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首页> 外文期刊>Journal of Computational Methods in Sciences and Engineering >Precision weighing control of coal mine paste backfilling weighing system
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Precision weighing control of coal mine paste backfilling weighing system

机译:煤矿浆料回填称重系统精密称重控制

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摘要

Coal mine paste backfilling (CMPB) technology is developed rapid recently as a sustainable and green mining tech-nology. As the application of paste technology matures gradually, it is developing towards fine research, aiming at improving filling quality and reducing filling cost. To increase feeding speed and improve weighing accuracy of the coal mine paste back-filling weighing system (CMPBWS), the mathematical weighing progress model of CMPBWS is established and the weighing control system is optimized based on the adaptive iterative algorithm. The weighing process is divided into three stages, which are the rapid feeding stage, the lower feeding stage, and the prediction feeding stage. The weighing speed of each stage is con-trolled with different ways. The adaptive iterative learning control method (AILCM) is introduced and used in the prediction feeding stage. The advance stop value is dynamically modified by the AILCM. The numerical simulation study shows that the actual value is much closer to the set value after several iterations by the AILCM. With the method proposed in the paper, the weighing accuracy and feeding speed of CMPBW are both improved.
机译:煤矿浆料回填(CMPB)技术最近开发为可持续和绿色矿业技术。随着粘贴技术的应用逐渐成熟,它正在开发精细研究,旨在提高填充质量并降低填充成本。为了提高喂养速度和提高煤矿膏背填充称重系统(CMPBW)的称重精度,建立了CMPBWS的数学称重进度模型,基于自适应迭代算法优化了称重控制系统。称重过程分为三个阶段,这是快速进给阶段,下馈级和预测饲料阶段。每个阶段的称重速度以不同的方式进行控制。自适应迭代学习控制方法(AILCM)被引入并用于预测馈送阶段。 AILCM动态修改前进的停止值。数值模拟研究表明,在anilecm几次迭代后,实际值更接近设定值。利用本文提出的方法,CMPBW的称重精度和馈送速度均得到改善。

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