翼型尾缘噪声源空间分布与辐射特性关系

详细研究了翼型湍流边界层尾缘宽频噪声源空间分布与辐射特性的关系.采用基于雷诺平均流场的翼型尾缘宽频预测方法研究了NACA0012翼型湍流边界层尾缘宽频噪声在4种不同工况下的噪声源空间分布与辐射特性.首先计算了NACA0012翼型湍流边界层尾缘噪声源在不同频率下的空间分布.计算结果发现:边界层中湍流是翼型湍流边界层尾缘噪声声源.随着频率的增加,噪声源强度和噪声源空间尺寸都是先增加后减小,噪声源位置不断靠近翼型尾缘.同时也计算了边界层内不同位置处的噪声源对远场噪声的辐射特性,结果表明:边界层内层区域,其噪声频谱能量集中在高频;边界层外部区域,其噪声能量集中在中低频;攻角增大或者来流速度减小,噪声能量向低频转移.      

低频信号的混沌高斯化检测方法

大气天电噪声是干扰低频信号的主要噪声源。文章主要针对大气噪声的高斯化方法进行研究,提出了基于混沌方程快速求解、混沌相变判别等技术的噪声高斯化方法,以非线性信号处理技术为依据,通过实验室模拟信道环境,完成低频弱信号的混沌高斯化及检测,2PSK弱信号检测的理论实验验证了其有效性,可为低频接收技术的发展提供依据。     

载人航天器设备隔舱噪声预测与控制方法研究

针对某载人航天器设备隔舱安装了多个高声级辐射噪声源设备,可能导致密封舱内噪声过大的问题。综合采用有限元法与统计能量分析法进行舱内噪声分析,并依据分析结果进行噪声控制。仿真结果表明密封舱噪声超过73 dBA,舱内声环境恶劣。采用吸声泡沫对设备隔舱内表面进行吸声处理,降低噪声高频能量;对设备隔舱仪器板用埋梁方式改变其低频模态特性,以降低设备低频噪声的透射。仿真结果表明,采取两项噪声控制措施可使噪声总声级降至60 dBA以下。     

民用客机缝翼气动噪声数值模拟研究

气动噪声水平是衡量民用客机设计水平的重要指标之一。在飞机着陆过程中,增升装置缝翼是机体气动噪声的重要噪声源。通过求解非线性扰动方程对增升装置缝翼噪声进行了二维数值模拟研究。分别针对不同来流攻角以及主翼钝后缘和尖后缘研究了缝翼噪音的频率特性。计算结果表明,缝翼缝道内的非定常涡是产生噪声的主要原因,随着来流攻角的减小,缝道内的非定常涡强度增大,活动区域变宽,进而辐射更多的噪声,从非定常声场及噪声的频率特性来看,缝翼噪声是一种偶极子声源,具有明显的宽频特性,主要噪声源集中在低频到中频段,随着频率增大,噪声幅值逐渐衰减。数值模拟较好地捕捉到了缝翼噪声源的发声机制和频率特性,为噪声控制打下了良好的基础。     

基于改进的传声器阵列数据分析技术的飞机机体噪声实验研究

 发展了一种平面传声器阵列数据处理新方法——洁净信号处理算法,通过对传声器阵列混淆和旁瓣信号的有效抑制,改进了对声源的分辨。基于改进的数据分析方法,研究了真实飞机结构和真实飞行条件下飞机起落架、襟翼等声源的频谱特性、指向特性。研究结果表明,新的信号处理算法可以更加清晰地分离出飞机表面的气动噪声源。起落架噪声的频谱是由宽频随机噪声与一些较为明显的单音噪声源组成,在不同辐射角度时,起落架噪声的声级在不同频率范围有一定的差异。襟翼侧缘噪声频谱是一个包含有个别明显单音噪声的宽频噪声谱,襟翼内侧缘噪声谱和外侧缘噪声谱有明显的差异,在低频范围,襟翼侧缘噪声的指向性比较明显,但在高频范围,襟翼侧缘噪声没有明显的指向性。     

轴流风扇自噪声强度特性的数值研究

利用流场/声场混合模型计算分析轴流风扇自噪声的强度特性。使用大涡模拟(LES)数值计算方法获取湍流流场信息,以此为输入,使用声类比方法噪声预测模型获得了不同来流条件下的自噪声频谱。0°攻角条件下,叶片噪声源主要位于叶片尾缘区域,并且叶背上的噪声强度大于叶盆;攻角增大和速度增大都会引起叶片自噪声强度的增大;攻角增大引起的噪声增大主要集中在低频区域。     

