Hasil untuk "Mechanical engineering and machinery"

Ruida Huang, Qi Zhou

Wenhui Ma, Yazhuo Zou, Jiachun Zou et al.

Yong Wang, Xinhui Liu, Changsheng Liu et al.

Yonggang Zuo, Fuze Chen, Jiansheng Huang et al.

AbstractIn order to determine the influence of longitudinal oil tank bodies with different cross-sectional shapes on the vehicle's center of gravity position and the lateral overturning moment generated during cornering and braking, this paper conducts oscillation simulation calculations and analysis on longitudinal oil tanks with three different cross-sectional shapes. The optimal cross-section of the longitudinal tank is ultimately determined, providing a basis for the stability calculation of oil tankers.

Haoze Wang, Zhigang Wu, Kun Liu et al.

This paper presents a novel permanent magnet (PM) bias hybrid thrust magnetic bearing (HTMB), which can be used to replace the traditional thrust magnetic bearings (TMBs) for high-speed rotating machinery. By adding two PM rings and by reducing the number of the control coils by half, this HTMB eliminates the bias current, reduces the number of amplifiers, and minimizes the magnetic bearing’s structure complexity and power consumption. The analytical modelling method of the HTMB is presented in this paper. Mathematical models for calculating the magnetic force capacity and the stiffnesses of this bearing are derived as simplified formulae, which can be used for the design, analysis, and control of this bearing. Electromechanical characteristics of the HTMB are analyzed, which is compared to the traditional TMB to demonstrate the advantages of the HTMB. The prototype of the HTMB is designed, analyzed, and fabricated, whereas, the 2-D FEM is used to verify the design and the analytical model. Finally, an experimental setup is constructed and tested. The analytical and experimental results indicate that the proposed novel topology of this HTMB is feasible and the presented analytical model is accurate.

Pierluca D’Adamio, Emanuele Galardi, Enrico Meli et al.

In the Oil & Gas industry, the testing of auxiliary lubrication plants represents a mandatory preliminary activity before the whole turbo-machinery train (including the auxiliary lubrication plant) can be put in operation. To this end, the employment of both efficient and accurate plant models becomes very important to synthesize satisfactory control strategies for both testing and normal operation purposes. This way, many benefits (e.g. in terms of safety, times and costs of execution) can be achieved. Therefore, this article focuses on the development of innovative and efficient real-time models and control architectures to describe and regulate the auxiliary lubrication systems. All the new strategies have been validated through accurate real experimental campaign and real-time hardware. According to the Bond-Graph modeling strategy, an efficient lumped parameter model of the lube oil console has been built to properly optimize the description of such system and the efficiency of the control strategies. The code has been compiled and uploaded on a commercial real-time platform that has been used to regulate the pressure control valve of the physical plant (to this aim, a new regulator has been developed). In particular, the control was designed according to a novel model-based methodology, including both identification and control optimization techniques (based on flexible simplex techniques). The comparison between the data obtained from the simulated system and the ones acquired from the physical plant shows the good agreement, reliability and efficiency of the proposed model and the control strategy. Both the modeling approach and the control strategy have been developed in collaboration with Baker and Hughes General Electric, while the experimental data were acquired in a plant located in Massa (Italy).

Mark S. Darlow

C. Cempel

Oberlin Smith

Thomas Greenwood

Hao Zhang, Adrian David Cheok, Yujun Zhang et al.

Masako Niwa, Fusako Seto

Shinichi Kitazawa, Kozo Susami

M. Niwa

Shozaburo Yamaguchi, Ko Oyanagi

Phillip Barkan

Seinosuke Kakiage, Kohji Yamaga, Tetsuyuki Sasai