Structural control and health monitoring scheme play key roles not only in enhancing the safety and reliability of infrastructure systems when they are subjected to natural disasters, such as earthquakes, high winds and sea waves, but it also optimally minimize the life cycle cost and maximize the whole performance through the full life cycle design. In this scheme, system identification is regarded as a major technique to identifiy system states and related parameter variables, thus preventing degradation of structural or mechanical systems when unexpected disturbances occur. In this paper, three different strategies are proposed to identify general hysteretic behavior of a typical shear structure subjected to external excitations. Different case studies are presented to analyze the dynamic responses of a time varying shear structural system with the early version of Bouc-Wen-Baber-Noori (BWBN) hysteresis model. By incorporating a "Grey Box" strategy utilizing an Intelligent Parameter Varying (IPV) and Artificial Neural Network (ANN) approach, a Genetic algorithm (GA) and a Transitional Markov Chain Monte Carlo (TMCMC) based Bayesian Updating framework system identification schemes are developed to identify the hysteretic behavior of the structural system. Hysteresis characteristics, computational accuracy and algorithm efficiency are further discussed by evaluating the system identification results. Results show that IPV performs superior computational efficiency and system identification accuracy over GA and TMCMC approaches.
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.
Reducing the torque and number of actuators has received great attention because it minimizes both the initial and running costs. This paper introduces a new design for the robot end-effector that reduces the Degree of Freedom (DoF) from 6 to 3. A compressor is employed to generate a vacuum during a vacuum cup. Since atmospheric pressure equalizes itself and the air fills any missing gaps. This pressure moves and pushes against the air outside of the suction cup. This allows pulling and picking up plates of metal or glass in industrial applications. Also, all actuators (three actuators) are installed in the robot base. Then they are linked to a four-bar mechanism to transfer the power to each joint. The four-bar mechanism transfers the power from the actuators to move each joint. Four-bar linkage consists of three rigid moving links connected with the frame. The four-bar mechanism provides rotating and oscillating and relatively high flexibility(high redundant). Installing the actuators in the base makes the arm lighter than the conventional design thus reducing the required torque to operate each joint. The optimization of the robot to select the optimal material and cross-section area is conducted using the Finite Element Method. The torque derivation based on the Lagrange theory is presented. The reduced torque of each joint and total power has been evaluated and compared with the conventional ones. It is observed that the maximum percentage of reduction in the torque occurs at joint 2 (68.1 %) where the torque is reduced from 5.8 Nm to 3.5 Nm for 15 S trajectory time. Besides, it is found that the percentage of reduction depends on the trajectory time, the joint number, and the payload.
Welding is the process of joining two pieces of materials utilizing heat and filler material to form a permanent connection: that is, it cannot be disassembled. Filler material is not used in some types of welding processes. Welding can cause welding residual stress and deformation in the welded structure, and certain defects will occur. Structural design should minimize the number of welds, select reasonable welded sizes and shapes, and reasonably select the structure form and arrange welded positions. This chapter describes and examines the design process of weld size, along with examples and solved/unsolved problems. The chapter studies force and stress analysis, and how to calculate the size of the different types of welds, such as thin fillet weld and butt weld. This chapter can be used as teaching material for courses in 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.
The deflection of a section is the displacement of the centroid of the cross section of the beam along the direction perpendicular to the axis of the beam, which is one of the basic quantities to measure the deformation of a beam. There are many factors that cause structure displacement, such as load, temperature change, support displacement, and so on. On the premises that the material obeys Hooke's law, the structure has small deformation, and the connection has no friction, the methods of structural mechanics are used to derive the displacement formula of the structure under load. This chapter examines the methods to derive the displacement formula, such as double integration, superposition, area moment, singularity functions, strain energy (Castigliano), and the three-moment equation, and then discusses the deflection in columns (buckling), along with examples and solved/unsolved problems. This chapter can be used as teaching material for courses in machine design for mechanical, industrial engineering, 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.
A proof-of-concept indirect tire-pressure monitoring system is developed using artificial neural networks to identify the tire pressure of a vehicle tire. A quarter-car model was developed with MATLAB and Simulink to generate... | Find, read and cite all the research you need on Tech Science Press
This paper aims specifically at developing an efficient but low-cost methodology that can help detect early transportation infrastructure damages either by permanent or periodic monitoring. In this research, we used LiDAR scanning units (ground units fixed on holders and movable units fixed on UAV) integrated with a novel deep neural network (DNN) for disease monitoring of bridges. The monitoring model is based on a recurrent neural network with long short-term memory blocks (RNN-LSTM) since the LiDAR scanning datasets have a time-dependent and memory-dependent behavior. The results give high performance, in this way, the monitoring of a real lifeline can be analyzed by combining with the data from Li-DAR and DNN models.
