ANALYSIS AND OPTIMIZATION OF TRUCK FUEL CONSUMPTION IN OPEN-PIT BASED ON MULTI-SOURCE DATA FUSION Genlai Shuai，Zhenhuan Li，Hongli Li Dandong Dongfang Measurement & Control Technology Co., Ltd. E-mail：shuaigenlai@dfmc.cc Genlai Shuai (born 1983), male, graduated from Northeastern University in 2006 with a degree in Surveying Engineering, currently serves as the Deputy Chief Engineer (Mining) in DFMC. With a focus on the mining sector, his work is dedicated to spearheading the development of intelligent systems and advancing energy efficiency management for heavy mining equipment. Tel: +86 13214151616 ABSTRACT In open-pit mining, fuel costs of large mining trucks represent a core component of operational expenses, making refined management and control crucial for cost reduction and efficiency improvement. Traditional fuel statistical methods suffer from limitations such as insufficient data precision and inaccurate identification of influencing factors. This study proposes an integrated analysis and management approach for mining truck fuel consumption by leveraging multi-source data fusion. By installing high-precision flow sensors in the fuel pipelines of mining trucks, real-time data acquisition at 1000 milliseconds intervals can be achieved. Combined with the dispatching system and digital maps, this approach accurately quantifies both instantaneous and cumulative fuel consumption during travelling, waiting, hauling and tipping. Furthermore, by integrating data from vibration sensors and inclinometers, the study elucidates the impact mechanisms of road roughness and slope on fuel efficiency. Based on this monitoring platform, an energy efficiency benchmarking system encompassing different truck types and drivers under the same operating conditions can be established. Through comparative analysis, the most fuel-efficient truck models and driving habits are identified.
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