SDG9.5

SDG 9.5

“Non-ferrous Metallurgy Automation” Engineering Research Center, Ministry of Education

Strategic Scientific Research/Major Achievements

Nonferrous concentrators have long relied on manual inspection to identify surface defects on load-bearing steel wire ropes, a practice characterised by low efficiency, limited reliability, lengthy inspection cycles, and elevated safety risks. At the same time, the weight of concentrate loaded into railcars has traditionally been estimated by grab-crane operators, often resulting in repeated weighing, unnecessary shunting, and prolonged dwell times due to subjective judgement. To address these challenges, the research team developed a suite of intelligent detection and measurement technologies. These advances include a high-resolution defect-detection method and system for steel wire ropes based on structural modelling and spatiotemporal gray-scale analysis, a block-subimage joint defect-detection framework employing denoising autoencoders and isolation forests, and a concentrate-weight measurement system built on weight-trend analysis and a multi-segment shared-weight LSTM equalisation-compensation model. The technologies have been deployed at the Fankou Lead-Zinc Mine of Shenzhen Zhongjin Lingnan Nonfemet Co., Ltd., where an intelligent monitoring system for aerial ropeway carrier cables and an automated concentrate-weight measurement system have been successfully implemented. Their application has significantly enhanced the intelligence, safety, and operational efficiency of ore-transport operations while reducing labour costs and minimising material and time losses caused by rework. The project received the First Prize of the 2022 China Nonferrous Metals Industry Science and Technology Awards.