scispace - formally typeset
Search or ask a question
Author

Yong Xia

Bio: Yong Xia is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Structural health monitoring & Finite element method. The author has an hindex of 37, co-authored 171 publications receiving 4343 citations. Previous affiliations of Yong Xia include Nanyang Technological University & Main Roads Western Australia.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, a structural health monitoring (SHM) system consisting of over 600 sensors has been designed and is being implemented by The Hong Kong Polytechnic University to GNTVT for both in-construction and in-service real-time monitoring.
Abstract: The Guangzhou New TV Tower (GNTVT), currently being constructed in Guangzhou, China, is a supertall structure with a height of 610 m. This tube-in-tube structure comprises a reinforced concrete inner tube and a steel outer tube adopting concrete-filled-tube columns. A sophisticated structural health monitoring (SHM) system consisting of over 600 sensors has been designed and is being implemented by The Hong Kong Polytechnic University to GNTVT for both in-construction and in-service real-time monitoring. This paper outlines the technology innovation in developing and implementing this SHM system, which includes (i) modular design of the SHM system, (ii) integration of the in-construction monitoring system and the in-service monitoring system, (iii) wireless-based data acquisition and Internet-based remote data transmission, (iv) design and implementation of a fiber Bragg grating sensing system,(v) structural health and condition assessment using static and dynamic monitoring data, (vi) verification of the effectiveness of vibration control devices by the SHM system, and (vii) development of an SHM benchmark problem by taking GNTVT as a test bed and using real-world measurement data. Preliminary monitoring data including those obtained during the Wenchuan earthquake and recent typhoons are also presented. Copyright © 2008 John Wiley & Sons, Ltd.

332 citations

Journal ArticleDOI
TL;DR: In this paper, a reinforced concrete slab, which was constructed and placed outside the laboratory, has been periodically vibration tested for nearly two years, and the results obtained over that time for the first four modes.

290 citations

Journal ArticleDOI
TL;DR: In this article, a genetic algorithm with real number encoding is applied to identify structural damage by minimizing the objective function, which directly compares the changes in the measurements before and after damage.
Abstract: Vibration-based methods are being rapidly applied to detect structural damage. The usual approaches incorporate sensitivity analysis and the optimization algorithm to minimize the discrepancies between the measured vibration data and the analytical data. However, conventional optimization methods are gradient based and usually lead to a local minimum only. Genetic algorithms explore the region of the whole solution space and can obtain the global optimum. In this paper, a genetic algorithm with real number encoding is applied to identify the structural damage by minimizing the objective function, which directly compares the changes in the measurements before and after damage. Three different criteria are considered, namely, the frequency changes, the mode shape changes, and a combination of the two. A laboratory tested cantilever beam and a frame are used to demonstrate the proposed technique. Numerical results show that the damaged elements can be detected by genetic algorithm, even when the analytical m...

265 citations

Journal ArticleDOI
TL;DR: In this paper, a sensitivity-analysis-based finite element (FE) model updating method has been used for condition assessment of bridges with particular reference to bridges, including specific considerations for FE modeling for updating and the model updating procedure for successful condition assessment.

260 citations

Journal ArticleDOI
Yong Xia1, Bo Chen1, Shun Weng1, Yiqing Ni1, You Lin Xu1 
TL;DR: In this article, the authors reviewed technical literature concerning variations in vibration properties of civil structures under changing temperature conditions and found that variations in material modulus under different temperatures are the major cause of the variations of vibration properties.
Abstract: Changing environmental conditions, especially temperature, have been observed to be a complicated factor affecting vibration properties, such as frequencies, mode shapes, and damping, of civil structures. This paper reviews technical literature concerning variations in vibration properties of civil structures under changing temperature conditions. Most of these studies focus on variations in frequencies of bridge structures, with some studies on variations in mode shapes and damping and other types of structures. Statistical approaches to correlation between temperature and frequencies are also reviewed. A quantitative analysis shows that variations in material modulus under different temperatures are the major cause of the variations in vibration properties. A comparative study on different structures made of different materials is carried out in laboratory. Two real structures, the 1,377-m main span Tsing Ma Suspension Bridge and the 600-m-tall Guangzhou New Television Tower, are examined. Both laboratory experiments and field testing, regardless of different construction materials used and structural types, verify the quantitative analysis. Variations in frequencies of reinforced concrete structures are much more significant than those of steel structures.

