INFORMATION FUSION TECHNOLOGY OF ARTIFICIAL NEURAL NETWORK FOR THE FAULT DIAGNOSIS OF TUNNEL BORING SYSTEM
Xia Zhang · Nondestructive Testing · 2004
Combining of the information fusion with artificial neural networks, various testing information of fault symptoms could be fully used to diagnose the faults of tunnel boring system accurately. By adopting the hybrid data fusion structure method, the original-level, the characteristic-level and the decision-making-level fusions were integrated with artificial neural networks, which solved the problem of dissymmetry of the input information, and made the information fusion of small data quantity and large data quantity to be possible.