Abstract
The stress wave sensor detect and process the electronic signal of friction, mechanical shock and dynamic load on equipment moving parts, the stress wave analysis are fulfilled by using the time domain and frequency domain feature extraction software, Polynomial neural network (PNN) and data fusion technology. The equipment status are quantitatively analyzed, the equipment fault are accurately predicted. Compared with the current adopted other analysis technologies, the system can monitor the operation condition of the equipment better in real-time, predict the fault earlier. The production safety is guaranteed, the equipment maintenance cost is reduced, and the production efficiency is improved.
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