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EN
With the widespread use of miniaturized electronic equipment in daily life, the problem of electromagnetic interference has become increasingly prominent, especially in precision instruments and communication equipment. To effectively reduce the causes of mechanical noise generated by small DC electrodes during operation and the electromagnetic interference effects on surrounding equipment, a mechanical noise control method that combines piezoelectric impedance technology and back-propagation neural networks is proposed. In the process, small DC motor electrodes were used as the research object, and the sources of mechanical noise generated by the motor were analyzed. At the same time, different analysis software was used to simulate and model the stator and rotor of the motor. The results show that when different algorithms are run on the training set and test set, when the amount of data increases to 560 and 1120 respectively, the method constructed in the experiment has the maximum fitness value, with values as high as 98.98% and 97.86%. When the training set is run, when the running time increases to 0.894s, the accuracy of the method constructed in the experiment to control mechanical noise reaches 91.68%. The application effect shows that when the material of the stator shell is steel, the occurrence of the maximum natural frequency of the stator is affected by the elastic modulus, which is far greater than the influence of the material density. The experiment provides new ideas and methods for noise and electromagnetic interference control of small DC electrodes.
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