Fire monitoring in coal mines using wireless underground sensor network and interval type-2 fuzzy logic controller

International Journal of Coal Science & Technology - From the view of underground coal mining safety system, it is extremely important to continuous monitoring of coal mines for the prompt...     

Preparation of Al--Al2O3 in-situ particle composites by addition of Fe2O3 particles to pure Al melt

Abstracts are not published in this journal This revised version was published online in November 2006 with corrections to the Cover Date.     

A hybrid unscented filtering and particle swarm optimization technique for harmonic analysis of nonstationary signals

This paper presents a modified unscented Kalman filter for accurate estimation of frequency and harmonic components of a time-varying signal embedded in noise with low signal-to-noise ratio. Further, the model and measurement error covariances along with the unscented Kalman filter parameters are selected using a modified particle swarm optimization algorithm. To circumvent the problem of premature convergence and local minima, a dynamically varying inertia weight based on the variance of the population fitness is used. This results in a better local and global searching ability of the particles, which improves the convergence of the velocity and better accuracy of the unscented Kalman filter parameters. Various simulation results for nonstationary sinusoidal signals with time varying amplitude, phase and harmonic content corrupted with noise, reveal significant improvement in noise rejection and speed of convergence and accuracy in comparison to the well known extended Kalman filter.     

High voltage pulse shaping of e-beam diode using perveance variation

This paper presents a new high voltage pulse shaping methodology for pulsed power applications. The aim is to generate high voltage square pulse across anode cathode gap of e-beam diodes. The non-linear time varying perveance characteristics of e-beam diodes are used for shaping of output voltage pulse across it, generated directly from Marx generator. Analytically, it has been shown in the paper that under certain conditions, if achieved, Marx generator feeding an e-beam diode can produce a square-like pulse at the output, without any extra pulse shaping arrangements. Experimental results to support the analysis are also presented in the paper.     

Effect of CH4/H2 plasma ratio on ultra-low friction of nano-crystalline diamond coating deposited by MPECVD technique

Nano-crystalline diamond coatings were deposited on the silicon substrate using Microwave Plasma Enhanced Chemical Vapor Deposition (MPECVD). Experiments were performed by varying the H₂ content in CH₄/H₂ plasma during synthesis. Raman spectral analysis revealed that with decrease in hydrogen content in the CH₄ plasma, the I_D/I_G ratio decreases with the formation of smaller crystallites. Such a film possesses a large grain boundary fraction containing hydrogenated amorphous carbon (a-C:H). During tribological test, sufficient amount of hydrogen present in the grain boundary passivates the dangling σ-bond causing ultra-low friction and extremely low wear evident by improvement in microstructure.     

Design and simulation of a solar–wind–biogas hybrid system architecture using HOMER in India

The renewable energy sources are accompanied by certain constraints as reliability, availability and continuous generation. In India, biomass is considered as the second best suitable combination with other renewable energy sources. Both solar and wind are undependable renewable energies as they are unpredictable. Now the key to successful renewable energy harvesting lies in the selection of hybrid system architecture for power generation. In rural areas, light is usually unavailable and if it does, it is mostly an incandescent light used for household lighting instead of fluorescent. System reliability, economy and environmental issues are the three major issues for decentralised electrification. So, finding the best suited hybrid system configuration to overcome these constraints is the need of the hour. It is at this stage that HOMER comes into the picture. HOMER, abbreviated name of hybrid optimization model for electric renewable, successfully realises system configuration before its installation and works for on-grid, off-grid and stand-alone systems, which make it useful for rural to urban applications. It simulates and optimises the best suitable solution for a hybrid system and generates reports incorporating all the aspects in designing a system. Here, a typical hybrid system is considered and the implementation of HOMER software has been incorporated.     

Electricity price classification using extreme learning machines

Forecasting electricity prices has been a widely investigated research issue in the deregulated power market scenario. High price volatilities, price spikes caused by a number of factors such as weather uncertainty, fluctuating fuel prices, transmission bottlenecks, etc., make the task of accurate price forecasting a formidable challenge for the market participants. A number of models have been proposed by researchers; however, achieving high accuracy is always not possible. In some specific applications such as self-scheduling by demand side participants, certain price thresholds are more useful than accurate price forecasts. In this paper, we have investigated the application of a novel neural network-based technique called extreme learning machine for the problem of classification of future electricity prices with respect to certain price thresholds. Different models corresponding to different lead times are developed and tested with data corresponding to Ontario and PJM markets. It is observed that classification with ELM is fast, less sensitive to user defined parameters and easily implementable.     

Long‐term irreversible changes in a lake ecosystem affected by the Indian Ocean Tsunami

This study focused on ecosystem responses to the environmental perturbations caused by the 2004 Indian Ocean Tsunami in a small lake that was a freshwater body in 1996, prior to the tsunami. The physicochemical and biological characteristics of Kokilamedu Lake (KKM) revealed drastic changes, compared with pretsunami conditions. Monthly average observations on water quality indicated the electrical conductivity of the water increased steeply to 17.41 mS cm^?1 in 2009, from the lowest pretsunami value of 1.83 mS cm^?1 (range of 1.83–5.25 mS cm^?1). Simultaneously, the nitrate + nitrite (NO₃ + NO₂) values increased significantly from 0.49 μmol L^?1 in 1996 to 74.47 μmol L^?1 in 2006. Silicate (SiO₄‐Si) exhibited a dramatic increase in concentration, from an average of 64.87 μmol L^?1 in the pretsunami period to 309.71 μmol L^?1 the post‐tsunami period (2009–2010). Inorganic phosphate had increased to a maximum of 9.59 μmol L^?1 from a pretsunami maximum of 1.09 μmol L^?1. The chlorophyll‐α concentrations did not respond to the increased nutrient stoichiometry of the lake. There was a decreased chlorophyll‐α concentration under post‐tsunami conditions. The recent infilling of the lake with sediment during the tsunami, associated with wind‐driven resuspension reduced the light penetration. There was a significant improvement in dissolved oxygen concentrations (2006–2010 average of 8.27 mg L^?1) in the lake, however, compared with the pretsunami values (1994–1995 average of 5.94 mg L^?1). The algal component is now dominated by blue‐green algae, while green algae had dominated in the pretsunami period. Pre‐ and post‐tsunami observations from a control site did not exhibit such dramatic shifts from the 1995 and 1996 conditions, whereas a shift was apparent in the case of KKM. Certain marine fishes have adapted to this altered ecosystem. These marine species encountered (Elops machnata, Cociella punctata, Sphyraena jello, Platycephalus indicus, Glossogobius giuris) might have been recruited during the intrusion of the tsunami waves.