有色设备

China's lead ore resources are characterized by “more poor ore and less rich ore”, and the excess supply of overseas lead concentrate has decreased. The lead smelting process is characterized by the coexistence of multiple element resources, large fluctuations in raw material quality, and complex smelting processes. Currently, China's non-ferrous metal smelting industry is in a state of mechanization, electrification, automation, and informatization, and the development of different enterprises is unbalanced. Based on the above, this article introduces the distribution of lead ore resources (lead concentrate and lead-containing waste) and the main uses of lead, the development process of lead smelting technology, and provides a detailed overview of the current main lead based material smelting technologies, such as oxygen bottom blowing smelting-melt reduction-oxygen rich volatilization refining technology, oxygen rich immersion top blowing smelting technology, lead sulfate slag wet smelting technology, side-submerged combustion melting pool smelting treatment technology for regenerated lead resources, brittle sulfur lead antimony ore treatment technology, lead anode mud treatment technology, copper floating slag and lead concentrate slag treatment technology, lead electrolysis technology, etc. Combining with the industrial production scenario of lead smelting, deep learning methods are used to establish a data-driven model of the smelting furnace, which can achieve real-time prediction and evaluation of key operating indicators of the system and promote the intelligence and digitization of lead smelting technology, to meet the development opportunities and challenges of the lead industry.