Classifier With Dispersing Blades for Deagglomeration
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Solution Overview
Problem
Existing classifiers lack sufficient selectivity, particularly in deagglomeration and separation of fine particles, leading to inefficient classification and separation of feed materials.
Innovation Solution
A classifier design featuring a classifier wheel with dispersing blades and a feed cone, combined with an air guidance system including guide vanes and baffles, which imparts vertical and radial movement to agglomerates, enhancing deagglomeration and separation by maximizing the impact effect on dispersing blades and further breaking down particles with an impact ring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional classifiers are used for feed material classification, then basic separation is achieved, but selectivity and deagglomeration are insufficient
Solution Approach 1:
The classifier is segmented into multiple functional zones: a dispersing zone with dispersing blades for deagglomeration, a classifying zone with classifier blades for separation, and an impact ring for additional particle breakdown. This segmentation allows each zone to perform its specific function optimally, improving both selectivity and deagglomeration efficiency simultaneously
Solution Approach 2:
The dispersing blades perform preliminary deagglomeration action on feed material before it enters the main classifying zone. By breaking down agglomerates in advance, the classifier achieves better selectivity in the subsequent separation stage without compromising overall productivity
2Manufacturing precision
If impact elements are added to enhance deagglomeration, then particle breakdown improves, but device complexity increases
Solution Approach 1:
The impact ring is merged with the existing classifier structure, combining the deagglomeration function with the overall classification process. This integration adds deagglomeration capability without requiring a completely separate system, thus improving particle breakdown while limiting the increase in device complexity
3Productivity
If guide vanes are arranged to direct material concentration, then separation efficiency improves, but air flow distribution may be compromised
Solution Approach 1:
Guide vanes are strategically positioned in specific locations where material concentration is needed, rather than uniformly distributed throughout the classifier. This localized arrangement optimizes separation efficiency in critical zones while minimizing interference with overall air flow distribution patterns
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Significantly improves the selectivity and deagglomeration of feed materials, allowing for nearly complete breakdown of agglomerates into individual particles and enhanced separation of fine particles, increasing the yield of particles below 3 μm by 54.8% compared to conventional classifiers.
Implementation Method 1
redirect the falling feed material onto the spreading disc
Implementation Method 2
Due to centrifugal forces, the feed material slides to the edge of the spreading disc
Implementation Method 3
the aggregates are crushed at this point
Implementation Method 4
an air guidance system (70) having guide vanes (73) for supplying classifying air
Implementation Method 5
a classifier wheel (60) having classifier wheel blades (62)... an annular classifying space (18) arranged between the classifier wheel and the air guide system
Data Source
Figure 1
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AI summary
A classifier (1) is described, comprising a housing (2), a feed cone (20), and a rotatable dispersion plate (30), on the upper surface (31) of which dispersion vanes (40) are arranged distributed around the circumference of the dispersion plate (30). The feed cone (20) is positioned at a distance from the dispersion plate (30) on the housing (2). The separation efficiency of the classifier (1) is improved compared to conventional classifiers.