A Correlation Coefficient Approach for Evaluation of Stiffness Degradation of Beams Under Moving Load
01 Jan 2019-Cmc-computers Materials & Continua (Computers, Materials and Continua (Tech Science Press))-Vol. 61, Iss: 1, pp 27-53
About: This article is published in Cmc-computers Materials & Continua.The article was published on 2019-01-01 and is currently open access. It has received 15 citations till now. The article focuses on the topics: Moving load & Correlation coefficient.
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TL;DR: This study concurrently identifies all three criteria of defect assessment, namely: quantity, location and growth rate, and has high potential for practical application to most structures.
31 citations
TL;DR: In this article, the authors proposed a correlation coefficient for detecting and evaluating defects in beams, which brings about a positive outcome in terms of accuracy and efficiency, which surpasses other parameters such as natural frequency and damping coefficient, thanks to its sensitivity to structural changes.
Abstract: This research proposes a correlation coefficient for detecting and evaluating defects in beams, which brings about a positive outcome in terms of accuracy and efficiency. This parameter surpasses other parameters, such as natural frequency and damping coefficient, thanks to its sensitivity to structural changes. Our results show that although the damping coefficient had more variation than the natural frequency value in the same experiment, its changes were insufficient and unstable at different levels of defects. In addition, the proposed correlation coefficient parameter has a linear characteristic and always changes significantly according to increasing levels of defects. The results outweigh damping coefficient and natural frequency values. Furthermore, this value is always sensitive to measurement channels, which could be an important factor in locating defects in beams. The testing index is statistically evaluated by a normal distribution of the amplitude value of vibration measurement signals. Changes and shifts in this distribution are the basis for evaluating beam defects. Thus, the suggested parameter is a reliable alternative for assessing the defects of a structure.
12 citations
TL;DR: This research investigates changes in the mechanical properties of complex structures using a combination of the discrete model, Fast Fourier Transform (FFT) analysis and deep learning, and applies deep learning in the noise reduction process for the original data.
Abstract: In this paper, we investigate changes in the mechanical properties of complex structures using a combination of the discrete model, Fast Fourier Transform (FFT) analysis and deep learning. The first idea from this research utilizes the discrete model from a perspective that is different from the finite element method (FEM) of previous works. As the method in this paper only models the mechanical properties of structures with finite degrees of freedom instead of dividing them into smaller elements, it reduces error in evaluation and produces more realistic results compared to the FEM model. Another advantage is how it allows the research to survey both parameters that affect the mechanical properties of structures—the overall stiffness (K) and the damping coefficient (c)—during vibration, while previous researches focus only on one of these two parameters. The second idea is to use FFT analysis to increase the sensitivity of the signal received during vibration. FFT analysis simplifies calculations, thereby reducing the effect of noise or errors. The sensitivity achieved in FFT analysis increases by 25% compared to traditional Fourier Transform (FT) analysis; moreover, the error in FFT analysis compared to experimental results is quite small, less than 2%. This shows that FFT is a suitable method to identify sensitive characteristics in evaluating changes in the mechanical properties. When FFT is combined with the discrete model, results are much better than those of several existing approaches. For the last idea, the manuscript applies deep learning (FFT-deep learning) in the noise reduction process for the original data. This makes the results much more accurate than in previous studies. The results of this research are shown through the monitoring of spans of the Saigon Bridge—the biggest and most important bridge in Ho Chi Minh City, Vietnam—during the past 11 years. The correspondence between the theoretically obtained result and the experimental one at the Saigon Bridge suggests a new area for development in evaluating and forecasting structural changes in the future.
12 citations
TL;DR: The idea behind this method is to use the representative power spectrum density as a powerful tool to evaluate the stiffness decline of spans during their operation period and a new measurement method has been introduced to replace the traditional method of monitoring the health conditions of bridges through a periodic measurement technique.
Abstract: We propose a novel representative power spectrum density as a specific characteristic for showing responses of spans during a long operational period. The idea behind this method is to use the representative power spectrum density as a powerful tool to evaluate the stiffness decline of spans during their operation period. In addition, a new measurement method has been introduced to replace the traditional method of monitoring the health conditions of bridges through a periodic measurement technique. This helps to reduce costs when carrying out testing bridges. Besides, the proposed approach can be widely applied not only in Vietnam but also in many other underprivileged countries around the world. Obtained results show that, during the operational process of spans, there is not only a pure vibration evaluation such as bending vibration and torsion vibration tests but also a combination of various vibration types including bending-torsion vibration or high-level vibrations like first-mode bending and first-mode torsion. Depending on each type of structure and material properties, different types of vibrations will appear more or less during the operational process of spans under a random moving load. Furthermore, the representative power spectrum density is also suitable for evaluating and determining many different fundamental vibrations through the same measurement time as well as various measurement times.
10 citations
Cites methods from "A Correlation Coefficient Approach ..."
...Procedure of Practical Measurement e model of the testing construction site is carried out in accordance with the experimental project which tests practical vibration [7, 8, 15, 16] on the majority of bridges in Ho Chi Minh City from October 2011 to 2014 by Ho Chi Minh City University of Technology, Laboratory of Applied Mechanics (LAM)....
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TL;DR: In this paper , the authors proposed a new indicator based on change in a vibration signal's probability spectrum center to assess structural change, which relies on the change of a central position of the probability spectrum (C-PSD).
4 citations