ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Historically, aircraft power monitoring has required the use of multiple signal conditioning functions to measure various parameters including voltage, current, frequency and phase. This information was then post processed to determine the characteristics of the 3-phase power quality on the aircraft. Recent developments in embedded DSP processors within signalconditioning systems provide the instrumentation engineer with expanded capabilities for realtime on-board power quality monitoring. Advantages include reduced space and bandwidth requirements and minimal wiring intrusion. For each phase, output data may include peak positive and negative voltages and currents, peak-to-peak, average and RMS voltages and currents, phase power (real and apparent), phase power factor, phase period (frequency), phase shift measurement from phase 1 (the reference phase) to phase 2, and from phase 1 to phase 3. In addition, a Fast Fourier Transform (FFT) is performed on each phase voltage to provide Total Harmonic Distortion measurements. This paper describes the methods employed in the implementation of these functions on a single signal-conditioning card in order to provide detailed information about the power quality of a three-phase aircraft power source.

Thesis (MEng)--Stellenbosch University, 2015. / AFRIKAANSE OPSOMMING: Raadpleeg die volteks vir opsomming, asseblief. / ENGLISH ABSTRACT: Please refer to full text for abstract

International Telemetering Conference Proceedings / October 30-November 02, 1989 / Town & Country Hotel & Convention Center, San Diego, California / The Naval Ocean Research and Development Activity (NORDA) has adapted the Loral Instrumentation Advanced Decommutation system (ADS 100) as a portable maintenance system for one of its remotely deployable buoy systems. This particular buoy system sends up to 128 channels of amplified sensor data to a centralized A/D for formatting and storage on a high density digital recorder. The resulting tapes contain serial PCM data in a format consistent with IRIG Standard 106-87. Predictable and correctable perturbations exist within the data due to the quadrature multiplexed telemetry system. The ADS 100 corrects for the perturbations of the telemetry system and provides the user with diagnostic tools to examine the stored data stream and determine the operational status of the buoy system prior to deployment.

International Telemetering Conference Proceedings / October 30-November 02, 1989 / Town & Country Hotel & Convention Center, San Diego, California / The Naval Ocean Research and Development Activity (NORDA) has adapted the Loral Instrumentation Advanced Decommutation system (ADS 100) as a portable maintenance system for one of its remotely deployable buoy systems. This particular buoy system sends up to 128 channels of amplified sensor data to a centralized A/D for formatting and storage on a high density digital recorder. The resulting tapes contain serial PCM data in a format consistent with IRIG Standard 106-87. Predictable and correctable perturbations exist within the data due to the quadrature multiplexed telemetry system. The ADS 100 corrects for the perturbations of the telemetry system and provides the user with diagnostic tools to examine the stored data stream and determine the operational status of the buoy system prior to deployment.

The main objective of this thesis is to obtain critical insight on the role of crystalline incompatibilities in strain and curvature, induced in presence of line defects i.e. dislocations and disclinations, on the energy and geometry of specific features of the local microstructure, and on the bulk mechanical response of nanocrystalline/ultra-fine grained materials. To that end, studies are performed at the (1) inter-atomic and fine scale, and (2) at the mesoscale. The modelling approach is based on the field dislocation and disclination mechanics theory of continuously representated dislocations and disclinations. New, thermodynamically rigorous, multi-scale elastic constitutive laws based on the couple stress theory are developed to capture the effect of strain and curvature incompatibilities on the Cauchy and couple stresses. A new meso-scale elasto-viscoplastic constitutive model of defect incompatibilities based on a fast Fourier transform technique is developed. The desired scale transitioning is achieved via novel phenomenological defect density transport equations and the newly developed elastic constitutive laws. At the fine scale, the model is applied to study energetic interactions between strain and curvature incompatibilities associated with grain boundaries and their influence on triple line energies. Results reveal that incompatible lattice strains have the most significant contribution to the energy. Incompatible lattice curvatures have negligible energetic contributions but are necessary to characterize the geometry of grain boundaries. Finally, both incompatible lattice strains and curvatures are necessary to capture the structure sensitive mechanical behavior of grain boundaries. At the mesoscale, deformation of nanocrystalline aggregates characterized by residual curvatures is studied to identify the impact of the latter's presence on the local and bulk mechanical response of the aggregate. Relaxation of local stresses generated from residual curvatures reproduces the effect of GB dislocation emission. Uniaxial tensile loading of nanocrystalline microstructures containing residual curvatures reveals a softening in the yield stress which could explain the breakdown in Hall-Petch law in the nanocrystalline regime. Next, the possibility of characterizing incompatibilities using X-ray or neutron diffraction techniques is tested. Results reveal that only strains and their gradients contribute to the broadening of diffraction peaks; curvatures and their gradients have no contribution. This study leads to the development of a new multi-scale averaged strain based Fourier technique for generating virtual diffraction peaks.

