Flexible, Self-Powered Sensor under Explosive Blast Loading
收藏DataCite Commons2026-04-29 更新2026-05-04 收录
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Here is presented the data used for the paper titled "Assessment of a Flexible, Self-Powered Sensor under Explosive Blast Loading". Authors: Gerardo L. Morales-Torres, Bianca Dávila-Montero, Luis A. Colón-Santiago, Muhamad Yusuf Bin Yaacob, Nelson Sepúlveda.
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, 48824, MI, United States
Department of Mechanical Engineering, Michigan State University, East Lansing, 48824, MI, United States
Link: https://doi.org/10.1016/j.nwnano.2026.100209
Abstract
Accurate measurement of explosive blast events is essential for understanding blast loading and evaluating sensing technologies for harsh, transient environments. Conventional blast pressure measurements rely on rigid, externally powered transducers that are difficult to deploy on compliant or distributed surfaces. This study investigates the response of a flexible, self-powered ferro-electret nanogenerator (FENG) subjected to controlled explosive blast loading within a large cross-section blast chamber. The FENG exhibited repeatable transient voltage responses across all blast levels, with peak output scaling linearly with measured static overpressure (R² = 0.934). Although the FENG rise time was consistently longer than that of the pressure transducer, it remained stable across repeated tests. Additional experiments demonstrated that the FENG detected blast events from multiple orientations, including configurations without direct line-of-sight exposure to the explosion. These results indicate that flexible FENG devices can reliably capture blast-related transients and suggest their potential suitability for distributed or wearable blast-monitoring applications where traditional rigid pressure sensors are impractical.
The FENG files contain the data of the ferro-electret nanogenerator voltages. The Pressure files contain the data of the angular velocity captured by sensors inside the dummy head. The python code is also presented , where all the processing and analysis was done.
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Mendeley Data
创建时间:
2026-04-29



