A Fast Diagnosis Method for Both IGBT Faults and Current Sensor Faults in Grid-Tied Three-Phase Inverters With Two Current Sensors

© 1986-2012 IEEE. This article considers fault detection in the case of a three-phase three-wire (3P3W) inverter, when only two current sensors are used to save cost or due to a faulty current sensor. With two current sensors, there is no current method addressing the diagnosis of both IGBT open-circuit (OC) faults and current sensor faults. In order to solve this problem, this article proposes a method which innovatively combines two kinds of diagnosis variables, line voltage deviations and phase voltage deviations. The unique faulty characteristics of diagnosis variables for each fault are extracted and utilized to distinguish the fault. Using an average model, the method only needs the signals already available in the controller. Both IGBT OC faults and current sensor faults can be detected quickly in inverter mode and rectifier mode, so that the converter can be protected in a timely way to avoid further damages. In addition, error-adaptive thresholds are adopted to make the method robust. Effects such as system unbalance are analyzed to ensure that the method is robust and feasible. Simulation and experimental results are used to verify and validate the effectiveness of the method

A wavelet-fuzzy based algorithm for condition monitoring and fault detection of a voltage source inverter.

Abstract Not Provided

Industrial and Technological Applications of Power Electronics Systems

The Special Issue "Industrial and Technological Applications of Power Electronics Systems" focuses on: - new strategies of control for electric machines, including sensorless control and fault diagnosis; - existing and emerging industrial applications of GaN and SiC-based converters; - modern methods for electromagnetic compatibility. The book covers topics such as control systems, fault diagnosis, converters, inverters, and electromagnetic interference in power electronics systems. The Special Issue includes 19 scientific papers by industry experts and worldwide professors in the area of electrical engineering

Research and development of diagnostic algorithms to support fault accommodating control for emerging shipboard power system architectures

The U.S. Navy has proposed development of next generation warships utilising an increased amount of power electronics devices to improve flexibility and controllability. The high power density finite inertia network is envisioned to employ automated fault detection and diagnosis to aid timely remedial action. Integration of condition monitoring and fault diagnosis to form an intelligent power distribution system is anticipated to assist decision support for crew while enhancing security and mission availability. This broad research being in the conceptual stage has lack of benchmark systems to learn from. Thorough studies are required to successfully enable realising benefits offered by using increased power electronics and automation. Application of fundamental analysis techniques is necessary to meticulously understand dynamics of a novel system and familiarisation with associated risks and their effects. Additionally, it is vital to find ways of mitigating effects of identified risks. This thesis details the developing of a generalised methodology to help focus research into artificial intelligence (AI) based diagnostic techniques. Failure Mode and Effects Analysis (FMEA) is used in identifying critical parts of the architecture. Sneak Circuit Analysis (SCA) is modified to provide signals that differentiate faults at a component level of a dc-dc step down converter. These reliability analysis techniques combined with an appropriate AI-algorithm offer a potentially robust approach that can potentially be utilised for diagnosing faults within power electronic equipment anticipated to be used onboard the novel SPS. The proposed systematic methodology could be extended to other types of power electronic converters, as well as distinguishing subsystem level faults. The combination of FMEA, SCA with AI could also be used for providing enhanced decision support. This forms part of future research in this specific arena demonstrating the positives brought about by combining reliability analyses techniques with AI for next generation naval SPS.The U.S. Navy has proposed development of next generation warships utilising an increased amount of power electronics devices to improve flexibility and controllability. The high power density finite inertia network is envisioned to employ automated fault detection and diagnosis to aid timely remedial action. Integration of condition monitoring and fault diagnosis to form an intelligent power distribution system is anticipated to assist decision support for crew while enhancing security and mission availability. This broad research being in the conceptual stage has lack of benchmark systems to learn from. Thorough studies are required to successfully enable realising benefits offered by using increased power electronics and automation. Application of fundamental analysis techniques is necessary to meticulously understand dynamics of a novel system and familiarisation with associated risks and their effects. Additionally, it is vital to find ways of mitigating effects of identified risks. This thesis details the developing of a generalised methodology to help focus research into artificial intelligence (AI) based diagnostic techniques. Failure Mode and Effects Analysis (FMEA) is used in identifying critical parts of the architecture. Sneak Circuit Analysis (SCA) is modified to provide signals that differentiate faults at a component level of a dc-dc step down converter. These reliability analysis techniques combined with an appropriate AI-algorithm offer a potentially robust approach that can potentially be utilised for diagnosing faults within power electronic equipment anticipated to be used onboard the novel SPS. The proposed systematic methodology could be extended to other types of power electronic converters, as well as distinguishing subsystem level faults. The combination of FMEA, SCA with AI could also be used for providing enhanced decision support. This forms part of future research in this specific arena demonstrating the positives brought about by combining reliability analyses techniques with AI for next generation naval SPS

