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Showing 4 results for Accelerometer
Estimation of natural frequencies using mass-cancellation method in operational modal testing
Mohammad Mahdi Khatybi, Mohammad Reza Ashory,
Volume 14, Issue 8 (11-2014)
Abstract
Conventional modal testing is known as a powerful tool for dynamic analysis of structures. However, for some engineering structures, conventional modal testing is difficult or even impossible to conduct due to the problems associated with the artificial excitation of structure. Operational Modal Analysis (OMA) is one solution to deal with these cases. In OMA the structure is excited by ambient forces and only the responses are measured and taken into account. Accelerometers are the traditional tools for measuring the responses of structure. It is well khonwn that the measured responses are contaminated by bias errors corresponding to the mass-loading effect of accelerometers. This causes the natural frequencies of structure are measured lower than the real values. In this paper a new method is proposed for eliminating the mass-loading effects of accelerometers from measured responses in OMA. A numerical model of a mass-spring-damper system is used for validation of the method. Also a steel plate is used for experimental validation of the proposed approach. The results are confirmed by those of conventional modal testing. Both numerical and experimental results show that the proposed method can effectively eliminate the mass-loading effects of accelerometers from measured responses in OMA. Also, the method has the ability to correct the measured natural frequencies from OMA accurately.
Design, Construction and Control of a Two-Wheel Self-Balancing Robot
Ali Reza Rarivar, Mohammad Reza Zakerzadeh,
Volume 15, Issue 7 (9-2015)
Abstract
The purpose of this paper is design, construction and the control of a two-wheel self-balancing robot. For this purpose firstly, a literature study is carried out on the history of manufactured self-balancing robots and the researches which have been done so far in this area are reported. In addition, the robot chassis with consideration of the size and material is analyzed; and the dynamic equations of the robot are computed according to the designed chassis. Then, the robot inertial parameters are measured through different experimental tests and these parameters are used in the equations. Also, the derived equations are simplified and the transfer functions are evaluated for considering the stability of the robot. In this self-balancing robot, the simplified Kalman and complementary filters are used for identifying of the bias angle from the vertical position by combination of data obtained from accelerometer and gyroscope sensors. The PID controller and the robot transfer functions are simulated in MATLAB software. Then, the controller gains are obtained for the stability of the constructed robot. These gains are computed by PID tuning toolbox of MATLAB software as well as theoretically, and the results in each method have been compared with each other. Finally, the robot control electronic circuit is designed for analyzing the results through AVR microcontroller, while angle identification sensor is used.
Investigating the Situation of Urban Pathways Pavements Surface in Future Smart Cities Using Accelerometer Sensors and GPS Tools of Smartphones and GIS Application.

Volume 22, Issue 5 (12-2022)
Abstract
In smart cities, with using lots of new technologies, while creating appropriate facilities in routine urban life, infrastructure problems are investigated and the necessary measures are taken in a targeted and systematic manner to solve these problems. One of the most important technologies for managing infrastructure in smart cities is IT technology. GPS and smartphone sensors are other technologies that can be widely used in these cities. Streets, roads, and pavements are important infrastructures in any city and the future smart cities. Proper supervision, repair, and improvement of pavements, streets, and urban pathways are the main factor in reducing the cost of depreciation of vehicles and providing comfort and safety for citizens. On the other hand, if timely action is taken to restore and improve the pavement, huge costs of repair and reconstruction will be avoided, and this can significantly reduce the costs of urban management. The first step to achieving this goal is to identify the location of the roughness and distortion of the surface of the streets and urban pathways and the severity of these failures in the shortest possible time. In this paper, road surface roughnesses and failures have been studied using accelerometer sensors and GPS smartphone devices. Location and vertical acceleration data have been entered into GIS software and a quantitative index based on the values of vertical acceleration has been introduced to determine the quality of each section of urban road pavement. In this research, Androsensor software, which is a useful application for using smartphone sensors, has been used. This software is installed on two smartphones, Huawei, P30 Lite, and BlackBerry, Priv STV100. To collect the data, the smartphones were placed in a fixed position on the right and left sides of the car, on the dashboard. The collected data for analysis is transferred to the computer in Excel files. This research has been done in Kerman city and to collect data, different routes with specific failures have been selected. Data collection was performed in 81 pieces with a length of 500 meters and 24 pieces with a length of 200 meters (105 pieces, 45300 meters in total). By analyzing the vertical acceleration data and calculating some proposed indexes and comparing them, the best index has been selected. This index is classified into different ranges according to the field inspection of the pavement condition in the routes in this study, that each of which indicates the quality status of the pavement. Each of these intervals is introduced with a specific color, and by examining the index obtained in each route and the corresponding interval, the studied routes are marked with different colors on the map. Finally, it was found that the accelerometer sensors and GPS of smartphones can be used with low cost, high speed, and appropriate accuracy to check the surface of pavement of urban roads and grading the quality of the pavement. It also seems that in the smart cities of the future, which are based on IT technology, the use of user data, high accuracy in locating, and speed of action in prevention, the proposed method in this research can be used more favorably.

Presenting a novel damage index of concrete piers of bridges using correlation between sensor data

Volume 24, Issue 4 (10-2024)
Abstract
Piers are vital design elements for a bridge under seismic loading; ensuring their stability and health is crucial for the overall safety of the bridge. The most common methods available for detecting damage, primarily used in the bridge deck, are modal methods. These methods have errors in detecting damage in the structure for various reasons. On the other hand, these methods require healthy pier information. In addition to modal methods, other methods based on energy and data analysis using wavelet transform also exist, the shortcomings of which are mentioned in this article. The fundamental problem that most methods face is the existence of healthy pier information, and furthermore, parameters that should be used to detect damage must be computable or measurable. In this study, a new method is presented, using the concept of correlation, to detect the presence and location of damage with minimal error and without having healthy pier information. To this end, the tallest pier of Ramp A of the Shahid Bakri Bridge complex in Tehran was selected as the case study. Before modeling, the accuracy of the modeling method was validated, and then a precise nonlinear model was built in the OpenSees software using as-built sheets. For the first time in this article, damage in the model was created in different scenarios: reduction of stiffness in concrete cover materials, reduction of cross-sectional area of rebars at various points of the section. The location of the damage was also separately applied at three heights of the pier: 15, 25, and 35 percent of the height. To generate data on the pier, it was considered to load it with an impact load on the top of the pier. This load was applied as an impact on the deck of the pier for a very short time, and the data was collected using accelerometers at the pier height, and the correlation between each pair of consecutive sensors was calculated. Due to the high velocity of the compressive wave in concrete and the overlap that occurs in the return of the wave at both ends of the pier, data collection was performed only for about 0.001 seconds. Finally, due to the weakness of the correlation coefficient in magnifying the location of damage, using the concept of correlation, a damage index based on this concept was presented, and the capability of the presented index in detecting the presence and location of damage in various damage scenarios was evaluated. The results obtained indicate the proper performance of this index in detecting damage in various scenarios and damage intensities between 10 and 30 percent. The presented index only made an error in detecting the location of damage in cases where damage occurred in the concrete cover and rebars in small areas, but even in these cases, the presence of damage was well demonstrated. Due to limitations in sensor placement at the pier height, increasing the distance between sensors and reducing their number was also investigated, and it was observed that even with greater distances between sensors, the presented index has the capability to detect the presence and location of damage, and after finding the approximate location of damage, it is possible to identify the exact location of damage by re-sensoring in probable areas.
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