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针对浮选中泡沫尺寸分布的特殊性,如非高斯分布,左偏斜,高峰值等,常规分析方法无法准确描述尺寸分布的特点,因此无法准确检测和诊断浮选过程中出现的故障。提出对泡沫尺寸分布的输出概率密度函数(PDF)的统计分析,形成了一种新的浮选过程故障检测和诊断方法。通过采用自设计的核方法逼近将输出PDF转化为动态权系数,建立带有时滞的非线性不确定性权动态模型,基于线性矩阵不等式设计得到可行的故障检测和诊断算法。通过仿真验证分析,证明此算法的有效性。结合现场浮选过程,讨论了此方法的应用前景和优势。
In view of the particularity of foam size distribution in flotation, such as non-Gaussian distribution, left skewness, high peak value and so on, conventional analytical methods can not accurately describe the characteristics of size distribution and therefore can not accurately detect and diagnose faults occurring during flotation. A statistical analysis of the output probability density function (PDF) of the foam size distribution is proposed, and a new fault detection and diagnosis method for flotation process is formed. By using self-designed kernel approach approximation, the output PDF is transformed into a dynamic weight coefficient, a dynamic model of nonlinear uncertainties with time delay is established, and a feasible fault detection and diagnosis algorithm is designed based on linear matrix inequality. Through the simulation verification analysis, this algorithm is proved to be effective. Combined with the field flotation process, the application prospects and advantages of this method are discussed.