Study on Dynamic Characteristics of Negative Flow Control Variable Axial Piston Pump for Hydraulic Excavator

Author(s):  
Jin-yan Sh ◽  
Ke-chang Zhang

Hydraulic excavator is important mechanical equipment in engineering construction, which is widely used in mining enterprises, construction industry, etc. Variable axial piston pump is the main power component of hydraulic excavator. The negative flow control variable axial piston pump is deduced and the mathematical model is established. The dynamic simulation model of negative flow control variable axial piston pump is built by using SIMULINK in MATLAB software, and the simulation analysis is carried out. The influence of the main parameters of negative flow control mechanism on the dynamic characteristics of negative flow control variable axial piston pump is obtained, which provides a reference for the parameter design of negative flow control mechanism.

Measurement ◽  
2021 ◽  
Vol 167 ◽  
pp. 108279
Author(s):  
Haogong Xu ◽  
Junhui Zhang ◽  
Guangmin Sun ◽  
Weidi Huang ◽  
Xiaochen Huang ◽  
...  

2020 ◽  
Vol 53 (3-4) ◽  
pp. 649-661
Author(s):  
Xiao Chaoang ◽  
Tang Hesheng ◽  
Ren Yan

Aiming at the mechanical equipment in the fault diagnosis process, the traditional Shannon–Nyquist sampling theorem is used for data collection, which faces main problems of storage, transmission, and processing of mechanical vibration signals. This paper presents a novel method of compressed sensing reconstruction for axial piston pump bearing vibration signals based on the adaptive sparse dictionary model. First, vibration signals were divided into blocks, and an energy sequence was produced in accordance with the energy of each signal block. Second, the energy sequence of each signal block was classified by the quantum particle swarm optimization algorithm. Finally, the reconstruction of machinery vibration signals was carried out using the K-SVD dictionary algorithm. The average relative error of the reconstructed signal obtained by the proposed algorithm is 4.25%, and the reconstruction time decreases by 43.6% when the compression ratio is 1.6.


2017 ◽  
Vol 7 (4) ◽  
pp. 328 ◽  
Author(s):  
Youshan Gao ◽  
Jie Cheng ◽  
Jiahai Huang ◽  
Long Quan

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