视觉传达下激光电力设备波束形信号频谱分解研究

Research on Spectrum Decomposition of Laser Power Equipment Beam Shaped Signal under Visual Communication

波束形信号频谱分解可在一定程度上保障激光电力设备的平稳运行,激光电力设备中的重复放电过程通常具有非常高的频率,每秒可能达到几千次甚至更高。同时,重复放电过程包含多个频率的成分和不同的幅度可能非常复杂,增加了频谱分解的难度。因此,重复放电情况是频谱分解过程中的难点问题。为此,在考虑重复放电情况的基础上,提出了视觉传达下激光电力设备波束形信号的频谱分解方法。首先,利用激光视觉传感器采集重复放电情况下电力设备的波束形信号。分析电压与电阻两个影响重复放电的因素,探究波束形信号的生成机制,获取波束输出的瞬态频谱表达式。通过多普勒带宽信号模型,得到波束形信号目标参数估计值,并利用多维小波分解获得波束形信号最大波峰与波谷差值,结合频谱能量分布特征完成分解。仿真实验证明,分解后的信号频谱图与原始信号匹配度较高,具有一定的实际应用性能。

The spectral decomposition of beam shaped signals can to some extent ensure the smooth operation of laser power equipment.The repeated discharge process in laser power equipment usually has a very high frequency,which may reach several thousand times or even higher per second.Meanwhile,the repeated discharge process may involve multiple frequency components and different amplitudes,which can be very complex,increasing the difficulty of spectral decomposition.Therefore,repeated discharge is a difficult problem in the spectrum decomposition process.Therefore,based on the consideration of repeated discharge,a spectral decomposition method for beam shaped signals of laser power equipment under visual transmission is proposed.Firstly,a laser vision sensor is used to collect the beam shape signal of power equipment under repeated discharge conditions.The two factors that affect repetitive discharge,voltage and resistance are analyzed.The generation mechanism of beam shaped signals is explored,and the transient spectrum expression of beam output is obtained.By using the Doppler bandwidth signal model,the estimated target parameters of the beamform signal are obtained,and the maximum peak and valley difference of the beamform signal is obtained through multi-dimensional wavelet decomposition.The decomposition is completed by combining the spectral energy distribution characteristics.Simulation experiments have shown that the decomposed signal spectrum has a high matching degree with the original signal,and has certain practical application performance.