This study presents a technique to identify the vibration characteristics in power transmission towers and to detect the potential structural damages. This method is based on the curvature of the mode shapes coupled with a continuous wavelet transform. The elaborated numerical method is based on signal processing of the output that resulted from ambient vibration. This technique benefits from a limited number of sensors, which makes it a cost-effective approach compared to others. The optimal spatial location for these sensors is obtained by the minimization of the non-diagonal entries in the modal assurance criterion (MAC) matrix. The Hilbert–Huang transform was also used to identify the dynamic anatomy of the structure. In order to simulate the realistic condition of the measured structural response in the field condition, a 10% noise is added to the response of the numerical model. Four damage scenarios were considered, and the potential damages were identified using wavelet transform on the difference of mode shapes curvature in the intact and damaged towers. Results show a promising accuracy considering the small number of applied sensors. This study proposes a low-cost and feasible technique for structural health monitoring.
This article presents a vibration-based technique for damage detection in the cylindrical equipment. First, a damage index based on the residual frequency responses is defined. This technique uses the principal component analysis for data reduction by eliminating the components that have the minimum contribution to the damage index. Then, the principal components are fed into neural networks to identify the changes in the damage pattern. Furthermore, the efficiency of this technique in the field condition is investigated by adding different noise levels to the output data. This study aims at proposing a cost-effective damage detection model using only one sensor. Therefore, the optimal location of the sensor is also discussed. A case study of capacitive voltage transformer is used for validation of finite element models. The neural networks are trained using numerical data and tested with experimental one. Several parametric analyses are performed to investigate the sensitivity of the model.
Summary Rapid health assessment of essential buildings such as hospitals, fire stations, and large residential complexes is crucial after damaging earthquakes. The use of advanced technologies such as wireless sensors, learning algorithms, and signal processing methods became more attractive in such fast applications due to their higher reliabilities and efficiencies compared to the conventional visual inspection methods. This paper presents a robust post‐earthquake damage detection framework for predicting the extent and location of damage occurrence in the braced‐frame structures after an earthquake. To do so, features derived from acceleration response of the structure were used along with a classification learner to determine the health condition of the structure. Decision tree classifiers are used for the purpose of damage classification where the Bayesian optimization algorithm is implemented to optimize the architecture of the mentioned classifier. A one‐story chevron steel‐braced frame, a three‐story X‐braced steel‐frame, and a five‐story three‐dimensional building are considered to validate the proposed method. The total number of 3774 and 1887 nonlinear response history analyses were respectively performed for 2D and 3D numerical models under scaled SAC motions, using the OpenSees simulation platform. Furthermore, in order to simulate the field condition, a maximum level of 10% white Gaussian noise is added to the output signals. Results obtained from the three case studies show that the proposed framework is robust and reliable in predicting the extent of damage level in the braced‐frame structures in a short time after an earthquake.
This paper presents the Real-Time Recursive Dynamics (RTRD) model that is developed for driving simulators. The model could be implemented in the Driving Simulator. The RTRD can also be used for off-line high-speed dynamics analysis, compared with commercial multibody dynamics codes, to speed up mechanical design process. An overview of RTRD is presented in the paper. Basic models for specific vehicle subsystems such as tire, steering, brake, power train, aerodynamics, etc., are interfaced with multibody dynamics to create a complete vehicle simulation model. Basic theories of each vehicle subsystem model are introduced and the interfaces with the multibody dynamic model are discussed. Required data for setting a vehicle model listed and an Army's High Mobility Multipurpose Wheeled Vehicle (HMMWV) modeling example is illustrated. For operator-in-the-loop simulation, the interface between the RTRD model and the simulator subsystems, i.e., visual, motion, audio, and terrain database, is presented. Finally, the parallel processing algorithm of RTRD model is illustrated. Benchmarks for the baseline RTRD code are analyzed using two vehicle examples, a passenger car and a tractor-semitrailer. D D
Near field earthquakes have imposed major damage to buildings in the past years. In some cases, the intensity of such damage is too considerable to be disregarded. The most effective way to improve seismic performance of buildings is applying a seismic control technique. The cylindrical friction damper is one of these methods, which has become popular for its desirable performance in the energy dissipation of lateral loads. The main objective of this study is to evaluate the near-field seismic performance of braced frame buildings equipped with cylindrical friction dampers. In this regard, four steel braced frame buildings, including a 4-, 8-, 12-, and 16-story braced frame building are modeled in OpenSees platform. Then, a set of near-field earthquake motions are applied to these structures and the structural response is captured in each story. Results show that there is a direct relation between the optimal slip load and the intensity of the input earthquake. In the next step, the structures are analyzed by selecting the optimum slip load for the damper. It is revealed that cylindrical friction dampers improved structural performance in terms of energy absorption of the structure. However, findings confirm that there is an indirect relationship between the number of floors in a building and the above mentioned feature of these dampers.
Dams are essential infrastructures as they provide a range of economic, environmental, and social benefits to the local populations. Damage in the body of these structures may lead to an irreparable disaster. This paper presents a cost-effective vibration-based framework to identify the dynamic properties and damage of the dams. To this end, four commonly occurred damage scenarios, including (1) damage in the neck of the dam, (2) damage in the toe of the structure, (3) simultaneous damage in the neck and the toe of the dam, and (4) damage in the lifting joints of the dam, are considered. The proposed method is based on processing the acceleration response of a gravity dam under ambient excitations. First, the random decrement technique (RDT) is applied to determine the free-vibration of the structure using the structural response. Then, a combined method based on Hilbert–Huang Transform (HHT) and Wavelet Transform (WT) is presented to obtain the dynamic properties of the structure. Next, the cubic-spline technique is used to make the mode shapes differentiable. Finally, Continuous Wavelet Transform (CWT) is applied to the residual values of mode shape curvatures between intact and damaged structures to estimate the damage location. In order to evaluate the efficiency of the proposed method in field condition, 10% noise is added to the structural response. Results show promising accuracy in estimating the location of damage even when the structure is subjected to simultaneous damage in different locations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.