Sensor selection based on possibility measure for grinding system

Grinding process is frequently used to produce a smooth surface in the manufacturing system. In this process, sensor fusion methods for inferring the surface roughness from online sensing information have received much attention, because it takes a long time to measure the surface roughness during process. In addition, it is necessary to select the sensing information for adapting to various situation flexibly. This paper proposes a sensor fusion system with sensor selection method for a grinding system. The sensor selection method is based on the production rules, considering with the reliability calculated by the possibility measure which is a type of the fuzzy measure. Then, the sensor fusion system fuses the sensor information selected by the sensor selection method using a recurrent neural network.