摘要
研究构建从复合油墨配方设计到智能算法优化的完整技术体系,通过网版印刷工艺制备碳纳米管/PDMS压阻传感阵列,结合改进型卡尔曼-卷积神经网络(CK-CNN)融合算法,实现人体运动姿态的高精度捕捉。系统分析油墨组分、印刷参数对传感性能的影响机制,建立了基于生物力学的阵列布局优化方法。实验成果为智能穿戴设备的姿态监测提供了兼具技术先进性与产业化潜力的解决方案。
This study constructs a complete technical system from composite ink formulation design to intelligent algorithm optimization.A carbon nanotube/PDMS piezoresistive sensing array is prepared by screen printing process,and a high-precision human motion posture capture is achieved by combining an improved Kalman-Convolutional Neural Network(CK-CNN)fusion algorithm.The influence mechanism of ink components and printing parameters on sensing performance is systematically studied,and a biomechanics-based array layout optimization method is established.The experimental results provide a solution with both technical advancement and industrialization potential for posture monitoring of intelligent wearable devices.
出处
《丝网印刷》
2025年第14期34-36,共3页
Screen Printing
