Synchronized switch damping on negative capacitance (SSDNC), as one of the nonlinear synchronized switch damping (SSD) techniques, has been received much attention in recent years. The damping effect depends on the effective voltage on the piezoelectric actuator in SSDNC control. The applicable bipolar voltage of a piezoelectric element is unsymmetrical. However, the voltage on the piezoelectric actuator is applied symmetrically in SSDNC, which greatly wastes the driving capability. An unsymmetrical SSDNC (un-SSDNC) is proposed in this paper to further boost the voltage on the PZT actuator and make full use of the driving ability to improve the control performance. A bypass capacitor, two diodes and switches are attached to the SSDNC circuit to realize unsymmetrical bipolar voltage. The control logic of the switches is introduced and the switched voltage is derived as well as the control performance. Experiments and simulations were carried out to verify the designed circuit and the theoretical results of the switched voltage. The influence of the bypass capacitor on the switched voltage and the stability of the un-SSDNC system were investigated. The voltage ratio and control performance increase with increasing bypass capacitor, but too large of bypass capacitor will cause the problem of system stability.

The thermal protection structures of supersonic vehicles are vulnerable to damage in the extreme environment of high temperature. With advantages of the large propagation range and high sensitivity to damage, guided waves show great potential for structural health monitoring. However, guided waves are susceptible to ambient temperature change, resulting in low reliability of damage detection results. Therefore, this paper proposed a multi-scale entropy feature extraction method for structural damage detection. Firstly, to eliminate the influence of multi-mode guided waves, a sliding window was used to extract the wave packet of different signals to analyze disturbance caused by damage and temperature. Then, an ant colony optimization algorithm was introduced as a feature fusion method to improve the classification performance. To evaluate the performance of features selected by the ant colony optimization algorithm, K-means clustering algorithm, and silhouette coefficients were utilized to calculate the evaluation function and represent the characteristics of damage. Finally, a set of guided wave signals from 20°C to 40°C were obtained to investigate the influence of temperature variation on the damage feature extraction. The results show that the multi-scale entropy method based on the sliding window can effectively extract damage features in the condition of temperature change.