行星齿轮箱耦合调制振动信号分离与故障诊断

针对故障状态下行星齿轮箱振动信号通常表现为稳态调制和冲击调制成分耦合问题,建立不同求解模型,提出耦合调制振动信号分离方法。应用稀疏全变分模型实现冲击调制成分分离,采用改进的非对称惩罚函数,根据峭度系数与方均根系数指标构建正则化参数优选策略,采用受控极小化(majorization-minimization, MM)方法进行模型求解;采用基追踪实现稳态调制成分分离。试验结果分析表明:该方法在噪声D为0.15的信号中能快速分离出微弱冲击调制成分,算法迭代次数少、收敛效果好。      

基于传感器关联网络的燃气轮机异常检测方法

通过分析燃气轮机4种典型异常形式的产生机理以及特征表现,得到了不同异常形式与传感器关联网络结构特征之间的映射关系。在此基础上,得到传感器关联网络的异常特征模式,提出了基于传感器关联网络的燃气轮机异常检测策略。通过实例分析,证明了融合多源信息基础上建立的传感器关联网络模型,可以过滤掉节点间关联指标低于阈值037的相关性,有效的实现燃气轮机的稳态异常检测,并可以检测出转速上升过程中,节点间相关性的正常线性变化趋势,存在大于12%的异常凹陷非线性趋势,从而有效的实现燃气轮机的动态异常检测。      

Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system (IHPS) based on a nonlinear unknown input observer (NUIO) is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS.     

基于自适应分段混合系统的轴承故障诊断

针对强噪声背景下轴承早期故障的诊断问题,提出一种基于自适应分段混合随机共振（adaptive piecewise hybrid stochastic resonance,APHSR）系统的检测方法。采用经验模态分解法（EMD）进行信号预处理,分别采用能量密度法和相关系数法去除高、低频噪声,自动筛选最优固有模态函数,经尺度变换后输入分段混合随机共振系统模型,提取故障信号。工程实验显示:经过APHSR系统,轴承故障特征频率的频谱幅值、频谱幅值与周围最大噪声之差和最大信噪比（SNR）均高于经验模态分解和经典随机共振方法,其中齿轮箱故障轴承信噪比分别提高了9.579 dB和7.473 dB,转子故障轴承信噪比分别提升了8.597 dB和5.695 dB,对凯斯西储大学故障轴承数据处理后的信噪比分别提升了3.369 dB和17.043 dB。数据表明APHSR方法具有高效性,提高了轴承故障信号诊断能力。      

QAR超限事件飞行操作风险诊断方法

利用某机型的快速存取记录器(QAR,Quick Access Record)数据,对飞机着陆阶段出现的某一QAR超限事件,选取飞机下降率、俯仰角等飞行员综合操作指标在无线电高度20 feet(1 feet=0.304 8 m)的数值以及20~0 feet之间的变化率,分析由这些指标构成的"空间"中发生该QAR超限事件的"高风险子空间".对同一机场同一机型的多个航班数据初步分析得到,着陆总重大于62 t、着陆温度小于32℃时,正常样本与QAR超限样本占比接近,表明环境因素并非该样本空间中QAR超限事件的主要因素.为进一步诊断,以超限事件发生率最大化为目标,以划分空间中包含的样本满足一定数量标准为约束,建立数学模型,并以黄金分割法为基础设计了算法,找出这些操作指标上区间的边界值,以此诊断可能触发该QAR超限事件的高风险区域,为飞行员模拟机针对性训练提供指导.      

高性能飞机发展对控制理论的挑战

根据笔者30余年来飞行试验研究的实践,从实际飞行的角度简要综述了影响飞行安全的大迎角过失速机动、超低空重载空投、飞行器突发故障和无人机控制方法研究。描述了操纵稳定性飞行试验获取飞机模型的手段和通常飞行控制器设计对模型的近似,给出了8个飞行鲁棒控制的研究问题;对超低空重载空投控制方法进行了描述,并给出了飞行器出现故障时突变模型和容错控制方法;同时,描述了测量对飞行控制特别是对保障无人机飞行安全的重要性,指出了飞行控制方法研究存在的部分问题,并建议有关高校研究单位从稳定性很好的四旋翼转向固定翼或单旋翼战术无人机等高层次研究。     

基于小波分析的转子不平衡故障诊断与控制技术研究CSCD

在对发动机挠性转子不平衡机理分析的基础上,利用小波分解和重构方法对信号进行提取与识别,实现了对转子不平衡故障的准确诊断,利用振型平衡法对挠性转子进行平衡。实验表明,此方法能够有效解决转子不平衡故障,为飞机发动机等旋转机械转子不平衡的检测和控制提供了一种有效的解决方法。     

Data Fusion of Multiple Curvature Mode Shapes for Structural Damage Diagnosis

This study aims to develop a reliable method for locating multiple cracks in a beam using data fusion of multiple curvature mode shapes.The identification of multiple damage in beams based on curvature mode shape has become a research focus in recent decades.However,the curvature mode shape method using a single mode carries limited damage information,and fails to reveal all cracks when multiple damage detection is required.To address this limitation,the curvature mode shape method is further enhanced by a data fusion algorithm to fuse damage information in multiple modes.The effectiveness of the method is proved through a numerical case of a beam with multiple cracks.The applicability of the method is experimentally validated by detecting multiple cracks in a composite laminated beam with mode shapes acquired by a scanning laser vibrometer.The results show that the method of fusing multiple curvature mode shapes carries more complete damage information than the traditional one using a single mode,and can successfully locate all cracks in a damaged beam.     

An analysis and enhanced proposal of atmospheric boundary layer wind modelling techniques for automation of air traffic management

The air traffic management automation imposes stringent requirements on the weather models, in such a way that they should be able to provide reliable short-time forecasts in digital formats in almost real time. The atmospheric boundary layer is one of the regions where aircraft operation and coordination are critical and therefore atmospheric model performance is also vital. This paper presents conventional and innovative techniques to improve the accuracy in the forecasting of winds in the lower atmospheric layer, proposing mechanisms to develop better models including deterministic and stochastic simulations. Accuracy is improved by optimizing the grid, assimilating observations in cycling simulations and managing a number of ensemble members. An operation-driven post-processing stage helps to incorporate detailed terrain definitions and real-time observations without re-running the model. The improvements are checked against mesoscale weather simulations at different scales and a dedicated flight campaign. The results show good performance of the model without sensitively increasing the required throughput.