空间站舱段精细化声振耦合建模与仿真

在空间站长期飞行中,持续、过度的噪声环境会危害航天员的身心健康,并影响工作效率。空间站设备功率大、噪声源数目多、噪声指标严苛,给噪声控制和设计带来很大的挑战。为确保舱段噪声指标满足要求,基于声学有限元方法,根据已掌握的噪声源频谱特性、舱段构型布局、设备安装方式等建立整舱复杂声振耦合精细化噪声仿真模型。对环控、热控及推进分系统等多种噪声源单独工作或同时工作时密封舱内的噪声进行仿真,得到舱内低频噪声水平特性分布。结果表明:声振耦合下舱内的总体噪声水平远高于不考虑声振耦合的情况,并导致三个航天员睡眠区头部的声压级分布差异较大。此外,睡眠区粘贴吸声材料后,对高频段的吸声降噪效果明显,对中频段有一定的降噪效果,但对低频段几乎不起作用。     

基于传声器阵列的航空发动机噪声源识别研究

为了实现新一代发动机的噪声源识别技术,对于测试所得到的民用飞机发动机的整体噪声数据,通过部件噪声分解方法,将其分解到各个部件,并且认识当代民用飞机发动机噪声源的基本特征.开发出利用发动机整机噪声数据的噪声源识别系统,采用反卷积法将波束成型法的结果作为中间声源,从中获取所需要的声源信息,使得最终的结果更加准确.通过获取的发动机整机噪声数据,验证传声器阵列技术的可行性,并且证明了系统的可行性和有效性.     

大型客机起飞着陆过程噪声辐射特性对比分析

 基于准稳态假设和分布点声源模型,并采用最新发展的噪声源半经验参数预测公式,发展和完善了用于飞机飞行过程中噪声辐射预测的计算模型和方法。该计算方法能够预测飞机起飞、着陆过程中的适航噪声,并能够对飞机不同噪声源的噪声辐射特性（声级、频谱特性和指向性等）进行计算分析。以某大型客机为对象,对飞机进场着陆过程和起飞过程中飞机噪声源进行了计算分析,计算结果表明,飞机进场着陆和起飞过程中,不同噪声源对远场噪声级的影响有明显的差异,起飞过程中发动机风扇噪声源是最主要的噪声辐射源,而在进场着陆过程中飞机机体噪声（包括起落架和襟翼等）是重要的飞机噪声源。文中也给出了不同噪声源频谱特性和指向特性等。     

基于dSPACE的永磁同步电机低振动噪声控制策略

为降低变频器供电引起的永磁同步电机(PMSM)电磁振动噪声,首先理论分析了变频器引入的PMSM振动噪声源,然后利用MATLAB/Simulink建立仿真模型,通过dSPACE进行编译并控制一台PMSM,比较了随机开关频率调制技术和死区补偿技术降低振动噪声的优缺点,提出一种混合随机开关频率死区补偿技术。试验结果表明,此方法综合随机开关频率调制技术和死区补偿技术的优点,能降低逆变器引入电流谐波引起的中低频振动噪声和逆变器开关频率与电流谐波相互作用引起的高频振动噪声。     

飞行器气动力参数辨识的一种实用滤波误差方法

提出了一种观测噪声相对于过程噪声较小情况下气动参数识别的实用滤波误差方法，方法不要求已知系统过程噪声和观测噪声方差阵，计算量小，具有一定的应用价值。     

Covariance Matrix for ?-?-? Filtering

Closed-form expressions are derived for the output noise response of an ?-?-? filter in steady-state operation with constant measurement noise statistics. To the author's knowledge such expressions have been unavailable until now. These formulas are useful for target tracking applications.     

基于系统级测量参量的红外成像仿真方法

针对新型红外成像系统的成像特性,通过对光电场景图像与系统输出图像特性的客观比较,推导了场景图像灰度到光电成像系统输出图像的灰度转换模型;首次提出了基于系统级的测量参数:SiTF、MTF、NETD、噪声等效背景照度的光电输出成像的仿真方法,并给出了仿真结果.最后现场试验验证了其合理性.     

On the Mean Frequency Measurement System Using Correlation Detection

This paper is concerned with the problem of measuring the mean frequency of the power spectrum of a zero-mean, stationary, narrowband Gaussian random signal in the presence of additive Gaussian noise. Signal-to-noise ratios at the output of the mean frequency measurement system using correlation detection are analyzed in terms of input signal-to-noise ratio, input signal and noise bandwidths, and integration time. The results obtained are verified experimentally, and a comparison with a conventional zero-crossing detector is also made.     

