中国高端体育智库建设助力体育国际话语权提升的价值、维度及策略

加强中国高端体育智库建设是助力体育国际话语权提升的重要途径。采用文献资料法,探究中国高端体育智库建设助力体育国际话语权提升的价值、维度及策略。研究认为,中国高端体育智库建设在提升中国参与全球体育治理能力、树立中国负责任的体育大国形象、推动中国体育思想与文化对外传播方面具有重要价值。中国高端体育智库与国际社会的交流互动、人才互派、成果互享、智媒互联四个维度助力体育国际话语权提升。提出以下策略:加强聚焦国际视野的体育交流合作,提升话语引导力;扩大国际化体育人才培养规模,强化话语渗透力;提升智库成果的国际影响力,增强话语创造力;注重国际化传播矩阵建设,增强话语传播力。

“日本足球百年计划”研究:历程、经验及启示

20世纪90年代,川渊三郎推出“日本足球百年计划”,助力日本足球腾飞,对现阶段中国足球“总体构想”“人才选拔”“普及工作”“国际交往”具有一定启示意义。采用文献资料法、逻辑分析法,以川渊三郎的治理思想及日本足协发布的政策文本为切入点,对“日本足球百年计划”历程、经验及启示展开研究。“日本足球百年计划”经历“曲折发展”“初创发展”“快速发展”3个阶段,其注重阶段计划的有效衔接,监督发展目标阶段性实现;建立完备的联赛体系,设计合理的足球人才选拔系统;发挥足球的人文关怀价值,引导足球运动普及化发展;主动融入世界足球主流体系,助力竞技体育国际话语权提升。基于此,我国应优化中国足球发展的总体规划,重建中国足球人才选拔系统,创设“三位一体”足球普及模式和增强中国足球国际化传播意识。

结构功能理论视角下中国特色新型体育智库建设路径研究

运用结构功能理论的AGIL分析模式,对中国特色新型体育智库的建设路径进行探析,结果表明:我国体育智库存在着以协同机制为代表的行为有机系统、以组织文化为代表的人格系统、以运行机制为代表的社会系统、以管理体制为代表的文化系统组成。目前我国体育智库存在协同机制不畅、组织文化缺失、运行机制失效及管理体制失灵等问题。针对上述问题,结合体育智库的时代使命提出建设路径:即共建良性多维互动关系的协同机制,拉紧体育智库协同决策的共同纽带;塑造以体育精神为核心的组织文化,打造体育智库品牌化发展道路;建立良性的运行机制,激活体育智库独立自主的发展引擎;创设灵活的管理体制,引导体育智库的全面提升和可持续发展。

新时代中国高端体育智库评价指标体系构建

中国高端体育智库评价指标体系是审视国家体育决策治理能力的重要理论依据和参考工具。运用文献资料法、德尔菲法、层次分析法等,从“智库组织力”“智库保障力”和“智库影响力”3个维度,对中国高端体育智库评价指标体系进行研究,建立由3个一级指标、9个二级指标和33个三级指标所构成的中国高端体育智库评价指标体系,确定中国高端体育智库评价体系各指标的权重系数,并对各项指标展开探讨与分析,为中国高端体育智库的评价工作提供科学的、系统的、准确的参考依据和工具选择。

航海类专业学生就业工作的思考

采用文献调研、数据分析等方法,从毕业生人数、就业率和上船就业比例等方面,对2013届-2017届全国航海类专业毕业生就业情况进行梳理,分析航海类专业就业存在的问题及产生的原因,从政府、企业和院校三个层面,提出加强航海类专业学生就业工作的对策。

一种基于SD-ICA的卫星电池健康状态估计方法

针对容量增量分析(ICA)法应用在卫星电池的健康状态(SOH)估计中存在较大误差的问题,提出了基于带平滑处理并使用放电数据的容量增量分析(SD-ICA)的电池健康状态估计方法。首先,利用光滑样条函数的拟合结果具有二阶导连续的特性,对低分辨率的遥测数据进行平滑处理,从而提高了计算结果的准确性。其次,针对ICA必须使用微小电流放电数据的限制,推导出有负载条件下的容量增量(IC)计算方法,降低了对卫星电池放电工况的要求。最后,利用IC曲线的第一特征点(FOI1)与电池容量的关系,对卫星电池的健康状态进行估计。经验证,所提方法具有对数据分辨率要求低、不需要增加电池工况、计算简便等优势,可以准确地从卫星遥测数据中估计电池健康状态。研究成果在卫星电池的健康管理和任务规划中具有重要的应用价值。

