Process Monitoring And Fault Trace Of Hydrometallurgy Leaching Process

With the steady development of the economy, human being demand for gold are growing. The rational and effective use of gold mine resource is becoming increasingly important. As one of the two extractive metallurgy technologies, the remarkable advantages of hydrometallurgy are high comprehensive recovery rates of valuable metals in raw materials, benefit for environmental protection, and easy fulfillment of continuous and automated production processes. Therefore hydrometallurgy is more suitable for recovering low-grade metal resources. Hydrometallurgy leaching process is one of the key links in gold production industry. In order to prevent serious production failure and improve the production efficiency, it is important to monitor and trace the fault of the leaching process of hydrometallurgy.PCA is a method to achieve process monitoring and fault diagnosis of complex production process through the statistical analysis of the manufacturing process data which is based on principal component analysis, it is widely used in the industrial production process. However, fault diagnosis based on the method PCA can only trace back to abnormal process variables, but we could not diagnose the actual fault source.The fault tree analysis is a method which is taking the most undesired event as the top events, establishing the fault tree model, through the fault inferring, and then tracing the root causes of the top event.The thesis is based on the leaching process of hydrometallurgy, the method of PCA and FAT are adopted to monitor and trace fault of leaching process. Through analyzing the factor which can influent the leaching process, establishing the model based on the PCA, achieving the real-time monitoring and fault trace of leaching process based on the model. Taking the process various information which can lead the system to an abnormal state as the top event, basing on the process mechanism, building up the fault tree model, finding out the root causes of the abnormal system by using the fault tree analysis method.