On-line signal analysis of partial discharges in medium-voltage power cables

Partial discharges are symptomatic of many degradation phenomena in power cables and may cause further deterioration of the insulation in many cases. Electrical im- pulses, generated by partial discharges, travel towards the cable ends, and can there be detected using appropriate sensors. Continuous monitoring of the insulation con- dition can be achieved by on-line detection and location of partial discharge (PD) signals. An important aspect of such a diagnostic is the analysis of on-line measure- ments. The research reported in this thesis is aimed at analysis of PD signals from on-line measurements and location of discharge sites. Signal analysis depends on knowledge of both signals and disturbances that are to be expected. To that end, characteristics of PD signals in medium voltage cables are studied in this thesis. The result of this study is a signal model of the propagation path between the discharge site and the sensors. The model accounts for cable sections with di®erent properties, and incorporates the propagation channel load impedances, i.e. the equipment to which a cable is terminated in an on-line situation. The exact propagation properties and load impedances depend on the speci¯c cable connection under test, and are unknown a priori. For this reason, research is conducted on meth- ods that enable experimental characterization of the parameters, by evaluating the response of the cable to applied transients. The presented methods rely on the ex- traction of pulses that are re°ected on impedance transitions within the cable system under test. On-line ¯eld measurements are corrupted by noise and interference, which impede PD signal detection and location. Generally, narrowband interferences resulting from radio broadcasts dominate the measurements, thus prohibiting data-acquisition trig- gered by PD signals. Broadband background noise is present within the entire PD signal bandwidth, and therefore poses a fundamental limit on PD signal analysis. Generally, existing extraction techniques for PD signals only partially exploit a priori knowledge of both signals and interference. In this thesis, matched ¯lters are ap- plied that are derived from the signal model, and are optimally adapted to the signals that can be expected. Besides signal extraction, matched ¯lters provide a means to estimate the PD magnitude and the signal arrival time. Likewise, discharge location methods based on the signal model are proposed, resulting in optimal location esti- mators. Computer simulations illustrate the e®ectiveness of the proposed algorithms and show that the attainable accuracy can be speci¯ed by theoretical bounds. Accurate PD location relies on estimation of the di®erence in arrival times of signals originating from the same discharge. In case of on-line detection, the cable is connected to the grid, and signals are not necessarily re°ected at the cable ends. Therefore signal detection at both sides is generally required for the purpose of dis- charge location. Synchronization of the measurement equipment is achieved using pulses that are injected into the cable connection. Finite-energy disturbances, such as PD signals that originate outside the cable connection under test, frequently occur in on-line situations. Since measurements are synchronously conducted at both cable ends, pulses originating within and outside the cable can be distinguished by examining the di®erence in time of arrival. Moreover, in many situations, the signal direction of arrival can be determined by detecting pulses in two di®erent current paths at a cable termination. This method is applied as an additional technique to discriminate PD signals and disturbances. Based on the results of research, a measurement system is proposed, which enables automated on-line PD detection and location in medium voltage cable connections. The conceptual design is validated by experiments, and the results demonstrate that the practical application is promising

Time domain reflectometry imaging - A new moisture measurement technique for industry and soil science

This thesis describes the theoretical and practical aspects of a new technique for quantitative, non-invasive and non-destructive imaging of the near-surface moisture content distribution of composite materials. The technique relies on the alteration by a nearby composite material, of the propagation velocity of an electromagnetic pulse along a parallel transmission line, through distortion of the evanescent field. A set of measurements taken at different relative positions of the transmission line and composite material are, in conjunction with a forward model describing propagation velocity on the line, inverted to provide the image of moisture content distribution. Development of the technique, called 'Time Domain Reflectometry Imaging' (TDRI), involved four steps: 1. Instrumentation to obtain a set of measurements of propagation times; 2. A forward model; 3. An inverse procedure; and 4. Conversion of a calculated permittivity distribution to a moisture distribution. Critical to the success of the inverse method is a set of measurements of propagation velocity that provide pico-second propagation time accuracy, and are sufficiently linearly independent to enable discrimination of the permittivity of each discretised cell within the composite material. Using commercial time domain reflectometry (TDR) instruments, a switched reference measurement, waveform subtraction and intersecting waveform tangents, sufficient timing accuracy has been achieved. The forward model was developed using the moment method. The advantage of such an integral equation method is that recalculation is not required when changing the impressed field. Hence for a particular model of the composite material's moisture distribution, just one execution of the forward model provides predicted propagation velocities for all positions of the transmission line. A new pseudo 3-D variant of the volume integral equation approach was developed to suit the 2-D transmission line, and resulted in a 100 fold reduction in memory use, and a greater than 10 fold reduction in execution time. The forward solution uses the telegrapher's equation to predict propagation velocity from an arbitrary permittivity distribution surrounding the line. Inversion of the measured data was accelerated by the use of three novel tactics: a rapid electric field surrogate for the Jacobian; a dynamic method of determining the conjugate gradient weighting factor; and a new blocking technique that accelerated the convergence of buried cells that have only a small influence on propagation velocity. The final TDRI step is a numerical model to translate both the a priori moisture distribution data to a permittivity distribution, and conversely the solution permittivity distribution to moisture content. A dielectric model based on an earlier model of Looyenga was adapted to include both the different characteristic of tightly held water, and the Debye relaxation of free water. The intention was a model with applicability to a range of composite materials. It was tested with data for soil, bentonite clay and wood, and except for one free parameter, model parameters were set by measurable physical properties of the host material

