193 publications from this institution
In this paper, the vibration behavior features are extracted from the combination between Wavelet Transform (WT), and Finite Strip Transition Matrix (FSTM) of skew composite plates (SCPs), with variable thickness, and intermediate elastic support. Although, the results of this technique and based on the previous work done by the authors, that show the method can reflect the vibration behavior of the composite plates. Due to the method's difficulty in terms of, a lot of calculations with a large number of iterations these results may not be good choices for quick and accurate vibration behavior extracting. Thus, the new deep neural network (NN) is designed to learn and test these results carrying out by extracting vibration behavior features that reflect the important and essential information about the mode shapes in SCP. The results give high indications about the proposed technique of deep learning is a promising method, particularly when the type structures are complicated and the ambient environment is variable.
Previously, many efforts and more time were required to simulate the torque of a robot due to the complicated formulation of the torque. In this paper, simplified equations of the torque for the planar robot are derived. As well as another form of the torque formulation as a Polynomial equation is proposed. The equations of motion for a planar robot have been presented using Lagrange Equation. The proposed derivation of the torque was verified for different sizes of robots (from microscale to large-scale robots). The time simulations of angular displacement, angular velocity, angular acceleration, torque, and power are demonstrated. The robot size effect on the output torque is investigated. The results exhibit an easiness of evaluation of the torque, especially for a robot with a higher degree of freedom. Finally, it is observed the high convergence between the proposed simple formulation and the Lagrange derivation with a maximum error of 0.3 %.
Railway and transit tracks are designed and constructed as smooth segments of straight lines and circular curves linked by transitional spirals. Dynamic traffic loads, material wear and environmental cycles gradually produce deviations in the track from the original smooth geometry. Such deviations lead to rough ride in the vehicles and furthermore higher dynamic vehicle-track interaction forces which lead to faster deviation growth. To monitor the geometric condition of the track and to guide maintenance and repair, hand tools were used to take consecutive measurements by track walkers. Modern state-of-the-art technology has since replaced the traditional slow and painful measurement practice. Inspections are now done from a moving vehicle at hundreds of km per hour without contacting the track. All track geometry parameters are measured up four times per meter; data are analysed in real time by onboard software to identify the location and magnitudes of deviations which exceeds the acceptable tolerance. Historical measurements are stored in databases which are used to establish degradation trends and to guide the planning of maintenance. With the help of high-speed imaging technology, automated video inspection systems are installed on some vehicles to detect other faults in the track structure. Four types of such modern inspection tools are introduced in the paper presentation. These are: a single-car comprehensive inspection vehicle; a dedicated inspection train; a highway-railway dual usage truck and an unmanned inspection system. Actual operational systems are used as examples to illustrate the design and capabilities of each of these types of inspection tools.
Although the effectiveness of discrete wavelet transform (DWT) for analyzing time-varying measurements has been studied for mechanical and civil engineering applications, a few fundamental questions still need to be answered, such as how to choose an optimal decomposition level (DL) for a specific task. Selection of the optimal DL still remains a question that has not been adequately explored and not thoroughly investigated. Vast majority of wavelet based methods in mechanical and civil engineering applications have been associated with nonstationary measurements and do not offer detail information on how DL should be selected or linked to useful features that can identify anomalies in a structure. This study proposes a new detailed framework for choosing the optimal DL to guarantee an effective wavelet analysis for time-varying structural responses. The approach proposed in this paper uses various wavelets and theoretical levels to decompose the signal and to identify those aspects that interact to affect the DL, such as data characteristics, frequency band features, noise reduction, similarity, sharing information, and reconstruction quality. To show the effectiveness of our proposed method, we considered a comparative study using various mother wavelets on El Centro earthquake and acceleration responses from shaking table results of physical experiment. Experimental results show that the optimal DL for El Centro earthquake is 4 and for the acceleration data is 6. These results obviously demonstrate the stability and the robustness of the proposed method in the analysis of contaminated time-varying signals.
Urban transport planning started in the United States in the 1950s with the Detroit and Chicago Transport Studies and was used to inform decision-makers about
Damages due to complex loading or under natural disasters may cause progressive collapse (PC) in structures have not received much attention despite the importance of the potentially catastrophic impact of these types of deteriorations. When a structure is exposed to external excitations, an energy flow in the structural components is accumulated and stored depending on the effective stiffness of these components. Any modification in the material properties, connections between components, or structural continuity would modify the effective stiffness, thus leads to the energy distribution variation in structural components. Once a member fails the load supported by the lost member is redistributed to the adjacent structural members. If these members are incapable of withstanding the additional loading, they continue to fail and that gives rise to damage and may result in a PC. The objective of this study is to use continuous wavelet transform (CWT) to study the consequences of the PC distribution trend and the energy redistribution after one of the structural members is lost due to external loading event. An efficient strategy based on various scenarios is developed and used via a robust finite element computational tool to model and simulate the damage in order to capture the structural vibration responses. Nonlinear static and dynamic analyses are used using Abaqus and CWT are used for investigation purposes. The results show proper and effective analysis of the structures having high potential to PC.
The applications of robotics in medical field have increased extensively in the last two decades. This paper aims at studing the effect of trajectory planning method on dynamic response of six degrees of freedom micro-robot intended for surgery applications. The kinematic equations of motion were obtained using Denavit-Hartemberg representation. The dynamic equations of motion, which are important for the proper design of robot controller, were first derived using the Lagrangian-Euler technique. Then the required hub torque to move each joint was calculated for the motor selection. The trajectory planning was derived using two different methods of trajectory planning. These methods are the fifth-order polynomial and soft motion trajectory planning. A comparison of the dynamic response was carried out to choose the best method that gives the smooth set trajectory planning and best performance of the robot under investigation. The simulation results were obtained using MATLAB software.
The approaches for enhancing resilience in Intelligent Transportation Systems (ITS) are the main topic of this chapter. It is performed by exploring the impact
The inherent variability of major infrastructure can be associated with structural properties such as member size and geometry, elastic constants, density, strength characteristics or external load types. These variables and factors may give rise to risk, safety and uncertainty for general structures. In this paper, a comprehensive reliability evaluation framework is presented for a laminate composite plate under hydrostatic pressure. An establishment and verification of a response surface, the determination of performance function in terms of input and output random variables, and the comparative application of combined algorithms such as Monte Carlo simulation, artificial neural network and fuzzy theory are conducted.
