TY -的A2 Martinez-Olmos安东尼奥AU -莱,克劳迪奥。非盟- Acuna克劳迪奥。非盟,马瑞医生路易斯盟——Luukkanen Saija AU - da Silva,克里斯托瓦尔PY - 2022 da - 2022/12/19 TI -在线表面气体速度,持枪抢劫,和深度传感器对浮选泡沫细胞SP - 7221294六世- 2022 AB -在浮选过程中,效率和选择性取决于矿物学,粒度分布和解放,试剂添加、混合、和粒子覆盖。然而,粒子动力学恢复是高度依赖于细胞水动力和电路配置和操作策略。控制泡沫深度和气体流速,测量表面气体速度,是一个简单的替代相关动力学的泡沫和收集区。然而,这些参数不准确测量。泡沫深度测量是基于一个浮动的设备加上声波传感器;这配置提出了磁滞和偏差由于气体停滞和果肉密度的变化。在self-aspirated机器,没有技术来测量气流速度。为了解决这个问题,智能在线气体分散传感器提出了基于两个同轴HDPE cylindres。智能在线气体分散传感器是基于两个同心HDPE汽缸。气速计算的方法提高了精度与新算法。 Froth depth measurement is based on two pressure transducers, reducing the uncertainty of the floating sonic sensor to 1 cm. Pulp bulk density is directly measured, and gas holdup can be estimated. Experimental results and industrial device validation indicate that the new intelligent system can measure superficial gas velocity (Jg) online and self-calibrate, with a 2% error, the froth depth error being ±1 cm. Therefore, a multiparameter sensor for measuring gas dispersion in industrial flotation cells was experimentally designed and validated in an industrial environment (TRL 8). In this context, the proposed online gas dispersion sensor emerges as a robust technology to improve the operation of the flotation process. SN - 1687-725X UR - https://doi.org/10.1155/2022/7221294 DO - 10.1155/2022/7221294 JF - Journal of Sensors PB - Hindawi KW - ER -