基于QAR数据的民航客机对称发动机差异监控模型和算法

从某型民航客机发动机机队管理的实际出发,利用HOLT双参数指数平滑方法,建立基于机载QAR数据的对称发动机性能参数的差异监控模型,并给出实现对称发动机差异监控的算法。算例分析表明模型和算法能有效地识别发动机运行状态,并能预测发动机故障征兆,使发动机排故端口提前,且方法简单易于实现。     

Workforce-constrained maintenance scheduling for military aircraft fleet: a case study

The problem is related to a fleet of military aircraft with a certain flying program in which the availability of the aircraft sufficient to meet the flying program is a challenging issue. During the pre- or after-flight inspections, some component failures of the aircraft may be found. In such cases, the aircraft are sent to the repair shop to be scheduled for maintenance jobs, consisting of failure repairs or preventive maintenance tasks. The objective is to schedule the jobs in such a way that sufficient number of aircrafts is available for the next flight programs. The main resource, as well as the main constraint, in the shop is skilled-workforce. The problem is formulated as a mixed-integer mathematical programming model in which the network flow structure is used to simulate the flow of aircraft between missions, hanger and repair shop. The proposed model is solved using the classical Branch-and-Bound method and its performance is verified and analyzed in terms of a number of test problems adopted from the real data. The results empirically supported practical utility of the proposed model.     

A new nonlinear blind source separation method with chaos indicators for decoupling diagnosis of hybrid failures: A marine propulsion gearbox case with a large speed variation

The normal operation of propulsion gearboxes ensures the ship safety. Chaos indicators could efficiently indicate the state change of the gearboxes. However, accurate detection of gearbox hybrid faults using Chaos indicators is a challenging task and the detection under speed variation conditions is attracting considerable attentions. Literature review suggests that the gearbox vibration is a kind of nonlinear mixture of variant vibration sources and the blind source separation (BSS) is reported to be a promising technique for fault vibration analysis, but very limited work has addressed the nonlinear BSS approach for hybrid faults decoupling diagnosis. Aiming to enhance the fault detection performance of Chaos indicators, this work presents a new nonlinear BSS algorithm for gearbox hybrid faults detection under a speed variation condition. This new method appropriately introduces the kernel spectral regression (KSR) framework into the morphological component analysis (MCA). The original vibration data are projected into the reproducing kernel Hilbert space (RKHS) where the instinct nonlinear structure in the original data can be linearized by KSR. Thus the MCA is able to deal with nonlinear BSS in the KSR space. Reliable hybrid faults decoupling is then achieved by this new nonlinear MCA (NMCA). Subsequently, by calculating the Chaos indicators of the decoupled fault components and comparing them with benchmarks, the hybrid faults can be precisely identified. Two specially designed case studies were implemented to evaluate the proposed NMCA-Chaos method on hybrid gear faults decoupling diagnosis. The performance of the NMCA-Chaos was compared with state of art techniques. The analysis results show high performance of the proposed method on hybrid faults detection in a marine propulsion gearbox with large speed variations.     

Fault tolerant routing algorithm based on the artificial potential field model in Network-on-Chip

Recent advances in semiconductor technology enable the VLSI chips to integrate hundreds of intellectual properties with complex functionality. However, as the chip scales, the probability of faults is increasing, making fault tolerance a key concern in designing the large scale chips. The fault tolerant routing algorithms can guarantee sustained communication even the faults exist. It is an efficient technique to achieve fault tolerance in Networks-on-Chip. In this paper, we propose a new model based on the theory of artificial potential field (APF) to design various fault tolerant routing algorithms. In our model, the faults are considered as the poles of the repulsive potential fields while the destinations as the poles of the attractive potential fields. Messages are attracted to destinations and repelled by faults in the combined artificial potential field. The parameters used in the proposed APF based model are optimized through theoretical analysis and simulation experiments. They can support flexible fault tolerant routing algorithms. Finally, we evaluate the performance of the proposed fault tolerant routing algorithm based on the APF model in 2D-mesh NoCs with random faults. The simulation results show that the proposed APF based model is feasible and the routing algorithm can maintain good network performance.     