SILOS: An Intelligent Fault Detection Scheme for Solar Insecticidal Lamp IoTs with Improved Energy Efficiency

Solar Insecticidal Lamp Internet of Things (SIL-IoTs) nodes are susceptible to failures due to the harsh environment, burn-in, theft, and vandalism in the agricultural setting. Most state-of-the-art research mainly focuses on fault detection without considering hardware and communication performance in terms of potential fault modes, energy consumption, and network loads. This study presents a completely decentralized solution, namely a SIL-Oriented binary Sliding window-based fault self-detection scheme (SILOS), which can be performed on each SIL-IoTs node. The problem we are trying to answer is how to detect faults as accurately as possible while keeping the communication overhead, memory, and computational costs low. Specifically, we develop a fault dictionary concept to 1) model the faults of SIL-IoTs nodes, 2) construct the fault dictionary according to the characteristics of measurements, and 3) detect faults via the fault dictionary. In addition, a binary-based sliding window (BSW) fault self-detection approach is proposed to save detection costs and reduce the false alarm rate (with only 92B system caches). A series of experiments are performed to evaluate the performance of the proposed method. The result demonstrates that the BSW method can detect faults with an average accuracy of 99.14% with less than 1% energy consumption. By only sending the fault code, 71B data (i.e., data transmitting and forwarding) can be reduced, saving energy consumption, and decreasing network congestion

Magnetic Material Modelling of Electrical Machines

The need for electromechanical energy conversion that takes place in electric motors, generators, and actuators is an important aspect associated with current development. The efficiency and effectiveness of the conversion process depends on both the design of the devices and the materials used in those devices. In this context, this book addresses important aspects of electrical machines, namely their materials, design, and optimization. It is essential for the design process of electrical machines to be carried out through extensive numerical field computations. Thus, the reprint also focuses on the accuracy of these computations, as well as the quality of the material models that are adopted. Another aspect of interest is the modeling of properties such as hysteresis, alternating and rotating losses and demagnetization. In addition, the characterization of materials and their dependence on mechanical quantities such as stresses and temperature are also considered. The reprint also addresses another aspect that needs to be considered for the development of the optimal global system in some applications, which is the case of drives that are associated with electrical machines

Multi-level simulation of nano-electronic digital circuits on GPUs

Simulation of circuits and faults is an essential part in design and test validation tasks of contemporary nano-electronic digital integrated CMOS circuits. Shrinking technology processes with smaller feature sizes and strict performance and reliability requirements demand not only detailed validation of the functional properties of a design, but also accurate validation of non-functional aspects including the timing behavior. However, due to the rising complexity of the circuit behavior and the steady growth of the designs with respect to the transistor count, timing-accurate simulation of current designs requires a lot of computational effort which can only be handled by proper abstraction and a high degree of parallelization. This work presents a simulation model for scalable and accurate timing simulation of digital circuits on data-parallel graphics processing unit (GPU) accelerators. By providing compact modeling and data-structures as well as through exploiting multiple dimensions of parallelism, the simulation model enables not only fast and timing-accurate simulation at logic level, but also massively-parallel simulation with switch level accuracy. The model facilitates extensions for fast and efficient fault simulation of small delay faults at logic level, as well as first-order parametric and parasitic faults at switch level. With the parallelization on GPUs, detailed and scalable simulation is enabled that is applicable even to multi-million gate designs. This way, comprehensive analyses of realistic timing-related faults in presence of process- and parameter variations are enabled for the first time. Additional simulation efficiency is achieved by merging the presented methods in a unified simulation model, that allows to combine the unique advantages of the different levels of abstraction in a mixed-abstraction multi-level simulation flow to reach even higher speedups. Experimental results show that the implemented parallel approach achieves unprecedented simulation throughput as well as high speedup compared to conventional timing simulators. The underlying model scales for multi-million gate designs and gives detailed insights into the timing behavior of digital CMOS circuits, thereby enabling large-scale applications to aid even highly complex design and test validation tasks

Measurements, Models, Systems and Design

531 s.

Use, Operation and Maintenance of Renewable Energy Systems:Experiences and Future Approaches

The aim of this book is to put the reader in contact with real experiences, current and future trends in the context of the use, exploitation and maintenance of renewable energy systems around the world. Today the constant increase of production plants of renewable energy is guided by important social, economical, environmental and technical considerations. The substitution of traditional methods of energy production is a challenge in the current context. New strategies of exploitation, new uses of energy and new maintenance procedures are emerging naturally as isolated actions for solving the integration of these new aspects in the current systems of energy production. This book puts together different experiences in order to be a valuable instrument of reference to take into account when a system of renewable energy production is in operation