229 citations


Cited by
More filters
Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Journal ArticleDOI
TL;DR: This article proposes a vision‐based method using a deep architecture of convolutional neural networks (CNNs) for detecting concrete cracks without calculating the defect features, and shows quite better performances and can indeed find concrete cracks in realistic situations.
Abstract: A number of image processing techniques IPTs have been implemented for detecting civil infrastructure defects to partially replace human-conducted onsite inspections. These IPTs are primarily used to manipulate images to extract defect features, such as cracks in concrete and steel surfaces. However, the extensively varying real-world situations e.g., lighting and shadow changes can lead to challenges to the wide adoption of IPTs. To overcome these challenges, this article proposes a vision-based method using a deep architecture of convolutional neural networks CNNs for detecting concrete cracks without calculating the defect features. As CNNs are capable of learning image features automatically, the proposed method works without the conjugation of IPTs for extracting features. The designed CNN is trained on 40 K images of 256 × 256 pixel resolutions and, consequently, records with about 98% accuracy. The trained CNN is combined with a sliding window technique to scan any image size larger than 256 × 256 pixel resolutions. The robustness and adaptability of the proposed approach are tested on 55 images of 5,888 × 3,584 pixel resolutions taken from a different structure which is not used for training and validation processes under various conditions e.g., strong light spot, shadows, and very thin cracks. Comparative studies are conducted to examine the performance of the proposed CNN using traditional Canny and Sobel edge detection methods. The results show that the proposed method shows quite better performances and can indeed find concrete cracks in realistic situations.

1,898 citations

Journal ArticleDOI
TL;DR: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented in this paper, and the damage identification algorithms in terms of signal processing are discussed.
Abstract: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented, and the damage identification algorithms in terms of signal processing...

1,613 citations

01 Jan 2016
TL;DR: The regularization of inverse problems is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can download it instantly.
Abstract: Thank you for downloading regularization of inverse problems. Maybe you have knowledge that, people have search hundreds times for their favorite novels like this regularization of inverse problems, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some infectious bugs inside their computer. regularization of inverse problems is available in our book collection an online access to it is set as public so you can download it instantly. Our book servers spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the regularization of inverse problems is universally compatible with any devices to read.

1,097 citations

01 Jul 1986
TL;DR: Structures in Other Domains The methodology of structural analysis discussed in this article has been applied beyond the narrow realm of natural language syntax that we have discussed in this paper, and it has been found that variation in the types of sentences that are used, whether during the course of children's acquisition of their native languages or in the centuries-long periods of linguistic change, are best characterized not as super cial and haphazard alterations, but rather in terms of parametric modi cations to the fundamental underlying grammatical rules and constraints.
Abstract: Structures in Other Domains The methodology of structural analysis discussed in this article has been applied beyond the narrow realm of natural language syntax that we have discussed in this article. Within the study of language, similar methods of analysis have been pervasively applied to the study of sounds (phonology), words (morphology), and meanings (semantics), yielding a range of of abstract structural representations whose properties bear considerable explanatory burden. There are a wealth of cases in each of these domains analogous to those discussed here, though space prevents us from going in these (see Akmajian, Demers, Farmer and Harnish 1995 for a traditional overview, and Jackendo 1994 for one more focused on connections with cognitive science). Additionally, these representations have shed substantial light on the processes of language acquisition and language change. It has been found that variation in the types of sentences that are used, whether during the course of children's acquisition of their native languages or in the centuries-long periods of linguistic change, are best characterized not as super cial and haphazard alterations, but rather in terms of parametric modi cations to the fundamental underlying grammatical rules and constraints. Moving outside the domain of language, one application of these same methods has been in the study of music cognition. Just as the representations of linguistic theory arise out of an attempt to model speakers' intuitions about well-formedness and possible meanings of the sentences of their

761 citations