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An approach to deconvoluting grain-flow within a conventional combine harvester using a parametric transfer function

机译:使用参数传递函数对常规联合收割机内的谷物流进行去卷积的方法

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摘要

Grain flow measured at the flow sensor in a commercial yield monitoring System is considered to be the convoluted result of grain entering the harvester at one time being mixed by the internal threshing and transport processes with grain entering atother times. A transfer function describing the flow of grin within a conventional combine harvester was used to deconvolve the recorded signal using Fast Fourier Transformation (FFT). This process of time series analysis-was shown to reposition the yield data in a more accurate manner than the simple time-delay process currently employed. The deconvolution increases the variability in the yield data from 10 percent to 17 percent which more closely-resembles, the variation in crop yield expected from small area samples. The spatial structure of yield variation obtained from small area samples was also shown to be more closely estimated by the deconvoluted data set, however the process does display sensitivity to noise introduced by mechanical/electrical sources and procedural errors.
机译:在商业产量监控系统中,在流量传感器处测得的谷物流量被认为是谷物通过内部脱粒和运输过程混合在一起进入谷物收割机的杂散结果,而谷物则在其他时间进入混合状态。传递函数描述了传统联合收割机中的咧嘴流,通过快速傅里叶变换(FFT)使用去卷积对记录的信号进行反卷积。与当前采用的简单时间延迟过程相比,这种时间序列分析过程已显示以更准确的方式重新定位产量数据。去卷积将产量数据的可变性从10%增加到17%,这与小面积样本预期的作物产量变化非常相似。从小面积样本获得的产量变化的空间结构也显示出通过反卷积数据集可以更精确地估算,但是该过程确实显示出对机械/电源引入的噪声和程序错误的敏感性。

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