Abstract
Railway tracks are the direct supporting structures of the trains, which are vulnerable to produce large deformation under the temperature stress or subgrade settlement. The health status of track is critical, and the track should be routinely monitored to improve safety, lower the risk of excess deformation and provide reliable maintenance strategy. In this paper, the distributed optical fiber sensor was proposed to monitor the continuous deformation of the track. In order to validate the feasibility of the monitoring method, two deformation monitoring tests on one steel rail model in laboratory and on one real railway tack in outdoor were conducted respectively. In the model test, the working conditions of simply supported beam and continuous beam in the rail model under several concentrated loads were set to simulate different stress conditions of the real rail, respectively. In order to evaluate the monitoring accuracy, one distributed optical fiber sensor and one fiber Bragg grating (FBG) sensor were installed on the lower surface of the rail model, the strain measured by FBG sensor and the strain calculated from FEA were taken as measurement references. The model test results show that the strain measured by distributed optical fiber sensor has a good agreement with those measured by FBG sensor and FEA. In the outdoor test, the real track suffered from displacement and temperature loads. The distributed optical fiber sensor installed on the rail can monitor the corresponding strain and temperature with a good accuracy.
Key Words
distributed optical fiber sensor; structural health monitoring; deformation measurement; temperature compensation; track
Address
Jianping He: School of Civil Engineering, Dalian University of Technology, Dalian 116024, P.R. China
Peigang Li: School of Civil Engineering, Dalian University of Technology, Dalian 116024, P.R. China;
Faculty of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, P.R. China
Shihai Zhang: School of Civil Engineering, Nanyang Institute of Technology, Nanyang 473001, P.R. China
Abstract
One of the most important aspects in structural health monitoring is the detection of fatigue damage. Structural components such as heavy-duty bolts work under high dynamic loads, and thus are prone to accumulate fatigue damage and cracks may originate. Those heavy-duty bolts are used, for example, in wind power generation and mining equipment. Therefore, the investigation of new and more effective monitoring technologies attracts a great interest. In this study the acoustic emission (AE) technology was employed to detect incipient damage during fatigue testing of a M36 bolt. Initial results showed that the AE signals have a high level of background noise due to how the load is applied by the fatigue testing machine. Thus, an advanced signal processing method in the time-frequency domain, the Hilbert-Huang Spectrum (HHS), was applied to reveal AE components buried in background noise in form of high-frequency peaks that can be associated with damage progression. Accordingly, the main contribution of the present study is providing insights regarding the detection of incipient damage during fatigue testing using AE signals and providing recommendations for further research.
Key Words
acoustic emission; empirical mode decomposition; Hilbert-Huang spectrum; crack detection; structural health monitoring
Address
Felix Leaman, Aljoscha Herz, Ralph Baltes and Elisabeth Clausen: Institute for Advanced Mining Technologies, RWTH Aachen University, Germany
Victoria Brinnel: Institute for Ferrous Metallurgy, RWTH Aachen University, Germany
Abstract
Dynamic stability of graded nonlocal nano-dimension plates on elastic substrate due to in-plane periodic loads has been researched via a novel 3- unknown plate theory based on exact position of neutral surface. Proposed theory confirms the shear deformation effects and contains lower field components in comparison to first order and refined 4- unknown plate theories. A modified power-law function has been utilized in order to express the porosity-dependent material coefficients. The equations of nanoplate have been represented in the context of Mathieu–Hill equations and Chebyshev-Ritz-Bolotin\' s approach has been performed to derive the stability boundaries. Detailed impacts of static/dynamic loading parameters, nonlocal constant, foundation parameters, material index and porosities on instability boundaries of graded nanoscale plates are researched.
Abstract
Pile foundations of existing bridges lie in soil and water environment for long term and endure relatively heavy vertical loads, thus prone to damages, especially after stricken by external forces, such as earthquake, collision, soil heap load and etc., and the piles may be injured to certain degrees as well. There is a relatively complete technical system for quality inspection of new bridge pile foundations without structures on the top. However, there is no mature technical standard in the engineering community for the non-destructive testing technology specific to the existing bridge pile foundations. The quality of bridge pile foundations has always been a major problem that plagues bridge maintenance. On the basis of many years\' experiences in test engineering and theoretical studies, this study developed a new type of detection technology and equipment for the existing bridge piles.
Key Words
existing bridge; pile foundation; non-destructive testing; bridge maintenance
Address
Xue-feng Zhang, Ying-sheng Ni and Chunxia Song: Research Institute of Highway Ministry of Transport, M.O.T, Beijing, 100088, P.R. China
Dong Xu: Department of Bridge Engineering, Tongji University, Shanghai, 200092, P.R. China
Abstract
This study aims to develop the fuzzy risk assessment model of the debris flow to verify the accuracy of risk assessment in order to help related organizations reduce losses caused by landslides. In this study, actual cases of landslides that occurred are utilized as the database. The established models help us assess the occurrence of debris flows using computed indicators, and to verify the model errors. In addition, comparisons are made between the models to determine the best one to use in practical applications. The results prove that the risk assessment model systems are quite suitable for debris flow risk assessment. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.
Key Words
landslide; natural disaster; feature based; computer vision; natural disasters detection; event warning system
Address
Tim Chen: AI LAB, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
D. Kuo: Faculty of Science, Monash University, Melbourne, 3122 Victoria, Australia
J.C.Y. Chen: Faculty of Decision Science, University of California, Los Angeles, USA
