Abstract
Capturing the three-dimensional (3D) shape of the burden surface of a blast furnace (BF) in real-time with high accuracy is crucial for improving gas flow distribution, optimizing coke operation, and stabilizing BF operation. However, it is difficult to perform 3D shape measurement of the burden surface in real-time during the ironmaking process because of the high-temperature, high-dust, and lightless enclosed environment inside the BF. To solve this problem, a real-time 3D measurement system is developed in this study by combining an industrial endoscope with a virtual multi-head camera array 3D reconstruction method. First, images of the original burden surface are captured using a purpose-built industrial endoscope. Second, a novel micro-pixel luminance polarization method is proposed and applied to compensate for the heavy noise in the backlit images due to high dust levels and poor light in the enclosed environment. Third, to extract depth information, a multifeature-based depth key frame classifier is designed to filter out images with high levels of clarity and displacement. Finally, a 3D shape burden surface reconstruction method based on a virtual multi-head camera array is proposed for capturing the real-time 3D shape of the burden surface in an operational BF. The results of an industrial experiment illustrate that the proposed method can measure the 3D shape of the entire burden surface and provide reliable burden surface shape information for BF control.
Highlights
The blast furnace (BF)-based ironmaking process accounts for more than 70% of carbon emissions, and BFs are primarily responsible for the greenhouse gas emissions caused by steel production [1]
To overcome the challenges associated with the extraction of depth information, a method for constructing a virtual multi-head camera array based on depth key frames is proposed, and the realizable shape of the burden surface is clarified substantially
To continuously measure the 3D shape of the BF burden surface, we proposed a real-time 3D
Summary
The blast furnace (BF)-based ironmaking process accounts for more than 70% of carbon emissions, and BFs are primarily responsible for the greenhouse gas emissions caused by steel production [1]. It is difficult to capture clear and reliable images of the burden surface because of the high levels of temperature, pressure, and dust in the enclosed environment. Direct detection methods for shape measurement of the BF burden surface mainly employ mechanical probes, radar probes, laser probes, and infrared imagers. To overcome the substantial interference created by the highly dynamic illumination conditions on the burden surface image due to the harsh environment and high dust levels in BFs, a real-time online full BF surface measurement system is developed in this study. To overcome the challenges associated with the extraction of depth information, a method for constructing a virtual multi-head camera array based on depth key frames is proposed, and the realizable shape of the burden surface is clarified substantially.
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