Methods and technologies for wideband spectrum sensing

The paper presents a review of the measurement methods and the technologies for wideband spectrum sensing. Wideband spectrum sensing is a relevant task in RF measurement instruments and telecommunications equipments. The first part of the paper is dedicated to the discussion of methods. They have been classified into five main approaches: (i) signal detection with known sub-band width; (ii) joint sub-band boundaries and level estimation; (iii) spectrum segmentation; (iv) compressed sensing; and (v) cooperative sensing. Methods following approaches (ii) and (iii) are the most suitable for the implementation in measuring instruments, since they allow separation of the signals, sharing the observed band. Therefore, greater attention has been paid to these approaches throughout the paper. A second part of the paper is dedicated to the analysis of main technologies enabling wideband spectrum sensing, dealing with the (i) RF frontend, (ii) A/D conversion, and (iii) waveform processing section of a potential instrument.     

Consistent structure determination of a noisy measurement system model

This paper describes a fast and accurate method for defining the structure of a noisy measurement system model without a previous parameters evaluation. The procedure is based on the following steps: (i) choosing a stable system structure; (ii) determing the real model order; (iii) estimating the model parameters. In (i) a value of the model order greater than the supposed one is assumed; in (ii), in order to determine the real structure, samples of the input/output signals of the actual model and the over-parametrised one are used; in (iii), by means of unbiased identification techniques, the model parameters are evaluated. The proposed method can be used both in batch and real-time processing. Experimental results concerning a single input-single output linear process with different model order and noise statistical properties are given.     

Computation of dynamic force coefficients for hybrid (hydrostatic/hydrodynamic) journal bearings by the finite disturbance and perturbation techniques

This paper presents non-dimensional linearized bearing coefficients for oil lubricated plain line-entry (slot) hybrid journal bearings. This represents the first stage of a programme of work on the dynamic characteristics of plain line-entry hybrid journal bearings. A full-scale dynamic analysis of this type of bearing, both theoretical and experimental is currently underway. Two techniques for predicting the linearized bearing coefficients are presented and compared: (i) the finite disturbance technique; (ii) the perturbation technique. Both analyses are based on a finite-difference approximation of the classical Reynolds equation, with provision for source flow and fluid-film rupture, although an isoviscous fluid is assumed.     

The Huang Hilbert Transform for evaluating the instantaneous frequency evolution of transient signals in non-linear systems

Traditional approaches for the analysis of transient signals are generally based on the apriori knowledge of the system under test for choosing a preliminary set of waveforms; consequently, they use a mathematical algorithm to decompose the signal itself into a suitable combination of the chosen waveforms. Conversely, this work is aimed to investigate the possibility of extracting the features of transient signals through the evaluation of their instantaneous frequency evolution. For this aim, the Huang Hilbert Transform (HHT) has been exploited (i) to decompose the input signal into a set of Intrinsic Mode Functions (IMFs), (ii) to extract the IMFs analytical signals, (iii) to evaluate their amplitude and phase evolutions, (iv) to compute the instantaneous frequency of the input signal and (v) to extract the signal information searched for. In order to evaluate its performance, the proposed approach has been firstly applied to a synthesized signal with known instantaneous amplitude and frequency evolution. Successively, in order to assess the reliability of HHT results with signals acquired on experimental circuits, the current flowing in an actual RLC circuit during its free natural oscillation has been analyzed. With the aim of analyzing the performance gained also in the presence of evident non-linearities, a saturable inductor has been introduced in the test circuit. Also in this case, by comparing the achieved results with those shown by different traditional approaches, great advantages have been experienced in terms of accuracy. Furthermore, beyond the accurate frequency representation, the experimental results evidenced the intrinsic ability of the proposed approach to extract meaningful information related to the knowledge of the underlying process. Finally, it is worth noting that the results reported in this paper requested no apriori knowledge about the signal/process under test.     

Control quality assessment using fractal persistence measures

Control Performance Assessment (CPA) has great practical importance. Control quality significantly affects final production throughput, efficiency and environmental impact. There are many approaches starting from time-domain methods, through Minimum Variance, Gaussian and non-Gaussian statistics up to alternative wavelet, fractal or entropy measures. Analysis of production data from process industry shows that signals are often described by non-Gaussian distributions, mostly fat-tail. On the other hand, simulations show that strong disturbances may significantly screen ability of proper detection. This work tests different approaches, i.e. Gaussian standard deviation and fat-tail distribution factors, integral indexes and focuses on persistence measures of rescaled range R/S plot. Robustness of above measures against disturbances with varying statistical properties is investigated. Results confirm that fractal measures may be applied as robust alternative to standard statistics.     

