beck's notes
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@ -12,7 +12,7 @@ The analysis of volume flow can be broken down into two fundamental operations t
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The methodology used in order to analyze the cross-sectional area of the material flow is \textbf{geometric analysis}. Simply put, the geometry of a laden belt is compared with that of an empty belt. The resulting difference in area is that of the material itself.
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In order to accomplish this analysis, a horizontal slice of the sensor data is used---see \autoref{fig:conveyor_top}. The slice represents the depth data of a single dimension, in this case, the crosswise dimension of the belt.
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As shown in \autoref{fig:conveyor_top}, the LIDAR sensor returns a 2-dimensional image with the value of each pixel representing depth data. This 2-dimensional image can then be separated into slices. A slice represents the depth data of a single dimension, in this case, the crosswise dimension of the belt.
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\begin{figure}[h]
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\centering
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@ -49,6 +49,8 @@ However, further operations may be implemented in order to increase accuracy, su
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It is important to note though, that the implementation of further operations may exhaust the processing capabilities of the platform. Therefore, a crucial balance must be struck between performance and accuracy.
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Furthermore, this method of estimating the cross-sectional area does not take into account the warping of the belt when it is laden with material. This algorithm operates under the assumption that the error introduced by warping is negligible. This error can further be reduced by placing the sensor strategically over sections of the belt which are supported by struts. The ability to re-calibrate the belt curve $f(x)$ regularly will also help reducing this error.
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\subsection{Belt Velocity}
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Conventional belt scales use some form of a rotary encoder in order to measure the belt velocity. This is---however accurate---only an approximation of the velocity of the material flow itself, since material velocity may deviate from belt velocity depending on environmental or material conditions.
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