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- W4226038907 abstract "Structural Health Monitoring (SHM) is a process that measures and analyzes the data from structures to interpret the condition, on a near real-time basis. The damage is identified by extracting the damage-sensitive features, from the measurements, acquired using sensors of various types. When accelerometers are useful to obtain the global features of the structure, strain gage is perfect to capture even the minor changes due to damage, which is a local phenomenon, provided it lies on or very close to the location of the damage. In a spatial civil structure, it is highly impossible to install and maintain many strain gages to obtain the point-to-point local information, due to damage. Also, the change in the measured dynamic response depends upon the location and the intensity of damage. In view of this, a combination of different types of sensors with different capabilities will enhance the feature extraction and damage localization processes. In this paper, a data fusion technique, which is formulated based on the established transfer function between the acceleration and strain data, to identify and locate the small damage in structures, is presented. The transfer function between the acceleration and strain data is established using a variant of the autoregressive model. The results of the validation studies conducted on a simply supported steel beam and a scaled-down model of an existing RCC T-beam bridge suggest that the proposed algorithm is capable of identifying the minor damage, handling the measurement noise and variability." @default.
- W4226038907 created "2022-05-05" @default.
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- W4226038907 date "2022-01-01" @default.
- W4226038907 modified "2023-10-18" @default.
- W4226038907 title "A Data Fusion Technique Using Acceleration and Strain Measurements for Enhanced Damage Localization in Civil Structures" @default.
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- W4226038907 doi "https://doi.org/10.1007/978-981-16-9093-8_30" @default.
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