A method for evaluating the effect of ore crushing and grinding
A technology of ore crushing and ore crushing, which is applied in the field of evaluation of ore crushing and grinding effects, can solve problems such as failure to meet related control requirements, and achieve the effect of improving efficiency and reducing enterprise costs
Active Publication Date: 2021-11-02
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a method for evaluating the effect of ore crushing and grinding, which solves the technical problem that the prior art cannot meet the requirements for the correlation control between particle size distribution and crushing and grinding parameters
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Embodiment 1
[0040] This embodiment provides a method for evaluating the effect of ore crushing and grinding, comprising the following steps:
[0041] Step 1, collect multiple ore images produced by crushers or grinders, use the multiple ore images as a training image set, and obtain the offset angle of each ore image in the training image set at 0°, 45°, 90° , the mean of the four eigenvectors of 135°;
[0042] include:
[0043] Step 11, select an ore image from the training image set as the current ore image;
[0044] Step 12, gray-scale processing is performed on the current ore image to obtain the current gray-scale ore image, and the current gray-scale ore image is generated into a gray-scale co-occurrence matrix by formula (1);
[0045] p(i,j|d,θ)=#{[(x,y),(x+d x ,y+d y )]∈(M,N)×(M,N)|d,θ,i,j} (1)
[0046] In formula (1), (x, y) is the center point of the grayscale matrix, (x+dx, y+dy) is the offset point of (x, y), [(x, y), (x+d x ,y+d y )] is the statistical point pair in th...
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The invention provides a method for judging the effect of ore crushing and grinding, which includes the following steps: Step 1, collecting a plurality of ore images produced by a crusher or a grinder, using the plurality of ore images as a training image set, and obtaining a training image set The offset angle of each ore image is the mean value of the four feature vectors at 0°, 45°, 90°, and 135°; Step 2, construct six SVM classifiers, train the six SVM classifiers, and obtain the ore crushing Grinding qualified discrimination model The present invention uses a camera to obtain texture information of ore grain size for feature extraction, then establishes an SVM classifier to classify and identify images of different grain sizes, obtains the output value and residual value of the classifier, and uses the residual value to establish a residual discriminant The model realizes the judgment of whether the ore particle size is qualified or not in the crushing and grinding process. The invention has important significance for realizing the real-time control and feedback mediation of the crushing and grinding process, improving the efficiency and reducing the cost of the enterprise.
Description
technical field [0001] The invention belongs to the technical field of image classification, and in particular relates to a method for evaluating ore crushing and grinding effects. Background technique [0002] Crushing and grinding is a necessary process in mining engineering, but in the crushing and grinding process, the crushing and grinding effect evaluation and the adjustment of the crushing and grinding process parameters can meet the process requirements. The current crushing and grinding process parameters are adjusted by determining the ore particle size The distribution is achieved by establishing the correlation between particle size and crushing and grinding parameters. [0003] The traditional methods for determining particle size distribution include sedimentation, sieving, electrophoresis, etc. With the development of image technology, many particle size detection methods based on image processing have emerged, which can accurately measure particle size and ev...
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IPC IPC(8): G06K9/62
CPCG06F18/2411G06F18/214
Inventor 阮顺领齐凡卢才武顾清华许璨景莹马玲刘武芳茗
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY