Optimal inverter design for an induction machine using resonant frequency matching

The frequency responses of two 50 Hz and one 400 Hz induction machines have been measured experimentally over a frequency range of 1 kHz to 400 kHz. This study has shown that the stator impedances of the machines behave in a similar manner to a parallel resonant circuit, and hence have a resonant point at which the Input impedance of the machine is at a maximum. This maximum impedance point was found experimentally to be as low as 33 kHz, which is well within the switching frequency ranges of modern inverter drives. This paper investigates the possibility of exploiting the maximum impedance point of the machine, by taking it into consideration when designing an inverter, in order to minimize ripple currents due to the switching frequency. Minimization of the ripple currents would reduce torque pulsation and losses, increasing overall performance. A modified machine model was developed to take into account the resonant point, and this model was then simulated with an inverter to demonstrate the possible advantages of matching the inverter switching frequency to the resonant point. Finally, in order to experimentally verify the simulated results, a real inverter with a variable switching frequency was used to drive an induction machine. Experimental results are presented.

Study of the variation of the input impedance of induction machines with frequency

The results of a study of the variation of three-phase induction machines' input impedance with frequency are proposed. A range of motors were analysed, both two-pole and four-pole, and the magnitude and phase of the input impedance were obtained over a wide frequency range of 20 Hz-1 MHz. For test results that would be useful in the prediction of the performance of induction machines during typical use, a test procedure was developed to represent closely typical three-phase stator coil connections when the induction machine is driven by a three-phase inverter. In addition, tests were performed with the motor's cases both grounded and not grounded. The results of the study show that all induction machines of the type considered exhibit a multiresonant impedance profile, where the input impedance reaches at least one maximum as the input frequency is increased. Furthermore, the test results show that the grounding of the motor's case has a significant effect on the impedance profile. Methods to exploit the input impedance profile of an induction machine to optimise machine and inverter systems are also discussed.

Application of neural network to hybrid systems with binary inputs

Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.

Induction of cytochrome P-450 activity in individual Chironomus riparius Meigen larvae exposed to xenobiotics

Cytochrome P450 activity in individual Chironomus riparius larvae was measured using a microtiter plate adaptation of the ethoxyresorufin-O-deethylase (EROD) assay. The sensitivity of this biomarker was tested by exposing larvae to phenobarbital (0.5 and 1.0 mM) and permethrin (1 and 10 mug/g). Both chemicals induced EROD activity in C. riparius larvae by up to 1.58-fold with PB and 2.47-fold with permethrin. EROD induction was more pronounced after 48 h. The initially high EROD activity in the controls suggested that P450s are induced by stress. Feeding levels prior to exposure also had a significant effect on EROD activity. EROD activity compared to the control was highest when larvae were fed double the normal ration. These results indicate that EROD activity in individual C. riparius may be a useful biomarker to add to a suite of biomarkers for the detection of freshwater pollution. (C) 2002 Elsevier Science (USA). All rights reserved.

Effects of a novel galactooligosaccharide on the faecal microbiota of healthy and inflammatory bowel disease cats during a randomized, double-blind, cross-over feeding study

Inflammatory bowel disease (IBD) is a common gastrointestinal disorder of cats with no known aetiological agent. Previous work has suggested that the faecal microbiota of IBD cats is significantly different from that of healthy cats, including significantly lower bifidobacteria, bacteroides and total counts in IBD cats and significantly lower levels of sulfate-reducing bacteria in healthy cats. Prebiotics, including galactooligosaccharides (GOS), have been shown to elicit a bifidogenic effect in humans and other animals. The purpose of the current study was to examine the impact of a novel GOS supplementation on the faecal microbiota of healthy and IBD cats during a randomized, double-blind, cross-over feeding study. Eight oligonucleotide probes targeting specific bacterial populations and DAPI stain (total bacteria) were used to monitor the feline faecal microbiota. Overall, inter-animal variation was high; while a trend of increased bifidobacterial levels was seen with GOS supplementation it was not statistically significant in either healthy or IBD cats. No significant differences were observed in the faecal microbiota of IBD cats and healthy cats fed the same diet. Members of the family Coriobacteriaceae (Atopobium cluster) were found to be the most abundant bacteria in the feline microbiota.

Regulation of expression of the rat orthologue of mouse double minute 2 (MDM2) by H2O2-induced oxidative stress in neonatal rat cardiac myocytes.

The Mdm2 ubiquitin ligase is an important regulator of p53 abundance and p53-dependent apoptosis. Mdm2 expression is frequently regulated by a p53 Mdm2 autoregulatory loop whereby p53 stimulates Mdm2 expression and hence its own degradation. Although extensively studied in cell lines, relatively little is known about Mdm2 expression in heart where oxidative stress (exacerbated during ischemia-reperfusion) is an important pro-apoptotic stimulus. We demonstrate that Mdm2 transcript and protein expression are induced by oxidative stress (0.2 mm H(2)O(2)) in neonatal rat cardiac myocytes. In other cells, constitutive Mdm2 expression is regulated by the P1 promoter (5' to exon 1), with inducible expression regulated by the P2 promoter (in intron 1). In myocytes, H(2)O(2) increased Mdm2 expression from the P2 promoter, which contains two p53-response elements (REs), one AP-1 RE, and two Ets REs. H(2)O(2) did not detectably increase expression of p53 mRNA or protein but did increase expression of several AP-1 transcription factors. H(2)O(2) increased binding of AP-1 proteins (c-Jun, JunB, JunD, c-Fos, FosB, and Fra-1) to an Mdm2 AP-1 oligodeoxynucleotide probe, and chromatin immunoprecipitation assays showed it increased binding of c-Jun or JunB to the P2 AP-1 RE. Finally, antisense oligonucleotide-mediated reduction of H(2)O(2)-induced Mdm2 expression increased caspase 3 activation. Thus, increased Mdm2 expression is associated with transactivation at the P2 AP-1 RE (rather than the p53 or Ets REs), and Mdm2 induction potentially represents a cardioprotective response to oxidative stress.

PMCRI: a parallel modular classification rule induction framework

In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction of Decision Trees (TDIDT) algorithm is a very widely used technology to predict the classification of newly recorded data. However alternative technologies have been derived that often produce better rules but do not scale well on large datasets. Such an alternative to TDIDT is the PrismTCS algorithm. PrismTCS performs particularly well on noisy data but does not scale well on large datasets. In this paper we introduce Prism and investigate its scaling behaviour. We describe how we improved the scalability of the serial version of Prism and investigate its limitations. We then describe our work to overcome these limitations by developing a framework to parallelise algorithms of the Prism family and similar algorithms. We also present the scale up results of a first prototype implementation.