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Wang J.,Jilin University | Wang Z.,Jilin University | Yu X.,Kunming University | Yao M.,Jilin University | And 2 more authors.
Chinese Journal of Mechanical Engineering (English Edition) | Year: 2012

Highly versatile machines, such as wheel loaders, forklifts, and mining haulers, are subject to many kinds of working conditions, as well as indefinite factors that lead to the complexity of the load. The load probability distribution function (PDF) of transmission gears has many distributions centers; thus, its PDF cannot be well represented by just a single-peak function. For the purpose of representing the distribution characteristics of the complicated phenomenon accurately, this paper proposes a novel method to establish a mixture model. Based on linear regression models and correlation coefficients, the proposed method can be used to automatically select the best-fitting function in the mixture model. Coefficient of determination, the mean square error, and the maximum deviation are chosen and then used as judging criteria to describe the fitting precision between the theoretical distribution and the corresponding histogram of the available load data. The applicability of this modeling method is illustrated by the field testing data of a wheel loader. Meanwhile, the load spectra based on the mixture model are compiled. The comparison results show that the mixture model is more suitable for the description of the load-distribution characteristics. The proposed research improves the flexibility and intelligence of modeling, reduces the statistical error and enhances the fitting accuracy, and the load spectra complied by this method can better reflect the actual load characteristic of the gear component. © Chinese Mechanical Engineering Society and Springer-Verlag Berlin Heidelberg 2012. Source


Wang J.,Jilin University | Wang N.,Jilin University | Wang Z.,Jilin University | Zhang Y.,Jilin University | Liu L.,Guangxi LiuGong Machinery Co.
Journal of Terramechanics | Year: 2012

The present paper aims to provide a new approach in estimating the minimum sample size of the transmission load of a wheel loader under multiple operating conditions based on multi-criteria decision-making (MCMD) technology. Extreme load values (ELVs) and load cycles under multi-operating conditions are carefully considered, and the mean and the standard deviation of ELVs and the fatigue life are the three criteria selected for estimating the sample size. Using MCMD, the weight values of the three criteria are determined, where the eigenvector and entropy information methods, together with linear combination weighting, are adopted. The optimal minimum sample size (MSS) is estimated based on the feasible values determined by the three criteria and their corresponding weight values. As an example, the load time history of the semi-axle of a wheel loader is analyzed in detail. As the ELVs and load cycles are studied, the optimal MSS can properly represent the load characteristics. The objectivity and validity of the optimal MSS are assured using the combination of the eigenvector and entropy information methods. Source


Liu Z.,Hefei University of Technology | Yuan H.,Hefei University of Technology | Cheng H.,Hefei University of Technology | Xie P.,Guangxi LiuGong Machinery Co.
Zhongguo Jixie Gongcheng/China Mechanical Engineering | Year: 2015

The main influencing factors of a swash plate axial piston pump's structure and properties were put forward, and correlation among the piston numbers and those main influencing factors was analyzed. A best program of the piston number was obtained by using the comprehensive factor evaluation method, which was a comprehensive weighted and comparison of every factor. For the K3V double-compound axial piston pump, the best piston number is as 9 using the above method. The method for determining the piston numbers provides the theory and method for selecting the best piston numbers of a swash plate axial piston pump. ©, 2015, China Mechanical Engineering Magazine Office. All right reserved. Source


Wang S.-L.,Jilin University | Ma W.-X.,Jilin University | Chu C.-X.,Guangxi LiuGong Machinery Co. | Lei Y.-L.,Jilin University | Liu C.-B.,Jilin University
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | Year: 2014

In order to study the influence of torque converter lock-up technology on loader power performance and fuel economy, the power performance and fuel economy of a certain type loader with lock-up clutch was calculated and compared with the same type loader without lock-up clutch. The results show that the accumulation of maximum output power of all gears of loader increased by 31.7% after equipping lock-up clutch, the maximum speeds of different gears are increased and the corresponding kinetic 100 km fuel consumptions are decreased. It illustrates that the torque converter lock-up technology can remarkably promote the power performance at high speed, the fuel economy and the working efficiency of loader. Source


Xia Y.-M.,Central South University | Zhang G.-Q.,Central South University | Nie S.-J.,Guangxi LiuGong Machinery Co. | Bu Y.-Y.,Central South University | Zhang Z.-H.,Central South University
Journal of Central South University of Technology (English Edition) | Year: 2011

Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head (the feed speed, the axes height of collecting head, and the rotate speed) are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 cm, then making use of the improved simulated annealing genetic algorithm (SAGA), the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn. © Central South University Press and Springer-Verlag Berlin Heidelberg 2011. Source

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