Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA.
Department of Exercise Sciences, Brigham Young University, Provo, UT 84062, USA.
Sensors (Basel). 2022 Jul 13;22(14):5239. doi: 10.3390/s22145239.
High-deflection strain gauges show potential as economical and user-friendly sensors for capturing large deformations. The interpretation of these sensors is much more complex than that of conventional strain gauges due to the viscoelastic nature of strain gauges. This research endeavor developed and tested a model for interpreting sensor outputs that includes the time-dependent nature of strain gauges. A model that captures the effect of quasi-static strains was determined by using a conventional approach of fitting an equation to observed data. The dynamic relationship between the strain and the resistance was incorporated by superimposing dynamic components onto the quasi-static model to account for spikes in resistances that accompany each change in sensor strain and subsequent exponential decays. It was shown that the model can be calibrated for a given sensor by taking two data points at known strains. The resulting sensor-specific model was able to interpret strain-gauge electrical signals during a cyclical load to predict strain with an average mean absolute error (MAE) of 1.4% strain, and to determine the strain rate with an average MAE of 0.036 mm/s. The resulting model and tuning procedure may be used in a wide range of applications, such as biomechanical monitoring and analysis.
高挠曲应变计作为经济且用户友好的传感器,具有捕捉大变形的潜力。由于应变计的黏弹性,这些传感器的解释比传统应变计复杂得多。本研究旨在开发和测试一种解释传感器输出的模型,该模型包括应变计的时变特性。通过使用拟合观测数据的传统方法,确定了捕获准静态应变影响的模型。通过将动态分量叠加到准静态模型上,考虑到伴随传感器应变变化的电阻峰值以及随后的指数衰减,从而纳入应变与电阻之间的动态关系。结果表明,通过在已知应变下取两个数据点,可以为给定的传感器进行校准。由此产生的特定于传感器的模型能够在循环载荷下解释应变计电信号,以预测应变,平均平均绝对误差(MAE)为 1.4%应变,并以平均 MAE 为 0.036mm/s 的速度确定应变率。该模型和调整过程可应用于广泛的应用,如生物力学监测和分析。