Estimation of optimal parameters of the multiplicative algorithm of wavelet filtering of images

In most widely used wavelet filtering algorithms, the decomposition coefficients are processed with the use of threshold functions, which makes it possible to account for the “energy” feature of each decomposition coefficient. To some extent, this disadvantage is removed in a class of multiplicative algorithms, which account for the energy of decomposition coefficients located in a given proximity from a processed decomposition coefficient. However, the effective error minimization in wavelet filtering of images requires that a parameter, the choice of the optimal value of which remains to be an unsolved problem, is introduced into these processing algorithms. Therefore, the problem solved in this paper is the estimation of the optimal value of this parameter, which minimizes the root-mean-square error of the filtering. The performed studies showed the effectiveness of the proposed estimation algorithm and the possibility of its use in practice.     

Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings

Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the previous studies, maximum correlated kurtosis deconvolution (MCKD) has been validated as an efficient method to extract fault feature in the fault signals. Nonetheless, there are still some challenges when MCKD is applied to fault detection owing to the rigorous requirements of multiple input parameters. To overcome limitation, a multi-objective iterative optimization algorithm (MOIOA) for multi-fault diagnosis is proposed. In this method, correlated kurtosis (CK) is taken as a criterion to select optimal Morlet wavelet filter using the whale optimization algorithm (WOA). Meanwhile, to further eliminate the effect of the inaccurate period on CK, the update process of period is incorporated. After that, the simulated and experimental signals are utilized to testify the validity and superiority of the MOIOA for multiple faults detection by the comparison with MCKD. The results indicate that MOIOA is efficient to extract weak fault features even with heavy noise and harmonic interferences.     

基于两步迭代TV正则化的电阻抗图像重建算法

针对电阻抗层析成像(electrical impedance tomography,EIT)逆问题求解的欠定性和病态性,克服传统基于L2范数的Tikhonov正则化对介质边界的模糊效应,提出一种基于两步迭代的正则化图像重建算法.该算法采用具有良好保边性的总变差(total variation,TV)正则化函数,利用两步迭代法引入TV去噪算子,达到解的双重正则化效果.与传统最小二乘迭代算法、TV相关迭代算法相比,不仅保证了逆问题求解的稳定性,而且进一步提高了非连续分布介质区域成像的分辨能力,具有较好的成像精度.     

Phase recovery for electron holography using Gerchberg-Papoulis iterative algorithm

The Gerchberg-Papoulis (GP) iterative algorithm is applied to electron holographic reconstruction to supplement the Fourier-transform method. The GP algorithm can recover the phase to high accuracy using simulated holograms. This method is useful when a region of known amplitude is present, such as a region of vacuum or uniform thickness. Modulations of the phase on the order of 0.1 rad can be corrected significantly using this algorithm.     

TIE和GS迭代算法用于生物细胞的相位恢复

提出了一种利用白光进行生物细胞图像高分辨率相位恢复方法,该方法结合了光强度传输方程(TIE)和Gerchberg-Saxton迭代(GS)算法。通过在显微镜的像平面附近连续采集3张生物细胞图像,并使用红色、蓝色和绿色通道分别对生物细胞图像的相位进行恢复,然后从3个通道的相位中提取该生物细胞的相位信息。实验结果表明,用该方法所得到的前后两次循环迭代的相位相对误差精度可以达到10^-7。     

A new iterative algorithm for kinematic synthesis of gear drives for optimal speed ratio

The double composite gear trains offer attractive design features. However, their analysis using the algebraic equations method involves lengthy and tedious manual manipulations. The existing theories of composite gear trains is useful in this process to some extent, but it will not facilitate development of an algorithm suitable for all kinematic versions of a drive. The present algorithm based on the Unified Theory has been used for analysis of all the 18 versions of the drive with similar structure. The input data is simplified to that of feeding values of index exponents for the applicable versions. The optimal version of the twelve speed drive is synthesized with the present algorithm from the 18 versions belonging to open type having similar structure.     

一种综合小波变换的心电信号消噪算法

针对心电信号中混有的基线漂移、工频干扰、肌电干扰等噪声,比较了适于心电信号的4种基于小波变换的心电信号消噪算法,结合消噪后的信噪比和信号失真度,提出一种综合小波变换的心电信号消噪算法.该算法先使用小波分解法消除心电信号中的基线漂移,再利用模极大值法消除工频干扰、肌电干扰等噪声.并且运用该算法对MIT-BIH心律失常数据库中的含有多种噪声的心电数据进行了仿真与实验,结果表明噪声被有效地消除并且失真度较小,可满足临床分析与诊断对心电波形的要求.     