Mechanical springs are common in engineering product designs and can be found in almost any engineering product, from consumer to heavy industrial. Disassemble anything that involves a mechanism, and chances are you will find some type of spring. This chapter examines the types of mechanical springs and covers the full design of springs subjected to static and dynamic loads, along with examples and solved/unsolved problems. The stress-strain analysis of spring types is covered, including helical compression springs and helical torsion springs. This chapter can be used as teaching material for courses in 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.
The objective of this chapter is to provide the target readers with different theories of failure for the effective design of mechanical parts. Depending on the mechanical properties of the raw materials and the applications of the mechanical parts or structure, this chapter also discusses the selection of a particular theory for design, such as maximum shear stress (MSS), distortion energy (DE), maximum normal stress (MNS), brittle Coulomb-Mohr (BCM), or modified Mohr (MM), along with examples and solved/unsolved problems. This chapter can be used as teaching material for machine design courses for mechanical, industrial engineering, 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.
In this work, a damage identification framework is presented for Basalt Fiber Reinforced Polymer (BFRP) composite plate systems using the wavelet packet energy curvature difference (WPECD) method. A finite element model (FEM) of the plate is established and an accumulative damage model is introduced to model the plate damage subjected to fatigue, and five damage cases are considered. In the WPECD method for damage identification, dynamic features such as shape models, natural frequencies, and frequency responses is used. To simulate the composite plate damage, four stiffness reduction levels (5%, 10%, 15%, 20%) are employed. The damage can be identified by the WPECD index curve plot, and the influence of the wavelet function and the number of decomposition layers on the damage nodes identification was investigated. The results show that the proposed WPECD index can be identified the low damage levels (i.e. a 5% stiffness reduction). The proposed WPECD index can be employed to effectively identify structural damage.
In this work, the Convolutional Neural Network (CNN) algorithm is introduced in pipeline surface cracks monitoring-based image processing method for improving the efficiency and accuracy of crack type, location, and area identification.The method is used to extract the cracks area called the CNN based on crack contour network (CCN-CNNs) method from locate and extract the crack shape.CCN-CNNs is provides the accuracy rate (P%), recall rate (R%), and F-score (F%) index to assess the algorithm in the problem while identifying the cracks, and then according to the maximum F-score, we computes the crack corresponding contour area.In this work the pipeline crake images datasets are provided using an inspection drone with high definition camera.To the best of the authors' knowledge, the methodology presented in this paper for pipeline crack identification is an original contribution to the literature.This work introduces an efficient approach that also significantly reduces the time for crack type, location, and area identification of pipelines, the accuracy rate (P%), recall rate (R%), and Fscore (F%) are recorded 91.8% ,86.1%, and 84.6% respectively.
This research studies a novel damage detection framework for beam structure systems using displacement sensors.First, a finite element model is established under the impact load.Based on this model, an accumulative damage model is introduced to model the beam damage, and the damage case is considered.Both static and transient displacement are collected from the beam sensors installing a long beam structure.A system transfer function (TF) is proposed and applied to the "open loop" beam system.Results show these approaches perform great promises when damage evolves in beam structure.
The optimization of the acoustic silencer volume is very important to develop it and to get high-performance, the importance of the silencer was appeared in industrial field to eliminate the noise of the duct by efficient and... | Find, read and cite all the research you need on Tech Science Press
A novel structural damage identification method based on the noncontact measurement technique and Jaya algorithm is presented. The “Features from Accelerated Segment Test” (FAST) algorithm and Kanade–Lucas–Tomasi algorithm are used to identify the displacements from the video clips synergistically. Since the fixed threshold value for the FAST algorithm may not meet the pixel requirements for different images, an adaptive threshold value strategy is applied in this study. The natural frequencies extracted from the acquired displacements are used to formulate a multisample objective function, which is defined on the basis of the Bayesian inference. The K-means clustering strategy, the Hooke–Jeeves pattern search mode, and the colony reduction mechanism are integrated into the Jaya algorithm to improve the convergence of the Jaya technique. Structural damage location and severity can be identified through minimizing the multisample objective function using this enhanced Jaya algorithm. The proposed method is then applied to a laboratory space frame. The damaged elements of the five verification cases (cases 1–5) are detected correctly. Finally, the damaged elements in cases 6–10 are identified and reported.
