Algorithms for Estimating Signal Information Parameters under the Action of Broadband Non-Gaussian Noise

This paper describes the synthesis of algorithms for estimating signal information parameters with noninertial nonlinear transformation of the input mixture of the signal and broadband non-Gaussian noise. There is also the analysis of algorithms optimal in the domain of small mismatch and quasioptimal algorithms, which are capable of operating in arbitrary mismatches between measured parameters and their estimates in the case of random signal/noise ratio at the gauge input. This work also presents the obtained basic estimated relations that help one determine the form of optimal amplitude characteristics of the nonlinear transformation unit, the quality of suppression of additive noise in a given unit with optimal and arbitrary amplitude characteristic, the steepness of the discrimination characteristic, and the value of the phase characteristic in the domain of small mismatches. It is shown that, by specifying the type of action and the transfer function of a smoothing chain, it is possible to determine the steady-state dynamic and fluctuation errors in a closed servo-system.     

Identification of the distribution parameters of additive and multiplicative non-Gaussian noise

This paper considers issues related to the identification of the parameters and form of the probability density function of generally non-Gaussian additive and multiplicative noise affecting the signal. The results of numerical simulation of methods for estimating the information parameters of random processes with a non-Gaussian probability density function for a finite sample.     

Potential accuracy of methods of laser Doppler anemometry in the single-particle scattering mode

Potential accuracy of methods of laser Doppler anemometry is determined for the singleparticle scattering mode where the only disturbing factor is shot noise generated by the optical signal itself. The problem is solved by means of computer simulations with the maximum likelihood method. The initial parameters of simulations are chosen to be the number of real or virtual interference fringes in the measurement volume of the anemometer, the signal discretization frequency, and some typical values of the signal/shot noise ratio. The parameters to be estimated are the Doppler frequency as the basic parameter carrying information about the process velocity, the signal amplitude containing information about the size and concentration of scattering particles, and the instant when the particles arrive at the center of the measurement volume of the anemometer, which is needed for reconstruction of the examined flow velocity as a function of time. The estimates obtained in this study show that shot noise produces a minor effect (0.004–0.04%) on the frequency determination accuracy in the entire range of chosen values of the initial parameters. For the signal amplitude and the instant when the particles arrive at the center of the measurement volume of the anemometer, the errors induced by shot noise are in the interval of 0.2–3.5%; if the number of interference fringes is sufficiently large (more than 20), the errors do not exceed 0.2% regardless of the shot noise level.     

非高斯随机振动试验并行控制策略研究

针对非高斯随机振动试验控制中功率谱均衡与峭度均衡相互干涉,影响控制精度的问题,提出非高斯随机振动试验并行控制策略。在提出整个系统控制流程的基础上,分别给出功率谱均衡控制算法和峭度均衡控制算法。对蕴含峭度信息的随机信号产生机理展开研究,先给出信号产生的流程图,然后推导出符合控制系统要求的随机信号设计参数。利用功率谱设计滤波器,通过卷积运算调制出用于系统控制的驱动信号。仿真与试验结果表明,采用非高斯随机振动试验并行控制策略进行系统控制,其输出响应谱与参考谱的误差完全满足工程中常用的±3 dB控制要求,峭度控制也达到很高的精度,满足工程试验要求,从而验证该控制策略的有效性。     

基于相关自适应器的EM-MWD信号检测系统设计

经EM-MWD(electromagnetic method measurement while drilling)电磁通道传输至地表的信号很微弱并且极易受到白噪声、奇异噪声、工频噪声及其谐波等干扰,导致信号特征参数提取的准确度降低,为了解决这一难题,通过对电磁波传输信道的研究,根据接收初始信号强度以及自适应检测和相关检测的特点,研究并设计了相关自适应器,并基于此设计了电磁随钻地表信号检测系统。然后用Hilbert变换求信号包络,完成了数据拟合和残差分析,并计算了信噪比、均方根误差和误码率,最后做了实验。仿真和实验结果表明,利用该检测系统,能够提高信号特征参数的准确度,达到有效降噪目的,对后续分析和研究提供了保证。     

