Phenomenological model of a response of a piezoelectric probe to acoustic-emission pulses

Parameters and characteristics of signals from a probe play an informative role in the solution of problems of evaluating the strength of structures by acoustic-emission (AE) techniques. The processes of signal formation in probes are complex and of random character, and the physics of formation of AE signals has not been well studied. Measuring processes are accompanied by inevitable noises. Under these circumstances, it is very important to develop a mathematical phenomenological model of AE signals from a probe so as to obtain processing algorithms. The fine structure of AE signals from a probe was analyzed using physical interpretations to develop an adequate model for application in processing algorithms.     

Theoretical basics for inspection of conducting coatings in aircraft fuel tanks

Problems related to testing the integrity of conducting coatings in aircraft fuel tanks are considered. Different types of flaws are analyzed, and the main problems encountered when detecting these flaws are revealed. The design of a capacitive device that improves the accuracy of the known technical solutions for testing the integrity of conducting coatings is presented. Theoretical foundations are considered for developing a mathematical model for shaping data signals in the testing procedure based on calculating the irrotational part of electric field inside the capacitive-gauge structure.     

小波分析在钢丝绳无损检测中的应用

本文论述了采用漏磁通法检测钢丝绳局部损伤的原理和方法，并将小波理论有效地用于检测信号的处理中，用来确定局部损伤的位置，识别内外部断丝。     

Damage localisation in plate-like structures based on PZT sensors

In this paper, signal processing algorithms for damage localisation purposes in plate-like structures were proposed. Algorithms use elastic wave propagation phenomenon for damage detection and localisation. As a result of application to signals registered from the structure, special maps are created that indicate damage location. In this work the algorithms were introduced, described and experimentally implemented. Also one example coming from numerical simulation was included. The proposed methods were successfully tested on aluminium alloy specimen and carbon–epoxy specimen.     

Estimation of the optimal regularization parameter of an iterative wavelet algorithm for signal recovery

Two methods of statistical estimation of the optimal regularization parameter of a nonlinear algorithm for signal recovery are proposed, one of which is based on the optimality criterion and the other one on the residual principle. These methods have simple algorithmic implementation and do not need a priori information about the quantitative characteristics of the sought solution. The results of numerical experiments show the effectiveness of the method based on the optimality criterion.     

HELICOPTER TRANSMISSION FAULT DETECTION VIA TIME-FREQUENCY,SCALE AND SPECTRAL METHODS

The vast majority of the powerful and effective algorithms in signal processing start with the assumption of stationarity. In addition, the deterministic portion of the signal is often assumed to be composed of complex exponentials which are the solutions to linear time-invariant (LTI) differential equations. Many signals do not comply with these assumptions, however, resulting in disappointment when conventional techniques are used. We now have at hand time–frequency (t–f) and scale transform analyses which can provide new insights into the nature of non-stationary signals. This paper describes some results using reduced interference distributions (RIDs) and scale transforms in the analysis of signals obtained from accelerometers placed strategically on a Westland helicopter transmission. Fault detection algorithms for several types of faults were compared and the methods based on the scale transform performed best followed by RID results. More conventional spectral-analysis-based methods were the least effective.     

改进遗传算法在减速器优化设计中的应用

针对简单遗传算法的早熟现象及不能处理带有复杂约束的优化问题,提出一种基于乘子法与伪并行遗传算法的改进遗传算法,并将其应用于斜齿轮减速器优化设计中。计算结果表明改进遗传算法,全局寻优能力强。     

Ultrasonic tomography of metal structures using the digitally focused antenna array method

Physical principles and algorithms for reconstructing images of the inner structure of an object made of a solid material are considered. These are based on the pulsed echo method of ultrasonic testing using multielement antenna arrays focused on each point of the visualized region of the object by spatiotemporal processing of signals from a combination sounding of the object by all possible pairs of the antenna array. Substantial improvement of the image during testing of a plane-parallel object is obtained by using signals that are multiply reflected from the object boundaries; the use of different algorithms of image reconstruction is expedient for different types of discontinuity flaws.     

Comparative analysis of the performance of laser Doppler systems using maximum likelihood and phase increment methods

This paper presents a comparative analysis of the errors of two alternative methods of estimating the central frequency of signals of laser Doppler systems, one of which is based on the maximum likelihood criterion and the other on the so-called pulse-pair technique. Using computer simulation, the standard deviations of the Doppler signal frequency from its true values are determined for both methods and plots of the ratios of these deviations as a measure of the accuracy gain of one of them are constructed. The results can be used by developers of appropriate systems to choose an optimal algorithm of signal processing based on a compromise between the accuracy and speed of the systems as well as the labor intensity of calculations.     

