Aiming at the problem of circuit fault diagnosis in high?precision resonant dewpoint measurement system, this paper proposes a circuit fault diagnosis model based on improved sparrow search algorithm (ISSA) to optimize the parameters of intelligent classifier. The support vector machine (SVM) suitable for small samples and nonlinear problems is selected as the intelligent classifier. In order to solve the problems of slow convergence speed and being easy to fall into local optima of sparrow search algorithm, an improved optimization algorithm is proposed and used to optimize the parameters of SVM, and the ISSA?SVM fault diagnosis model is constructed for resonant circuit fault diagnosis. The experimental results show that the fault diagnosis accuracy rate can reach 88.9 % on the established circuit, and the ISSA?SVM classifier can be used as a high precision resonant dewpoint sensor circuit fault diagnosis method.