马铃薯粉添加量对新疆馕加工品质的影响

探讨马铃薯雪花粉添加量对新疆馕加工品质的影响。小麦粉中添加不同比例(0~50%)的马铃薯粉成混合粉,测定混合粉粉质特性、面团拉伸特性、产气能力及制备马铃薯馕制品挂壁率、质构特性及感官评价值。随着马铃薯粉添加量的增加,混合粉吸水率增高,弱化度增高;马铃薯粉添加量10%以上,会使面团加工性能下降。但随着和面时间增加,面团阻力增大。马铃薯粉添加量35%以上,会导致面团醒发体积迅速减小。马铃薯粉添加量45%以上,马铃薯馕会出现无法挂壁或脱壁滑落现象。马铃薯粉添加量5%以上,馕边硬度显著下降。马铃薯粉添加量15%以上,会降低酥脆口感。但20%以上,馕风味值下降。马铃薯粉的添加对混合粉的粉质、面团拉伸特性、产气能力及馕制品的挂壁率、质构、感官评价值均有不同程度的影响。

铵离子对多杀菌素发酵生产的影响

通过研究铵离子对多杀菌素生产的影响,优化发酵条件,提高多杀菌素产量。结果表明,当培养基中添加0.75 g·L^(-1)的硫酸铵时,多杀菌素产量提高了9.2%。在此基础上,通过Plackett-Burman设计确定了葡萄糖、棉籽蛋白和硫酸铵是对多杀菌素产量影响最大的3个因素。经响应面优化后,多杀菌素产量为80.7 mg·L^(-1),较初始产量提高了13.7%。随后,使用优化培养基进行5 L罐分批和补料分批发酵,多杀菌素产量为90.5 mg·L^(-1)和158.3 mg·L^(-1),较摇瓶发酵分别提升了12.1%和96.2%。

Model-Based Degree Estimation of Unbalance and Misalignment in Flexible Coupling-rotor System

The condition of rotor system must be assessed in order to develop condition-based maintenance for rotating machinery. It is determined by multiple variables such as unbalance degree, misalignment degree, the amount of bending deformation of the shaft, occurrence of shaft crack of rotor system and so on. The estimation of the degrees of unbalance and misalignment in flexible coupling-rotor system is discussed. The model-based approach is employed to solve this problem. The models of the equivalent external loads for unbalance and misalignment are derived and analyzed. Then, the degrees of unbalance and misalignment are estimated by analyzing the components of the equivalent external loads of which the frequencies are equal to the 1 and 2 times running frequency respectively. The equivalent external loads are calculated according to the dynamic equation of the original rotor system and the differences between the dynamical responses in normal case and the vibrations when the degree of unbalance or misalignment or both changes. The denoise method based on bandpass filter is used to decrease the effect of noise on the estimation accuracy. The numerical examples are given to show that the proposed approach can estimate the degrees of unbalance and misalignment of the flexible coupling-rotor system accurately.

Reliability-based Maintenance Optimization under Imperfect Predictive Maintenance

The reliability-based maintenance optimization model has been focused by the engineers and scholars but it has never been solved effectively to formulate the effect of a maintenance action on the optimization model. In existing works, the system reliability was assumed to be increased to 1 after a predictive maintenance. However, it is very difficult in the most practical systems. Therefore, a new reliability-based maintenance optimization model under imperfect predictive maintenance (PM) is proposed in this paper. In the model, the system reliability is only restored to R i (0<R i <1, i∈N, N is natural number set) after the ith PM. The system uptimes and the corresponding probability in two cases whether there is an unexpected fault in one cycle are derived respectively and the system expected uptime model is given. To formulate the system expected downtime, the probability of each imperfect PM number in one cycle is calculated. Then, the system expected total time model is obtained. The total expected long-term operation cost is composed of the expected maintenance cost, the expected loss due to the downtime and the expected additional cost due to the occurrence of an unexpected failure. They are modeled respectively in this work. Jointing the system expected total time and long-term operation cost in one cycle, the expected long-term operation cost per time could be computed. Then, the proposed maintenance optimization model is formulated where the objective function is to minimize the expected long-term operation cost per time. The results of numerical example show that the proposed model could scheme the optimal maintenance actions for the considered system when the required parameters are given and the optimal solution of the proposed model is sensitive to the parameters of effective age model and insensitive to other parameters. The proposed model effectively solves the problem of evaluating the effect of an imperfect PM on the system reliability and presents a more practical optimization method for the reliability-based maintenance strategy than the existing works.

Characterization of the Elastic-plastic Region Based on Magnetic Memory Effect

Detecting stress concentration, especially critical stress state leading to structure damage or failure, is one of the most important tasks of equipment diagnosis. Metal magnetic memory technique needs further research to evaluate stress concentration quantitatively due to ambiguous physical mechanism, though it has potential to detect early defects in ferromagnetic materials. Mild Q235 steel defective specimens in demagnetization state were loaded in tension up to visible necking, with magnetic memory signals measurement made at increasing stress levels. Magnetic signals varied greatly under first several loadings and subsequently tended to stability in the elastic region, which showed that the magnetization always approaches the anhysteretic magnetization curve and was explained by the theory of magnetomechanical effect. In the plastic stage, an abnormal wave occurred in the stress concentration zone and its height value was sensitive to plastic deformation levels and dependent on the distance between the probe and defect, in accordance with the simulation results based on the magnetic dipole model. Different magnetic signal characteristics in the elastic-plastic region indicate that the magnetic memory technique can identify macroyielding and early damage, which is of profound significance for ensuring safe operation of equipment in service.

