Abstract
This article designs and implements a fault diagnosis system for diaphragm pump. The key components of the diaphragm pump are equipped with three-axis vibration intelligent sensor to collect vibration data, the edge side completes the data pre-processing, and then transmits it to the cloud platform through NBIoT. For the non-linear, non-smooth complex system, the time frequency representation is obtained by continuous wavelet transformation, after compressing the time frequency representation as the input of the two-dimensional neural network model, using the two-dimensional convolutional neural network model for training and monitoring, to complete the identification and positioning of diaphragm pump fault.
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