Rapid progress in the field of sensor technology has led to acquisition of massive amounts of measured data from structures being monitored. The data, however, contain inevitable measurement errors which often cause quantitative damage assessment to be ill conditioned. Attempts to incorporate a probabilistic method into a model have provided promising solutions to this problem by treating the uncertainties as random variables usually modeled with Gaussian distribution. However, the success enjoyed by the probabilistic method is limited by the lack of adequate information to obtain an unbiased probabilistic distribution of uncertainties. In addition, the probabilistic surrogate models involve complex and expensive computations, especially when generating output data. In this study, a non-probabilistic surrogate model based on wavelet weighted least squares support vector machine (WWLS-SVM) is proposed to address the problem of uncertainty in vibration based damage detection. The input data for WWLS-SVM consists of selected wavelet packet decomposition (WPD) features of the structural response signals, and the output is the Young's modulus of structural elements. This method calculates the lower and upper boundaries of the changes in the Young's modulus based on an interval analysis method. Considering the uncertainties in the input parameters, the surrogate model is used to predict the output of this interval bound. The proposed approach is applied to detect simulated damage in the four-story benchmark structure of IASC-ASCE SHM group. The results show that the proposed method can perform well in uncertainty-based damage detection of structures with less computational efforts compared to direct finite element model.
The applications of robotics in medical field have increased extensively in the last two decades. The aim of this paper is to study the effect of trajectory planning method duration time on correct dynamic response selection of six degrees of freedom micro-robot intended for surgery applications using two different methods of trajectory planning with different four duration times (5, 10, 20 and 60 s). 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 LagrangianEuler 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 with different four duration times (5, 10, 20 and 60 s). These methods are the fifth-order polynomial and soft motion trajectory planning. A comparison of the trajectory planning and dynamic response for the different four duration times was carried out of the two different methods of trajectory planning to choose the best duration time and the best method of trajectory planning that gives the correct dynamic response, smooth set trajectory planning and best performance of the robot under investigation. The simulation results were obtained using MATLAB software.
The principal uses of threads are fastening, adjusting, and transmitting power. In this section we consider power screws. A power screw is used to convert a rotary motion into a linear motion for power transmission. Power screws should be designed for smooth and noiseless transmission of power with an ability to carry heavy loads with high efficiency. Power screws are capable of producing uniform motion. This chapter on mechanical power screws describes and examines the power screw design process, and provides examples and solved/unsolved problems. The chapter is equipped to study force and stress analysis as well as calculation of the load-carrying capacity of different types of power screws, such as square and Acme screw threads. This chapter can be used as teaching material in courses on machine design for mechanical and industrial engineering majors in colleges and universities, and can also be used as a reference for scientific and technical personnel engaged in scientific and engineering calculations.
Machine design is an important part of mechanical engineering, the first step in mechanical production, and the most important factor determining mechanical performance. The goal of machine design is to design the best machinery under various limited conditions (such as materials, processing capabilities, theoretical knowledge, and calculation methods): that is, to create optimal designs. This chapter provides readers with an introduction to machine design principles. It begins with the fundamentals of machine design, such as design codes and standards, design organization, design considerations, and basic procedures of machine design. This chapter can be used as teaching material for courses in machine design for mechanical, industrial, and materials engineering majors in colleges and universities, and can also be used as a reference for scientific and technical personnel engaged in scientific and engineering calculations.
Failure detection-based Electrical Potential Change (EPC) is a promising technique. In this article, the internal layers delamination is inspected in basalt fiber-reinforced polymer (BFRP) pipe under long-term fatigue loading (LTFL) of internal pressure effect via an Electrical Capacitance Sensor (ECS) by evaluating the dielectric characteristics of pipe materials and classification between intact and delamination stats. The 3D maps of the capacitance array values and EPC distribution of node potential are tested. The maps can reflect delamination between pipe layers based on the researcher's previous works, however, because the pipes are modeled in 3D, therefore, the bending and twisted effects of the model make these maps not a good choice to accurately detect delamination location/size. Therefore, a new type of convolutional neural network (CNN) algorithm is adopted to train and test the EPC maps to evaluate delamination location/size. The training accuracy of the current technology ( P % ), recall rate ( R % ), and F-score ( F % ) are equal to 95.2 % , 93.7 % , and 90.9 % respectively, which indicates that the current technology shows identification efficiency and accuracy of the technology. The proposed method results converge with available traditional methods in the literature for assessing the delamination location/size such as the response surface methodology (RSM), and the error band from the diagonal line is less than 4.86 and 1.14 degrees for location and size respectively, thus validating the proposed technique's reliability, accuracy, and applicability for the relevant structures.
The phenomenon of hysteresis in engineering systems has been with us for ages and has been attracting the attention of many investigators for a long time [...]
With the emergence of the Internet, a large quantity of data are generated by the communication network, largely triggered by human activity. Adding to this,
Structural health monitoring (SHM) of civil infrastructures has become one of the fastest-growing research areas over the past two decades. SHM has evolved into measuring, processing, collecting, and storing massive amounts of data to provide valuable information for...
