A Luenberger state observer for stator resistance estimation in sensorless induction motor drives

The primary objective of this paper is to elimination of the problem of sensitivity to parameter variation of induction motor drive. The proposed sensorless strategy is based on an algorithm permitting a better simultaneous estimation of the rotor speed and the stator resistance including an adaptive mechanism based on the lyaponov theory. To study the reliability and the robustness of the sensorless technique to abnormal operations, some simulation tests have been performed under several cases. The proposed sensorless vector control scheme showed a good performance behavior in the transient and steady states, with an excellent disturbance rejection of the load torque. © 2013 Praise Worthy Prize S.r.l. - All rights reserved.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Calculations of capacitive couplings in induction generators to analyse shaft voltage

This paper deals with the analysis of the parameters which are effective in shaft voltage generation of induction generators. It focuses on different parasitic capacitive couplings by mathematical equations, finite element simulations and experiments. The effects of different design parameters have been studied on proposed capacitances and resultant shaft voltage. Some parameters can change proposed capacitive coupling such as: stator slot tooth, the gap between slot tooth and winding, and the height of the slot tooth, as well as the air gap between the rotor and the stator. This analysis can be used in a primary stage of a generator design to reduce motor shaft voltage and avoid additional costs of resultant bearing current mitigation.

Remediation strategies of shaft and common mode voltages in adjustable speed drive systems

AC motors are largely used in a wide range of modern systems, from household appliances to automated industry applications such as: ventilations systems, fans, pumps, conveyors and machine tool drives. Inverters are widely used in industrial and commercial applications due to the growing need for speed control in ASD systems. Fast switching transients and the common mode voltage, in interaction with parasitic capacitive couplings, may cause many unwanted problems in the ASD applications. These include shaft voltage and leakage currents. One of the inherent characteristics of Pulse Width Modulation (PWM) techniques is the generation of the common mode voltage, which is defined as the voltage between the electrical neutral of the inverter output and the ground. Shaft voltage can cause bearing currents when it exceeds the amount of breakdown voltage level of the thin lubricant film between the inner and outer rings of the bearing. This phenomenon is the main reason for early bearing failures. A rapid development in power switches technology has lead to a drastic decrement of switching rise and fall times. Because there is considerable capacitance between the stator windings and the frame, there can be a significant capacitive current (ground current escaping to earth through stray capacitors inside a motor) if the common mode voltage has high frequency components. This current leads to noises and Electromagnetic Interferences (EMI) issues in motor drive systems. These problems have been dealt with using a variety of methods which have been reported in the literature. However, cost and maintenance issues have prevented these methods from being widely accepted. Extra cost or rating of the inverter switches is usually the price to pay for such approaches. Thus, the determination of cost-effective techniques for shaft and common mode voltage reduction in ASD systems, with the focus on the first step of the design process, is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. Electrical power generation from renewable energy sources, such as wind energy systems, has become a crucial issue because of environmental problems and a predicted future shortage of traditional energy sources. Thus, Chapter 2 focuses on the shaft voltage analysis of stator-fed induction generators (IG) and Doubly Fed Induction Generators DFIGs in wind turbine applications. This shaft voltage analysis includes: topologies, high frequency modelling, calculation and mitigation techniques. A back-to-back AC-DC-AC converter is investigated in terms of shaft voltage generation in a DFIG. Different topologies of LC filter placement are analysed in an effort to eliminate the shaft voltage. Different capacitive couplings exist in the motor/generator structure and any change in design parameters affects the capacitive couplings. Thus, an appropriate design for AC motors should lead to the smallest possible shaft voltage. Calculation of the shaft voltage based on different capacitive couplings, and an investigation of the effects of different design parameters are discussed in Chapter 3. This is achieved through 2-D and 3-D finite element simulation and experimental analysis. End-winding parameters of the motor are also effective factors in the calculation of the shaft voltage and have not been taken into account in previous reported studies. Calculation of the end-winding capacitances is rather complex because of the diversity of end winding shapes and the complexity of their geometry. A comprehensive analysis of these capacitances has been carried out with 3-D finite element simulations and experimental studies to determine their effective design parameters. These are documented in Chapter 4. Results of this analysis show that, by choosing appropriate design parameters, it is possible to decrease the shaft voltage and resultant bearing current in the primary stage of generator/motor design without using any additional active and passive filter-based techniques. The common mode voltage is defined by a switching pattern and, by using the appropriate pattern; the common mode voltage level can be controlled. Therefore, any PWM pattern which eliminates or minimizes the common mode voltage will be an effective shaft voltage reduction technique. Thus, common mode voltage reduction of a three-phase AC motor supplied with a single-phase diode rectifier is the focus of Chapter 5. The proposed strategy is mainly based on proper utilization of the zero vectors. Multilevel inverters are also used in ASD systems which have more voltage levels and switching states, and can provide more possibilities to reduce common mode voltage. A description of common mode voltage of multilevel inverters is investigated in Chapter 6. Chapter 7 investigates the elimination techniques of the shaft voltage in a DFIG based on the methods presented in the literature by the use of simulation results. However, it could be shown that every solution to reduce the shaft voltage in DFIG systems has its own characteristics, and these have to be taken into account in determining the most effective strategy. Calculation of the capacitive coupling and electric fields between the outer and inner races and the balls at different motor speeds in symmetrical and asymmetrical shaft and balls positions is discussed in Chapter 8. The analysis is carried out using finite element simulations to determine the conditions which will increase the probability of high rates of bearing failure due to current discharges through the balls and races.

