Vibration-Based Monitoring of Civil Structures with Subspace-Based Damage Detection

Analyzing changes in vibration properties (e.g. natural frequencies) of structures as a result of damage has been heavily used by researchers for damage detection of civil structures. These changes, however, are not only caused by damage of the structural components, but they are also affected by the varying environmental conditions the structures are faced with, such as the temperature change, which limits the use of most damage detection methods presented in the literature that did not account for these effects. In this article, a damage detection method capable of distinguishing between the effects of damage and of the changing environmental conditions affecting damage sensitivity features is proposed. This method eliminates the need to form the baseline of the undamaged structure using damage sensitivity features obtained from a wide range of environmental conditions, as conventionally has been done, and utilizes features from two extreme and opposite environmental conditions as baselines. To allow near real-time monitoring, subsequent measurements are added one at a time to the baseline to create new data sets. Principal component analysis is then introduced for processing each data set so that patterns can be extracted and damage can be distinguished from environmental effects. The proposed method is tested using a two-dimensional truss structure and validated using measurements from the Z24 Bridge which was monitored for nearly a year, with damage scenarios applied to it near the end of the monitoring period. The results demonstrate the robustness of the proposed method for damage detection under changing environmental conditions. The method also works despite the nonlinear effects produced by environmental conditions on damage sensitivity features. Moreover, since each measurement is allowed to be analyzed one at a time, near real-time monitoring is possible. Damage progression can also be given from the method which makes it advantageous for damage evolution monitoring.

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Structural Health Monitoring Using Synchrosqueezed Wavelet Transform on IASC-ASCE Benchmark Phase I

International Journal of Structural Stability and Dynamics ◽

10.1142/s0219455420501382 ◽

2020 ◽

Vol 20 (12) ◽

pp. 2050138

Author(s):

Wilson D. Sanchez ◽

Jose V. de Brito ◽

Suzana M. Avila

Keyword(s):

Wavelet Transform ◽

Dynamic Response ◽

Phase I ◽

Damage Detection ◽

Health Monitoring ◽

Natural Frequencies ◽

Detection Methods ◽

State Of Health ◽

Civil Structures ◽

Synchrosqueezed Wavelet Transform

Civil structures suffer deterioration either for years of service, deficiency due to environmental factors or damages caused by factors such as earthquakes, winds, impact loads, and cyclical loads. When a structure ages, it is necessary to know its state of health and make a decision of maintenance or replacement. When a structure such as a bridge or building is subjected to destructive environmental forces, determining its state of health becomes a priority since its recovery is urgently required to function normally. Structural Health Monitoring (SHM) is a technology that aims to prevent the collapse of structures and loss of human life through early diagnosis of the health status of a structure. There are a large number of damage detection methods that can be classified into (1) non-destructive testing methods, (2) dynamic characteristics-based damage detection methods, (3) dynamic response-based, (4) multi-scale damage detection method and (5) damage detection methods with consideration of uncertainties. In this work, it is implemented synchrosqueezed wavelet transform (SWT), which can be classified as a methods based on the dynamic response. To validate the robustness of the method it is identified first, the natural frequencies of the Benchmark Phase I without damage, which consists of a steel structure of 4-story [Formula: see text] bay 3D steel frame structure subjected to ambient vibrations. Subsequently, some damage patterns are validated according to IASC-ASCE SHM Task Group. The results obtained in the identification of natural frequencies are compared with those reported in literature. SWT was efficient, presenting a minimum error of 0.12[Formula: see text] and a maximum of 3.06[Formula: see text] in the identification of natural frequencies about the AISCE-ASCE group model. SWT overcomes some other damage detection methods, which are deficient in the identification of closely spaced frequencies, commonly present in many civil structures due to symmetric geometry or similar physical properties in different directions.

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