循环射流混合槽内压力脉动时间序列多尺度分析

为探讨循环射流混合槽(Circulating jet tank,CJT)内瞬态压力脉动的复杂性特性,采用动态数据采集系统对射流混合区内不同轴向、径向和周向位置的压力脉动信号(Pressure fluctuation signal,PFS)进行测量。根据PFS的标准差、峰度和偏度分布,优化PFS序列最佳样本数i=110 000。基于有限统计复杂性,比较综合法、动态法和静态法等三种时间序列符号化方法,得出综合法比动态法和静态法的适应性强,并确定最佳小波分解尺度。对CJT内各尺度的PFS进行有限统计复杂性和复杂度分析,发现CJT内PFS的两种复杂性分布趋势相似。通过对PFS多尺度分析发现:随着分解尺度的增加,复杂度先急剧衰减后趋于平稳,表明CJT内PFS随机性减弱周期性增强;PFS分解得到0~0.98 Hz低频A10尺度概貌信号的复杂度趋于0,揭示CJT内动力系统为整体稳定、局部不稳定的多尺度结构。     

A portable instrument for automatic detection and classification of telecommunication signals

In this paper, a new portable instrument for the analysis of telecommunication signals is proposed, which is able to: (i) observe a wideband in which even multiple signals can be present at different carrier frequencies; (ii) divide the observed wideband in smaller sub-bands and detect the presence of a signal in each sub-band; and (iii) recognize the modulation type of the detected signals, among the most common digital schemes, without requiring any knowledge about their parameters.The proposed instrument, completed with the signal-dependant measurement routines, represents a considerable advancement of the research among the instruments for telecommunication systems, as it is capable of working autonomously on unknown signals. Such feature avoids both the intervention of a skilled operator in setting up the measurement task, and make it ready to be used in the next generation telecommunication scenarios, where a more flexible use of the radio spectrum and a dynamic allocation of users are foreseen. The hardware architecture is based on a PXI data acquisition system and a laptop PC processing unit while the control software has been developed in LabVIEW. The paper proposal has been validated using actual signals in several scenarios emulating real world communications.     

Toggle mechanisms: Dynamics and energy dissipationDynamik,reibung und energieverluste beim kniehebelgetriebe

The dynamic performance of a toggle mechanism is investigated. Particular attention is given to (i) the collapse of the toggle in the presence of Coulomb friction, and (ii) the effect of a varying periodic force on the mechanism with damped elastic coupling. For case (i), a method utilizing both equations of motion and the kinetostatic analysis is outlined to solve for frictional torque and it is concluded that the performance of the mechanism under the influence of Coulomb friction depends highly upon the input energy to the system. It is shown that there is an optimum impulse speed almost equal to a defined version of the quasi-natural frequency of the system which can minimize the energy loss. For case (ii), a dimensionless grouping in terms of the forcing amplitude and the parameters of the system is found for determining the stability of the system. An approximate analytical solution for the time history of motion under the assumed condition is obtained.     

BLIND SOURCES SEPARATION APPLIED TO ROTATING MACHINES MONITORING BY ACOUSTICAL AND VIBRATIONS ANALYSIS

Blind Sources Separation (BSS) is a promising technique for signal processing and data analysis that allows the recovery of unknown signals (called sources) from observed signals mixed by an unknown propagation medium. The adjective ‘blind’ indicates that no assumption was done on the signals and the mixture. This lack of knowledge is compensated by assuming the independence of the source and the linearity of the propagation medium. We apply this technique to a test bench where various machines operate simultaneously in order to diagnose each element. So, by applying the superposition principle, the signals measured by every sensor positioned on each machine, are disrupted by the influence of other signals from the surrounding machines of the factory. Our goal was to remove the influence of the other machines, without having to stop them, which would be damaging for production. BSS methods provide an interesting alternative, since they permit in theory to solve our problem, i.e. to restore on every sensor the signature of its own machine. The sensor signals were assumed to be a convolutive mixture of independent signals arising from different physical phenomena. The method used is based on the N'guyen Jutten algorithm initially developed to separate speech signals. The algorithms used were adaptive and worked on the measured temporal signals from accelerometers or microphones. The signals were produced on a test bed carrying two low-power d.c. motors fixed to the same structure, whose speed of rotation could be varied. The signature received by each sensor therefore contained the contributions of the two motors. The results indicate that this approach can be successfully applied to these signals for vibration analysis; acoustical analysis is more complex and will be discussed in detail.     

