With the increasing demand for electricity, the reliability and safety of electric energy metering devices have attracted much attention. Aiming at the problem of low accuracy of fault diagnosis of electric energy metering device, an improved seagull algorithm optimized support vector machine (ISOA-SVM) model is studied and designed. In order to make up for the deficiency of seagull optimization algorithm (SOA), an improved seagull optimization algorithm (ISOA) with better optimization performance is proposed. The internal parameters of SVM are optimized by ISOA, and the fault diagnosis model of electric energy metering device based on ISOA-SVM algorithm is constructed. The experimental results show that under the same evaluation index, the average value of 50 fault diagnosis of ISOA-SVM model is as high as 96.575%, which is 6.681%, 5.63%, 11.95% and 12.79% higher than that of PSO-SVM, SOA-SVM, SVM and ELM model. It shows that the designed ISOA-SVM algorithm has strong robustness and good fault diagnosis performance.