Quasi-optimal algorithm of estimating the coefficients of wavelet expansions during signal filtration

The proposed algorithm calculates its own filtration factor for each coefficient of the wavelet expansion of a noisy signal. The optimal filtration factor depends on the signal-to-noise ratio, which is estimated with a specially constructed iterative procedure. The limit points of this procedure are determined. A computational experiment performed shows that the proposed approach can be effectively used in problems of filtration and compression of noisy signals and images.     

Estimation of optimal threshold values in algorithms of wavelet filtration of images

A new algorithm is proposed for estimating optimal threshold values in thresholding algorithms of wavelet filtration of signals and images. Numerous computational experiments are performed to compare this threshold with threshold values widely used in wavelet filtration algorithms. Application of the proposed threshold is demonstrated to ensure substantial reduction of the filtration error of both smooth and high-contrast images.     

Maximum kurtosis principle for the parameter selection of Gabor wavelet and its application to ultrasonic signal processing

The noise suppression techniques with wavelet transform (WT) are widely used in nondestructive testing and evaluation (NDT&E), especially in ultrasonics. But the wavelet based filter has the property of equal Q-factor, so, it is impossible to choose the central frequency and the bandwidth arbitrarily at the same time. This paper develops a new technique using WT to eliminate this drawback. In this paper, a weak ultrasonic signals identification method by using the optimal parameter Gabor wavelet transform is proposed. We address the choice of the optimal central frequency and bandwidth of the Gabor wavelet using the kurtosis maximization algorithm. The central frequency and bandwidth of the optimal parameter Gabor wavelet matched that of the ultrasonic signal very well. Numerical and experimental results have been presented to evaluate the effectiveness of the optimal parameter Gabor wavelet transform on ultrasonic flaw detection. This technique is a simpler and effective technique for processing heavy noised ultrasonic signals.     

基于小波变换及FFT算法的涡街信号处理

近年来涡街流量计的应用越来越广泛,但在实际使用时管道振动和流场扰动等引起的噪声易对涡街信号造成干扰,导致实际测量精度达不到要求。本文使用小波变换及FFT算法对涡街信号进行处理。该方法对涡街信号提取和去除噪声效果良好。有利于扩大涡街流量计的量程范围,提高测量精度。     

基于稀疏小波变换的超宽带低信噪比信号检测算法

脉冲超宽带信号是时域瞬态脉冲,功率谱密度极低,在远距离通信时,信号淹没在噪声中较难检测,对前端采样率要求较高.针对脉冲超宽带低信噪比检测问题,提出了一种在脉冲波形先验信息已知条件下,基于稀疏小波变换的低信噪比检测方法.针对超宽带信号在小波域具有稀疏分布这一特征,依据压缩传感理论,分析并仿真了稀疏基矩阵选择时域采样矩阵和小波矩阵时,信噪比对于性能的影响,提供了重构算法中迭代终止门限的选择方法.仿真实验表明,相对于稀疏基矩阵为时域采样矩阵,采用小波变换矩阵可以在较低信噪比条件下实现超宽带信号的降噪重构.     

Computationally lean algorithm of novel optimal FIR adaptive filter for vortex signal extraction

In a vortex flowmeter vortices are generated by a bluff body, inserted in the path of flow, which has a piezoelectric sensor embedded in it. This piezosensor develops a signal having a fundamental frequency that is proportional to flow. The flow measurement relies completely on extraction of true vortex signal and estimation of the correct frequency. A novel adaptive FIR filter has been designed and implemented using low power computational resource (8.25 mW), which gives better results than an existing contemporary system when tested on an industrial flow rig. Further more a comparative study of autocorrelation, EMD Scales filter and proposed algorithm is carried on the good and bad vortex signals. From this comparative study it is seen that proposed algorithm is effective for bad vortex signals and low flowrates where vortex signals are weak.     

