Automatic Monitoring Method for Hybrid Supercapacitor Power Failure
The sensitive feature quantity can be used to monitor the state of capacitor power supply.Based on the sensitive feature quantity and machine learning,the automatic monitoring method of hybrid supercapacitor power sup-ply failure is studied.After constructing the mathematical model of the hybrid supercapacitor power supply system,the basic data such as voltage and current during the operation of the capacitor power supply are obtained,and the ESR value of the sensitive characteristic quantity is calculated using the time-domain method,and then the ESR val-ue is used as the input,and the multi-cascaded forest deep network of the random forest model and the rotating for-est model components is used to output the failure monitoring results of the hybrid supercapacitor power supply.Ex-perimental results show that this method can effectively obtain the current during the operation of the hybrid super-capacitor power supply,accurately calculate its sensitive characteristic ESR value,and obtain the automatic monitoring results of the hybrid supercapacitor power supply failure.
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