Wavelet Modulus Maxima for Single Switch Open Fault in Multi-level Inverter

The multi-level inverter is widely used in high-power and high-voltage applications. Multi-level inverters use a large number of switches for high power conversion, resulting in increased system's fault probability. To ensure stable operation of the system, several fault diagnosis methods have been carried out by researchers. In this article, a fault diagnostic system in a multi-level inverter using wavelet modulus maxima is developed. The working situation of the power devices of a five-level diode-clamped multi-level inverter drive system under an open-circuit fault is analyzed through MATLAB (The MathWorks, Natick, Massachusetts, USA) simulation. The wavelet modulus maxima of output phase voltages are used to detect faulty phase (leg), and wavelet modulus maxima of DC bus currents are used to detect fault type and fault switch. Wavelet analysis is used for feature extraction, which can be used as input to the expert system to develop a fault identifier. The open-circuit fault on the five-level diode-clamped multi-level inverter of power devices is carried out experimentally. The experimental prototype is developed to validate the fault analysis with simulation results.     

Hierarchically Nanoperforated Graphene as a High Performance Electrode Material for Ultracapacitors

High performance is reported for a symmetric ultracapacitor (UC) cell made up of hierarchically perforated graphene nanosheets (HPGN) as an electrode material with excellent values of energy density (68.43 Wh kg^?1) and power density (36.31 kW kg^?1). Perforations are incorporated in the graphite oxide (GO) and graphene system at room temperature by using silica nanoparticles as template. The symmetric HPGN‐based UC cell exhibits excellent specific capacitance (Cs) of 492 F g^?1 at 0.1 A g^?1 and 200 F g^?1 at 20 A g^?1 in 1M H₂SO₄ electrolyte. This performance is further highlighted by galvanostatic charge–discharge study at 2 A g^?1 over a large number (1000) of cycles exhibiting 93% retention of the initial Cs. These property features are far superior as compared to those of symmetric UC cells made up of only graphene nanosheets (GNs), i.e. graphene sheets without perforations. The latter exhibit Cs of only 158 F g^?1 at 0.1 A g^?1 and the cells is not stable at high current density.     

Mechanism of coal pyrolysis in relation to industrial practice

The validity of our earlier postulates of the mechanism of primary pyrolysis (at and up to 600 °C) is critically examined and it is indicated that the mechanism is strictly followed only under ideal conditions, e.g. in thin beds at rapid rates of carbonization, as in fluidbed and transport reactors. The departure of the Gray-King assay (600 °C) from the ideal path of pyrolysis, e.g. by yielding 20–30% less tar than the yield corresponding to hydroaromatic carbon content, is shown to be due to interaction between the potential tar-forming constituents and the incipient coke-forming substance. This appears to be a function of the thickness of the coal bed, the rate of heating, etc. The greater the thickness, the greater is the degree of interaction and consequent inhibition of tar formation, resulting in a proportionate increase in coke yield. Coke and tar yields are thus partly interconvertible, and the proportions of such interaction have virtually no effect on the proportion of carbon appearing as gas. In industrial high-temperature carbonization, the higher yields of coke and lower yields of tar are due to the same interaction, which occurs to a greater extent primarily because of the greater thickness and/or depth of the coal bed in coke ovens. The fixation of up to 75% of the ‘tar-forming’ carbon (hydroaromatic carbon according to the theory) does not appear to be due to cracking of tar after its formation, but is shown to be foreshadowed well within the primary stage of pyrolysis (below 600 °C), perhaps through condensation-polymerization reactions within the formative coke mass, the mechanism of which is ill-understood at present. The process appears to be very different from the cracking mechanism hitherto believed to explain it. This conclusion is also supported by a study of the distribution of carbon in the gas. Further, such comparative studies between laboratory and industrial conditions do not indicate any significant cracking of methane, hitherto believed to occur in coke ovens. Correspondingly, the reasons for carbon deposition on the exposed hot walls and other regions of coke ovens are discussed and doubt is thrown on the belief that it derives from the cracking of tar and gas.     

