Search results

This paper aims to propose a novel mathematical model of bearingless switched reluctance motor (BSRM). This model differs from conventional mathematical models in the calculation of torque and suspension forces. Conventional mathematical models neglect the coupling relationship between the α- and β-axes or ignore the magnetic saturation of the Si-Fe material. This study considers these issues simultaneously. Additionally, considering the air-gap edge effect, the fringing coefficient is used to establish a high-precision mathematical model.

An innovative mathematical model of BSRM based on the Maxwell stress method was established by selecting an appropriate integration path. The fringing coefficient of the air-gap was computed based on the finite element analysis results at the aligned position of the stator and rotor poles. Using the least squares fitting method, the piecewise fitted magnetization curve of the Si-Fe material was utilized to calculate flux density.

The appropriate integration path of the Maxwell stress method was selected, which considered the coupling relationship of the suspension forces in the α- and β-axes and was closer to the actual situation. The fringing coefficient of the air-gap improved the calculation accuracy of air-gap flux density. The magnetomotive force was consumed by the magnetic resistance of the stator and rotor poles considering the magnetic saturation.

A novel mathematical model of BSRM is proposed. Different from conventional mathematical models, the proposed model can effectively solve the coupling relationship of the suspension forces in the α- and β-axes. Additionally, this model is consistent with the actual situation of motor as it includes a reasonable calculation of the air-gap flux density, considering the air-gap edge effect and magnetic saturation.

Parameter identification of photovoltaic (PV) modules plays a vital role in modeling PV systems. This study aims to propose a novel hybrid approach to identify the seven parameters of the two-diode model of PV modules with high accuracy.

The proposed hybrid approach combines an improved particle swarm optimization (IPSO) algorithm with an analytical approach. Three parameters are optimized using IPSO, whereas the other four are analytically determined. To improve the performance of IPSO, three improvements are adopted, that is, evaluating the particles with two evaluation functions, adaptive evolutionary learning and adaptive mutation.

The performance of proposed approach is first verified by comparing with several well-established algorithms for two case studies. Then, the proposed method is applied to extract the seven parameters of CSUN340-72M under different operating conditions. The comprehensively experimental results and comparison with other methods verify the effectiveness and precision of the proposed method. Furthermore, the performance of IPSO is evaluated against that of several popular intelligent algorithms. The results indicate that IPSO obtains the best performance in terms of the accuracy and robustness.

An improved hybrid approach for parameter identification of the two-diode model of PV modules is proposed. The proposed approach considers the recombination saturation current of the p–n junction in the depletion region and makes no assumptions or ignores certain parameters, which results in higher precision. The proposed method can be applied to the modeling and simulation for research and development of PV systems.

This paper aims to establish a piecewise Maxwell stress analytical model of bearingless switched reluctance motor (BSRM) for the full rotor angular positions. The proposed model varies from the existing models, which are only applicable to the partial-overlapping positions of stator and rotor poles. By extending the applicable rotor angular positions, this model provides a basic analytical model for the multi-phase excitation control of BSRM.

The full rotor angular positions are classified into the partial-overlapping positions and the non-overlapping positions. At first, two different air gap subdividing methods are proposed, respectively, for the two-position ranges. Then, different integration paths are selected accordingly. Furthermore, two approximate methods are presented to calculate the average flux density of each air gap subdivision. Finally, considering the mutual coupling between the two perpendicular radial suspension forces, a piecewise Maxwell stress analytical model is derived for the full rotor angular positions of BSRM.

A piecewise Maxwell stress analytical model of BSRM is built for the full rotor angular positions, and applicable to the multi-phase excitation mode of BSRM. For the partial-overlapping positions and the non-overlapping positions, two sets of air gap subdividing methods, integration paths and approximate calculation methods of air gap flux densities are proposed, respectively. The accuracy and reliability of the proposed model are verified by the finite element method.

The piecewise Maxwell stress analytical model of BSRM for the full rotor angular positions is proposed for the first time. The novel air gap subdividing methods, integration paths, approximate calculation methods of air gap flux densities and the coupling between the two radial suspension forces are adopted to improve the modeling accuracy. As the applicable range of rotor angular position is extended, this model overcomes the limitation of the existing models only for single-phase excitation mode and contributes to the accurate control of BSRM multi-phase excitation mode.

An improved analytical method for calculating the natural frequencies of a switched reluctance motor (SRM) stator is proposed in this paper. The method is different from traditional analytical methods, which only consider the influence of mass of the stator poles and windings on the natural frequencies of the SRM stator. This paper aims to consider the influence of stiffness and mass of the stator poles and windings simultaneously and reasonably.

An innovated analytical method based on the electromechanical analogy method is presented. In the proposed analytical formulae for calculating the natural frequencies, the influence of the windings on natural frequencies is considered by using the springs to simulate the flexible connection between the stator core and windings, and the stator poles are treated as both additional mass and additional equivalent stiffness. Both three-dimensional (3D) finite-element analysis (FEA) and experimental modal analysis results validate the improved method.