Optimal classifier design based on pairwise statistical separability maximisation of time–frequency features

This paper presents a novel classification algorithm based on the time–frequency features extracted from multiple-sensor signals. Multiple-sensor signals are difficult to handle for classification purpose since each signal may have a different separability measure between classes and, hence, it may be difficult to pick a set of best sensors for classification. This paper provides a new separability measure, the so-called miss-classification probability, in order to overcome such a difficulty. A mathematical representation of the statistical aspect of the time–frequency features is introduced for efficient calculation of the miss-classification probability. Yet, another difficulty may be encountered in extracting a set of time–frequency features, which may best represent the difference among classes. This paper also proposes a pairwise statistical separability maximisation scheme to overcome this difficulty. The resultant classification algorithm based on these new developments is validated through seeded-fault tests with rotary compressors.     

Calculation of the areas of peaks in measurements of isotopic ratios using MI-1201SG mass spectrometer

A method for measuring the isotopic ratios for various elements based on the calculation of peak areas is proposed. The areas of peaks are calculated by means of approximation of an experimental signal by a phenomenological peak-shape model, which takes into account the physical principles of detecting signals of sector mass spectrometers. The method is simple to implement and allows measurements of the isotopic ratios when standard measurement techniques are inapplicable and/or do not yield the desirable accuracy, e.g., because of an insufficient resolution of the mass spectrometer.     

A new computing approach for power signal modeling using fractional adaptive algorithms

Estimating the harmonic parameters is fundamental requirement for signal modelling in a power supply system. In this study, exploration and exploitation in fractional adaptive signal processing (FrASP) is carried out for identification of parameters in power signals. We design FrASP algorithms based on recently introduced variants of generalized least mean square (LMS) adaptive strategies for parameter estimation of the model. The performance of the proposed fractional adaptive schemes is evaluated for number of scenarios based on step size and noise variations. Results of the simulated system for sufficient large number of independent runs validated the reliability and effectiveness of the given methods through different performance measures in terms of mean square error, variance account for, and Nash Sutcliffe efficiency.     

Computer method for kinematic analysis of lower-pair mechanisms—II position problemsEine neue methode zur analyse von mechanismen teil 2: Positionsprobleme

In the first part of this study, a new method for solving the problem of kinematic analysis was presented, based on the concepts of “basic coordinates” and “link constraint equations”. In this second part, these same concepts are used to solve the problems of initial position, finite displacements and static equilibrium position of a mechanism with springs between its links. The proposed algorithms are elementary in their formulation and of exceptional efficiency in their performance. The methods describes are based on the solution of a problem of mathematical programming. Several examples are presented, giving an idea of the potential of said algorithms.     

An efficient cardiac signal enhancement using time–frequency realization of leaky adaptive noise cancelers for remote health monitoring systems

Nowadays telecardiology is an important tool in cardiac diagnosis from a remote location. During Electrocardiogram (ECG) or Cardiac Signal acquisition several artifacts strongly affect the ST segment, degrade the signal quality, frequency resolution, produce large amplitude signals in ECG that can resemble PQRST waveforms and mask the tiny features that are important for clinical monitoring and diagnosis. So the extraction of high-resolution cardiac signals from recordings contaminated with artifacts is an important issue to investigate. In this paper, various novel block based time–frequency domain adaptive filter structures for cardiac signal enhancement are presented. These filters estimate the deterministic components of the cardiac signal and remove the noise component. The Block Leaky Least Mean Square (BLLMS) algorithm, being the solution of the steepest descent strategy for minimizing the mean squared error in a complete signal occurrence, is shown to be steady-state unbiased and with a lower variance than the LMS algorithm. To improve the filtering capability some variants of BLLMS, Block Normalized LLMS (BNLLMS) and Block Error Normalized LLMS (BENLLMS) algorithms are implemented in both time domain (TD) and frequency domains (FD). Finally, we have applied these algorithms on real cardiac signals obtained from the MIT-BIH data base and compared their performance with the conventional LLMS algorithm. The results show that the performance of the block based algorithms is superior to the LLMS counterparts in terms of signal to noise ratio improvement (SNRI), excess mean square error (EMSE) and misadjustment (M). Among all the algorithms FDBENLLMS achieves higher SNRI than other techniques. These values are 25.8713 dB, 20.1548 dB, 21.6718 dB and 20.7131 dBs for power line interference (PLI), baseline wander (BW), muscle artifacts (MA) and electrode motion artifacts (EM) removal.     

