A new algorithm for improving the accuracy of periodic signalanalysis

Digital periodic signal analysis often requires synchronized sampling with the signal being analyzed. In certain practical situations, however, this condition is difficult to satisfy. As a result, a number of undesirable effect such as the spectral leakage associated with the discrete Fourier transform (DFT), and the truncation errors in digital wattmeters arise and degrade system performance. This paper presents a new approach which attempts to remedy the underlying problem. The basic idea of the proposed method is to modify the actual sampled sequence such that it becomes an ideal sample sequence which is synchronized with the signal subjected to sampling. A simple algorithm for modifying the sampled sequence on-line is derived based on interpolation. The proposed approach requires quite modest additional computational burden which makes it suitable for real-time signal professing. To illustrate the practical applicability of the proposed algorithm, the paper considers two distinct but common cases. First, it shows how the proposed method can be used in the case of DFT analysis of harmonic signals, and secondly, it considers the digital wattmeter application area in electrical power-system measurement. Results show that the proposed algorithm is capable of reducing both the leakage effect in DFT analysis and truncation errors in digital wattmeters     

DESPLATE: an expert system for abnormal shape diagnosis in theplate mill

DESPLATE, an expert system designed to diagnose abnormal plan view shapes of steel plates in the plate mill, is described. A brief overview of the production process in the plate mill and the problems that motivate the development of DESPLATE are provided. The goal of DESPLATE is to locate the possible causes (such as electrical failures, mechanical breakdowns or wear, operational errors, and prerolling conditions) for a particular abnormal shape and to suggest appropriate remedies. A number of issues have arisen in the course of developing DESPLATE. Some of these issues are addressed, including the use of graphics for user interface, forward and backward chaining techniques, and knowledge acquisition methodologies from multiple experts from different disciplinary backgrounds     

Improving the measurement performance for a self-mixing interferometry-based displacement sensing system

Approaches that are, to our knowledge, novel, are proposed in this paper to improve the accuracy performance of self-mixing interferometry (SMI) for displacement measurement. First, the characteristics associated with signals observed in SMI systems are studied, based on which a new procedure is proposed for achieving accurate estimation of the laser phase. The studies also revealed the reasons for the inherent errors associated with the existing SMI-based techniques for displacement measurement. Then, this paper presents a new method for estimating the optical feedback level factor (denoted by C) in real time. Combining the new algorithms for estimating the laser phase and updating C value, the paper finally presents a novel technique for displacement measurement with improved accuracy performance in contrast to existing techniques. The proposed technique is verified by both simulation and experimental data.     

A centroid-based PWM switching technique for full-bridge inverterapplications

A novel centroid-based pulse-width-modulation (PWM) switching strategy is proposed which is suitable for full-bridge inverter applications. This method is evaluated, and its performance is compared with existing PWM switching strategies. The performance evaluation and comparison are based on the total harmonic distortion (THD) and number of pulses per cycle of the inverter output waveform. The objective of the new switching strategy is to minimize both the THD and low-order harmonics. Simulation results show that this technique yields a significant improvement in performance. In addition, a hybrid switching sequence is developed for the proposed scheme, which can lead to further reduction in switching losses     

Power system harmonic signal estimation and retrieval for activepower filter applications

This paper presents a new adaptive infinite impulse response (IIR) line enhancer (LE) comb filter configuration for the purpose of power system harmonic signal estimation and retrieval. The approximate maximum likelihood (AML) algorithm is employed for the parameter update. The proposed solution is characterised by modest computational burden, effective tracking capabilities and provides the retrieved harmonic components with little or no distortion. The retrieved power system harmonics may be obtained on an individual basis or as a composite signal. Practical test results are included which show the performance achieved by the proposed technique     

Study on Generalized Analysis Model for Fringe Pattern Profilometry

This paper presents a generalized analysis model for fringe pattern profilometry. We mathematically derived a new analysis model that gives a more general expression of the relationship between projected and deformed fringe patterns. Meanwhile, based on the proposed generalized model, a new algorithm is presented to retrieve 3-D surfaces from nonlinearly distorted fringes. Without any prior knowledge about the projection system, we still can obtain very accurate measurement results by using a generalized analysis model and a proposed algorithm. Computer simulation and experimental results show that the generalized model and the proposed algorithm can significantly improve the 3-D reconstruction precision, especially when the projected fringe pattern is nonlinearly distorted.     

A constrained notch Fourier transform

The paper presents a new sliding algorithm for estimating the amplitude and phase of the Fourier coefficients of noise corrupted harmonic signals given a priori knowledge of the signal frequencies. The proposed method is similar in principle to the notch Fourier transform (NFT) technique suggested by Tadokoro et al. [1987] except that it employs an infinite impulse response (IIR) rather than a finite impulse response (FIR) notch filter parameterization. This modification provides bandwidth controlled bandpass (BP) filters whose center frequencies are equally spaced in the frequency spectrum. In this sense, the proposed technique can be regarded as a constrained notch Fourier transform (CNFT). Sliding algorithms have been derived for both the NFT and CNFT for the purpose of estimating the Fourier coefficients of the sinusoidal components. The paper also proposes a similar algorithm to the CNFT for the signals containing sinusoids at arbitrary known frequencies. The main feature of the modified CNFT is that it uses second-order IIR BP filters whose bandwidth and center frequency can be adjusted independently. The bandwidth control aspect provides the user with an efficient means of achieving the required resolution as well as reducing spectral leakage. In general, the proposed approach leads to considerable reduction in terms of computational burden and memory storage     

Estimating the parameters of semiconductor lasers based on weak optical feedback self-mixing interferometry

The paper presents a practical approach for measuring the linewidth enhancement factor /spl alpha/ of semiconductor lasers and the optical feedback level factor C in a semiconductor laser with an external cavity. The proposed approach is based on the analysis of the signals observed in an optical feedback self-mixing interferometric system. The parameters /spl alpha/ and C are estimated using a gradient-based optimization algorithm that achieves best data-to-theoretical model match. The effectiveness and accuracy of the method has been confirmed and tested by computer simulations and experiments, which show that the proposed approach is able to estimate /spl alpha/ and C with an accuracy of 6.7% and 4.63%, respectively.     

Neural network digital fringe calibration technique for structured light profilometers

We present a novel neural network signal calibration technique to improve the performance of triangulation-based structured light profilometers based on digital projection. The performance of such profilometers is often hindered by the capture of aberrated pattern intensity distributions, and hence we address this problem by employing neural networks in a signal mapping approach. We exploit the generalization and interpolation capabilities of a feed-forward backpropagation neural network to map from distorted fringe data to nondistorted data. The performance of the calibration technique is gauged both through simulation and experimentation, with simulation results indicating that accuracy can be improved by more than 80%. The technique requires just one image cross section for calibration and hence is ideal for rapid profiling applications.     

Principles and realizations of FBG wavelength tuning with elastic beams

FiberBragggrating(FBG)isasignificanttechnology thatisusedtodesignkeydevicesorcomponentsinthesystemsoffibercommunicationandfibersensing[1], suchastunablefiberlasers[2],WDW/DM[3],WADM[4],tunablefiberfilter[5],fiberdispersioncom pensation[6],gainflattingofEDFA[7],FBG typeinter ferometer[8]andfibergratingsensors[9,10].OneofthekeyresearchissuesonFBGdevicesistomakethetun ingwavelengthdeviceswhichhavegoodcharacteristics ofwidetunablewavelengthrange,stableoutput,goodmultiplexingcapability. …