2022
DOI: 10.1007/s40430-022-03518-7
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An artificial neural network supported performance degradation modeling for electro-hydrostatic actuator

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Cited by 4 publications
(3 citation statements)
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“…Using deep learning and other methods to determine the relationships between input and output data, system operation prediction, as well as fault diagnosis and analysis can be achieved. Deep learning is used in some studies to investigate the degradation failure of EHA [7,8]. Li et al [9] proposed a fault tree method for hydraulic systems failure analysis in case of incomplete data.…”
Section: Introductionmentioning
confidence: 99%
“…Using deep learning and other methods to determine the relationships between input and output data, system operation prediction, as well as fault diagnosis and analysis can be achieved. Deep learning is used in some studies to investigate the degradation failure of EHA [7,8]. Li et al [9] proposed a fault tree method for hydraulic systems failure analysis in case of incomplete data.…”
Section: Introductionmentioning
confidence: 99%
“…The speed- change, reversing, and shock-absorption functions of the vehicles are all performed by the transmission. 1 The transmission is as important as the engine. With the development of vehicles toward higher speeds and power, an increasing number of vehicles use hydraulic wet clutches to shift gears.…”
Section: Introductionmentioning
confidence: 99%
“…4 With the development of vehicle technology in the context of Industry 4.0, a shifting quality was proposed to examine the performance of shift systems. 5 Detrimental torque shock is unavoidable when a vehicle is shifting gears. The impacts can make the occupants physically uncomfortable and can affect the fatigue lives of the vehicle components.…”
Section: Introductionmentioning
confidence: 99%