光纤光栅微弱信号检测的解调电路

为了在光纤光栅匹配解调系统中实现对光纤光栅微弱信号的检测与处理,在应用微弱光电信号检测原理的基础上设计一种高信噪比、高检测精度的解调电路,该解调电路采用低噪声电路元件参数选取原则和前置放大器设计的一般方法,在雪崩光电二极管与信号数模转换之间采用互阻放大器、巴特沃斯滤波电路和多级放大电路,实现了电路的最佳噪声匹配,有效地抑制了电路的噪声和干扰。该解调电路在光纤光栅匹配解调系统中具有很高的信噪比和测量精度,且具有很好的灵敏度,在测量低频率振动信号试验中具有优异的性能。实验表明:该电路解调系统在25～200 Hz正弦激励振动信号下具有很好的低噪声性能,精确的测试出振动信号,同时该电路所采用的方法与措施对其他测量系统也有借鉴意义。     

基于广义S变换奇异值分解的料位回波检测与校正

非平稳及多奇异点的调频料位测量雷达回波中包含虚假回波及噪声,影响料位回波信号检测,导致料位测量精度不高.本文提出了一种基于广义S变换和奇异值分解的料位回波检测与校正方法.首先,将料位变化视作低速运动目标,将料位回波信号与雷达发射信号进行混频解调,并根据回波信号的频率分布特点对广义S变换窗口的变化趋势进行调节.之后对其变换所得到的二维时频系数矩阵利用奇异值分解方法重构系数矩阵,并对其进行广义S逆变换,得到校正后的回波信号.实验结果表明:该方法能够准确检测料位回波信号,在抑制噪声的同时能最大限度保留信号的细节特征,减少虚假回波干扰.料位测量误差不超过4.01％,测量精度可达到0.40％F.S.     

Application of Hilbert-Huang Decomposition to Reduce Noise and Characterize for NMR FID Signal of Proton Precession Magnetometer

The parameters in a nuclear magnetic resonance free induction decay (FID) signal contain information that is useful in magnetic field measurement, magnetic resonance sounding and other related applications. A real time sampled FID signal is well modeled as a finite mixture of exponential sequences plus noise. We propose to use the Hilbert-Huang transform (HHT) for noise reduction and characterization, where the generalized Hilbert-Huang represents a way to decompose a signal into so-called intrinsic mode function (IMF) along with a trend, and obtain instantaneous frequency data. First, acquiring the actual untuned FID signal by a developed prototype of proton magnetometer, and then the empirical mode decomposition is performed to decompose the noise and original FID. Finally, the HHT is applied to the obtained IMFs to extract the Hilbert energy spectrum of the signal on the frequency axis. By theory analysis and the testing of an actual FID signal, the results show that, compared with general noise reduction methods such as auto correlation and singular value decomposition, combined with the proposed method can further suppress the interfered signals effectively, and can obtain different components of FID signal, which can be used to identify the magnetic anomaly, the existence of groundwater etc. This is a very important property since it can be exploited to separate the FID signal from noise and to estimate exponential sequence parameters of FID signal.     

基于宽频激励电磁声谐振 7075 铝合金板厚检出概率

电磁超声换能器(EMAT)换能效率低、激发信号弱,而基于长周期激励信号以产生声波共振的电磁声谐振技术(EMAR)虽然可以提高接收信号的信噪比,然而可能导致主脉冲加宽并扩大超声波检测盲区,降低测量精度。本文应用一种宽频激励电磁声谐振技术(BE-EMAR)和一种Halbach阵列纵波EMAT,以单周期宽频激励作为EMAT输入信号,并利用EMAR方法对7075型铝合金试件板厚进行测量,借助检出概率(POD)模型来表征该技术针对微金属板厚的测量精度。实验结果表明,在未降噪时BE-EMAR得到的三种信噪比下的POD曲线中,对应的a_(50)或a_(90/95)最大差异值为0.05 mm,同一信噪比下降噪前后的最大差异值为0.07 mm,而在时差法(ToF)得到的POD曲线中这一最大差异值则为0.21 mm,因此说明BE-EMAR降噪前后得到的结果并无较大差别,该方案对于常规噪声信号不敏感;且降噪前后,在BE-EMAR得到的POD曲线中,a_(50)和a_(90/95)均可稳定在0.55 mm以内,证明了BE-EMAR比ToF测厚具有更优的精度、稳定性和抗噪能力。     

Sparse representation and its applications in micro-milling condition monitoring: noise separation and tool condition monitoring

This paper presents a new approach for cutting force denoising in micro-milling condition monitoring. In micro-milling, the comparatively small cutting force signal is contaminated by heavy noise, and as a result, it is necessary to denoise the force signal before further processing it. The traditional denoising methods, based on Gaussian noise assumption, are not effective in this situation because the noise is found to contain high non-Gaussian component. Based on the force and noise's sparse structures in the time–frequency domain, this approach employs a sparse decomposition approach and solves denoising as a convex optimization problem. It is shown that the proposed approach can separate the heavy non-Gaussian noise and recover useful information for condition monitoring.     

