Construction machinery hydraulic transmission system fault analysis and elimination methods

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Abstract

The hydraulic system plays the role of power transmission in the working process of construction machinery, but their complex structure leads to their frequent failure, which in turn leads to serious consequences. Therefore, this paper first takes the fault diagnosis and troubleshooting of the hydraulic system of construction machinery as the research theme and introduces the working principle of the hydraulic system of construction machinery and common fault mechanism and common methods of fault monitoring and diagnosis. Secondly, it proposes to analyze the key components of the hydraulic system based on the power bonding diagram theory and establish its bonding diagram model to analyze the working principle and power flow characteristics of key components. Finally, the pressure and velocity characteristic parameters are identified with the help of wavelet technology, and the energy distribution and energy entropy value of the hydraulic cylinder velocity signal are obtained by wavelet packet transform. The simulation results show that the wavelet-based analysis model proposed in this paper has good fault tolerance and robustness for fault diagnosis of the hydraulic system of construction machinery, and the correct rate of hydraulic pump fault diagnosis is up to 97%, with a correct average rate increased by 16%; the correct rate of hydraulic cylinder fault diagnosis is up to 95%, with a correct average rate increased by 13%. The wavelet analysis model can be widely applied to the fault diagnosis of hydraulic systems of various construction machinery, and it effectively improves the performance of hydraulic fault analysis systems and provides a key technology for fault identification and troubleshooting of construction machinery.

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APA

Lin, Z., & Gong, Q. (2023). Construction machinery hydraulic transmission system fault analysis and elimination methods. Applied Mathematics and Nonlinear Sciences. https://doi.org/10.2478/amns.2023.1.00165

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