基于双树复小波的遥测振动信号多尺度噪声调节随机共振分析

Multi-scale noise tuning stochastic resonance analysis of telemetry vibration signal based on double tree complex wavelet

遥测振动信号包含大量反映飞行器试验过程中的状态特征信息,具有非线性、非平稳性、强噪声等特点,如何提取反映系统运行状态的微弱非线性特征直接关系到飞行状态监测和故障诊断的准确性,针对这一问题,提出一种基于双数复小波的多尺度噪声调节随机共振分析方法,充分考虑多尺度带限噪声对非线性随机共振的影响,利用多尺度噪声调节和樽海鞘群算法优化非线性随机共振,对遥测振动信号的微弱特征信息进行增强,仿真和实测数据实验结果表明该方法的有效性。

Telemetry vibration signal contains a great deal of information that reflects the status of aircrafts during test,and has characteristics of non-linear,non-stationary,strong noise.How to extract the weak nonlinear features which reflect the operating status of the system is directly related to the accuracy of flight status monitoring and fault diagnosis.To solve this problem,a multi-scale noise tuning stochastic resonance analysis method based on double tree complex wavelets was proposed.The impact of multi-scale band limited noise on nonlinear stochastic resonance was fully considered,and a multi-scale noise tuning and salp-swarm-algorithm was used to optimize the iteration of nonlinear stochastic resonance,so the weak feature information of telemetry vibration signal was enhanced.Simulation and experimental results show the effectiveness of the method.