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / In any satellite communication, the Doppler shift associated with the satellite’s position and velocity must be calculated in order to determine the carrier frequency. If the satellite state vector is unknown then some estimate must be formed of the Doppler-shifted carrier frequency. One elementary technique is to examine the signal spectrum and base the estimate on the dominant spectral component. If, however, the carrier is spread (as in most satellite communications) this technique may fail unless the chip rate-to-data rate ratio (processing gain) associated with the carrier is small. In this case, there may be enough spectral energy to allow peak detection against a noise background. In this paper, we present a method to estimate the frequency (without knowledge of the Doppler shift) of a spread-spectrum carrier assuming a small processing gain and binary-phase shift keying (BPSK) modulation. Our method relies on a simple, averaged discrete Fourier transform along with peak detection. We provide simulation results indicating the accuracy of this method. In addition, we will describe an all-digital hardware design based around a Motorola DSP56303 and high-speed A/D which implements this technique in real-time. The hardware design is to be used in NMSU’s implementation of NASA’s demand assignment, multiple access (DAMA) service.

No description available.

The purpose of this thesis is to automate the online detection of weaving defects by a computerized system based on image processing software. Obviously, fabric inspection has an importance to prevent risk of delivering inferior quality product. Until recently, the visual defect detection is still under taken offline and manually by humans with many drawbacks such as tiredness, boredom, and, inattentiveness. Fortunately, the continuous development in computer technology introduces the online automated fabric inspection as an effective alternative. Because the defect-free fabric has a periodic regular structure, the occurrence of a defect in the fabric breaks the regular structure. Therefore, the fabric defects can be detected by monitoring fabric structure. In our work, Fast Fourier Transform and Cross-correlation techniques, i.e. linear operations, are first implemented to examine the structure regularity features of the fabric image in the frequency domain. To improve the efficiency of the technique and overcome the problem of detection errors, further thresholding operation is implemented using a level selection filter. Through this filter, the technique is able to detect only the actual or real defects and highlight their exact dimensions. A software package such as Matlab or Scilab is used for this procedure. It is implemented firstly on a simulated plain fabric to determine the most important parameters during the process of defect detection and then to optimize each of them even considering noise. To verify the success of the technique, it is implemented on real plain fabric samples with different colours containing various defects. Finally, a vision-based fabric inspection prototype that could be accomplished on-loom to inspect the fabric under construction with 100% coverage is proposed.

