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长期以来人们都认为对浮选泡沫的肉眼观察通常可定性地说明浮选过程的特性。本文论述了用这种途径来建立一个以图象分析为手段的浮选过程在线控制系统的可能性研究。应用已有的图象分析和中枢网络技术研完了锡浮选厂中的浮选泡沫图象分析过程。对图象进行处理,以产生泡沫表面的颜色特性和结构的指示标志。然后,根据过程性能特点(品位、水、固体流量)数据进行校正,校正过程是用常规的统计法及中枢网络模拟法实现的。已表明可用浮选泡沫的颜色来预测所得的精矿品位。已研完了不同的描述泡沫表面结构的程序,包括采用部分泡沫分析的新方法。研究结果表明,泡沫结构可较好地说明浮选槽的工作性能。文章讨论了在一个健全的控制系统中应用这一判断方法的可能性。
It has long been believed that the naked eye observation of flotation foams generally characterizes the characteristics of the flotation process. This article discusses the possibility of using this approach to establish an online control system for flotation processes that uses image analysis as a tool. Application of existing image analysis and backbone network technology research finished tin flotation plant flotation foam image analysis process. The image is processed to create an indication of the color characteristics and structure of the foam surface. Then, according to the process performance characteristics (grade, water, solid flow) data to be corrected, the calibration process is to use conventional statistical methods and the hub network simulation method to achieve. It has been shown that the color of the flotation foam can be used to predict the resulting concentrate grade. Different procedures for describing the surface structure of foams have been developed, including a new method using fractional foam analysis. The results show that the foam structure can better illustrate the working performance of the flotation cell. The article discusses the possibility of applying this method of judgment in a robust control system.