Key Laboratory of Micro-Systems and Micro-Structures Manufacturing, Ministry of Education and School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel). 2018 Jun 5;18(6):1820. doi: 10.3390/s18061820.
In daily contexts, fabrics embodied in garments are in contact with human body all the time. Since fabric material properties-such as softness or fineness-can be easily sensed by human fingertips, fabric materials can be roughly identified by fingertip sliding. Identification by simply touching and sliding is convenient and fast, although the room for error is always very large. In this study, a highly discernible fabric humanoid identification method with a fingertip structure inspired tactile sensor is designed to investigate the fabric material properties by characterizing the power spectrum integral of vibration signal basing on fast Fourier transform integral (), which is generated from a steel ball probe rubbing against a fabric surface at an increasing sliding velocity and normal load, respectively. and are defined as the slope values to identify the fabric surface roughness and hardness. A sample of 21 pieces of fabric categorized by yarn weight, weave pattern, and material were tested by this method. It was proved that the proposed humanoid sensing method has more efficient compared with fingertip sliding while it is also much more accurate for fabric material identification. Our study would be discussed in light of textile design and has a great number of potential applications in humanoid tactile perception technology.
在日常生活中,服装所采用的织物材料始终与人的身体直接接触。由于织物材料的柔软度或精细度等特性可以通过人类指尖轻易感知,因此可以通过指尖滑动对织物材料进行大致识别。这种仅凭触摸和滑动的识别方法既方便又快捷,尽管误差空间总是很大。在这项研究中,设计了一种基于快速傅里叶变换积分()的具有指尖结构的高识别度仿人识别方法,通过对钢球探针在逐渐增加的滑动速度和法向载荷下摩擦织物表面所产生的振动信号的功率谱积分进行特征化,来研究织物材料特性。和被定义为斜率值,用于识别织物表面的粗糙度和硬度。通过该方法对 21 块不同纱线重量、织物组织和材料的织物进行了测试。结果表明,与指尖滑动相比,所提出的仿人传感方法效率更高,而对于织物材料识别的准确性也更高。我们的研究将从纺织品设计的角度进行讨论,并在仿人触觉感知技术中有许多潜在的应用。