Community Detection as an Inference Problem

We express community detection as an inference problem of determining the most likely arrangement of communities. We then apply belief propagation and mean-field theory to this problem, and show that this leads to fast, accurate algorithms for community detection.Comment: 4 pages, 2 figure

Regularized Newton Methods for X-ray Phase Contrast and General Imaging Problems

Like many other advanced imaging methods, x-ray phase contrast imaging and tomography require mathematical inversion of the observed data to obtain real-space information. While an accurate forward model describing the generally nonlinear image formation from a given object to the observations is often available, explicit inversion formulas are typically not known. Moreover, the measured data might be insufficient for stable image reconstruction, in which case it has to be complemented by suitable a priori information. In this work, regularized Newton methods are presented as a general framework for the solution of such ill-posed nonlinear imaging problems. For a proof of principle, the approach is applied to x-ray phase contrast imaging in the near-field propagation regime. Simultaneous recovery of the phase- and amplitude from a single near-field diffraction pattern without homogeneity constraints is demonstrated for the first time. The presented methods further permit all-at-once phase contrast tomography, i.e. simultaneous phase retrieval and tomographic inversion. We demonstrate the potential of this approach by three-dimensional imaging of a colloidal crystal at 95 nm isotropic resolution.Comment: (C)2016 Optical Society of America. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modifications of the content of this paper are prohibite

An approach for selecting cost estimation techniques for innovative high value manufacturing products

This paper presents an approach for determining the most appropriate technique for cost estimation of innovative high value manufacturing products depending on the amount of prior data available. Case study data from the United States Scheduled Annual Summary Reports for the Joint Strike Fighter (1997-2010) is used to exemplify how, depending on the attributes of a priori data certain techniques for cost estimation are more suitable than others. The data attribute focused on is the computational complexity involved in identifying whether or not there are patterns suited for propagation. Computational complexity is calculated based upon established mathematical principles for pattern recognition which argue that at least 42 data sets are required for the application of standard regression analysis techniques. The paper proposes that below this threshold a generic dependency model and starting conditions should be used and iteratively adapted to the context. In the special case of having less than four datasets available it is suggested that no contemporary cost estimating techniques other than analogy or expert opinion are currently applicable and alternate techniques must be explored if more quantitative results are desired. By applying the mathematical principles of complexity groups the paper argues that when less than four consecutive datasets are available the principles of topological data analysis should be applied. The preconditions being that the cost variance of at least three cost variance types for one to three time discrete continuous intervals is available so that it can be quantified based upon its geometrical attributes, visualised as an n-dimensional point cloud and then evaluated based upon the symmetrical properties of the evolving shape. Further work is suggested to validate the provided decision-trees in cost estimation practice

A Novel A Priori Simulation Algorithm for Absorbing Receivers in Diffusion-Based Molecular Communication Systems

A novel a priori Monte Carlo (APMC) algorithm is proposed to accurately simulate the molecules absorbed at spherical receiver(s) with low computational complexity in diffusion-based molecular communication (MC) systems. It is demonstrated that the APMC algorithm achieves high simulation efficiency since by using this algorithm, the fraction of molecules absorbed for a relatively large time step length precisely matches the analytical result. Therefore, the APMC algorithm overcomes the shortcoming of the existing refined Monte Carlo (RMC) algorithm which enables accurate simulation for a relatively small time step length only. Moreover, for the RMC algorithm, an expression is proposed to quickly predict the simulation accuracy as a function of the time step length and system parameters, which facilitates the choice of simulation time step for a given system. Furthermore, a rejection threshold is proposed for both the RMC and APMC algorithms to significantly save computational complexity while causing an extremely small loss in accuracy.Comment: 11 pages, 14 figures, submitted to IEEE Transactions on NanoBioscience. arXiv admin note: text overlap with arXiv:1803.0463