梁友斌,许建康,周俊,张颖华,何瑞银.基于小波阈值–卡尔曼的水田旋耕平地机倾角信号的去噪方法[J].湖南农业大学学报:自然科学版,2020,46(2):.
基于小波阈值–卡尔曼的水田旋耕平地机倾角信号的去噪方法
  
DOI:
中文关键词:  水田旋耕平地机  倾角信号  小波阈值法  卡尔曼滤波  融合去噪算法
英文关键词:paddy field rotary-leveling machine  inclination signal  wavelet threshold method  Kalman filter  de-noising fusion algorithm
基金项目:江苏省科学技术厅苏北科技专项(SZ–LYG2017009)
作者单位
梁友斌,许建康,周俊,张颖华,何瑞银 1.南京农业大学工学院江苏 南京2100312.连云港双亚机械有限公司江苏 连云港 222000 
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中文摘要:
      基于全球卫星导航系统(GNSS)的水田旋耕平地机田间试验,采集平地机在调平过程中的倾角信号,采用小波硬阈值法,获取低频信号,并实时估计倾角信号的噪声方差,作为卡尔曼滤波的修正信息,再将低频信号作为系统输入,运用卡尔曼滤波对信号进行二次修正。试验结果表明:小波硬阈值–卡尔曼融合算法的滤波效果优于单一的小波阈值法和卡尔曼滤波,倾角信号经融合算法处理后,信号的信噪比由21.704提高到39.116,均方根误差从0.035 1减小至0.012 6。倾角信号中的噪声成分明显减少,信号的精确度更高。
英文摘要:
      Based on the global satellite navigation system(GNSS), the angle signal of the grader during the leveling process was detected by using paddy field rotary tiller field test. The wavelet hard threshold method was used to obtain the low frequency signal, and real-timely estimate the noise variance of the angle signal as the corrective information of Kalman filter. And then the second correction on the signal was performed using Kalman filtering with the system input of the low-frequency signal. The experimental results show that the wavelet hard threshold-Kalman fusion algorithm has better filtering effect than the single wavelet threshold method and Kalman filtering, respectively. When the inclination signal is processed by the fusion algorithm, the signal-to-noise ratio of the signal is increased from 21.704 to 39.116, and the root mean square error reduced from 0.035 1 to 0.012 6.
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