ECT图像重建正则化参数选取新方法

电容层析成像图像重建是一不适定反问题。此种情况下，仅使用最小二乘法不能保证获得满意的介质分布图像重建结果，因此广泛使用TIkhonov正则化算法来产生适当的解。正则化参数的合适选取对图像重建至关重要，其对重建质量和计算时间都有影响。本文提出了一种基于最平坦斜率的Tikhonov正则化参数选择方法，并针对2种典型介质分布，将基于此方法计算的正则化参数同L-曲线法在电容测量数据无噪声和施加噪声情况下的图像重建结果进行了比较。     

基于谐波小波和Prony算法的转子不平衡信号提取

高精度动平衡测量系统中的信噪比很低,尤其是在邻近频率干扰背景下,常规的快速博里叶变换(fast Fourier trasformation,FFT)等方法无法准确提取不平衡信号.提出一种基于谐波小波和Prony算法的不平衡信号提取方法,先采用自适应谐波小波带通滤波提高信噪比,然后以滤波后的数据作为样本,采用Prony算法识别不平衡信号的幅值和相位,有效解决了邻近频率干扰导致的不平衡信号无法准确提取的问题.仿真和实验结果表明,该方法具有精度高、重复性好等优点,特别适合于信噪比较低的高精度动平衡测量系统中.     

基于改进阈值小波算法的汽车轮速信号处理

在汽车制动过程中,轮速信号中的噪声对制动有着直接的影响,运用小波理论可以对轮速信号中的噪声进行去噪处理。噪声的幅值随着小波变换尺度的增加会逐渐减小,而信号的幅值与小波变换的尺度变化无关。在Donoho的软、硬阈值去噪方法基础上,提出了一种新的阈值函数量化法,该方法克服了硬阈值法不连续性和软阈值法有偏差的缺点,并把它们应用在汽车轮速信号的去噪上。新的阈值函数具有物理意义清晰、表达式简单等优点。实际信号处理结果表明,这种经改进的方法可以有效地去除噪声干扰,在信噪比指标上也明显优于常用的软、硬阈值去噪算法。     

Error tolerance of an iterative phase retrieval algorithm for moveable illumination microscopy

This paper examines the behaviour of the new Ptychographical Iterative Engine (PIE) algorithm when part of the initial information it requires is inaccurately known. This could be the parameters describing the illuminating wavefunction, the precise location of the specimen relative to the illuminating wavefunction, or other information that is assumed about the physical system. The tolerance of the algorithm for unavoidable problems such as noise and source incoherence is also investigated, leading to the conclusion that this approach to phase retrieval is very robust. It can not only tolerate errors in the assumed parameters, but can often be used as a method of characterising the parameters more accurately.     

Digital lock-in algorithm and parameter settings in multi-channel sensor signal detection

In order to implement demodulation of multi-channel composite signal in sensor signal detection system with high accuracy and high speed, in this paper we present a demodulation algorithm and schemes on how to optimize performances in detail based on the idea of software radio. A multi-channel composite signal was demodulated by the algorithm combined with a high-speed digital lock-in algorithm based on oversampling. To further enhance the signal-to-noise ratio, we discussed how to cut down crosstalk between adjacent channels, and a cascade filter was proposed. The result is helpful to effectively set carrier frequencies, from which a method of choosing parameters in frequency division multiplexing is obtained. Theoretical analysis shows that the new method has advantages such as high accuracy, high speed, and wide application range. It is suitable for sensor signal detection with AC signal excitation, and it can also improve overall system performance.     

Localization algorithm for small objects in an image using wavelet transforms

This paper presents an algorithm for determining the coordinates of small objects appearing in a sequence of scene images based on sum and difference processing of the detailing wavelet coefficients of the current and reference images, followed by a morphological analysis of the generated pseudo-image. The effectiveness of the algorithm is compared with the difference algorithm for analyzing changes in the observation scene. It is shown that the proposed algorithm is more resistant to the effects of relative shifts of the current and reference images.     

电容层析成像图像重建的总变差正则化算法

针对电容层析成像（ECT）逆问题解的不适定性,本文提出一种基于总变差（total variation,TV）正则化的图像重建算法。同传统的2范数Tikhonov正则化方法相比,该算法（基于1范数正则化）不仅保证了逆问题求解的稳定性,而且提高了对介质非连续分布的区域成像的分辨能力,具有良好的保边缘性。仿真及实验结果表明,该算法在重建图像质量和重建速度两方面均具有优势。