Cloud computing possesses the benefits of flexibility,high efficiency and low cost,while edge computing possesses the ability to solve the problems of delayed transmission response,wastage of bandwidth resources,increased transmission costs and data privacy risks.Therefore,the fault prediction algorithm of cloud-edge collaboration was studied for the respective characteristics of cloud compu-ting and edge computing.Firstly,the wavelet transform is used to analyze the time-frequency analysis of the original signal and convert the one-dimensional signal data into time-frequency image data.Then,the time-frequency image obtained by wavelet transform is first predicted by using the MobileNetV3 model at the edge.If the maximum probability value of the prediction result reaches the pre-defined threshold,the edge prediction is considered reliable.Otherwise,the time-frequency image will be uploaded to the cloud and re-predicted by the GoogLeNet model in the cloud.Experiment results show that the proposed cloud-edge collaborative fault prediction algorithm can accurately and efficiently predict equipment faults,and reduce the latency of prediction to a certain extent.
维普
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