灰色系统理论在飞机操纵钢索磨损预测中的应用

钢索是软式飞行操纵系统的核心组成部件,其工作性能将直接影响飞机的飞行安全.因操纵钢索磨损问题具有典型的贫信息、小样本特点,采用灰色系统理论,建立钢索磨损量灰色预测模型,研究钢索随飞行小时数的磨损量灰色预测方法.实例分析和实际预测验证表明,灰色系统理论用于钢索磨损量预测是可行有效的.研究也有助于飞机维修从定检修理向视情维修转变.     

An exact multi-objective mixed integer nonlinear optimization approach for aircraft conflict resolution

An exact mixed integer nonlinear optimization (MINO) model is presented for tackling the aircraft conflict detection and resolution problem in air traffic management. Given a set of flights and their configurations, the aim of the problem was to provide new configurations such that all conflict situations are avoided, with conflict situation understood to mean an event in which two or more aircraft violate the minimum safety distances that must be maintained in flight. The proposed model solves the problem using both horizontal (velocity and angle turn change) and vertical (altitude level change) maneuvers. As a special case, another model is presented in which only horizontal maneuvers are used. The models proposed are based on a geometric construction which involves trigonometric functions, so the constraint system is included via a large set of trigonometric and nonconvex inequalities. A multicriteria approach is presented to provide useful information to air traffic control officers about the maneuvers to be performed. The main results of an extensive computational experiment are reported in which the performance of the state-of-the-art nonconvex MINO solver Minotaur is studied.     

Modeling safety culture as a socially emergent phenomenon: a case study in aircraft maintenance

Safety culture is often understood as encompassing organizational members’ shared attitudes, beliefs, perceptions and values associated with safety. Safety culture theory development is fraught with inconsistencies and superficiality of measurement methods, because the dynamic and political nature of culture is often ignored. Traditionally, safety culture is analyzed by survey-based approaches. In this paper we propose a novel, systemic, interdisciplinary approach for investigating safety culture that combines multi-agent system modeling with organizational ethnography. By using this approach, mechanisms of emergence of safety culture from daily practices, operations and interactions of organizational actors can be modeled and analyzed. The approach is illustrated by a case study from the aircraft maintenance domain, based on existing ethnographic data. Using the proposed approach we were able to reproduce and explain emergent characteristic patterns of commitment to safety in the maintenance organization from this study. The model can be used for theory development and as a management tool to evaluate non-linear impacts of organizational arrangements on workers’ commitment to safety.     

A theoretical model of honeycomb material arresting system for aircrafts

Takeoff and landing overruns account for most of the accidents that occur on or in the immediate vicinity of the runway, and it would cause accidental aircraft damage and loss of life. The current Engineered Material Arresting System (EMAS) materials are weak in water resistance and durability, expensive in acquiring and installing, and have negative environmental impacts. So it is significantly required to find a new alternative material with good mechanical properties, higher arresting coefficient and excellent environmental performance. In this article, the arresting properties of metal honeycomb material are studied. A Tire-Honeycomb material Interaction Mechanical Model (THIMM) is proposed. Combining with the dynamic model of aircraft, the theoretical model is coded by MATLAB to finish arresting simulation on aircraft B737-900ER and B727-100. In addition, finite element model of the tire-honeycomb material interaction was built to verify the correctness of the theoretical model. The results obtained by finite element simulation are in a good agreement with the theoretical results. In comparison with the results for traditional materials, the calculated results show that the honeycomb material can stop the overrunning aircraft more efficiently in the condition that the forces induced by the stopping process are safe for the passengers and aircraft.     

Memory-based adaptive event-triggered asynchronous tracking control for semi-Markov jump systems with hybrid actuator faults

In this paper, the extended dissipative asynchronous tracking control problem is studied for semi-Markov jump systems with hybrid actuator faults via a memory-based adaptive event-triggered mechanism. Firstly, since the system mode and controller mode do not match exactly, an asynchronous tracking control based on hidden Markov model is designed. Secondly, compared with existing memory-based and memoryless event-triggered mechanisms, the memory-based adaptive event-triggered mechanism proposed in this paper can achieve better performance according to the historical data released and the adaptive event triggering threshold. Next, considering the unsafe operating environment of the device, an asynchronous hybrid actuator failure model is constructed. Furthermore, by designing appropriate Lyapunov–Krasovskii functional, the stochastic stability and extended dissipative performance of the closed-loop system can be guaranteed. Finally, the effectiveness of the proposed method is proved by simulation examples.     

