基于改进EM算法的氧化槽温控系统故障诊断

氧化槽是生物氧化提金的重要设备。在季节性强的中国西北地区,氧化槽温控系统运行在极端天气环境中不可避免会出现各类运行故障,若不及时排查会导致提金率的降低和矿产资源的浪费。针对此问题提出一种基于改进EM算法的氧化槽温控系统故障分类法,从而快速准确找出具体故障。仿真结果表明,改进EM算法能够充分利用工业大数据的优势,比传统EM算法与BP神经网络算法的分类正确率更高。

Fault Diagnosis of Temperature Control System of Oxidation Tank Based on Improved EM Algorithm

Oxidation tank is important equipment for gold bio-oxidation extraction. In the northwestern region in China with obvious season features, various operating failures of temperature control system of oxidation tank running in extreme weather environment arise inevitably. Failure of timely finding out will lead to drop of gold extraction rate and waste of mineral resources. Therefore, a fault classification method for oxidation tank temperature control system based on improved EM algorithm is proposed, which can quickly and accurately identify specific faults. The simulation results show that improved EM algorithm can make full use of advantages of industrial big data and has higher classification accuracy rate than that of traditional EM algorithm algorithms and BP neural network algorithm.