Demonstration of closed-­loop airborne sense-­and-­avoid using machine vision

This paper describes a vision-based airborne collision avoidance system developed by the Australian Research Centre for Aerospace Automation (ARCAA) under its Dynamic Sense-and-Act (DSA) program. We outline the system architecture and the flight testing undertaken to validate the system performance under realistic collision course scenarios. The proposed system could be implemented in either manned or unmanned aircraft, and represents a step forward in the development of a “sense-and-avoid” capability equivalent to human “see-and-avoid”.

Modeling and sensorless direct torque and flux control of a dual-airgap axial flux permanent-magnet machine with field-weakening operation

This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

Design of mode switching scheme for low-voltage ride-through of doubly fed induction generators

A mode switching doubly fed induction generator (MSDFIG) scheme is proposed for the purpose of achieving low-voltage ride-through for wind turbines. The MSDFIG operates as a doubly fed induction generator (DFIG) under normal condition but upon the detection of a low-voltage incident, the generator is to smoothly transfer to operate under the induction generator mode through the switching in of a set of stator-side crowbar. The MSDFIG automatically reverts back to the DFIG mode when network voltage recovers. A new strategy on the control of the crowbar resistance is included. Analysis shows that the proposed MSDFIG scheme can ride through the complete low-voltage and voltage recovery stages. Effectiveness of the scheme is demonstrated through simulation and experiment studies.

Machine learning approaches to analysing textual injury surveillance data: A systematic review

Objective To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Design Systematic review. Data sources The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. Selection criteria For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. Methods The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Results Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. Conclusions The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field.

Ratcheting and wear behavior of Australian rail steel: Experimental investigation of material properties and sampling method

To The ratcheting behavior of high-strength rail steel (Australian Standard AS1085.1) is studied in this work for the purpose of predicting wear and damage to the rail surface. Historically, researchers have used circular test coupons obtained from the rail head to conduct cyclic load tests, but according to hardness profile data, considerable variation exists across the rail head section. For example, the induction-hardened rail (AS1085.1) shows high hardness (400-430 HV100) up to four-millimeters into the rail head’s surface, but then drops considerably beyond that. Given that cyclic test coupons five millimeters in diameter at the gauge area are usually taken from the rail sample, there is a high probability that the original surface properties of the rail do not apply across the entire test coupon and, therefore, data representing only average material properties are obtained. In the literature, disks (47 mm in diameter) for a twin-disk rolling contact test machine have been obtained directly from the rail sample and used to validate rolling contact fatigue wear models. The question arises: How accurate are such predictions? In this research paper, the effect of rail sampling position on the ratcheting behavior of AS1085.1 rail steel was investigated using rectangular shaped specimens. Uniaxial stress-controlled tests were conducted with samples obtained at four different depths to observe the ratcheting behaviour of each. Micro-hardness measurements of the test coupons were carried out to obtain a constitutive relationship to predict the effect of depth on the ratcheting behaviour of the rail material. This work ultimately assists the selection of valid material parameters for constitutive models in the study of rail surface ratcheting.

Altered formalin-induced pain and Fos induction in the periaqueductal grey of preadolescent rats following neonatal LPS exposure

Animal and human studies have demonstrated that early pain experiences can produce alterations in the nociceptive systems later in life including increased sensitivity to mechanical, thermal, and chemical stimuli. However, less is known about the impact of neonatal immune challenge on future responses to noxious stimuli and the reactivity of neural substrates involved in analgesia. Here we demonstrate that rats exposed to Lipopolysaccharide (LPS; 0.05 mg/kg IP, Salmonella enteritidis) during postnatal day (PND) 3 and 5 displayed enhanced formalin-induced flinching but not licking following formalin injection at PND 22. This LPS-induced hyperalgesia was accompanied by distinct recruitment of supra-spinal regions involved in analgesia as indicated by significantly attenuated Fos-protein induction in the rostral dorsal periaqueductal grey (DPAG) as well as rostral and caudal axes of the ventrolateral PAG (VLPAG). Formalin injections were associated with increased Fos-protein labelling in lateral habenula (LHb) as compared to medial habenula (MHb), however the intensity of this labelling did not differ as a result of neonatal immune challenge. These data highlight the importance of neonatal immune priming in programming inflammatory pain sensitivity later in development and highlight the PAG as a possible mediator of this process

Experimental and Analytical Investigations of the actions taking place in a Synchronous machine during the starting period when the starting Is effected by means of alternating current

The literature on the subject of the present investigation is somewhat meagre. A rotary converter or synchronous motor no! provided with any special starting devices forms, when started from the alternating current side, a type of induction motor whoso Htator is provided with a polyphase winding, and whoso rotor has a single-phase (or single magnetic axis) winding.

A Current Source Inverter Fed Induction Motor Drive with Power Factor Angle Control Using Microprocessor

This paper describes a method of adjusting the stator power factor angle for the control of an induction motor fed from a current source inverter (CSI) based on the concept of space vectors (or park vectors). It is shown that under steady state, if the torque angle is kept constant over the entire operating range, it has the advantage of keeping the slip frequency constant. This can be utilized to dispose of the speed feedback and simplify the control scheme for the drive, such that the stator voltage integral zero crossings alone can be used as a feedback for deciding the triggering instants of the CSI thyristors under stable operation of the system. A closed-loop control strategy is developed for the drive based on this principle, using a microprocessor-based control system and is implemented on a laboratory prototype CSI fed induction motor drive.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.