A heuristic approach based on shortest path problems for integrated flight,aircraft, and passenger rescheduling under disruptions

In this paper, we present a heuristic method to solve an airline disruption management problem arising from the ROADEF 2009 challenge. Disruptions perturb an initial flight plan such that some passengers cannot start or conclude their planned trip. The developed algorithm considers passengers and aircraft with the same priority by reassigning passengers and by creating a limited number of flights. The aim is to minimize the cost induced for the airline by the recovery from the disruptions. The algorithm is tested on real-life-based data, as well as on large-scale instances and ranks among the best methods proposed to the challenge in terms of quality, while being efficient in terms of computation time.     

大型客机协同研制工艺技术风险的正态云模型评估

研究不确定情景下大型客机协同研制正态云模型风险评估方法及应用问题。建立了正态云模型的偏差熵测度,提出了面向云模型偏差熵的指标权重确定模型,构建了面向多数据类型的正态云模型风险评估方法。建立了涵盖工艺标准、工艺方案等五个指标的大型客机协同研制供应商工艺技术风险评估指标体系,并基于正态云模型评估方法进行了实际应用。     

人因飞行事故诱发因素的分析与Bootstrap预测仿真

提出一套系统的人因飞行事故诱发因素的分析和Bootstrap预测仿真的方法。首先,在"瑞士奶酪"模型基础上构建空军某机种的人因飞行事故诱因分析分类体系;然后,在此基础上采用数据挖掘技术辨识重要的单诱因、两两诱因组合及诱发模式;最后,使用Bootstrap分析方法对辨识出的单诱因、两两诱因组合及诱发模式执行预测仿真,并据此制订出针对性强、易于操作的预防策略。研究成果可为指导和加强安全管理,保证飞行安全提供决策参考依据。     

Robust Estimation in Partial Linear Mixed Model for Longitudinal Data

In this article, robust generalized estimating equation for the analysis of partial linear mixed model for longitudinal data is used. The authors approximate the nonparametric function by a regression spline. Under some regular conditions, the asymptotic properties of the estimators are obtained. To avoid the computation of high-dimensional integral, a robust Monte Carlo Newton-Raphson algorithm is used. Some simulations are carried out to study the performance of the proposed robust estimators. In addition, the authors also study the robustness and the efficiency of the proposed estimators by simulation. Finally, two real longitudinal data sets are analyzed.     

Hybrid modeling based double-granularity fault detection and diagnosis for quadrotor helicopter

Fault detection and diagnosis (FDD) is an effective technology to assure the safety and reliability of quadrotor helicopters. However, there are still some unsolved problems in the existing FDD methods, such as the trade-offs between the accuracy and complexity of system models used for FDD, and the rarely explored structure faults in quadrotor helicopters. In this paper, a double-granularity FDD method is proposed based on the hybrid modeling of a quadrotor helicopter which has been developed in authors’ previous work. The hybrid model consists of a prior model and a set of non-parametric models. The coarse-granularity-level FDD is built on the prior model which can isolate the faulty channel(s); while the fine-granularity-level FDD is built on the nonparametric models which can isolate the faulty components in the faulty channel. In both coarse and fine granularity FDD procedures, principal component analysis (PCA) is adopted for online fault detection. Using such a double-granularity scheme, the proposed FDD method has inherent ability in detecting and diagnosing structure faults or failures in quadrotor helicopters. Experimental results conducted on a 3-DOF hover platform can demonstrate the feasibility and effectiveness of the proposed hybrid modeling technique and the hybrid model based FDD method.     

推出冲突避免的机场停机位分配问题

为了科学合理地利用机场停机位资源,克服现有模型对飞机进出机位安全性的考虑不足,研究兼顾运行安全和运行效率的机场停机位分配问题.首先分析了飞机在停机坪中的运行过程,提出以主动避免方式来解除飞机进出机位过程中的冲突,从而将具有潜在冲突的飞机对的机位分配作为约束条件,建立了一类推出冲突避免的停机位分配模型.然后对目标函数和约束条件进行分析和简化,将模型转化为线性模型来求解.算例仿真结果验证了该模型的有效性,表明所提出的主动避免冲突方法是能兼顾运行安全和效率的一种有效方法.     

