Xiandong Ma

Interpretation of wavelet analysis and its application in partial discharge detection

The objective of the paper is to discuss a tool which is proving extremely efficient in partial discharge measurement studies. Though the technique itself is not new, its application to partial discharge studies is. It will be demonstrated in this paper that it has tremendous power and this accounts for its rapid growth as an application in this field. The paper begins with the description of the fundamentals of wavelet analysis, wavelet categories and the properties of the associated wavelet transforms. PD pulses as acquired from detectors composed of different detection circuits are investigated and numerically simulated, and a method on how to select optimally the wavelet corresponding to the representative forms of PD pulse is then presented. Finally, applications of wavelet analysis to partial discharge studies are explored. The paper demonstrates that the wavelet based denoising method proposed in the paper can be employed in separating PD pulses from electrical noise successfully and can be used in pulse propagation studies of partial discharge in distributed impedance plant to provide enhanced information and further infer the original site of the PD pulse.

Automated wavelet selection and thresholding for PD detection

Presents a discussion of some important and unresolved issues related to previous work to provide a more comprehensive understanding of the practicability of wavelet-based denoising.

Hardware and software design for an electromagnetic induction tomography (EMT) system for high contrast metal process applications.

This paper presents the latest development of an EMT system designed for use in the metal production industry such as imaging molten steel flow profiles during continuous casting. The system that has been developed is based on a commercial data acquisition board residing in a PC host computer and programmed in the LabView graphical language. The paper reviews the new EMT hardware electronics and software. The noise effects and the detectability limits of the system are given in the paper followed by the system sensitivity map analysis. Optimal image reconstructions, including the simultaneous iterative reconstruction technique (SIRT) and non-iterative Tikhonov regularization, truncated singular value decomposition (TSVD), are also discussed and applied for the system. The system has been demonstrated in real time (10 frames s−1 for 5 kHz excitation) with test phantoms that represent typical metal flow profiles such as central, annular stream and multiple streams.

A three-dimensional inverse finite-element method applied to experimental eddy-current imaging data

Eddy-current techniques can be used to create electrical conductivity mapping of an object. The eddy-current imaging system in this paper is a magnetic induction tomography (MIT) system. MIT images the electrical conductivity of the target based on impedance measurements from pairs of excitation and detection coils. The inverse problem here is ill-posed and nonlinear. Current state-of-the-art image reconstruction methods in MIT are generally based on linear algorithms. In this paper, a regularized Gauss-Newton scheme has been implemented based on an edge finite-element forward solver and an efficient formula for the Jacobian matrix. Applications of Tikhonov and total variation regularization have been studied. Results are presented from experimental data collected from a newly developed MIT system. The paper also presents further progress in using an MIT system for molten metal flow visualization in continuous casting by applying the proposed algorithm in a real experiment in a continuous casting pilot plant of Corus RD&T, Teesside Technology Centre.

Dynamic imaging in electrical capacitance tomography and electromagnetic induction tomography using a Kalman filter

Electrical capacitance tomography (ECT) and electromagnetic induction tomography (EMT) attempt to visualize the distributions of materials with different permittivity and conductivity/permeability, aiming to reveal electrical and magnetic characteristics of an object, by measuring electrical capacitance and electromagnetic inductance on the periphery of the object. In ECT, capacitances of pairs of electrodes placed around the periphery are measured and in EMT, mutual induction of pairs of coils is measured. In this paper, a dynamic imaging technique is developed for ECT and EMT with a linearized Kalman filter to improve the temporal resolution of images. The inverse problem is treated as a state estimate. A Kalman estimator is used to obtain the material distribution. Experimental results demonstrate that the dynamic imaging technique can improve the spatio-temporal resolution of both ECT and EMT.