Reliability analysis of the dynamic system for the Chen model through sequential order statistics

Recently, the two-parameter Chen distribution has widely been used for reliability studies in various engineering fields. In this article, we have developed various statistical inferences on the composite dynamic system, assuming Chen distribution as a baseline model. In this dynamic system, failure of a component induces a higher load on the surviving components and thus increases component hazard rate through a power-trend process. The classical and Bayesian point estimates of the unknown parameters of the composite system are obtained by the method of maximum likelihood and Markov chain Monte Carlo techniques, respectively. In the Bayesian framework, we have used gamma priors to obtain Bayes estimates of unknown parameters under the squared error and generalized entropy loss functions. The interval estimates of the baseline reliability function are obtained by using the Fisher information matrix and Bayesian method. A parametric hypothesis test is presented to test whether the failed components change the hazard rate function. A compact simulation study is carried out to examine the behavior of the proposed estimation methods. Finally, one real data analysis is performed for illustrative purposes.     

Modelling and prediction of antibacterial activity of knitted fabrics made from silver nanocomposite fibres using soft computing approaches

Neural Computing and Applications - Antibacterial activity of knitted fabrics has been modelled and predicted by using two soft computing approaches, namely artificial neural network (ANN) and...     

Detection of Winding Faults in Wound Rotor Induction Motor Using Loci of Direct and Quadrature Axes of Rotor Currents

In this paper, loci of direct and quadrature axis of rotor currents are used for online detection of winding fault on stator side as well as rotor side in three-phase wound rotor induction motor. The proposed technique is used for detecting load on induction motor and open circuit fault condition on stator side as well as rotor side. Detection of winding fault is affected by unbalanced supply voltage. In order to overcome this problem, FFT of modulus of direct and quadrature axis is used. The experimental results of rotor current analysis are validated with stator current analysis. Research works reported in the literature are based on stator currents analysis. The proposed technique of detecting winding faults and distinguishing between stator winding faults and unbalanced supply voltage using rotor current is not reported in the literature.     

Dielectric behavior of polyaniline–CNTs composite in microwave region

Films of polyaniline (PANI) and polyaniline–CNTs composites have been synthesized by solution casting technique. Fourier transform infrared spectroscopic studies of PANI and PANI–CNTs composite films indicated the presence of interaction between CNTs and molecular chains of PANI. Dielectric properties of PANI and composite films have been investigated in the frequency range of 8.0–12.0 GHz. The real part of permittivity (ε′) and loss factor (tan δ) were found to be higher in PANI–CNTs composite films as compared to the PANI film. The increasing behavior of ε′ and tan δ has been attributed to the interaction present between CNTs and PANI molecular chains and increase of conductivity of PANI films after incorporation of CNTs.     

Toxicological evaluation of aspartame against Madin–Darby canine kidney cells

Aspartame is most widely used as artificial sweeteners in more than 6000 food varieties. Aspartame digested into aspartic acid, phenylalanine, and methanol, and several peroxides, superoxide molecules also generated together. The kidney is the secondary site for the cellular metabolism. The present study examined whether the treatment of aspartame induces oxidative stress in the Madin–Darby kidney cells (MDCK). The effects of aspartame on MDCK cell viability were investigated by the sulphorhodamine-B assay and flow cytometry. Morphology of MDCK cells following aspartame exposure was observed. Mitochondria-derived reactive oxygen species (ROS) was also determined using 2′,7′-dichlorodihydrofluorescein diacetate. Lipid peroxidation (LPO), glutathione reduced (GSH) levels and activities of superoxide dismutase (SOD), and catalase enzymes were also determined. Cell viability was significantly altered following aspartame exposure. Morphology of MDCK cells did not change significantly. However, there was a marginal morphological change, including rounding, sporadic distribution and loss of adherence were observed at higher doses of aspartame exposure. Mitochondria-derived ROS was increased in a dose-dependent manner following aspartame exposure. A significant increase in LPO levels, whereas GSH level was reduced after 48 and 72 h of aspartame exposure. SOD and catalase enzyme activities were significantly reduced in a dose- and time-dependent manner. Taking all these data together, it is concluded that aspartame may induce oxidative stress in the MDCK cells.