Vibration analysis of an experimental double bridge crane system with artificial neural networks (original) (raw)
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Kinematic Analysis of Cranes Using Neural Networks
Proceedings of the ... ISARC, 1999
Due to load uncertainties of cranes, it is necessary to find exact kinematic parameters of crane mechanisms. prograrruning techniques [41. The objective function for minimization was taken as the weight of the girder. The limitations on the stresses and the deflections induced in the girder in different load conditions were stated in the form of inequality constraints. This research is concerned with application of neural network to the kinematic analysis of a crane mechanism. The type of network investigated is a Radial Basis Neural Network (RBNN). The crane mechanism is considered as a double-rocker four-bar mechanism. Desired kinematic parameteres of the crane is found by a a software deal ing with simulation and analysis of nrecharmisms. The RBNN is employed in four parameters prediction schemes; displacement, velocity, acceleration and force. The results obtained have supported the theory that the proposed RBNN is able to predict different types of crane system.
Force Analysis of Bearings on Cranes Using a Proposed Recurrent Hybrid Neural Network
Due to load uncertainties of cranes, it is necessary to find exact kinematic parameters of crane mechanisms. This research is concerned with application of neural network to the force analysis of a crane mechanism. The type of network investigated is a Recurrent Hybrid Neural Network (RHNN). The crane mechanism is considered as a double-rocker four-bar mechanism. Desired kinematic parameteres of the crane is found by a software dealing with simulation and analysis of mechanisms. The RHNN is employed in four parameters prediction schemes: displacement, velocity, acceleration and joints forces. The results obtained have supported the theory that the proposed RHNN is able to predict different types of crane system.
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20th Annual International Conference on Mechanical Engineering-ISME2012, 2012
In the present work, the adaptive neural network controlling technique is considered in order to have tracking control of a 3-D overhead gantry crane system which uses in industry to transport heavy loads. The dynamic equation used in this paper is based on close form equations of motion, made by lagrangian method. To control this system, a proper control law was conceived and used. With the aim of having an experimental condition in common with the real condition, the controller is designed in the appearance of load disturbance. The Simulation results substantiate the accuracy and the similarity between the desired values and the tracked ones.
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2020
This paper proposes an input shaping technique for efficient payload swing control of a tower crane with cable length variations. Artificial neural network is utilized to design a zero vibration derivative shaper that can be updated according to different cable lengths as the natural frequency and damping ratio of the system changes. Unlike the conventional input shapers that are designed based on a fixed frequency, the proposed technique can predict and update the optimal shaper parameters according to the new cable length and natural frequency. Performance of the proposed technique is evaluated by conducting experiments on a laboratory tower crane with cable length variations and under simultaneous tangential and radial crane motions. The shaper is shown to be robust and provides low payload oscillation with up to 40% variations in the natural frequency. With a 40% decrease in the natural frequency, the superiority of the artificial neural network–zero vibration derivative shaper ...
Mathematical and s-models of cargo oscillations during movement of bridge crane
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 2019
The effectiveness of research on the basis of mathematical models (linear, nonlinear) describing the dynamics of bridge cranes and cargo oscillations during transitional modes of movement, increases significantly with the use of numerical methods and simulation models created by visual programming tools. Purpose. To develop and evaluate proposed simulation models of bridge crane dynamics. methodology. On the basis of wellknown mathematical models, simulation models of the "bridge crane (trol ley)-cargo on a flexible suspension" system are developed. The simulation models are created using the visual pro gramming tools of the SIMULINK application running on the MATLAB system. Simulink libraries and DSP System Toolbox components are used in the simulation. findings. Smodels of cargo oscillations during the bridge crane movement have been developed and adjusted. A comparative analysis of the proposed models has been performed. originality. With the help of SIMULINK visual programming tools for the first time we received a set of simula tion models of cargo oscillations during the transition modes of the bridge crane movement for linear and nonlinear formulation of the task. Practical value. The proposed smodels allow automating and visualizing studies of dynamics of bridge crane movement in order to determine their rational kinematic and dynamic characteristics. The models are provided with examples of calculation of dynamic motion modes.
Overhead travelling cranes work with intermittent motion, and therefore are most exposed to dynamic loads. In steel constructions, as a result of load pick up from the ground, vibrations of various degrees of intensity are induced, which should be included in crane design. These loads affect both the hoisting mechanisms and load-carrying structures. The aim of this study is the formulation of a phenomenological model of an overhead travelling crane enabling the identification of dynamic factors caused by lifting the load off the ground. The object of the study was 107 overhead travelling cranes with lifting capacities from 5 to 50 tones, designed in the Centre for Research and Development of Cranes and Transport Equipment " Detrans " in Bytom and produced in Poland in the period 1970-2005. Cranes were classified according to the stiffness classes proposed in European standards for crane safety. In this paper, computer simulations are carried out on the basis of a phenomeno...
Adaptive hierarchical sliding mode control using neural network for uncertain 2D overhead crane
International Journal of Dynamics and Control, 2019
This paper proposes an adaptive hierarchical sliding mode control method based on radial basis function neural network for an uncertain 2D overhead crane system. A second-level sliding surface is defined by a linear combination of two subsystem's sliding surfaces. A radial basis function neural network is adopted to approximate the unknown dynamic model. The control law is designed in order to ensure the stability of sliding surfaces and an updated law for neural network's weight matrices is derived from a candidate of Lyapunov function. Simulation results show that the effectiveness of the proposed control scheme, such as smaller swing and accurate position as desired. Besides that, the controller is installed in micro-controller for the actual model in laboratory and experiment result evaluate the applicability of this control design in industrial applications. Keywords 2D overhead crane • Adaptive hierarchical sliding mode control • Neural network • Radial basis function
2007
In this work paper we will study the dynamic behavior of the tower crane during the horizontaltranslational movement of the load hanging in the crane's boom. Using computer simulations of the crane's virtual model, we will study the influentia of this motion in the crane's construction when fully engaged with load. We will try to find how does the load swinging effect the carrying construction, what happens when load stops somewhere in the crane's boom and at the peak point, and how does this effects some main parts of crane. For this case we created virtually a whole Tower Crane using Finite Elements and model design application MSC.VisualNastran [4]. Dimensions are from standard manufacturers and using DIN 44 [1]. The results will give us a better view about the dynamic occurrences caused by the load horizontal movement.
International Journal of Automation and Computing, 2019
In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented for two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are intractable to be determined. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and real-life systems, where the results obtained by our method are highly promising.