Advanced Materials Research Vols. 594-597

Abstract: Wireless Sensor network (WSN) is an emerging technology widely applied in environmental disasters monitoring. With the constraint of computation resource, it face big challenge of stability and reliability of monitoring network. A statistical model of strain data and distributed monitoring algorithm for landslide based on WSN is studied in this paper. The strain data is modeled using variable mean of Gaussian process. Miss alarm rate and false alarm rate are introduced as critical performance parameters of landslide prediction. Comparing with centralized monitoring method, simulation result shows that distributed monitoring algorithm performs better than centralized monitoring.

Abstract: Based on the generalized flexibility matrix, a method for detecting structural damage is presented in this paper. The generalized flexibility matrix is approximately constructed by using the first frequency and the corresponding mode shape only. Then the difference of generalized flexibility curvature between undamaged and damaged state is used to detect the possible damaged elements. Finally, a numerical example concerning a simple supported beam is used to illustrate the effectiveness of the proposed method.

Abstract: In order to ensure the safety of the blasting excavation, it must monitor the vibration caused by blast with the information technology. Based on one tunnel, the monitoring method about the tunnel blasting vibration under the complex construction is systematically studied, combining with engineering practice, the correction mathematical formulas of the blasting seismic wave attenuation are given.

Abstract: Moving load could enhance damage-structural nonlinear character. High-order statistical analysis described character of non-stationary signal more exactly than traditional fourier spectrum based on second-order statistics analysis. The result of high-order spectrum analysis was two-dimensional，and spectrum entropy of different frequency can extract its intrinsic information and characters from it. Using these characters, the structural damage pattern could be recognized by neural network. The validity of this method was reviewed by a beam under moving load. When structure has damage, its state information can be extracted availably from high-order spectrum entropy of structural vibration, and it isn’t sensitive to noise. It can be used as eigenvectors of pattern recognition based on neural network.

Abstract: This article describes the successful application of video surveillance technology in various fields of security, government, education, expounds some commonly used landslide monitoring methods and characteristics of remote video monitoring system, demonstrates that it’s essential to apply the remote video surveillance to landslide monitoring. That remote video surveillance technology and professional platform software are combined establish a set of landslide video surveillance system. Through the real-time pictures, we can make reasonable explanation for the phenomenon of abnormal fluctuations, thus the damage due to unexpected geological landslide can be prevented and timely resolved.

Abstract: This device is designed to monitor the temperature and optical intensity in specific entironment and situation, and then to carry out the related follow-up treatment and control. The device is based on microcomputer AT89S52 to manage the information collected by the temperature sensor monolithic integrated circuits DS18B20, light intensity sensors and light-sensitive resistance. And the managed result is displayed by the man-machine interface FYD12864 . After that,the collected data is analysed and compared with the predicted data ,and then it will give an alarm when the data exceeds the provided standard..

Abstract: In this paper, a statistical methodology is introduced for identifying the most effective way to install a limited number of sensors on a typical distributed-parameter system, i.e., a three-span continuous bridge model with two elastic supports to extract as much information as possible. This is performed by minimizing the uncertainties associated with the identified bridge modeling parameters. In the proposed methodology, the information entropy is employed as a measure to quantify the uncertainty of the identified structural modeling parameters. The problem of optimal sensor placement is then formulated as a continuous optimization problem, in which the information entropy is minimized, with the sensor configurations as the minimization variables. The generally used discrete-coordinate systems modeled by the finite element (FE) method can only approximate their actual dynamic behavior, which would in turn influence the sensor configuration results, and the sensors are confined to be only put on discrete nodes related to the coarse mesh scheme usually employed. For structures such as bridges belonging to typical distributed-parameter systems, it’s more reasonable and convenient to be modeled as continues-coordinate system with analytical formulation. It’s the main purpose of this paper to develop a sensor placement method for continues-coordinate systems following the Bayesian theorem and the information entropy method, with the binary-encoded genetic algorithm (GA) employed as the optimization technique.

Abstract: In recent years,most existing engineering structures which have approached their normal life span, such as concrete plate, concrete beam etc., Almost all of these architecture structures are subjected to damage due to external loads, initial design defect etc. Structural damage detection and assessment has been becoming a focus of increasing interest in civil engineering field. However,At present, the study on structural damage detection is still at initial stage and the adopted main approaches are theoretical analysis and numerical simulation, but physical models are scarce. This leads to the yielded theories and methods are not sufficiently applicable for practical engineering application. Aiming at this, this paper focuses on developing effective methods of using wavelet and neural networks to detect the damage of elastic thin plate due to their extensive applications in civil engineering.

Abstract: The pile foundations are used widely in the construction engineering, so the nondestructive inspection applied in the pile foundation is especially important. This article, based on the basic principle of elastic wave propagation in the pile, elaborates the application of the elastic wave reflection method in the non-destructive inspection of the pile foundation.

Abstract: Structural modal parameters can be identified using both output responses and input excitations or only using output responses of structures. When the input excitations are known, some frequency response functions (FRF) can be obtained and further used to accurately identify the modal frequencies and mode shapes of structures, but the identified modal damping ratio is often lack of reliability. Under ambient excitations, the peak picking method (PP) is often used to quickly identify the modal parameters of structures, but some vibration modes are missed sometimes, particularly when the dense modes or subjective errors may appear around the peaks picked. Modal parameters can be identified using the stochastic subspace identification method (SSI) based on statistical data, however, the SSI method easily produces false modes in practice. In order to compensate the deficiencies of SSI method, the PP and the SSI methods are combined to identify the modal parameters of the benchmark structure which proposed by the International Association for Structure Control and the task group of American Society Civil Engineers (IASC-ASCE) in this paper. The illustrated results show that this combination method can accurately identify the modal parameters of the benchmark structure with some application prospects.