一种特殊白化滤波器的广义最小二乘法

 本文提出一种采用特殊白化滤波器的广义最小二乘法,简记为GLS（SF）。这种算法中不需要单独估计白化滤波器的阶次及参数,只需迭代估计模型参数,算法简单,准确度和收敛性也较好。对于输入噪声较小、输出端测量噪声近似白噪声的系统来说,文中证明,用此算法所得模型输出与系统输出观测值之误差平方和最小。文中给出几个实际动态校准中建立动态数学模型的例子。     

A multiscale transform denoising method of the bionic polarized light compass for improving the unmanned aerial vehicle navigation accuracy

In recent years, the bionic polarized light compass has been widely studied for the unmanned aerial vehicle navigation. However, it is found from the obtained investigation results that a polarized light compass with a sensitive and high dynamic range polarimeter still provides inferior output precision of the heading angle due to the presence of the noise generating from the compass.The noise is existed not only in the angle of the polarization image acquired by polarimeters but also in the out...     

双轴连续旋转调制捷联惯导系统大失准角初始对准技术

由于可以补偿惯性器件在三个轴向上的输出误差,双轴旋转调制技术被广泛应用于捷联惯导系统(SINS)。选择了一种合理且实用的十六次序双轴转位方案,并对其调制原理和误差进行了分析。初始对准技术是捷联惯导系统的一项重要技术,其对准精度直接决定了后续导航的精度。在粗对准完成后,当姿态误差角较大时,后续的精对准误差模型呈非线性特性,故选择了滤波精度高、稳定性强的平方根容积Kalman滤波算法(SCKF)来解决这一问题。考虑到在实际对准过程中,量测噪声的统计特性易发生变化,将SCKF算法与Sage-Husa算法相结合,在传统Sage-Husa SCKF算法的基础上提出了一种改进的自适应滤波算法(ASCKF)。该算法采用QR分解来完成对噪声协方差的平方根矩阵估计,从而避免了传统Sage-Husa SCKF算法中所估噪声协方差矩阵不正定的问题。最后,通过仿真证实了ASCKF算法可被很好地应用于量测噪声统计特性发生变化的初始对准中。     

A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence

It is common for aircraft to encounter atmospheric turbulence in flight tests. Turbulence is usually modeled as stochastic process noise in the flight dynamics equations. In this paper, parameter estimation of nonlinear dynamic system with both process and measurement noise was studied, and a practical filter error method was proposed. The linearized Kalman filter of first-order approximation was used for state estimation, in which the filter gain, along with the system parameters and the initial states, constituted the parameter vector to be estimated. The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method, and the sensitivities of observations to unknown parameters were calculated by finite difference approximation. Some practical aspects of the method application were discussed. The proposed filter error method was validated by the flight simulation data of a research aircraft. Then, the method was applied to the flight tests of a subscale aircraft, and the aerodynamic stability and control derivatives were estimated. All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach. It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.     

Calculation of Output Noise Variances for Discrete Time-Invariant Filters

Certain calculations to minimize output noise variance are introduced. Many applied problems in sampled data systems require that data be smoothed in the presence of noise for the prediction of future positions, velocities, or accelerations. Smoothing coefficients in discrete time-invariant filters are computed to minimize the output noise variance, but under the constraints that the function and derivatives be predicted ahead. The output noise variance is seen to be a function of the input noise, the number of input signals (N+1) that the filter has to smooth, and the prediction time ?T. Four examples are given in the derivation of smoothing coefficients for step and ramp inputs subjected to either almost white noise or Gaussian-Markoff noise. The examples illustrate the number of constraint relations that the filter smoothing coefficients must satisfy for function and/or derivative convergence under noise-free conditions. The smoothing coefficients are also a function of the type of noise input into the system or the discrete filter. From the examples, it can be observed that as N becomes larger, the output noise variance becomes smaller, but the computation time is increased.     

Impulse Response Determination by Cross Correlation

This paper describes the design of a digital cross correlator and its application in determining the impulse response in linear systems. The output of the cross correlator, which correlates the input and the output of a linear system excited by noise, is the same as the response of the linear system to a pulse which is identical to the noise autocorrelation. The impulse response error is defined as the normalized mean-square deviation of the actual from the true impulse response. A digital computer simulation confirms that the conventional technique yields the same impulse error as the correlation technique, when the width of the input rectangular pulse is equivalent to the width of the noise autocorrelation function. The operation and design of the digital correlator are discussed. An advantage of the specially designed digital correlator over a general-purpose digital computer is to operate in real time without problems of software and storage. The presented experimental and digitally computed results show that the digital correlator can accurately determine the impulse response, even in presence of perturbations. Only the correlation technique allows measurement of system impulse response without disturbing normal operation. Suggestions are made to simplify the design and improve the speed (bandwidth capability).