基于虚拟仪器的超声波高精度测时系统

提出了一种基于相位法测量超声波信号时间延迟的测量技术,建立了超声波信号飞行时间测量的数学模型。针对超声波测量要求响应速度快、单次测量精度高的要求,依据信号相位匹配原理对超声波信号时延估计的理论和方法进行了理论推导与仿真,得出基于相位法的时间测量精度受接收信号信噪比的影响。通过虚拟仪器平台的实验,表明该测量系统的信号传播时间测量具有ns级的测量精度。     

基于灰色预测恢复算法的流式细胞仪多参数提取

针对流式细胞仪测控系统由于脉冲信号信息不完整导致多参数提取存在误差的问题,提出了一种基于灰色预测恢复算法的多参数提取方法。利用基于GM(1,1)模型的灰色预测梯形递推信号恢复算法对脉冲信号进行高精度恢复,提高信号的信息完整性。同时,对直流恢复模块进行了优化设计,通过高速数字信号处理芯片对脉冲信号模拟偏移量及直流恢复进行反馈,提高直流恢复精度及信号信噪比。最后,搭建了测控系统实验环境,对该系统进行了验证。实验结果表明,多参数提取精度均在±1.5%范围内;同时可以将流式细胞仪检测细胞的速度提高到10万个/s。     

A new velocity estimation method using spectral identification of noise

In all measurement techniques one seeks accuracy and precision. In ultrasonic Doppler velocimetry, those qualities strongly depend on signal to noise ratio of the Doppler signal and on the performance of the velocity estimator. The most widely used estimation method in ultrasonic coherent Doppler velocimetry is the pulse pair method. Its success is due to the computation efficiency of the algorithm combined to an unbiased estimator. Unfortunately, for a wide range of experimental fluid flows, the pulse pair estimation is less efficient, especially for clear water or concentrated mud where the signal to noise ratio can be very low, or for highly turbulent flows where the Doppler signal has a broad spectrum. Our approach is based on the treatment of the Doppler spectral information. It uses a simple parametric identification inspired by theoretical models and experimental observations. It acts through noise subtraction and subsequent cutting. Thus, we have developed a fast velocity estimation algorithm superior to the pulse pair one in terms of accuracy. The robustness of the method was evaluated by adding different levels of white Gaussian noise to an experimental Doppler signal. The results demonstrate an increase of noise immunity up to one decade compared to the pulse pair method.     

基于小波的分布式光纤测温系统中噪声信号处理研究

分布式光纤测温系统具有本质安全、抗电磁干扰能力强、快速多点测量和定位、易于安装等特点。但采集到拉曼散射温度信号完全淹没在噪声之中。因此,为得到含有温度信息的有用信号,噪声信号的处理显得尤为重要。本文针对现有小波阈值函数的不足,采用一种改进的小波阈值函数和阈值选取方法来对拉曼散射温度信号进行去噪,仿真实验表明,改进阈值函数的小波去噪有效地提高去噪效果,从而提高分布式光纤测温系统的精度。     

基于DSP的低成本涡街流量计信号处理系统

涡街流量计易受噪声影响，现场测量精度得不到保证，节程比受限。本文选用片上资源丰富的TMS320LF2407A DSP芯片作为处理器，研制相应的数字信号处理系统。系统选用数宁滤波加频谱分析的信号处理方法处理传感器信号，提高仪表抑制噪声的能力，扩展量程比；模拟信号调理部分加入限幅滤波电路，解决传感器信号强度变化大、需要调整硬件电路参数的问题。该系统体积小、成本低、功能齐全，并可与不同口径的一次仪表匹配。目前该系统已通过实验标定，并应用于工业现场。     

