首页> 外文期刊>International Journal of Information Acquisition >RECOGNITION OF CONTACT STATE BY USING NEURAL NETWORK FOR MICROMACHINED ARRAY TYPE TACTILE SENSOR
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RECOGNITION OF CONTACT STATE BY USING NEURAL NETWORK FOR MICROMACHINED ARRAY TYPE TACTILE SENSOR

机译:基于神经网络的微机阵列式触觉传感器的接触状态识别

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摘要

In this paper, a force sensing element having a pillar and a diaphragm is proposed and thereafter fabricated by micromachining. Piezo resistors are fabricated on a silicon diaphragm for detecting distortions caused by a force input to a pillar on the diaphragm. Since a practical arrayed sensor consisting of many of this element is still under development, the output of an assumed arrayed type tactile sensor is simulated by FEM (finite element method). Using simulated data, the possibility of tactile pattern recognition using a neural network (NN) is investigated. The learning method of NN, the number of units of the input layer and the hidden layer, as well as the number of training data are investigated for realizing high probability of recognition. The 14 subjects having different shape and size are recognized. This recognition succeeded even if the contact position and the rotation angle of these objects are changed.
机译:在本文中,提出了一种具有支柱和隔膜的力感测元件,然后通过微加工来制造。压电电阻器制造在硅膜片上,用于检测由输入到膜片柱上的力引起的变形。由于仍在开发由许多这种元素组成的实用的阵列传感器,因此通过FEM(有限元方法)模拟假定的阵列型触觉传感器的输出。使用模拟数据,研究了使用神经网络(NN)进行触觉模式识别的可能性。研究了神经网络的学习方法,输入层和隐藏层的单元数以及训练数据的数量,以实现较高的识别概率。识别出具有不同形状和大小的14个对象。即使这些物体的接触位置和旋转角度发生了变化,该识别也成功。

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