Electromagnetic techniques for imaging the cross-section distribution of molten steel flow in the continuous casting nozzle

Control of molten steel delivery through the pouring nozzle is critical to ensure an optimum laminar flow pattern in continuous casting, which influences the surface quality, cleanliness, and hence the value of the cast product. A nonintrusive and nonhazardous visualization technique, which uses rugged and noninvasive sensors, would be highly desirable in such harsh industrial production environments. This paper presents an electromagnetic approach for tomographically visualizing the molten steel distribution within a submerged entry nozzle (SEN). The tomographic system consists of an eight-coil sensor array, data acquisition unit, associated conditioning circuitry, and a PC computer, which have been purposely designed and constructed for hot trials. The paper starts with an overview of electromagnetic imaging techniques. The construction of the sensor array and associated electronics are then discussed, followed by sensitivity map analysis and a description of the applied image reconstruction algorithm. Image results, as reconstructed from cold sample measurements and hot pilot plant trials, are also presented. Despite a low frame acquisition rate (1.35s per frame), the images generated from the prototype system are capable of providing an adequate representation of the changes of real molten steel flow profiles within the SEN. The paper demonstrates that the application of electromagnetic tomographic technique to this problem shows significant promise for future industrial processes.

A Digital Method for the Discrimination of Neutrons and

A digital method for the discrimination of neutron and γ-ray events from an organic scintillator has been investigated by using frequency gradient analysis (FGA) based on the Fourier transform. Since the scintillation process and the photomultiplier tube (PMT) anode signal are often very noisy, most pulse-shape discrimination methods in a scintillation detection system (e.g., the charge comparison (CC) method or pulse gradient analysis (PGA)) using time-domain features of the signal depend greatly on the associated de-noising algorithm. In this research, the performance of the new FGA method and the PGA method have been studied and compared on a theoretical basis and then verified by time-of-flight (TOF). The frequency-domain features extracted by the FGA method exhibit a strong insensitivity to the variation in pulse response of the photomultiplier tube (PMT) and can be used to discriminate neutron and γ-ray events in a mixed radiation field. It is shown that the FGA method results in an increased figure of merit (FOM) which corresponds to a reduction in the area of overlap between neutron and γ-ray events. The FGA method has the potential to be implemented in current embedded electronic systems to provide real-time discrimination in standalone instruments.

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This paper presents recent developments in the use of electromagnetic induction tomography (EMT) for steel flow visualization. Several aspects are reported. First, results are shown from an 8-coil, single-frequency, EMT system from tests using liquid steel. The results are consistent with video recordings of an exposed section of the steel flow passing through a submerged entry nozzle, in terms of flow size and position, providing a good representation of the steel flow profile changes during trials. The second part describes the development of a system with a C-shaped sensor, which is capable of being slotted in place for practical deployment as well as being rapidly removed during nozzle changes. The effects of reducing the number of coils in this configuration were also studied. Finally, the development of a multiple-frequency system for plant use is reported. The system is designed based on a commercial data acquisition board, which can provide three sinusoidal signals with target frequencies for excitation simultaneously. This paper describes the new hardware electronics and software. Experimental results show that the system is able to identify a variety of test samples. Instead of imaging the cross-section of the steel flow profiles, the current system is developed for checking signal levels at different operation frequencies, which are of more interest for industrial use. Nevertheless, the work demonstrates a significant step forward to develop a multiple-frequency EMT system for practical use in this industrial process application.

Rays With Organic Scintillation Detectors Using Frequency Gradient Analysis

This paper reports the results of an investigation of an intelligent DSP-based PD analyzer using wavelet analysis for partial discharge characterisation. The basic theory of wavelet transform is firstly introduced followed by an analysis of the possible applications of the wavelet transform in partial discharge analysis. The practical implementation of such a novel DSP analyzer is then proposed. The advantages of the proposed approach are discussed.

Development of multiple frequency electromagnetic induction systems for steel flow visualization

This paper will study condition monitoring signals of a distributed generation (DG) system not only due to the mechanical and electrical faults inside the wind turbines but also due to the grid system fluctuations. A novel feature extraction and characterisation method based on singularity detection of the monitoring data will be presented, aiming to identify the abnormal events and fault conditions as early as possible. The algorithm used to calculate Lipschitz values is given in the paper and efficient processing and storage of monitoring data is also discussed. The preliminary research has produced promising results.