Cleaning validation of pharmaceutical manufacturing equipment is required by legislation. Generally, wet chemical techniques are employed using swabbing and/or rinse sampling methods. These are generally either selective and time consuming, or less selective and give results in a shorter period. The infrared reflection absorption spectroscopy (IRRAS) technique explored here attempts to deliver accurate, selective surface contamination information in real time to complement current methods and reduce down-time. The IRRAS instrument used in this research is a Fourier transform infrared (FTIR) spectrometer coupled by an IR fibre-optic cable to a grazing-angle sampling head with a fixed incidence angle of 80°. The introduced flexibility permits collection of in situ spectra from contaminated surfaces. Calibration models are developed using the multivariate, linear partial least squares (PLS) statistical method. The research focuses on sodium dodecyl sulfate (SDS), a model cleaning agent, on metal (aluminium and stainless steel) and dielectric (glass, EPDM and silicone) surfaces. The effects of surface finish are investigated for SDS on stainless steel. Calibrations for SDS and paracetamol in the presence of each other on glass surfaces are examined, as well as a common industrial cleaner (P3 cosa® PUR80) on polished stainless steel. For the calibration sets in this thesis, RMSECV values were < 0.41 µg cm⁻², corresponding to conservative surface residues detection limits of better than ~0.86 µg cm⁻². However, RMSECV values depend on the calibration loading range, and the detection limits were typically ~0.2 µg cm⁻² for loading ranges 0-2.5 µg cm⁻². These are below visual detection limits, generally taken to be 1-4 µg cm⁻², depending on the analyte and substrate. This shows that IRRAS is a viable method for the real-time detection and quantification of surface contamination by surfactants and active pharmaceutical ingredients on metals and dielectrics.

The dissertation considers an indirect approach for the estimation of the cointegrating parameters, in the sense that the estimators are jointly constructed along with estimating other nuisance parameters. This approach was proposed by Robinson (2008) where a bivariate local Whittle estimator was developed to jointly estimate a cointegrating parameter along with the memory parameters and the phase parameters (discussed in chapter 2). The main contributions of this dissertation is to establish, similar to Robinson (2008), a joint estimation of the memory, cointegrating and phase parameters in stationary and nonstationary fractionally cointegrated models in a multivariate framework. In order to accomplish such task, a general shape of the spectral density matrix, first noted in Davidson and Hashimzade (2008), is utilised to cover multivariate jointly dependent stationary long memory time series allowing more than one cointegrating relation (discussed in chapter 3). Consequently, the notion of the extended discrete Fourier transform is adopted based on the work of Phillips (1999) to allow for the multivariate estimation to cover the non stationary region (explained in chapter 4). Overall, the estimation methods adopted in this dissertation follows the semiparametric approach, in that the spectral density is only specified in a neighbourhood of zero frequency. The dissertation is organised in four self-contained chapters that are connected to each other, in additional to this introductory chapter: • Chapter 1 discusses the univariate long memory time series analysis covering different definitions, models and estimation methods. Consequently, parametric and semiparametric estimation methods were applied to a univariate series of the daily Egyptian stock returns to examine the presence of long memory properties. The results show strong and significant evidence of long memory in the Egyptian stock market which refutes the hypothesis of market efficiency. • Chapter 2 expands the analysis in the first chapter using a bivariate framework first introduced by Robinson (2008) for long memory time series in stationary system. The bivariate model presents four unknown parameters, including two memory parameters, a phase parameter and a cointegration parameter, which are jointly estimated. The estimation analysis is applied to a bivariate framework includes the US and Canada inflation rates where a linear combination between the US and Canada inflation rates that has a long memory less than the two individual series has been detected. • Chapter 3 introduces a semiparametric local Whittle (LW) estimator for a general multivariate stationary fractional cointegration using a general shape of the spectral density matrix first introduced by Davidson and Hashimzade (2008). The proposed estimator is used to jointly estimate the memory parameters along with the cointegrating and phase parameters. The consistency and asymptotic normality of the proposed estimator is proved. In addition, a Monte Carlo study is conducted to examine the performance of the new proposed estimator for different sample sizes. The multivariate local whittle estimation analysis is applied to three different relevant examples to examine the presence of fractional cointegration relationships. • In the first three chapters, the estimation procedures focused on the stationary case where the memory parameter is between zero and half. On the other hand, the analysis in chapter 4, which is a natural progress to that in chapter 3, adjusts the estimation procedures in order to cover the non-stationary values of the memory parameters. Chapter 4 expands the analysis in chapter 3 using the extended discrete Fourier transform and periodogram to extend the local Whittle estimation to non stationary multivariate systems. As a result, the new extended local Whittle (XLW) estimator can be applied throughout the stationary and non stationary zones. The XLW estimator is identical to the LW estimator in the stationary region, introduced in chapter 3. Application to a trivariate series of US money aggregates is employed.