Restoration of a temporal indicator specific to each vibratory sources for a predictive maintenance

The monitoring of rotating machinery is increasingly important for industry. Partly, it is made from indicators given by vibration analysis. These indicators give only the overall state of operation of the studied machine. Indeed, the piezoelectric sensors, which are used for vibration analysis, record the vibrations generated by the various components of the machine. Numerous studies have developed techniques for locating and quantifying the vibration sources from the recorded signals. Thus, it is legitimate to believe that these sources can give us an indicator which should be characteristic of the damage of each critical component and which should allow to follow the severity of a defect. This paper studies the feasibility (i) firstly, to restore an indicator (RMS value) for each component, (ii) secondly, to monitor the evolution of this indicator through the severity of the defect.     

The initiation of wear cracks

The relevance of fracture mechanics to wear is briefly discussed and the stress-raising effect of second-phase particles is cited as a possible mechanism for crack initiation. It is assumed that any inclusions present are rigid and elliptical, so that they may be made to approximate several morphologies. It is shown that (i) subsurface initiation is to be expected, (ii) shakedown stresses reduce the local stress found at an inclusion and (iii) the worst orientation of flake-like inclusions is perpendicular to the surface.     

Investigation of deep neural network with drop out for ultrasonic flaw classification in weldments

Ultrasonic signal classification of defects in weldment, in automatic fashion, is an active area of research and many pattern recognition approaches have been developed to classify ultrasonic signals correctly. However, most of the developed algorithms depend on some statistical or signal processing techniques to extract the suitable features for them. In this work, data driven approaches are used to train the neural network for defect classification without extracting any feature from ultrasonic signals. Firstly, the performance of single hidden layer neural network was evaluated as almost all the prior works have applied it for classification then its performance was compared with deep neural network with drop out regularization. The results demonstrate that given deep neural network architecture is more robust and the network can classify defects with high accuracy without extracting any feature from ultrasonic signals.     

A statistical characterization method for damping material properties and its application to structural-acoustic system design

The performance of surface damping treatments may vary once the surface is exposed to a wide range of temperatures, because the performance of viscoelastic damping material is highly dependent on operational temperature. In addition, experimental data for dynamic responses of viscoelastic material are inherently random, which makes it difficult to design a robust damping layout. In this paper a statistical modeling procedure with a statistical calibration method is suggested for the variability characterization of viscoelastic damping material in constrained-layer damping structures. First, the viscoelastic material property is decomposed into two sources: (i) a random complex modulus due to operational temperature variability, and (ii) experimental/model errors in the complex modulus. Next, the variability in the damping material property is obtained using the statistical calibration method by solving an unconstrained optimization problem with a likelihood function metric. Two case studies are considered to show the influence of the material variability on the acoustic performances in the structural-acoustic systems. It is shown that the variability of the damping material is propagated to that of the acoustic performances in the systems. Finally, robust and reliable damping layout designs of the two case studies are obtained through the reliability-based design optimization (RBDO) amidst severe variability in operational temperature and the damping material.     

Analysis of diametral strain in uniaxial tensile and compression testing of round specimens of anisotropic materials

The development of elliptical cross sections in initially round test pieces of anisotropic materials makes it difficult to measure the true strain on a cross section using a transverse extensometer. In this paper, an analysis is given of the diametral strain and strain rate on a round cross section. Based on the experimental observation that static and dynamic microstructural changes of many anisotropic materials was too small to cause a noticeable change in anisotropic factor, R, up to relatively low strain levels, it is assumed that R is independent of strain in this analysis. Analytical results suggest that, when both the imposed axial strain rate and the anisotropic factor R remain constant and R0.5, the change in diametral strain rate is negligible no matter which orientation a transverse strain extensometer is positioned on a cross section. The analysis includes two methods of measuring the diametral strain: (i) measurement of the distance between two diametral-intercept points on the circumference of a cross section; and (ii) measurement of the distance between two parallel tangent lines of the cross section. Based on the analytical and experimental results, a new method has been proposed for obtaining true stress–strain data in uniaxial tensile or compression testing of anisotropic materials with constant or varying anisotropic factor.     

Compliance of rough cylinders in compression

Compression of a rough turned cylinder between two hard, smooth, flat plates has been analysed with the aid of a mathematical model based on statistical analysis. It is assumed that the asperity peak heights follow Gaussian or normal and beta distribution functions and that the loaded asperities comply as though they are completely isolated from the neighbouring ones. Equations have been developed for the loadcompliance relation of the real surface using a simplified relation of the form W₀ = K₁ δⁿ for the load-compliance of a single asperity. Parameters K₁ and n have considerable influence on the load-compliance curve and they depend on the material, tip angle of the asperity, standard deviation of the asperity peak height distribution and the density of the asperities.     

