In this paper, isolation forest algorithm is used to construct an abnormal parameter monitoring model for surge protectors. By making the model learn the distribution of normal SPD parameter data, the abnormal parameter data of SPD that cannot fit into the distribution will be identified, then the actual state and deterioration degree of the device can be evaluated and warned. The study first performs multi-parameter sampling on the SPD, pre-processes the obtained 390 sets of experimental data, and combines the algorithm model to calculate the abnormal value corresponding to each set of sampling data to identify the corresponding abnormal sampling data. Finally, according to the label corresponding to each set of data, Verify the accuracy of the algorithm. The test results show that the monitoring model based on the isolation forest algorithm can evaluate the abnormality of the SPD sampling data, and lock the parameter values corresponding to the SPD that may appear bad or degraded in the system. For the experimental data set, the performance index AUC value of the algorithm model under different parameters is not less than 96%, which provides a new idea for the monitoring research of SPD performance.