Aiming at the problem of composite anomaly detection and health monitoring, the impedance spectroscopy combined with support vector machine (SVM) is applied to aircraft composite materials component health monitoring. A uniplanar dual electrode sensor and two carbon fiber composite samples are fabricated,and an experiment circuit is designed, and two carbon fiber material electrical impedance spectrum is measured.On Matlab software platform, the support vector machine (SVM) are used to identify health status of the composites after extracting the characteristic parameters of the different types of electrical impedance. The analysis of the support vector machine (SVM) identification accuracy under different types of characteristics parameters is carried out.The results show that comparing with the Cole-Cole curve segment real or imaginary part of electrical impedance average, and the frequencyreal or imaginary part of electrical impedance piecewise linear fitting curve slope，the support vector machine has higher identification accuracy while the Cole-Cole piecewise linear fitting curve slope is used to be a characteristic parameter. Preliminary experiment shows that the support vector machine(SVM) combined with electrical impedance spectrum method for aircraft health monitoring of composite components is effective.