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- W4313232384 abstract "To effectively reduce the operation intensity of drivers, it is essential to research the intelligent operation for various stages of loaders. The traditional operation mode of the loader requires the driver to manually complete the high repeatability and frequency operation of various stages, which makes the energy-saving characteristics of the loader particularly affected by the driver. Hence, this paper proposes intelligent operation methods for various stages of loaders based on the extraction and analysis of multi-sourced data characteristics of the experiment. Specifically, the automatic adjustment of the working device attitude in the shoveling stage is achieved. During the loading and unloading stages, the working device can be automatically lifted to the memorized angle, and the bucket can also be automatically leveled. The intelligent operation method solves the problem that the loader requires the driver to work with high intensity for various stages and improves the economic aspects." @default.
- W4313232384 created "2023-01-06" @default.
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- W4313232384 date "2023-03-01" @default.
- W4313232384 modified "2023-10-06" @default.
- W4313232384 title "Intelligentization of wheel loader shoveling system based on multi-source data acquisition" @default.
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- W4313232384 doi "https://doi.org/10.1016/j.autcon.2022.104733" @default.
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