Intrinsic component filtering for fault diagnosis of rotating machinery

Fault diagnosis of rotating machinery has always drawn wide attention. In this paper, Intrinsic Component Filtering (ICF), which achieves population sparsity and lifetime consistency using two constraints: $l_{1/2}$ norm of column features and $l_{3/2}$ -norm of row features, is proposed for the machinery fault diagnosis. ICF can be used as a feature learning algorithm, and the learned features can be fed into the classification to achieve the automatic fault classification. ICF can also be used as a filter training method to extract and separate weak fault components from the noise signals without any prior experience. Simulated and experimental signals of bearing fault are used to validate the performance of ICF. The results confirm that ICF performs superior in three fault diagnosis fields including intelligent fault diagnosis, weak signature detection and compound fault separation.     

典型阻尼结构正弦振动响应模型修正方法

直接基于正弦响应数据的模型修正研究较少,发展基于正弦振动试验数据的模型修正方法对航天工程实际中有限元建模水平的提高具有重要意义。基于正弦振动响应数据的模型修正关键在于修正后曲线特征频率及其响应幅值的一致性。文章对基础激励下结构响应分析方法进行了推导,在此基础上用两步修正方法实现了分析模型与试验模型特征频率和响应峰值的匹配,最后采用国际通用算例GARTEUR桁架模型对两步修正方法进行了验证。结果表明,经两步修正后分析模型基频与试验模型一致,且前10阶频率误差低于0.15%,典型节点响应峰值误差低于1%。     

时变微弱扩频信号检测

提出了一种解决微弱高动态扩频信号捕获的新方法,利用分数阶域滤波设计了伪码—时频联合匹配滤波的框架,最后进行了相关计算并给出了应用实例。     

基于VS-IMM算法的A-SMGCS场面运动目标跟踪

为实现先进场面运动引导控制系统中场面监视雷达对运动目标的跟踪,研究了将变结构交互式多模型(Variable structure interacting multiple model,VS-IMM)算法应用到该系统中。首先,根据飞机的真实运动情况建立了飞机的匀速运动、匀加速运动和匀速转弯运动模型;然后,针对固定结构交互式多模型(Fixed structureinteractive multiple model,FS-IMM)算法在目标跟踪方面的不足,结合机场地图,将VS-IMM算法应用到机场场面运动目标跟踪中;最后,基于扩展卡尔曼滤波将VS-IMM算法与FS-IMM算法进行仿真比较。结果表明:VS-IMM算法的跟踪精度及模型选择均优于FS-IMM算法,VS-IMM算法在场面跟踪方面具有更大的应用价值。     

空间低温制冷控制器的缓启动电路建模分析

随着大功率空间低温斯特林制冷机的出现,制冷控制器仍采用传统缓启动和LC储能滤波串联抑制电路会产生不平稳/大超调的启动电流,造成制冷机控制器过流保护并对卫星电源及其他设备造成可能的浪涌破坏。在不增加元器件的情况下,提出一种具有启动电流反馈功能的缓启动和LC储能滤波电路配合方式。首先通过采用非线性器件MOSFET的低频微变等效模型对新旧配合电路进行了数学建模。之后针对小电感小电容和大电感大电容两种应用模式下的数学模型进行了简化和分析,在小电感小电容模式下新旧配合电路均可简化为无超调的一阶系统,在大电感大电容模式下传统配合电路为具有振荡特性的二阶系统,而新的配合电路仍为一阶系统,可以满足大电感大电容模式下启动电流无超调要求。最后通过Multisim仿真对比分析和实际试验证明了新的配合电路的合理性和有效性,试验表明启动电流均匀平稳无超调,启动电流峰值抑制约50%。     

基于CPP与S变换的自适应时频滤波及其在滚动轴承故障诊断中的应用

针对变转速下滚动轴承故障调制信息的提取与分离,提出了基于线调频小波路径追踪(CPP)与S变换的自适应时频滤波方法。该方法先采用Hilbert解调对齿轮箱振动信号进行分析获取其包络信号,并对包络信号进行S变换,以获取其时频分布,同时,采用CPP算法从齿轮箱振动信号中估计出啮合频率曲线,进而获取转轴转速;然后,根据估计的转速信号分别设计各阶时频滤波器;再采用时频滤波器对包络信号的时频分布进行时频滤波,并将滤波结果进行S逆变换,以获取各阶故障调制信号;最后对各阶故障调制信号进行阶次谱分析,并根据阶次谱中的调制信息诊断滚动轴承故障。算法仿真和应用实例表明,自适应时频滤波方法可根据轴承故障调制信号的频率变化特点自适应地改变滤波器的中心频率与带宽,能有效提取并分离轴承的各阶调制信息,且分离效果优于基于集合经验模态分解（EEMD）的阶次谱方法。      

Directional Filtering Due to Mesospheric Wind Shear on the Propagation of Acoustic-gravity Waves

Gravity waves with periods close to the Brunt-V?is?l? period of the upper troposphere are often observed at mesopause altitudes as short period, quasi-monochromatic waves. The assumption that these short period waves originate in the troposphere may be problematic because their upward propagation to the mesosphere and lower thermosphere region could be significantly impeded due to an extended region of strong evanescence above the stratopause. To reconcile this apparent paradox, an alternative explanation is proposed in this paper. The inclusion of mean winds and their vertical shears is sufficient to allow certain short period waves to remain internal above the stratopause and to propagate efficiently to higher altitudes. A time-dependent numerical model is used to demonstrate the feasibility of this and to determine the circumstances under which the mesospheric wind shears play a role in the removal and directional filtering of short period gravity waves. Finally this paper concludes that the combination of the height-dependent mean winds and the mean temperature structure probably explains the existence of short period, quasi-monochromatic structures observed in airglow images of mesopause region.      

基于无奇点根数的空间相对导航插值滤波算法

为了提高椭圆轨道航天器的相对导航精度,将基于Stirling公式的多项式插值滤波方法（DDF2）引入导航算法,降低了传统的卡尔曼滤波方法中泰勒级数展开线性化     

复杂背景中红外弱小目标检测技术研究

对复杂背景中红外弱小目标检测识别的一种图像处理技术进行了研究。用最大中值滤波进行预处理以抑制孤立噪声影响,采用时域方差滤波抑制背景信息,对滤波后的图像根据直方图信息进行自适应二值化处理,由多帧轨迹确定目标。用实验与基于形态学算子滤波的目标检测算法进行了比较,结果表明该算法能获得较满意的目标检测结果,两种滤波方法的组合可有效提高信噪比。     

A Tracking Filter in Spherical Coordinates Enhanced by De-noising of Converted Doppler Measurements

Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalman filter (KF) is proposed to reduce the converted Doppler measurement errors before updating the target states for the constant velocity (CV) model. The states from the de-noising filter are then combined with the Cartesian states from the converted measurement Kalman filter (CMKF) to produce final state estimates. The nonlinearity of the de-noising filter states are handled by expanding them around the Cartesian states from the CMKF in a Taylor series up to the second order term. In the mean time, the correlation between the two filters caused by the common range measurements is handled by a minimum mean squared error (MMSE) estimation-based method. These result in a new tracking filter, CMDN-EKF2. Monte Carlo simulations demonstrate that the proposed tracking filter can provide efficient and robust performance with a modest computational cost.