Improving fault ride through capability of DFIG during RSC flashover fault

Wind power generation is growing rapidly. However, maintaining the wind turbine connection to grid is a real challenge. Recent grid codes require wind turbines to maintain connected to the grid even during fault conditions which increases concerns about its sensitivity to external faults. So, researchers have given attention to investigating the impact of various external faults, and grid disturbances such as voltage sag and short circuit faults, on the fault ride through (FRT) capability of the doubly fed induction generator (DFIG). However, no attention has been given to the impact of internal faults on the dynamic performance of the machine when the fault occurs within the voltage source converters (VSCs) that interface the DFIG with the grid. This paper investigates the impact of the rotor side converter (RSC) IGBT flashover fault on the common coupling (PCC) reactive power and the FRT is proposed. The DFIG compliance with numerous and recently released FRT grid codes under the studied fault, with and without the STATCOM are examined and compared. Furthermore, the capability of a proposed controller to bring the voltage profile at the point of PCC to the nominal steady-state level; maintain the unity power factor operation; and, maintain the connection of the wind turbine to the grid are examined

Impact of nanodiffusion on the stacking fault energy in high-strength steels

A key requirement of modern steels – the combination of high strength and high deformability – can best be achieved by enabling a local adaptation of the microstructure during deformation. A local hardening is most efficiently obtained by a modification of the stacking sequence of atomic layers, resulting in the formation of twins or martensite. Combining ab initio calculations with in situ transmission electron microscopy, we show that the ability of a material to incorporate such stacking faults depends on its overall chemical composition and, importantly, the local composition near the defect, which is controlled by nanodiffusion. Specifically, the role of carbon for the stacking fault energy in high-Mn steels is investigated. Consequences for the long-term mechanical properties and the characterisation of these materials are discussed.

Increased Biomass, Seed Yield and Stress Tolerance Is Conferred in Arabidopsis by a Novel Enzyme from the Resurrection Grass Sporobolus stapfianus That Glycosylates the Strigolactone Analogue GR24

Isolation of gene transcripts from desiccated leaf tissues of the resurrection grass, Sporobolus stapfianus, resulted in the identification of a gene, SDG8i, encoding a Group 1 glycosyltransferase (UGT). Here, we examine the effects of introducing this gene, under control of the CaMV35S promoter, into the model plant Arabidopsis thaliana. Results show that Arabidopsis plants constitutively over-expressing SDG8i exhibit enhanced growth, reduced senescence, cold tolerance and a substantial improvement in protoplasmic drought tolerance. We hypothesise that expression of SDG8i in Arabidopsis negatively affects the bioactivity of metabolite/s that mediate/s environmentally-induced repression of cell division and expansion, both during normal development and in response to stress. The phenotype of transgenic plants over-expressing SDG8i suggests modulation in activities of both growth- and stress-related hormones. Plants overexpressing the UGT show evidence of elevated auxin levels, with the enzyme acting downstream of ABA to reduce drought-induced senescence. Analysis of the in vitro activity of the UGT recombinant protein product demonstrates that SDG8i can glycosylate the synthetic strigolactone analogue GR24, evoking a link with strigolactone-related processes in vivo. The large improvements observed in survival of transgenic Arabidopsis plants under cold-, salt- and drought-stress, as well as the substantial increases in growth rate and seed yield under non-stress conditions, indicates that overexpression of SDG8i in crop plants may provide a novel means of increasing plant productivity.

Endurance training in obese humans improves glucose tolerance and mitochondrial fatty acid oxidation and alters muscle lipid content

Muscle fatty acid (FA) metabolism is impaired in obesity and insulin resistance, reflected by reduced rates of FA oxidation and accumulation of lipids. It has been suggested that interventions that increase FA oxidation may enhance insulin action by reducing these lipid pools. Here, we examined the effect of endurance training on rates of mitochondrial FA oxidation, the activity of carnitine palmitoyltransferase I (CPT I), and the lipid content in muscle of obese individuals and related these to measures of glucose tolerance. Nine obese subjects completed 8 wk of moderate-intensity endurance training, and muscle biopsies were obtained before and after training. Training significantly improved glucose tolerance, with a reduction in the area under the curve for glucose (P< 0.05) and insulin (P = 0.01) during an oral glucose tolerance test. CPT I activity increased 250% (P = 0.001) with training and became less sensitive to inhibition by malonyl-CoA. This was associated with an increase in mitochondrial FA oxidation (+120%, P < 0.001). Training had no effect on muscle triacylglycerol content; however, there was a trend for training to reduce both the total diacylglcyerol (DAG) content (−15%, P = 0.06) and the saturated DAG-FA species (−27%, P = 0.06). Training reduced both total ceramide content (−42%, P = 0.01) and the saturated ceramide species (−32%, P < 0.05). These findings suggest that the improved capacity for mitochondrial FA uptake and oxidation leads not only to a reduction in muscle lipid content but also a to change in the saturation status of lipids, which may, at least in part, provide a mechanism for the enhanced insulin action observed with endurance training in obese individuals.

The association between attributions of responsibility for motor vehicle accidents and patient satisfaction: a study within a no-fault injury compensation system

This study set out to test the relationship between attributions of responsibility for motor vehicle accidents and satisfaction with personal injury compensation systems.