射频信号在超声检测缺陷识别中的应用研究

针对工业超声检测过程中缺陷难以准确定性的问题，基于射频回波对缺陷分类中的信号处理等方法进行了研究。分析了射频和检波信号的特点，在对所采集的缺陷信号进行处理的基础上，利用类内、类间距离和可分性测度比较了两类信号的类别可分性，同时采用ＢＰ神经网络和ＲＢＦ神经网络作为分类器，对缺陷信号的小波均方幅值特征进行了学习和识别研究     

数字信号处理技术在科氏质量流量计中的应用

科氏质量流量计是目前应用范围最广、发展速度最快的流量计之一。数字信号处理技术是科氏质量流量计的核心技术,直接决定其测量精度、测量稳定性等性能指标;而流量传感器输出信号的数学模型是信号处理的依据和基础。国内外学者提出了多种信号处理方法,但是,没有根据不同的信号模型和不同的应用场合对各种信号处理方法进行比较和评价。为此,根据不同数字信号处理方法的特征量提取原理,分析了其具有的优缺点。针对科氏质量流量计单相流、批料流与气液两相流测量这3种典型应用场合中存在的关键技术问题,依据随机游动信号模型、突变信号模型和自回归滑动平均(ARMA)信号模型,分别从计算精度、响应速度、收敛性、抗干扰能力和对参数变化的敏感度等方面,对不同信号处理方法进行考核和对比,确定了3种典型应用场合下,解决关键技术问题,性能最佳的数字信号处理方法。     

基于AMESim与Simulink的线控液压转向系统控制策略研究

在分析液压转向系统工作原理的基础上,建立液压转向系统数学模型,设计控制系统的PID算法和模糊控制算法。对比PID控制和模糊控制在阶跃信号、正弦信号和方波信号下的液压转向系统响应特性。利用AMESim和Simulink联合仿真,得出油缸在不同控制策略下的响应速度。     

Job-shop scheduling using certain heuristic search algorithms

This paper presents a family of sub-optimal algorithms based on the A^* heuristic search algorithm, aimed at solving the general job-shop scheduling problem. A methodology is suggested for algorithms that require adjustable memory resources, by compromising algorithmic admissibility. Different possibilities for (admissible or non-admissible) heuristic estimates are suggested and dynamically weighted heuristics are introduced to the job-shop scheduling problem, with good results. Bottleneck scheduling is introduced within this problem-solving scheme, proving a base for more powerful heuristics. In terms of solution nearness to optimal and speed, the techniques investigated generally compare favourably with similar work in this field.     

Hybrid time–frequency methods for non-stationary mechanical signal analysis

This paper presents a family of hybrid time–frequency methods to be used as a tool for transient signal analysis. These methods are based on autoregressive models of the signal, and on the maximum likelihood method. A classical Wigner–Ville distribution and a parametric time–frequency methods are used for comparison purposes. The characteristics, advantages and disadvantages, of non-parametric, parametric and hybrid methods are discussed and their performances are compared by analysing actual data. The superiority of time–frequency resolution of the hybrid methods is pointed out over that of the parametric and non-parametric ones. Three practical examples of transient signals illustrate the discussion: the vibration signal issued from a damaged gearbox, a signal from a pendular scratch test presenting beating phenomenon and the vibration signal measured in an electrical motor during start-up.     

基于最优小波包Shannon熵的再制造电机转子缺陷诊断技术

为了实现对再制造电机转子质量的有效监控,采用超声波技术对其内部缺陷进行检测与评价。引入滤波效果良好的最优小波包滤波法和对超声波信号噪声含量变化敏感的Shannon信息熵算法,定义一种新的最优小波包Shannon熵(Best wavelet packet Shannon entropy,BWPSE)的概念,并提出基于BWPSE的超声波信号消噪方法。对采集到的再制造电机转子超声检测信号进行最优小波包滤波处理,得到各尺度的小波包分解系数,在此基础上计算各尺度小波包分解系数的Shannon熵,通过分析小波包系数Shannon熵的变化规律确定分解层数及阈值。采用该方法对再制造电机转子超声检测信号进行消噪处理,结果表明该方法对噪声消除比较彻底,对比Sqtwolog阈值小波分析及Heursure阈值小波分析等其他信号消噪方法,该方法可显著提高再制造电机转子内部缺陷定量分析的准确度。