The influence of the mass and stiffness of stator winding is considered by using the springs to simulate the flexible connection between the stator core and windings, and the stator poles are treated as both additional mass and additional equivalent stiffness. The traditional analytical method only considers the influence of mass. Therefore, the calculation results are comparatively lower than 3D FEA results and may lead to a large error. The 3D FEA and experimental modal analysis confirm that the proposed method has good precision for low-order natural frequency calculation of SRMs.

An improved analytical method for calculating the natural frequencies of an SRM stator is proposed. Unlike the traditional analytical method, the proposed method can consider the influence of stiffness and mass of the stator poles and windings. This method is valuable for designers to predict the natural frequencies accurately.

Stimulated by previous reference, which proposed making straight line of regression to test gear gravimetric wear loss sequence distribution, this paper aims to propose using straight line of regression to fit gear gravimetric wear loss sequence based on stationary random process suppose. Faced to that the stationary random sequence suppose had not been proved by previous reference, and that prediction did not present high precision, this paper proposes a method of fitting non-stationary random process probability distribution function.

Firstly, this paper proposes using weighted sum of Gauss items to fit zero-step approximate probability density. Secondly, for the beginning, this paper uses the method with few Gauss items under low precision. With the amount of points increasing, this paper uses more Gauss items under higher precision, and some Gauss items and some former points are deleted under precision condition. Thirdly, for particle swarm optimization with constraint problem, this paper proposed improved method, and the stop condition is under precision condition.

In experiment data analysis section, gear wear loss prediction is done by the method proposed by this paper. Compared with the method based on the stationary random sequence suppose by prediction relative error, the method proposed by this paper lowers the relative error whose absolute values are more than 5%, except when the current point sequence number is 2, and retains the relative error, whose absolute values are lower than 5%, still lower than 5%.

Finally, the method proposed by this paper based on non-stationary random sequence suppose is proved to be the better method in gear gravimetric wear loss prediction.

The electrical properties of piezoelectric vibrators have a crucial influence on the operating state of ultrasonic motors. In order to solve the problem that the current piezoelectric vibrator generates a large amount of heat during vibration to degrade its performance, which in turn affects the normal operation of ultrasonic motors, this paper prepares a novel piezoelectric vibrator and tests its maximum vibration velocity under the working condition, which is more than twice as much as that of the current commercial PZT-8.

The crystal structures of the samples were analyzed by using an X-ray diffractometer. For microstructure observation, samples were observed by scanning electron microscope (SEM). The quasi-static piezoelectric coefficient meter (ZJ-3AN) was used for piezoelectric measurement. Dielectric properties were measured by utilizing an impedance analyzer (Agilent 4294A) with a laboratory heating unit. Ferroelectric hysteresis loops were obtained using a ferroelectric analyzer (Radiant, Multiferroic 100). A Doppler laser vibrometer (Polytec PSV-300F, Germany) and a power amplifier were used for piezoelectric vibration measurements, during which the temperature rise was determined by an infrared radiation thermometer (Victor 303, China).

The ceramics exhibit enhanced piezoelectric performance at 0.1–0.4 mol% of Yb doping contents. The ceramic of 0.4 mol% Yb reaches the maximal internal bias field and presents a larger mechanical quality factor of 1,692 compared with that of 0.2 mol% Yb-doped ceramic, in spite of a slightly decreased dielectric constant of 439 pC/N, the unit of the piezoelectric constant, which is the ratio of the local charge (pC) to the frontal force (N) and electromechanical coupling coefficient of 0.63. The vibrator with this large mechanical quality factor ceramic displays a vibration velocity of up to 0.81 m/s under the constraint of 20 °C temperature rising, which is much higher than commercial high-power piezoelectric ceramics PZT-8.

The enhanced high-power properties of the piezoelectric vibrator by Yb doping may provide a potential application for the high-performance USM and offer the possibility of long-term stable operation under high power for special equipment like USM. In the subsequent phase of research, the novel PZT-based high-power piezoelectric vibrator can be utilized in the USM, and the motor's performance will be evaluated under aerospace conditions to objectively assess the reliability of the piezoelectric vibrator.

There is a relatively low risk management (RM) level and maturity in China’s state-owned construction enterprises (CSCEs). The purpose of this paper is to find the main factors impacting RM in practice to promote rapid, sound and sustained development in CSCEs.

There are a few state-owned CSCEs in China. Most enterprises know little about RM. Because of the limited number of RM departments in these enterprises, 200 questionnaires were sent to the enterprises to investigate the RM strategies employed by them. The research is quantitative and used a questionnaire survey to determine the important factors influencing RM practice. The collected data were analyzed with the Statistical Package for the Social Sciences to identify the most important factors affecting RM as well as the extent of influence of these factors, in order to facilitate further research.

