Accelerated Degradation Test Design and Degradation Trajectory Prediction of Radar Gain Control Module

As an important part of radar receiver, radar gain control module determines whether the radar system can work normally and reliably. Therefore, it is necessary to estimate its life reliably. Whereas, there are few designs for radar degradation tests and the traditional accelerated life test method is no longer suitable for long life analog integrated circuit. In this paper, an environment test system for multi-stress loading is built, and the power control board and the fixed board of the radar gain control module are designed and made based on the idea of accelerated degradation test. The test data are obtained through the temperature cycle accelerated degradation test, and the eigenvectors are extracted which can reflect the performance degradation trajectory of the radar gain control module. The extreme learning machine combining a kernel based on grey wolf optimization is used to fit the degradation trajectory, and it is compared with the grid search method, the extreme learning machine with hidden layers and several other regression methods. The results show that, the accelerated degradation test and the extreme learning machine combining a kernel based on grey wolf optimization proposed in this paper can satisfy the performance evaluation of high reliability electronic products and have high precision and great application value.