门机机电状态综合监测与分析

针对500 t门座起重机（简称门机）的工作环境和工作特征,结合电气量信号和机械量信号对其进行状态监测和分析,同时对电气信号和机械信号进行监测.以PLC信号为分类标准,将机电信号分成不同工况,再通过统计学方法进行分析.以MATLAB为平台,综合利用了基于连接与嵌入对象的过程控制（OPC）通讯、统计质量控制等技术和方法对数据进行采集、处理和分析.由实验结果可知,通过分析和研究不同工况下机电信号之间的相关特性,可以准确地掌握门机的钢结构受力情况和动态特征.此外,通过基于PLC电气信号的工况分类,可以有效减少由于使用单一的判断标准而产生的误判断.最终达到提高诊断和评估的针对性、准确率的目的,同时也为今后门机设计、建造的改进提供可靠的依据.     

Parametric study of two-phase flow by integral analysis based on power law distribution

To understand the fluid dynamic forces acting on a structure subjected to two-phase flow, it is essential to obtain detail information on the characteristics of that flow. The distributions of flow parameters across a pipe, such as gas velocity, liquid velocity and void fraction, may be assumed to follow a power law (Cheng 1998; Serizawa et al. 1975). The void fraction profile is, for example, uniform for bubbly flow, whereas for slug flow it is more or less parabolic. In the present work, the average values of momentum flux, slip ratio and other parameters were derived by integral analysis, based on approximate power law distributions. A parametric study with various distributions was performed. The existing empirical formulations for average void fraction, proposed by Wallis (1969), Zuber et al. (1967) and Ishii (1976), were considered in the derivation of the present results. Notably, the unsteady momentum flux for slug flow was approximated.     

Dynamic plane-strain finite element simulation of industrial sheet-metal forming processes

A plane-strain implicit dynamic finite element formulation is applied for the analysis of sheet-forming processes. The bending model developed here uses an updated Lagrangian formulation based on incremental nonlinear shell theory which neglects the shear deformation but takes very large displacements and rotations into account. Hill's normally anisotropic yield criterion and associated flow rule are employed. The material is assumed to follow a power law of hardening with strain-rate sensitivity once the initial elastic limit strain is reached. The modified Coulomb law is used to model the interfacial friction. The frictional contact is treated by imposing the constraints directly into the tangent stiffness matrix. The Newton-Raphson algorithm is employed by considering the change in normal due to incremental displacements for contact nodes. Hermite cubic elements are used for the in-plane and out-of-plane displacements, resulting in four degrees of freedom at each node. The results from the developed formulation are found to be in good agreement with other numerical solutions and measured data. Applications are made to industry-scale problems using complex tool geometries with multiple curvatures.     

Time–frequency ratio-based blind separation methods for attenuated and time-delayed sources

We propose two types of time–frequency (TF) blind source separation (BSS) methods suited to attenuated and delayed (AD) mixtures. These approaches, inspired from a method that we previously developed for linear instantaneous (LI) mixtures, almost only require each source to occur alone in a tiny TF zone, i.e. they set very limited constraints on the source sparsity and overlap, unlike various previously reported TF-BSS methods. Our approaches consist in identifying the columns of the (filtered permuted) mixing matrix in TF zones where these methods detect that a single source occurs, using TIme–Frequency Ratios Of Mixtures (hence their name TIFROM). We thus identify columns of scale coefficients and time shifts. The detection stage for time shifts uses regression lines associated to the above-mentioned TF ratios of mixtures. The detection stage for scale coefficients uses the variance of these TF ratios of mixtures, either in Constant-Time or in Constant-Frequency analysis zones. This yields two alternative BSS methods, which are resp. called AD-TIFROM-CT and AD-TIFROM-CF. These methods are especially suited to non-stationary sources. We derive their performance from many tests performed with AD mixtures of speech signals. This demonstrates that they yield major SNR improvements, i.e. about 45 dB with optimum parameters for time shifts ranging from 0 to 20 samples and above 18 dB for 200-sample time shifts.     

AUTOREGRESSIVE MODEL AND POWER SPECTRUM CHARATERISTICS OF CURRENT SIGNAL IN HIGH FREQUENCY GROUP PULSE MICROELECTROCHEMICAL MACHINING

The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining (HGPECM) is mainly discussed. The auto-regressive(AR) model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green's function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum(CPS), to the current signals related to the different inter-electrode gap size in the range of 0-5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.