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Nonlinear dynamic analysis of cutting head-rotor-bearing system of the roadheader
Zhilong Huang,Zhongchao Zhang,Yiming Li,Guiqiu Song,Yang He 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.3
In order to study the dynamic characteristics of cutting head and cantilever system, a nonlinear dynamic model with a 13 degrees of freedom (13-DOF) lateral torsional coupled cutting head-rotor-bearing system (CHRBS) is established. The nonlinear coupled factors of spline clearance and bearing contact force are mainly considered, the dynamic analysis of CHRBS under time-varying load is carried out. The results show that there is no positive correlation between the cutting rock thickness and the states of chaotic motion and quasiperiodic motion. The system is in the two states mentioned above when in low speed region. With the increase of rotational speed, the chaotic motion becomes periodic motion. When the hardness of rock is lower, increasing rotational speed can reduce the vibration of the system, and the cutting thickness can be increased to improve the productivity and lump rock rate. As the hardness of rocks increases, the coupled system shows complex dynamic characteristics when the rotational speed changes from low to high, and the vibration increased. When cutting hard rock, the cutting speed should be increased. However, when the speed is too high, the cutting torque of system becomes smaller. In the case of cutting hard rock, reasonable rotational speed should be chosen between improving stability and increasing cutting force. The dynamic analysis results provide strong support for the vibration reduction and dynamic design of roadheader.
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Gao Yuan,Zhang Liang,Zhou Jiawei,Wei Bojia,Yan Zhongchao 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.5
For the first time, the fault tree mapping dynamic Bayesian network (DBN) method is applied to the reliability research study of centrifugal compressor units, and its usability and reliability are evaluated dynamically. First, the fault data using the K-means method eliminates abnormal data and builds a fault tree model. The structure is mapped to the DBN structure to complete the structure learning, and the logic gate is mapped to the conditional probability to achieve the parameter learning. Then the model is solved bidirectionally. The change rule of system node reliability with time is solved forward, and the posterior probability of the system node is solved reversely to complete fault diagnosis. Finally, Monte Carlo simulation analysis and the Markov process verify the dynamic reliability and steady-state availability. The results show that the Monte Carlo simulation method is almost consistent with the reliability prediction curve of the DBN model. Indicating that the accuracy of the DBN model is reliable and the computational efficiency is improved by about 81434 times. The steady-state availability calculated using the DBN model is approximately 0.99963, which is close to reality compared to the Markov process. This method can better describe centrifugal compressor units’ dynamic reliability and maintainability and provide decision support for regular maintenance of essential parts and enterprise procurement.
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Wenxuan Dong,Juntao Li,Zhongchao Li,Shuo Zhang,Xiaozhen Li,Chundi Yang,Ling Liu,Shuai Zhang 아세아·태평양축산학회 2020 Animal Bioscience Vol.33 No.11
Objective: The objective of this study was to determine the digestible energy (DE) and metabolizable energy (ME) of yellow dent corn sourced from different meteorological origins fed to growing pigs and develop equations to predict the DE and ME of yellow dent corn from southwestern China. Methods: Sixty crossbred barrows were allotted to 20 treatments in a triplicate 20×2 incomplete Latin square design with 3 replicated pigs per dietary treatment during 2 consecutive periods. Each period lasted for 12 days, and total feces and urine during the last 5 days of each period were collected to calculate the energy contents. Results: On dry matter (DM) basis, the DE and ME in 20 corn grain samples ranged from 15.38 to 16.78 MJ/kg and from 14.93 to 16.16 MJ/kg, respectively. Selected best-fit prediction equations for DE and ME (MJ/kg DM basis) for yellow dent corn (n = 16) sourced from southwestern China were as follows: DE = 28.58–(0.12×% hemicellulose)+(0.35×% ether extract)–(0.83×MJ/kg gross energy)+(0.20×% crude protein)+(0.49×% ash); ME = 30.42–(0.11×% hemicellulose)+(0.31×% ether extract)–(0.81×MJ/kg gross energy). Conclusion: Our results indicated that the chemical compositions, but not the meteorological conditions or physical characteristics could explain the variation of energy contents in yellow dent corn sourced from southwestern China fed to growing pigs.
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