Novel Series Resonant High-Voltage Dc-Dc Converter Topologies For X-Ray Systems

Conventional pulse-frequency-modulated (PFM) series resonant high-voltage (HV) direct-current (DC) power supplies have the limitations of poor controllability at light load, high conduction loss, large output voltage ripple, slow transient response and high current stress on circuit components at low switching frequencies. This thesis proposes four novel topologies of HV DC-DC converters, namely, ZCSSR (zero current switching - series resonant) inverter-fed, ZCS-SR inverter-fed voltage multiplier (VM) based, ZCS-DSR (zero current switching - double series resonant) inverter-fed and ZCS-DSR inverter-fed VM based. First and second topologies are controlled by using digital tuning of tank capacitance and variable pulse frequency with dual-mode operation. Third and fourth topologies are controlled by PFM with dual-mode operation. The effectiveness of all the proposed power converter topologies and corresponding control scheme are verified by simulation and experimental results. First and second converters have superior performances compared to the conventional PFM converter in terms of their wider range of output voltage controllability, lower percent ripple, lower current stress on circuit components and higher efficiency. The main features of third and fourth proposed converters are that they are highly efficient and have very simple circuit operations. Among all the proposed converters, the ZCS-SR inverter-fed VM based HV DC-DC converter is the best choice for X-ray systems with the power range from 100W to 350W. The measured efficiency at 100W is 87% and 92% at 350W

Switched-battery boost-multilevel inverter with GA optimized SHEPWM for standalone application

This paper presents a boost-multilevel inverter design with integrated battery energy storage system for standalone application. The inverter consists of modular switched-battery cells and a full-bridge. It is multifunctional and has two modes of operation: the charging mode which charges the battery bank and the inverter mode which supplies AC power to the load. This inverter topology requires significantly less power switches compared to conventional topology such as cascaded H-bridge multilevel inverter, leading to reduced size/cost and improved reliability. To selectively eliminate low-order harmonics and control the desired fundamental component, nonlinear system equations are represented in fitness function through the manipulation of modulation index and the Genetic Algorithm is employed to find the optimum switching angles. A 7-level inverter prototype is implemented and experimental results are provided to verify the feasibility of the proposed inverter design

Active Neutral Point-Clamped Five-Level Inverter With Single-Stage Dynamic Voltage Boosting Capability

The circuit performance of conventional active neutral point-clamped (ANPC) inverter is widely accepted in many renewable energy-based applications like photovoltaic (PV) or electric vehicle grid-connected systems. This is mainly because of its excellent characteristics in terms of voltage/current stress profile of the switches, bidirectional power flow capability, and efficient operation. Nonetheless, due to its half-dc link voltage utilization in the ac output voltage, another power processing stage with additional active and passive elements is required to make its output voltage compatible with the grid when low and wide varying input dc source is available. In this paper, a novel ANPC-based five-level (ANPC5L) inverter with a single-stage boost-integrated circuit design is presented. The proposed topology is able to make the peak output voltage of the conventional ANPC5L inverter followed by a front-end bidirectional boost converter double using the same number of power switches but with less total standing voltage across semiconductors. The working principles of the proposed topology is discussed. Experimental results obtained from 1.3 kW laboratory-built prototype under the grid-connected condition are also given to support the discussion

Mindfulness-based cognitive therapy v. group psychoeducation for people with generalised anxiety disorder: randomised controlled trial

Background: Research suggests that an 8-week mindfulness-based cognitive therapy (MBCT) course may be effective for generalised anxiety disorder (GAD). Aims: To compare changes in anxiety levels among participants with GAD randomly assigned to MBCT, cognitive–behavioural therapy-based psychoeducation and usual care. Method: In total, 182 participants with GAD were recruited (trial registration number: CUHK_CCT00267) and assigned to the three groups and followed for 5 months after baseline assessment with the two intervention groups followed for an additional 6 months. Primary outcomes were anxiety and worry levels. Results: Linear mixed models demonstrated significant group × time interaction (F(4,148) = 5.10, P = 0.001) effects for decreased anxiety for both the intervention groups relative to usual care. Significant group × time interaction effects were observed for worry and depressive symptoms and mental health-related quality of life for the psychoeducation group only. Conclusions: These results suggest that both of the interventions appear to be superior to usual care for the reduction of anxiety symptoms

Predictive direct power control for dual-active-bridge multilevel inverter based on conservative power theory

This paper explores the feasibility of multilevel dual-active bridge-inverter (DABMI) applications for grid-connected applications of a modern Model of Predictive Direct Power Control (MPDPC) based on the conservative power theory (CPT). In the case of unbalanced grid voltages, the objective of the study is to promote continued active and reactive energy in MPDPC without reducing effciency such as transient response and current harmonics. The nature of the instantaneous p-q theory permits only one out of three control targets to be fulfilled. The proposed control approached directly regulates the instantaneous active and reactive power to achieve three particular control objectives namely sinusoidal and symmetrical grid current, cancelling twice of fundamental grid frequency reactive power ripples, and removing twice grid frequency active power ripple. The techniques of complicated Grid part sequence extraction are unnecessary and improved at no extra expense, as is the case with current MPDPC fault-tolerant approaches. The instantaneous power at the next sampling instant is predicted with the newly developed discrete-time model. Each possible switching state will then be evaluated in the cost function defined until the optimal state which lead to the minimum power errors is determined. In MATLAB/Simulink simulation, the proposed CPT-based MPDPC measures reliability and performance at balanced and unbalanced grid voltages then compared with the conventional and existing MPDPC The proposed method manages to achieve all of three control targets which generates sinusoidal grid currents and attenuates active and reactive power ripple of twice the grid frequency exactly at the same time without losing its critical effciency including transient reaction and current harmonics

Induced Metric And Matrix Inequalities On Unitary Matrices

Recently, Chau [Quant. Inform. & Comp. 11, 721 (2011)] showed that one can define certain metrics and pseudo-metrics on U(n), the group of all $n\times n$ unitary matrices, based on the arguments of the eigenvalues of the unitary matrices. More importantly, these metrics and pseudo-metrics have quantum information theoretical meanings. So it is instructive to study this kind of metrics and pseudo-metrics on U(n). Here we show that any symmetric norm on ${\mathbb R}^n$ induces a metric on U(n). Furthermore, using the same technique, we prove an inequality concerning the eigenvalues of a product of two unitary matrices which generalizes a few inequalities obtained earlier by Chau [arXiv:1006.3614v1].Comment: 6 pages, extensively rewritten with an earlier error fixed. It generalizes and simplifies the mathematical results concerning certain matrix inequalities originally reported in arXiv:1006.3614v1. To appear in J.Phys.

Person Verification Based on Multimodal Biometric Recognition

Nowadays, person recognition has received significant attention due to broad applications in the security system. However, most person recognition systems are implemented based on unimodal biometrics such as face recognition or voice recognition. Biometric systems that adopted unimodal have limitations, mainly when the data contains outliers and corrupted datasets. Multimodal biometric systems grab researchers’ consideration due to their superiority, such as better security than the unimodal biometric system and outstanding recognition efficiency. Therefore, the multimodal biometric system based on face and fingerprint recognition is developed in this paper. First, the multimodal biometric person recognition system is developed based on Convolutional Neural Network (CNN) and ORB (Oriented FAST and Rotated BRIEF) algorithm. Next, two features are fused by using match score level fusion based on Weighted Sum-Rule. The verification process is matched if the fusion score is greater than the pre-set threshold t. The algorithm is extensively evaluated on UCI Machine Learning Repository Database datasets, including one real dataset with state-of-the-art approaches. The proposed method achieves a promising result in the person recognition system