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Failure can be predicted based on the load conditions by estimating the load applied to a machine during operation. However, the load applied to construction machinery, such as hydraulic excavators, varies depending on the work environment and nature of the work; therefore, it is necessary to construct a load estimation model that adapts to these conditions. This study proposes a load-estimation modeling method that builds a database for each operation, selects a database based on the operation judgment by long short-term memory, and performs database-driven modeling. Applying the proposed method enables the selection of an appropriate database according to the work content and perform a highly accurate load estimation. The effectiveness of the proposed method was verified experimentally using a radio-controlled excavator.
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Naruta et al. (2024) studied this question.
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