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首页> 外文期刊>Computers & Chemical Engineering >Multivariate video analysis and Gaussian process regression model based soft sensor for online estimation and prediction of nickel pellet size distributions
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Multivariate video analysis and Gaussian process regression model based soft sensor for online estimation and prediction of nickel pellet size distributions

机译：基于多元视频分析和高斯过程回归模型的软传感器在线估计和预测镍颗粒尺寸分布

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摘要

Accurate measurement and prediction of pellet size distributions are critically important for material processing because they are essential for model predictive control, real-time optimization, planning, scheduling and decision support of material production. Mechanical sieving is one of the traditional methods for pellet size measurement in industrial practice but cannot be applied in real-time fashion. Alternately, multivariate image analysis based pellet sizing methods may acquire the size information non-intrusively and thus can be implemented for on-line measurement in industrial applications. Nevertheless, the conventional multivariate image analysis based pellet sizing methods cannot effectively deal with the pellet overlapping effects in the stitl images, which may lead to inaccurate and unreliable measurements of size distributions. In our study, two novel video analysis based pellet sizing methods are proposed for measuring the pellet size distributions without any off-line and intrusive tests. The videos of free-falling pellets are first taken and then the free-falling tracks of pellets in video frames are analyzed through the two video analysis based pellet sizing approaches. In the first video analysis method, the Sobel edge detection strategy is adopted to identify and isolate the free-falling tracks in order to estimate the diameters of the corresponding pellets. For the second video analysis approach, the filtered grayscale video frames are scanned row by row and then the particle diameters are estimated and predicted through the built Gaussian process regression (GPR) models and a fine designed counting rule so as to eliminate the overlapping effects of nickel pellets along the horizontal and vertical directions. The utility of these two video analysis based pellet sizing methods is demonstrated through the measurement and estimation of free-falling nickel pellets in two test videos.
机译：颗粒尺寸分布的准确测量和预测对于材料加工至关重要，因为它们对于材料生产的模型预测控制，实时优化，计划，调度和决策支持至关重要。机械筛分是工业实践中测量颗粒尺寸的传统方法之一，但不能实时应用。或者，基于多元图像分析的颗粒尺寸测定方法可以非侵入式获取尺寸信息，因此可以实现工业应用中的在线测量。然而，传统的基于多元图像分析的颗粒尺寸测定方法不能有效地处理stitl图像中的颗粒重叠效应，这可能导致尺寸分布的测量结果不准确和不可靠。在我们的研究中，提出了两种基于视频分析的新型颗粒尺寸测定方法，无需任何离线和侵入式测试即可测量颗粒尺寸分布。首先拍摄自由落体颗粒的视频，然后通过两种基于视频分析的颗粒定径方法分析视频帧中颗粒的自由落体轨迹。在第一种视频分析方法中，采用Sobel边缘检测策略来识别和隔离自由下落的轨道，以便估计相应颗粒的直径。对于第二种视频分析方法，逐行扫描过滤后的灰度视频帧，然后通过建立的高斯过程回归（GPR）模型和精细设计的计数规则来估计和预测粒子直径，从而消除重叠的影响沿水平和垂直方向的镍粒。通过测量和评估两个测试视频中自由落体的镍球，证明了这两种基于视频分析的颗粒尺寸测定方法的实用性。

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