Effect of pin rotating speed on lap shear strength of stationary shoulder friction stir lap welded 6005A-T6 aluminum alloy

Stationary shoulder friction stir lap welding （SSFSLW） was successfully used to weld 6005A-T6 aluminum alloy in this paper. Effect of pin rotating speed on cross section morphologies and lap shear strength of the SSFSLW joints were mainly discussed. Results show that joints without flash and shoulder marks can be obtained by the stationary shoulder. Cross section of the SSFSLW joint presents a basin-like morphology and little material loss. By increasing the rotating speed from 1 000 rpm to 1 600 rpm, both effective sheet thickness and lap width increase, while lap shear failure load firstly decreases and then increases. The maximum failure load of 14. 05 kN /s attained when 1 000 rpm is used. All SSFSLW joints present shear fracture mode.

110/60-12摩托车轮胎的不同轮廓设计及性能对比

对比两种不同膨胀程度轮廓设计的110/60-12摩托车轮胎的性能。成品轮胎试验结果表明:两种轮廓轮胎的充气外缘尺寸、强度性能、耐久性能和高速性能均达到相应的国家标准要求;低膨胀状态轮廓轮胎的充气外缘尺寸稳定性和耐久性能较充分膨胀轮廓轮胎有较大提升。

Satellite range scheduling with the priority constraint: An improved genetic algorithm using a station ID encoding method

Abstract Satellite range scheduling with the priority constraint is one of the most important prob lems in the field of satellite operation. This paper proposes a station coding based genetic algorithm to solve this problem, which adopts a new chromosome encoding method that arranges tasks according to the ground station ID. The new encoding method contributes to reducing the complex ity in conflict checking and resolving, and helps to improve the ability to find optimal resolutions. Three different selection operators are designed to match the new encoding strategy, namely ran dom selection, greedy selection, and roulette selection. To demonstrate the benefits of the improved genetic algorithm, a basic genetic algorithm is designed in which two cross operators are presented, a singlepoint crossover and a multipoint crossover. For the purpose of algorithm test and analysis, a problemgenerating program is designed, which can simulate problems by modeling features encountered in realworld problems. Based on the problem generator, computational results and analysis are made and illustrated for the scheduling of multiple ground stations.

Rescheduling of observing spacecraft using fuzzy neural network and ant colony algorithm

This paper aims at rescheduling of observing spacecraft imaging plans under uncertainties. Firstly, uncertainties in spacecraft observation scheduling are analyzed. Then, considering the uncertainties with fuzzy features, this paper proposes a fuzzy neural network and a hybrid rescheduling policy to deal with them. It then establishes a mathematical model and manages to solve the rescheduling problem by proposing an ant colony algorithm, which introduces an adaptive control mechanism and takes advantage of the information in an existing schedule. Finally, the above method is applied to solve the rescheduling problem of a certain type of earth-observing satellite. The computation of the example shows that the approach is feasible and effective in dealing with uncertainties in spacecraft observation scheduling. The approach designed here can be useful in solving the problem that the original schedule is contaminated by disturbances.

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities （LMIs）. Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The mance in estimating states and actuator faults. It also successfully. simulation results show satisfactory perfor- shows that multiple faults can be estimated

Fault detection of flywheel system based on clustering and principal component analysis

Considering the nonlinear, multifunctional properties of double-flywheel with closed- loop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the multifunctional flywheels. At the first step of the proposed algorithm, clustering is taken as feature recognition to check the instructions of ＂integrated power and attitude control＂ system, such as attitude control, energy storage or energy discharge. These commands will ask the flywheel system to work in different operation modes. Therefore, the relationship of parameters in different operations can define the cluster structure of training data. Ordering points to identify the clustering structure （OPTICS） can automatically identify these clusters by the reachability-plot. K-means algorithm can divide the training data into the corresponding operations according to the teachability-plot. Finally, the last step of proposed model is used to define the rela- tionship of parameters in each operation through the principal component analysis （PCA） method. Compared with the PCA model, the proposed approach is capable of identifying the new clusters and learning the new behavior of incoming data. The simulation results show that it can effectively detect the faults in the multifunctional flywheels system.

Approach of fault diagnosis based on similarity degree matching distance function

A new diagnosis method based on the similarity degree matching distance function is proposed.This method solves the problem that the traditional fault diagnosis methods based on transition system model cannot deal with the"special state"which cannot match the target states completely.For evaluating the relationship between the observation and the target states,this paper first defines a new distance function based on the viewpoint of energy to measure the distance between two attribute values.After that,all the distances of the attributes in the state vector are used to synthesize the distance between two states.For calculating the similarity degree between two states,a trend evaluation method is developed.It analyzes the main direction of the trend of the state transfer according to the distances between the observation and each target state and their historical records.Applying the diagnosis method to a primary power subsystem of a satellite,the simulation result shows that it is effective.