基于时序矩阵分解的缺失销售数据估计

企业的历史销售记录是供应链优化研究的基础数据来源,然而,在日常的研究中,几乎所有可以通过公开途径获得的销售记录都是高度不完整的,这为研究者开展工作带来了极大的不便。为解决此问题,本文提出,以销售数据集中已有的数据为基础,使用面向时序数据的矩阵分解模型MAFTIS对其缺失的部分进行估算,从而把残缺的数据集补全完整。进一步地,为提高MAFTIS的计算效率,本文还为该模型设计了一种基于交替最小二乘法的求解策略MAFTIS^ALS。在评估实验中,MAFTIS^ALS被用于三个真实销售数据集的缺失记录估计,结果显示,与其它估计模型相比,MAFTIS^ALS能获得更准确的估计结果,并且具有更高的收敛速度。     

基于层次分析和二元语义的飞机结构安全评价研究

针对当前飞机结构的设计要求,建立了飞机结构安全的评价模型指标集,利用AHP方法提炼出4大类,14项具体指标,并确定指标权重,采用二元语义及其算子将评价语言值进行集结,对飞机结构安全进行评价.给出了评价步骤,并用实例说明该方法具有一定的可操作性,且合理可信.     

基于Markov的模块化电传操纵系统软件可靠性模型

电传操纵系统是影响飞行安全的关键系统,建立有效的电传操纵系统软件可靠性模型是软件可靠性测试和验证的基础.针对某型飞机系统安全性设计中横向通道电传操纵系统软件可靠性建模问题,建立了模块化的基于Markov的电传操纵系统软件可靠性模型.提出了综合考虑重要度和复杂度的软件可靠性指标分配方法,将可靠性目标分配到子模块.最后,通过实例验证了所建立的模型和指标分配方法的有效性.     

A new compound faults detection method for rolling bearings based on empirical wavelet transform and chaotic oscillator

The rolling bearings often suffer from compound faults in practice. The concurrence of different faults increases the fault detection difficulty and the decoupling detection of compound faults is attracting considerable attentions. Recent publications report the application of the multiwavelets and empirical mode decomposition (EMD) for compound faults decoupling. However, due to limited adaptability they would induce mode mixing or/and overestimation problems in the signal processing. Particularly, the mode mixing would greatly degrade their performance on compound faults detection. To address this issue, this work presents a new method based on the empirical wavelet transform-duffing oscillator (EWTDO) for compound faults decoupling diagnosis of rolling bearings. The empirical wavelet transform (EWT) is able to extract intrinsic modes of a signal by fully adaptive wavelet basis. Hence, the mode mixing and overestimation can be resolved in decoupling processing and the compound faults can be correctly decomposed into different single faults in the form of empirical modes. Then, each single fault frequency was incorporated into a duffing oscillator to establish its corresponding fault isolator. By directly observing the chaotic motion from the Poincar mapping of the isolator outputs the single faults were identified one by one from the empirical modes. Experimental tests were carried out on a rolling bearing fault tester to examine the efficacy of the proposed EWTDO method on compound faults detection. The analysis results show attractive performance with respect to existing decoupling approaches based on the multiwavelets and EMD. In particular, our proposed method is much more reliable in decoupling the compound faults. Hence, the proposed method has practical importance in compound faults decoupling diagnosis for rolling bears.     

A new fuzzy comprehensive evaluation model based on the support vector machine

In this paper, focused on a proper weight distribution vector of a fuzzy comprehensive evaluation method, a new fuzzy comprehensive evaluation model based on the supper vector machine (SVM) is proposed for overcoming the subjective limitation in traditional fuzzy comprehensive evaluation model. Furthermore, a multilevel fuzzy comprehensive evaluation model based on SVM of network learning has also been designed, and the improved algorithm is used to make an instant computation. This method gives good performance on determination of the weight distribution vector and improves the evaluation accuracy and generalization with an example.