Abstract: In order to achieve automatic diagnosis of burning-plate fault on the cathode bar and real-time monitoring of current distribution in the process of copper electrolysis, based on the principle of infrared imaging, an infrared camera was used to shoot the image of copper electrolytic tank, and the gray value on the cathode bar in the processed image was extracted. A mathematical model between gray value and cathode bar temperature was developed on the basis of field tests, and the surface temperature of the cathode bar could be calculated. A partial least squares (PLS) method was used to develop a mathematical model between surface temperature and current value of the cathode bar. The square of current value after integration was found to be in quasi-linear relationship with surface temperature of the cathode bar, the coordinates of cathode bar and ambient temperature. Contrast between the current on the cathode bar derived from the model and the current measurement on the field showed that the current on the cathode bar could be accurately determined with this method, which realized real-time monitoring of current value in the copper electrolysis process. In addition, the cathode bar with burning-plate fault could be accurately and automatically diagnosed, and this fault could be predicted by monitoring the current value on the cathode bar, achieving automatic diagnosis of the fault in the copper electrolysis process, thereby reducing burning-plate fault on the cathode bar and resulting in good economic benefits.

Key words: imaging, electrolysis, algorithm, cathode bar, parameter identification, experimental validation

摘要： 铜电解过程中,为了实现阴极棒“烧板”故障的自动诊断和电流分布的实时监测。提出依据红外成像原理,采用红外相机拍摄铜电解槽槽面图像,提取处理后图像阴极棒部位灰度值,结合现场试验建立灰度值与物体表面温度的数学模型,进而求出阴极棒表面温度。其次,应用偏最小二乘法(PLS)分区建立阴极棒表面温度与电流之间的数学模型,整合后得出阴极棒中电流的平方值与阴极棒表面温度、阴极棒坐标点和环境温度为拟线性关系。依据模型导出的阴极棒电流与现场实测电流对比表明:该方法能较准确地测量阴极棒中电流,实现了铜电解过程阴极棒中电流分布的实时监测。此外,能准确自动诊断出发生“烧板”故障的阴极棒,通过阴极棒中电流的监控也能对“烧板”故障进行预测,实现了“烧板”故障的自动诊断。从而降低了阴极棒“烧板”故障的发生,为企业带来了良好的经济效益。

关键词: 成像, 电解, 算法, 阴极棒, 参数识别, 实验验证