Development of tribosensor system using neural networks (Trihosensor using piezoelectric ceramics)

摘要

This paper presents a study on the development of a new tribosensor that has the sensitivity of human skin. The sensor is basically a piezoceramic AE sensor. It is placed and moved on the material to be identified. The voltage signal from the sensor is first stored in digital memory for a fixed period of time. It is then analyzed to obtain the maximum signal strength, the total number of concaves and convexes of the signal, and the number of crossings with the line of mean signal strength. Each set of the parameters obtained is compared with the training set of data in the neural networks, and the material of the measured sample is fixed. Experimental results obtained show that the present sensor system identifies the material 85 correctly for 120 samples of 6 different materials.