Optimization strategy for improving the efficiency of mineral processing shaker

      #Industry ·2025-02-28

      Optimization strategy for improving the efficiency of mineral processing shaker
      As an important gravity beneficiation equipment, the mineral selection shaker plays a crucial role in the sorting process of mineral resources. Improving its efficiency is of great significance for enhancing the economic benefits and resource utilization of mining enterprises, and optimization strategies can be implemented from the following aspects.
      1、 Optimization of shaker structure
      Adjusting bed parameters: The length, width, and slope of the bed directly affect the sorting efficiency of mineral particles. Appropriately increasing the length of the bed surface can prolong the sorting process of mineral particles, allowing more sufficient time for separation of particles with different densities. For example, for shaking tables used to process finer grained ores, increasing the bed length by 10% -20% can effectively improve the concentrate grade and recovery rate. At the same time, adjust the bed slope reasonably according to the properties of the ore and the amount of ore to be fed. Generally speaking, when processing coarse-grained ore, the slope can be appropriately increased to enhance the sliding speed of the ore particles; When processing fine-grained ores, the slope should be appropriately reduced to ensure sufficient stratification time for the ore particles.
      Improving the structure of the headboard: The headboard is a key component that generates reciprocating differential motion in the shaker, and its motion characteristics have a significant impact on the efficiency of the shaker. By adopting a new cam lever type headboard structure, the stroke and frequency of the shaker can be precisely controlled. Compared with traditional headboards, it can more flexibly adapt to the sorting requirements of different ores. By optimizing the cam profile curve, the shaking table has a faster acceleration during the return journey, enhancing the loosening effect on the mineral particles and improving the stratification effect.
      2、 Optimization of operating conditions
      Reasonably control the feeding concentration: If the feeding concentration is too high, it will increase the viscosity of the slurry, intensify the mutual interference between mineral particles, and affect the sorting effect; If the ore concentration is too low, it will cause the slurry flow rate to be too fast, and the residence time of the ore particles on the bed surface to be too short, which is also not conducive to sorting. In general, for most ores, the appropriate feeding concentration is between 20% and 30%. By installing an online concentration detection device, the feed concentration is monitored in real time, and the amount of feed water added is automatically adjusted based on the detection results to ensure that the feed concentration remains stable within the optimal range.
      Optimize the amount of flushing water: The purpose of flushing water is to wash away light mineral particles and enrich heavy mineral particles on the bed surface. Excessive use of flushing water can also wash away some heavy mineral particles, reducing the recovery rate; If the amount of rinsing water is too small, it will not be able to effectively separate light minerals. Accurately adjust the flow rate and pressure of the flushing water based on the properties of the ore and the processing capacity of the shaker, so that the flushing water can fully remove light minerals without affecting the enrichment of heavy minerals. Usually, the flow rate of flushing water can be controlled at 1-2 times the amount of ore fed.
      3、 Optimization of Mineral Properties
      Strictly control the feeding particle size: The shaker has different sorting effects on ores of different particle sizes, and particles that are too coarse or too fine will reduce the efficiency of the shaker. By using appropriate crushing and grinding equipment and process flow, the feed particle size is controlled within the optimal sorting particle size range of the shaker. For example, for the shaking table used to process tin ore, the optimal feeding particle size is generally between 0.074-2mm. At the same time, it is necessary to ensure the uniformity of the ore particle size and avoid particle size segregation.
      Pre desliming treatment: Fine mud in the ore can affect the stratification and sorting of ore particles, reducing the efficiency of the shaking table. Before feeding the ore, efficient desliming equipment such as hydrocyclones and high-frequency fine screens are used to perform pre desliming treatment on the ore, removing most of the fine mud smaller than 0.037mm. After desliming, the ore can be further sorted by a shaking table, which can significantly improve the processing capacity and sorting effect of the shaking table.
      4、 Automation and Intelligence Upgrade
      Installation of online monitoring and control system: Using sensor technology, real-time monitoring of the operating parameters of the shaking table, such as stroke, flushing times, ore concentration, flushing water flow rate, etc., and automatically adjusting these parameters through the control system to ensure that the shaking table is always in the optimal operating state. For example, when a change in ore concentration is detected, the system automatically adjusts the flow rates of ore feed water and flushing water to maintain optimal sorting conditions.
      Introducing artificial intelligence technology: With the help of artificial intelligence algorithms, historical operating data and sorting results of the shaker are analyzed, and a predictive model is established to predict performance changes and malfunctions in advance, so as to take timely maintenance measures. At the same time, utilizing artificial intelligence technology to optimize the operating parameters of the shaker, achieving intelligent control, and further improving the efficiency and stability of the shaker.


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      Jiangxi Mingxin Metallurgy Equipment Co., Ltd
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