National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China.
College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China.
Sensors (Basel). 2022 Mar 20;22(6):2396. doi: 10.3390/s22062396.
Piezoelectric ceramics have good electromechanical coupling characteristics and a high sensitivity to load. One typical engineering application of piezoelectric ceramic is its use as a signal source for Weigh-In-Motion (WIM) systems in road traffic monitoring. However, piezoelectric ceramics are also sensitive to temperature, which affects their measurement accuracy. In this study, a new piezoelectric ceramic WIM sensor was developed. The output signals of sensors under different loads and temperatures were obtained. The results were corrected using polynomial regression and a Genetic Algorithm Back Propagation (GA-BP) neural network algorithm, respectively. The results show that the GA-BP neural network algorithm had a better effect on sensor temperature compensation. Before and after GA-BP compensation, the maximum relative error decreased from about 30% to less than 4%. The sensitivity coefficient of the sensor reduced from 1.0192 × 10/°C to 1.896 × 10/°C. The results show that the GA-BP algorithm greatly reduced the influence of temperature on the piezoelectric ceramic sensor and improved its temperature stability and accuracy, which helped improve the efficiency of clean-energy harvesting and conversion.
压电陶瓷具有良好的机电耦合特性和对负载的高灵敏度。压电陶瓷的一个典型工程应用是将其用作道路交通监测中称重系统（WIM）的信号源。然而，压电陶瓷对温度也很敏感，这会影响其测量精度。在这项研究中，开发了一种新型压电陶瓷 WIM 传感器。获得了在不同负载和温度下传感器的输出信号。分别使用多项式回归和遗传算法反向传播（GA-BP）神经网络算法对结果进行了修正。结果表明，GA-BP 神经网络算法对传感器的温度补偿效果更好。GA-BP 补偿前后，最大相对误差从约 30%降低到小于 4%。传感器的灵敏度系数从 1.0192×10/℃降低到 1.896×10/℃。结果表明，GA-BP 算法大大降低了温度对压电陶瓷传感器的影响，提高了其温度稳定性和精度，有助于提高清洁能源的收集和转换效率。
