【摘 要】
：
PH value of the slurry is a key parameter in froth flotation,which influences directly the process performance.However,the pH detector is easy to be disturbed and expensive to maintain,because the slu
【机 构】
：
Central South University,China Central South Univ
【出 处】
：
第三届先进计算智能与智能信息学国际研讨会(The Third International Workshop on Adv
论文部分内容阅读
PH value of the slurry is a key parameter in froth flotation,which influences directly the process performance.However,the pH detector is easy to be disturbed and expensive to maintain,because the slurry is muddy and contains fine solid particles.So,pH value is usually measured manually,which is time delayed and with low efficiency.Surface features of the froth are direct indicator of the pH value.In this paper,considering the mechanism of froth flotation,an image feature reduction method is proposed based on the attribute significance,and key image features related to pH value are obtained.Multiple models using least square support vector with multi-cores(MK-LSSVM)based on affinity propagation clustering are then proposed for pH value soft sensing.Optimal partitions of data samples are obtained through affinity propagation clustering,which are used to respectively establish the MK-LSSVM sub-models.Weight fusion of the output of all the sub-models is the final predicted pH value.Application results show that the model is of high accuracy and stable,and requirement of the production is satisfied.
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