Prediction of nonlinear pilot-induced oscillation using an intelligent human pilot model

This paper proposes a method to predict nonlinear Pilot-Induced Oscillation (PIO) using an intelligent human pilot model. This method is based on a scalogram-based PIO metric, which uses wavelet transforms to analyze the nonlinear characteristics of a time-varying system. The intelligent human pilot model includes three modules: perception module, decision and adaptive module, and execution module. Intelligent and adaptive features, including a neural network receptor, fuzzy decision and adaptation, are also introduced into the human pilot model to describe the behavior of the human pilot accommodating the nonlinear events. Furthermore, an algorithm is proposed to describe the procedure of the PIO prediction method with nonlinear evaluation cases. The prediction results obtained by numerical simulation are compared with the assessments of flight test data to validate the utility of the method. The flight test data were generated in the evaluation of the Smart-Cue/Smart-Gain, which is capable of reducing the PIO tendencies considerably. The results show that the method can be applied to predict the nonlinear PIO events by human pilot model simulation.     

飞机修理厂人力资源管理与中长期规划匹配探析

人力资源是企业发展动力的源泉,是可持续发展的根本保障。本文根据中国通用航空发展的态势和飞机修理厂的现状与发展目标,对飞机修理厂提出了规划要求和适应发展需要的应对措施。     

面向市场服务"三农"打造高职教育特色--杨凌职业技术学院农科教结合的实践与探索

杨凌职业技术学院与彬县小章镇经过十多年的农科教结合实践，探索出了一条符合西部地区农业技术推广应用及农民教育培训的新方法和新途径，加快了农业科技成果的转化和普及，提高了农民科技文化素质，增加了农民收入，极大地推动了农业科技进步和农村经济发展，实现了学院超常规、跨越式发展。     

企业人力资源管理新趋势-人事外包

人事外包是人力资源管理的一种新形式 ,企业将事务性传统人力资源管理活动外包出去 ,有利于企业人力资源部专注于战略性人力资源管理。本文阐述了人事外包的内容 ,分析了人事外包给企业创造的管理优势 ,指出企业人事外包必须要有明确的目的 ,并结合企业的实际需要进行     

民用飞机设计驾驶舱操纵设备的评估

人机工效影响着飞行员操纵飞机的感受,因此在民用飞机设计过程中,对人机工效进行及早考虑是非常重要的。在民用飞机设计的各个阶段,都需要适时邀请具有一定资质的飞行员对驾驶舱的人机工效进行评估。对民用飞机设计中飞控驾驶舱飞行员评估方法进行介绍,对评估的要点进行总结分析,供相关工程设计人员参考。     

Human factors quantification via boundary identification of flight performance margin

A systematic methodology including a computational pilot model and a pattern recognition method is presented to identify the boundary of the flight performance margin for quantifying the human factors. The pilot model is proposed to correlate a set of quantitative human factors which represent the attributes and characteristics of a group of pilots. Three information processing components which are influenced by human factors are modeled： information perception, decision making, and action execution. By treating the human factors as stochastic variables that follow appropriate probability density functions, the effects of human factors on flight performance can be investigated through Monte Carlo（MC） simulation. Kernel density estimation algorithm is selected to find and rank the influential human factors. Subsequently, human factors are quantified through identifying the boundary of the flight performance margin by the k-nearest neighbor（k-NN） classifier. Simulation-based analysis shows that flight performance can be dramatically improved with the quantitative human factors.     

基于VC++/GL Studio的通用飞行组合虚拟仪表设计及实现

为了满足某无人机半实物仿真系统视景显示需要,针对视景界面复杂、显示数据种类多、实时性和流畅性要求高的特点,设计了基于GL Studio的组合虚拟仪表界面。详细介绍了组合虚拟仪表设计和实现过程,并通过VC++平台实现了网络通信和数据驱动仪表显示功能。仿真系统实际应用表明：该飞行组合仪表工作性能可靠,人机界面友好,具有良好的可重构性,满足不同无人机飞行仿真系统和飞行训练系统使用需求。     

Past, present and future implications of human supervisory control in space missions

Achieving the United States’ Vision for future Space Exploration will necessitate far greater collaboration between humans and automated technology than previous space initiatives. However, the development of methodologies to optimize this collaboration currently lags behind development of the technologies themselves, thus potentially decreasing mission safety, efficiency and probability of success. This paper discusses the human supervisory control (HSC) implications for use in space, and outlines several areas of current automated space technology in which the function allocation between humans and machines/automation is sub-optimal or under dispute, including automated spacecraft landings, Mission Control, and wearable extra-vehicular activity computers. Based on these case studies, we show that a more robust HSC research program will be crucial to achieving the Vision for Space Exploration, especially given the limited resources under which it must be accomplished.     

Optimal motion cueing algorithm for accelerating phase of manned spacecraft in human centrifuge

This paper presents a novel optimal Motion Cueing Algorithm (MCA) to control the rotations of a Human Centrifuge (HC) and achieve the best simulation of a SpaceCraft (SC) motion. Relations of the specific forces sensed by astronauts of the SC and the HC have been derived and linearized. A Linear Quadratic Regulator (LQR) controller is implemented for the problem which tends to minimize the error between the two sensed specific forces as well as control input in a cost function. It results in control inputs of the HC to generate its sensed specific force as close as possible to the one in the SC. The algorithm is implemented for both linearized and nonlinear portions of a US space shuttle mission trajectory as a verification using MATLAB. In longitudinal direction, the proposed MCA, works well when the acceleration is less than 2g in which the tracking error does not exceed 12%. In lateral direction the tracking is much better even in nonlinear region since the error remains less than 7% for tilting up to 50°. Finally, the effect of weight matrixes in the LQR cost function on overall weight and power of the HC motion system is discussed.     

An integrated graphic–taxonomic–associative approach to analyze human factors in aviation accidents

Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inadequate human–aircraft–environment interactions and organizational deficiencies effectively, and highly depend on analysts' skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphic–taxonomic–associative approach. A new graphic model named accident tree(AcciTree), with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system(HFACS) to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to factors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.