipulator model, integrated with a control strategy to optimize and obtain stable kinematics solutions. The hydrodynamic forces are integrated to the manipulator model considering buoyancy forces and surface drag forces. A basic algorithm is used to generate the joint angles using 7 geometrical parameters. The control of the manipulator was done to simply follow any path that represents the given coordinates. The P, I and D parameters are tuned individually to optimize the kinematic solution of the manipulator. 3-DOF articulated manipulator is the commonly used manipulator configuration. However, a 6-DOF manipulator configuration was selected in this study to allow for change in orientation using wrist motions.
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    PublicationEmbargo
    Development of an Eccentric Legged Quadruped Robot for a Predefined Uneven Terrain
    (IEEE, 2022-06-01) Dayawansa, B; Vasudevan, P; Irfan, I; Liyanage, M
    Bio-inspired robotics is a relatively new branch in the field of robotics. It involves the study of the anatomical, morphological and physical behavior of natural living animals and implementing such morphologies and mechanisms in an electro-mechanical system. The field of bio-inspired robotics has given birth to many complex mobile robot topologies which also include legged locomotion. Legged robots help the designers gain an insight into how the biomechanics of animals operate which also can help inspire new technologies in the field of prosthetics and artificial limbs. Legged robots have a higher terrain adaptability and mobility compared to wheeled robots which makes them a good choice for uneven terrain navigation. Legged locomotion itself has a wide scope with various topologies and morphologies involved. In this paper we have evaluated all existing quadruped robot models currently, and have proposed a distinctive quadruped model structure and morphology for uneven terrain locomotion. The robot model has been analyzed through computational modelling and simulation techniques for optimum leg morphologies and gait patterns. The results demonstrated that certain leg morphologies were more efficient compared to other considered leg morphologies. The robot was fabricated physically and tested for the same morphologies in an uneven terrain as well.
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    PublicationOpen Access
    Experience of Automatic Traffic Data Collection for Development of Adjustment Factors in Colombo Suburban
    (Eastern Asia Society for Transportation Studies, 2019-12-31) AHAMED, R. W; LANKATHILAKE, T. N; AMARASINGHA, N
    Annual Average Daily Traffic (AADT) is one of the key parameters in the field of transportation. It is traditionally used for planning and designing purposes in road sector. This research was carried out for development of adjustment factors for AADT estimation two-way two-lane road of Colombo suburban. Malabe-Kaduwele roadway was selected to conduct the research. Data were collected using automatic traffic counter (Metro-Count device) at Malabe-Kaduwele road in front of SLIIT Malabe campus for the period of five and half months. From the data, hourly expansion factors (HEF) and daily expansion factors (DEF) were estimated. The data collection period was not sufficient to develop monthly expansion factors (MEF) but an attempt was made to develop factors for months fall in data collection period. The experience obtained in this study could be used for developing adjustment factors in future.
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    PublicationEmbargo
    Development of multi-sensory feedback system for building automation systems
    (IEEE, 2017-10) Basnayake, B. A. D. J. C. K; Amarasinghe, Y. W. R; Attalage, R. A; Jayasekara, A. G. B. P; Devinda, M. G. K
    Under this research, the multi-sensory feedback system has been developed utilizing commercially available MEMS based and miniaturized sensors for building automation systems. This system consist of non-contact infrared thermal array sensor based occupancy identification / localization system and self-floor locations categorization system with an environmental monitoring system. Further, it has smart realtime energy monitoring system which capable to identify the load devices and their status while operation. The entire system is capable of obtaining quantitative values of this sensory information and applied for the development of more convenient and energy efficient automation in building premises. The implemented system was tested and validated using fuzzy logic based building automation controller via the wireless network.
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    PublicationOpen Access
    Development of a Formula to Quantity Emlsslons Generated from Dlesel Vehicles in Sri Lanka
    (ACEPS-2017, 2017) Konara, K. M. T. N; Samarasekara, G. N; Chaminda, G. G. T; Dissanayaka, A. W; Perera, S. V. T
    Using the combination of optical properties of diesel exhaust and Beer Lambart law, particulate concentration was derved. Major component of the particulate matter of diesel exhaust was elė carbon which was derived from the optical properties of diesel exhaust. Characteriza emission composition was done through literature. According to the Spaciate 4.0 databa state environmental agency, characterization of diesel emission was finalized. Spaciate 4 the diesel exhaust is a primary combination of Organic carbon (31.80%), Elemental ca Sulphate (0, 67%), Nitrate (0.19%) and others including metallic components and etc.(6 that, a balanced chemical equation was formed for the incomplete combustion of the di air. Calculation of CO2, CO and PM was derived based on the stoichiometric ratio of the bäjä chemical equation.
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    PublicationEmbargo
    Development and testing of a novel high speed SCARA type manipulator for robotic applications
    (IEEE, 2011-05-09) Liyanage, M. H; Krouglicof, N; Gosine, R
    This paper proposes using servo hydraulics for high speed robotic manipulation. It details the development of a novel double vane rotary type actuator custom designed for use in a Selective Compliant Assembly Robotic Arm (SCARA). The system, which is mathematically modeled and simulated, consists of an electro-hydraulic servo valve, double vane rotary actuator, manipulator and a controller. Based on the simulation results, hydraulic actuators were sized for optimal performance. A prototype of the proposed manipulator was built and tested. The test results show that the proposed actuator is capable of reaching torques of up to 860 Nm. The end effector of the manipulator is capable of reaching average velocities in excess of 2.7 ms -1 with a payload capability of 5.3 kg. Comparable performance is not feasible with contemporary SCARA type robots with electric motors.
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    PublicationOpen Access
    Development of wind power prediction models for Pawan Danavi wind farm in Sri Lanka
    (Hindawi, 2021-05) Peiris, A. T; Jayasinghe, J. M. J. W.; Rathnayake, U. S
    This paper presents the development of wind power prediction models for a wind farm in Sri Lanka using an artificial neural network (ANN), multiple linear regression (MLR), and power regression (PR) techniques. Power generation data over five years since 2015 were used as the dependent variable in modeling, while the corresponding wind speed and ambient temperature values were used as independent variables. Variation of these three variables over time was analyzed to identify monthly, seasonal, and annual patterns. The monthly patterns are coherent with the seasonal monsoon winds exhibiting little annual variation, in the absence of extreme meteorological changes during the period of 2015–2020. The correlation within each pair of variables was also examined by applying statistical techniques, which are presented in terms of Pearson’s and Spearman’s correlation coefficients. The impact of unit increase (or decrease) in the wind speed and ambient temperature around their mean values on the output power was also quantified. Finally, the accuracy of each model was evaluated by means of the correlation coefficient, root mean squared error (RMSE), bias, and the Nash number. All the models demonstrated acceptable accuracy with correlation coefficient and Nash number closer to 1, very low RMSE, and bias closer to 0. Although the ANN-based model is the most accurate due to advanced features in machine learning, it does not express the generated power output in terms of the independent variables. In contrast, the regression-based statistical models of MLR and PR are advantageous, providing an insight into modeling the power generated by the other wind farms in the same region, which are influenced by similar climate conditions.