Abstract
Certain error exists in the data collected from multi-sensor network, which is caused by the external interference and defect of sensors. Thus, data fusion algorithm is applied in such monitoring to improve the reliability. In this paper, we propose a heterogeneous sensor data fusion algorithm for temperature monitoring in carbon fiber carbonization process. Through an improved adaptive weighting algorithm and iteration algorithm based on the average value, data from heterogeneous sensors are merged to obtain data closer to the real values. The feasibility of the method is verified in experiment.
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