光伏板积尘散射检测中的去噪方法研究

Denoising Method in Dust Scattering Detection of Photovoltaic Panels

由于光伏板测得的灰尘散射数据受到各种噪声和干扰因素的影响,导致测量数据的误差大。因此,为了得到准确的检测结果,提出了一种结合卡尔曼滤波和数字锁相放大技术的信号去噪方法,对混合了噪声的光伏板灰尘散射信号进行去噪处理。通过仿真实验和对实测的光伏板灰尘散射信号去噪,并计算信噪比、均方根误差和平滑度,验证了联合算法的去噪性能。结果表明,卡尔曼滤波和数字锁相放大器联合去噪算法的信噪比比单一数字锁相放大器去噪算法提高了36%,能够有效降低光电探测系统中的噪声干扰,提高光电探测系统的精度和稳定性。

The dust scattering data measured by photovoltaic panels are affected by various noise and interference factors,resulting in large errors in the measured data.For the sake of accurate detection results,a signal denoising method is proposed,combining Kalman filtering and digital phase-locked amplification technology to denoise the dust scattering signal of photovoltaic panels mixed with noise.The denoising performance of the joint algorithm is verified by simulation experiments and denoises the measured dust scattering signal of photovoltaic panels,and calculates the signal-to-noise ratio,root-mean-square error and smoothness.The results show that the signal-to-noise ratio of Kalman filter combined with digital lock-in amplifier denoising algorithm is 36%higher than that of single digital lock-in amplifier denoising algorithm,which can effectively reduce the noise interference in photoelectric detection system and improve the accuracy and stability of photoelectricdetection system.