A combined pulse modulation-processing method for ADCP applications

Acoustic Doppler Current Profiler (ADCP) based on the Doppler principle is the sonar for velocity measurements, which is mainly applied in the large-scale measurements of the oceanic current velocity. In order to satisfy the increasing requirement of high measurement resolution and accuracy compared with the traditional ADCP, this paper investigates the ambiguous functions of different signals and indicates that the pulse combined by several sinusoidal signals will improve the time resolution when keeping good frequency resolution. Then the present research proposes the modulation of a combined pulse as the ADCP׳s emitted signal, as well as the corresponding signal processing method. Two examples are demonstrated to show the effectiveness of the combined pulse modulation-processing method, and it is seen that: 1. the combined pulse has the same spatial resolution as one subpulse, while achieves better frequency resolution and better signal–noise ratio than the latter; 2. although the combined pulse results in a little worse signal–noise ratio than the long sinusoidal signal, the former has much higher spatial resolution; 3. the measurement accuracy of the combined pulse is better than the broadband coded-pulse when they have the same pulse width.     

A hybrid unscented filtering and particle swarm optimization technique for harmonic analysis of nonstationary signals

This paper presents a modified unscented Kalman filter for accurate estimation of frequency and harmonic components of a time-varying signal embedded in noise with low signal-to-noise ratio. Further, the model and measurement error covariances along with the unscented Kalman filter parameters are selected using a modified particle swarm optimization algorithm. To circumvent the problem of premature convergence and local minima, a dynamically varying inertia weight based on the variance of the population fitness is used. This results in a better local and global searching ability of the particles, which improves the convergence of the velocity and better accuracy of the unscented Kalman filter parameters. Various simulation results for nonstationary sinusoidal signals with time varying amplitude, phase and harmonic content corrupted with noise, reveal significant improvement in noise rejection and speed of convergence and accuracy in comparison to the well known extended Kalman filter.     

基于双谱熵的齿轮裂纹故障特征提取

针对裂纹故障导致齿轮振动信号非高斯性变化这一特点,提出采用双谱熵对信号非高斯成分在双频域内的分布形态进行定量描述,并据此提取故障信息,得到裂纹产生期、扩展期的特征趋势。结果表明,双谱熵不基于信号能量信息,受非故障因素影响小,而且能有效抑制高斯噪声,同时又对微弱故障十分敏感。研究结果为后续故障诊断与趋势预测提供了新的有效方法。     

Weak fault feature extraction of rolling bearing under strong poisson noise and variable speed conditions

Fault feature extraction of the rolling bearing under strong background noise is always a difficult problem in bearing fault diagnosis. At present, most of the research focuses on weak signal extraction under Gaussian white noise and has certain practical significance. However, the noise in engineering is often complex and changeable, Gaussian white noise cannot fully simulate the actual strong background noise. Poisson white noise is a type of typical non-Gaussian noise, which widely exists in complex mechanical impact. It is of great significance to study the weak fault feature extraction of a faulty bearing under this type of noise. At the same time, variable speed conditions occupy most rotating machinery speed conditions. Non-stationary vibration signals make it difficult to extract fault features, and the frequency spectrum ambiguity will occur because of speed fluctuation. To solve the above problems, a method of weak feature extraction of a faulty bearing based on computed order analysis (COA) and adaptive stochastic resonance (SR) is proposed. Firstly, by numerical simulation, the non-stationary fault characteristic signal corrupted with strong Poisson noise is transformed into a stationary signal in the angle domain by COA. Secondly, the influence of the parameters of the pulse arrival rate and noise intensity of Poisson white noise on the optimal SR response in the angle domain are studied, and the influence of the parameters of Poisson white noise on the fault feature extraction is given. Then, adaptive SR method is used to extract and enhance fault feature information. Finally, the effectiveness of this method in weak fault characteristic signal extraction under strong Poisson noise is verified by experiments. Numerical simulation and experimental results verify the effectiveness of the proposed method in bearing fault diagnosis under strong Poisson noise and variable speed conditions.

     

汽车发动机瞬时转速测量中的噪声分析及补偿方法

对汽车发动机的瞬时转速信号中的量测噪声进行补偿。试验测量结果表明,由飞轮齿圈的齿形误差引起的噪声是瞬时转速信号中的主要噪声源。并且该噪声的幅值与发动机的平均转速成正比。由于这种噪声的频带与飞轮瞬时转速信号物频带可能重叠,因此采用传统的滤波等方法无法完全肖除齿形误差引起的噪声,提出采用２个传感器的补偿新方法,可将齿形误差引起的噪声从瞬时转速信号中消除,试验结果验证了该方法的可行性,训利用瞬时转速检测