Medical University of South Carolina

Juan M Caicedo

Benjamin Michael Davis

Mohammod Ali

Xiaohua Jin

Paul Ziehl

Jianguo Peter Yu

Boris A Zarate

Johannio Marulanda Casas

An impact detection methodology is disclosed. Systems and methods can be utilized to detect impacts of concern such as collisions, falls, or other incidents. Systems and methods can be utilized to monitor an area and detect falls or collisions of an individual, for instance, as may require intervention to aid the subject. A system can include two or more accelerometers and a controller. The accelerometers can be in communication with the structure (e.g., within or on the walls or floor of a structure) and can monitor the structure for vibrations. The accelerometers can be coupled to a controller that is configured to process data obtained from the accelerometers and provide output with regard to the force and/or location of an impact within the structure.

Impact force estimation and event localization

In accordance with the present disclosure, a method of using acoustic emission data to predict the state of a structural element is described. The method includes capturing acoustic emission data for a structural element. The method further includes predicting the future stress intensity in the structural element using the captured acoustic emission data and calculating the probability of future failure of the structural element using the predicted future stress intensity.

Determination of the remaining life of a structural system based on acoustic emission signals

In certain embodiments of the present disclosure, a wireless sensor system is described. The wireless sensor system includes a near-field wireless power transfer component, at least one measurement sensor, and an antenna. The antenna is in communication with the measurement sensor and can transmit measurements from the measurement sensor. The near-field wireless power transfer component can wirelessly receive power to operate the measurement sensor.

Wireless power transfer to embedded sensors

Systems and methods for determining spatially dense dynamic properties of a structure are disclosed. In particular, spatially dense mode shapes are determined using acceleration records collected when one or several sensors are moving. The mobile sensor gathers vibration response data for the structure as the mobile sensor moves over the structure. The vibration response data is used to extract a fine grid of modal coordinates with a reduced number of sensors and without requiring mode shape expansion. The high spatially dense mode shapes can be included as part of accurate numerical models for the structure that can be used for a variety of purposes, such as damage detection, earthquake engineering, wind engineering, and other suitable purposes.

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Columbia, SC, United States of America

Juan M Caicedo