Approach to fault detection of time-delay systems using functional observers

A new methodology is reported for designing functional observers to detect actuator faults of a class of time-delay systems where the matrix pair (A, C) is not observable. First, a generalised state transformation is used to transform the system into new coordinates where the delay term associated with the state vector is injected into the system's output and input. Then, a minimum-order functional observer is designed to construct a residual function that can trigger system faults. The finding is significant as it is now possible to detect faults of time-delay systems where the pair (A, C) is not required to be observable. A numerical example is given to illustrate the effectiveness of the proposed design approach. © The Institution of Engineering and Technology 2014.

The correlation between stacking fault energy and the work hardening behaviour of high-mn twinning induced plasticity steel tested at various temperatures

High-Mn Twinning Induced Plasticity (TWIP) steels have superior mechanical properties, which make them promising materials in automotive industry to improve the passenger safety and the fuel consumption. The TWIP steels are characterized by high work hardening rates due to continuous mechanical twin formation during the deformation. Mechanical twinning is a unique deformation mode, which is highly governed by the stacking fault energy (SFE). The composition of steel alloy was Fe-18Mn-0.6C-1Al (wt.%) with SFE of about 25-30 mJ/m2 at room temperature. The SFE ensures the mechanical twinning to be the main deformation mechanism at room temperature. The microstructure, mechanical properties, work hardening behaviour and SFE of the steel was studied at the temperature range of ambient ≤T[°C]≤ 400°C. The mechanical properties were determined using Instron tensile testing machine with 30kN load cell and strain rate of 10-3s-1 and the work hardening behaviour curves were generated using true stress and true strain data. The microstructure after deformation at different temperatures was examined using Zeiss Supra 55VP SEM. It was found that an increase in the deformation temperature raised the SFE resulting in the deterioration of the mechanical twinning that led to decrease not only in the strength but also in the total strain of the steel. A correlation between the temperature, the SFE, the mechanical twinning, the mechanical properties and the work hardening rate was also found. © (2014) Trans Tech Publications, Switzerland.

Motor fault detection and diagnosis using a hybrid FMM-CART model with online learning

In this paper, a hybrid online learning model that combines the fuzzy min-max (FMM) neural network and the Classification and Regression Tree (CART) for motor fault detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, incorporates the advantages of both FMM and CART for undertaking data classification (with FMM) and rule extraction (with CART) problems. In particular, the CART model is enhanced with an importance predictor-based feature selection measure. To evaluate the effectiveness of the proposed online FMM-CART model, a series of experiments using publicly available data sets containing motor bearing faults is first conducted. The results (primarily prediction accuracy and model complexity) are analyzed and compared with those reported in the literature. Then, an experimental study on detecting imbalanced voltage supply of an induction motor using a laboratory-scale test rig is performed. In addition to producing accurate results, a set of rules in the form of a decision tree is extracted from FMM-CART to provide explanations for its predictions. The results positively demonstrate the usefulness of FMM-CART with online learning capabilities in tackling real-world motor fault detection and diagnosis tasks. © 2014 Springer Science+Business Media New York.

Recover fault services via complex service-to-node mappings in wireless sensor networks

With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node's perspective i.e., migrating the service of faulty node to it's nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don't fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level. © 2014 Springer Science+Business Media New York.

Poor tolerance of motor cortex rTMS in chronic migraine

Background:
Two small studies had evaluated the efficacy of rTMS in migraine. One tested high frequency rTMS over the dorsolateral prefrontal cortex while the other evaluated 1 Hz rTMS over the vertex.
Aim:
To test the feasibility of 10 Hz rTMS of motor cortex as an adjunctive therapy in patients with chronic migraine.
Materials and Methods:
We randomized (2:1 ratio) chronic migraine patients on medical preventive treatment to receive either rTMS or sham therapy for 10 sessions. rTMS (80% resting motor threshold, 10Hz, 20 trains, 5 secs/train, inter-train interval 1 min, total 1000 stimuli/session) was applied over the right motor cortex.
Result:
Nine patients were randomized. Six received rTMS
and three had sham therapy. Three patients in the rTMS arm withdrew from the study due to increased headache frequency and discomfort from the treatment. The remaining six cases (3 rTMS, 3 sham) completed the study. The study was prematurely stopped due to the significant worsening of headache from rTMS. No significant differences in outcome measures were found between real and sham rTMS.
Conclusion:
Although the study was terminated prematurely, the high dropout rate (50%) due to worsening headaches suggested that rTMS over the motor cortex is poorly tolerated in chronic migraine.

A functional observer based fault detection technique for dynamical systems

This paper presents a functional observer based fault detection method. The fault detection is achieved using a functional observer based fault indicator that asymptotically converges to a fault indicator that can be derived based on the nominal system. The asymptotic value of the proposed fault indicator is independent of the functional observer parameters and also the convergence rate of the fault indicator can be altered by choosing appropriate functional observer parameters. The advantage of using this new method is that the observed system is not necessarily needed to be observable; therefore, the proposed fault detection technique is also applicable for systems where state observers cannot be designed; moreover, the functional observer fault detection scheme is always of reduced order in comparison to a state observer based scheme.

A fault detection scheme for time-delay systems using minimum-order functional observers

This paper presents a method for designing residual generators using minimum-order functional observers to detect actuator and component faults in time-delay systems. Existence conditions of the residual generators and functional observers are first derived, and then based on a parametric approach to the solution of a generalized Sylvester matrix equation, we develop systematic procedures for designing minimum-order functional observers to detect faults in the system. The advantages of having minimum-order observers are obvious from the economical and practical points of view as cost saving and simplicity can be achieved, particularly when dealing with high-order complex systems. Extensive numerical examples are given to illustrate the proposed fault detection scheme. In all the numerical examples, we design minimum-order residual generators and functional observers to detect faults in the system.