DFCluster: An efficient algorithm to mine maximal differential biclusters for single pilot operations task synthesis safety analysis

With the continuous advancement of the avionics system, crew members are correspondingly reduced, and Single Pilot Operations(SPO) has attracted widespread attention from scholars.To meet the flight requirements in SPO mode, it is necessary to further strengthen air-ground coordination system integration, but at the same time, there will be some safety issues caused by resource integration, function fusion, and task synthesis. Aimed at the safety problems caused by task synthesis, an efficient d...     

民用飞机载荷校准试验关键技术浅析

民用飞机载荷校准试验是飞机载荷验证试飞的关键工作之一,飞行载荷验证的有效性很大程度上取决于校准试验的可靠性。为了提高校准试验的质量,对民用飞机校准试验中的关键技术进行研究和总结,阐述民用飞机载荷校准试验中测载站位的选取、应变法测量典型方案、校准载荷的确定、载荷方程的建立、试验报告的编制等内容,提出合理化意见和建议,可为我国民用飞机载荷试飞的开展提供一定的技术指导和帮助。     

High dynamic output feedback robust control of cascaded extended state observer

High dynamic tracking performance is a key technical index of hydraulic flight motion simulator(HFMS). However, the strong nonlinearities, various model uncertainties and measurement noise in hydraulic actuation systems limit the high dynamic performance improvement. In this paper, the outer axis frame of a HFMS is taken as a case study and its nonlinear dynamic model with consideration of strong nonlinearities, matched and mismatched uncertainties is established.A novel cascaded extended state ...     

A geographical and operational deep graph convolutional approach for flight delay prediction

Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning, flight scheduling, airport operation, and passenger service. Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity, which brings critical challenges to accurate flight delay prediction. In recent years, Graph Convolutional Networks (GCNs) have become popular in flight delay prediction due to the advantage in extracting complicated relationships. However, most of the existing GCN-based methods have failed to effectively capture the spatial–temporal information in flight delay prediction. In this paper, a Geographical and Operational Graph Convolutional Network (GOGCN) is proposed for multi-airport flight delay prediction. The GOGCN is a GCN-based spatial–temporal model that improves node feature representation ability with geographical and operational spatial–temporal interactions in a graph. Specifically, an operational aggregator is designed to extract global operational information based on the graph structure, while a geographical aggregator is developed to capture the similar nature among spatially close airports. Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.     

民用飞机飞行机组非正常操作程序编制研究

非正常操作程序是指在飞机或系统功能非正常情况下,飞行机组安全操作飞机的重要依据,是保证飞行安全最重要的因素之一.非正常操作程序的编制耗时长且涉及多个技术领域,是一项复杂的系统工程.通过研究国外相关资料,结合成熟机型程序的编制经验,提出非正常操作程序编制流程.首先,系统地介绍非正常操作程序的组成和功能、程序项目的确定方法以及程序格式;然后,定义非正常操作程序编制过程的四个阶段、各阶段的工作内容以及人员资质;最后,结合国产新支线客机实例证明所提非正常操作程序编制流程的有效性.本文提出的非正常操作程序编制流程对民用飞机主制造商非正常操作程序的编制具有指导意义.