The survey revealed the top eight factors (i.e. leaders’ support, personnel’s responsibility, comprehensiveness of identification, costs and benefits, risk appetite, understanding of language, frequency of training and performance management) that highly impact RM in CSCEs and the extent to which these factors impact RM. The data reveal that the average RM level is low. Some methods have been recommended to improve RM.

The research lays the foundation for further RM development in CSCEs. The low RM level in CSCEs should encourage researchers to find better ways to improve RM. Some factors in the research will function as valuable guides for China’s private and public-private partnership enterprises.

A quantitative analysis methodology for RM has been developed for CSCEs that can reflect their RM level. In addition, the degree of impact of key factors on RM has been shown. The results can act as a reference to improve RM quantitatively, making the RM system more explicit in dealing with risks more accurately and instructively.

Structural RM research is utilized to evaluate RM in CSCEs by following an empirical method. With the continuous improvement in RM, CSCEs can cooperate well with construction enterprises of other countries for infrastructure projects and gain more benefits.

As the excessive lifting force can lead to catwalk rollover and well site accidents, the lifting process boundary conditions and structural parameters have a significant effect lifting force, it is important to analysis the structural parameters on the maximum lifting force in the lifting process of power catwalk.

A new model is proposed to analyze the influence of structure parameters on its lifting force for lifting power catwalk in this paper, and the geometric and dynamic equations are established according to the different boundary conditions in different stages. In addition, the establishment of dynamics equations is based on D'Alembert's principle. To solve the model, dynamic analysis software is developed, which uses c # call MATLAB to solve the geometric and dynamic equations. The maximum lifting force is analyzed and optimized according to the software, the influence of structural parameters on the maximum lifting force is obtained and the correctness of the optimization is proved by experiments.

The best value of offset e is 0. The length of L22 should as small as possible while the installation size of the end of the conveying arm are guaranteed. The length of L1 should as small as possible while ensuring the not exceed the maximum value. The maximum lifting force remain the same in the second phase, the maximum lifting force decreases with the increase of Lcp, Lcpshould as small as possible. The maximum pressure of the hydraulic oil dropped by an average of 13.62% under optimized parameters.

This paper provides a theoretical basis for the selection of hydraulic winch, which also provides the theoretical basis and data support for the design and optimization of the structural parameters of the power catwalk.

This research has industrial applications in SJ Petroleum Machinery CO.LTD, SINOPEC (China) .CANRIG, North Rig, TESCO, Sichuan HONGHUA petroleum equipment CO.LTD of CNPC., Baoji Oil field Machinery CO.LTD, SJ Petroleum Machinery Co. LTD of SINOPEC, Yantai Jereh Oilfield Services Group CO.LTD, Nanyang clips oil equipment (group) CO. LTD, etc are the likely users.

A new model is proposed to analyze the lifting force of lifting power catwalk. The model takes into account the inertia force of the structure, development of dynamics software and analysis and optimization of structural parameters. The maximum lifting force is analyzed and optimized according to the software, the influence of structural parameters on the maximum lifting force is obtained and the correctness of the optimization is proved by experiments.

The paper aims to propose a clustering model for panel data. More specifically, the paper aims to construct a gray incidence model for panel data to solve the classification with multi-factors and multi-attributes.

The paper opted for a clustering theory study using gray incidence theory based on dynamic weighted function. The paper presents an example to verify the rationality of the new model, which suggests that the new model can reflect the incidence degree of panel data.

The paper provides a new gray incidence model based on a dynamic weighted function that can amplify the characteristics of the sample to some extent. The properties of the new incidence model, such as normalization, symmetry and nearness, are all satisfied. The paper also shows that the new incidence model performs very well on cluster discrimination.

The new model in this paper has supplemented and improved the gray incidence analysis theory for panel data.

Consumers are giving greater attention to the selection of food due to the improvement in income and urbanization. Meanwhile, in recent years, the vegetables' farmers in Malaysia have been reported using an excessive quantity of pesticides. The vegetables exported to Singapore and China have been rejected in 2018 and 2017 due to the presence of excessive levels of pesticides. Such incidences have created massive concern to improve the safety standard of the vegetable industry. The purpose of this paper is to evaluate consumers' willingness to pay for food safety attributes of tomato.

Discrete choice experiments has been used, and 490 respondents have completed the survey.

Results suggested that consumers were willing to pay RM4.18 more for wholesome tomato relative to slightly damage tomato. Consumers also were willing to pay RM2.75 more for organic tomato relative to inorganic tomato. They were also willing to pay RM2.30 and RM1.29 more for certified and tomato sold at supermarket relative to uncertified and tomato sold at the wet market, respectively. The willingness to pay for safety attributes of tomato also varied according to the income, age and education level of the consumers.

If the farmers can respond effectively to the changes in consumers demand, it can be translated into business opportunities.

This research able to provide relevant information related to the consumers' willingness to pay for food safety attributes of tomato in Malaysia.