Research on Energy-Saving Operation Optimization Method of Slurry Circulation Pump Based on Fuzzy C-Means Clustering Algorithm
During the operation phase of the slurry circulation pump,its power consumption is relatively high due to fluctuations in objective application requirements.Therefore,an energy-saving operation optimization method for slurry circulation pumps based on fuzzy C-means clustering algorithm is proposed.In the feature extraction stage of the operation data of the slurry circulation pump,an unsupervised deep learning model is adopted,and a randomly initialized convolution kernel is used to perform convolution calculation on the input data to obtain a low dimensional feature map.Then,the operating parameter features of the slurry circulation pump are determined through deconvolution.In the energy-saving operation optimization stage,the fuzzy C-means clustering algorithm is introduced to cluster data with the same characteristics,and the parameter with the lowest power consumption within the same cluster is selected as the optimization result under the same operating conditions.The results showed that although the power consumption of the test circulation pump showed a stable increase trend with the increase of the maximum particle size passed,the corresponding increase was relatively small.Compared with the control group,it showed significant advantages in terms of energy-saving degree and energy-saving adaptability.
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