JOURNAL ARTICLE

Mine Gallery Rig Performance Test Based on BP Neural Network and Multi-sensor Data Fusion

Abstract

Traditional gallery rig's factory inspection process is complex and the result is not accurate. It is necessary to find a simple way to realize the factory inspection. In this paper multisensor data fusion based on Grubbs criterion is used in gallery rig performance test, and a classification algorithm based on BP neural network is analyzed and simulated. The results showed the validity of the algorithm, and it successfully realized the accurate evaluation of the gallery rig performance. So it has a strong practical value under the premise of both control costs and ensure the evaluation effect.

Keywords:
Factory (object-oriented programming) Artificial neural network Sensor fusion Process (computing) Computer science Fusion Engineering Artificial intelligence Real-time computing Operating system

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