Adaptive sliding mode approach for learning in a feedforward neural network

An adaptive learning algorithm is proposed for a feedforward neural network. The design principle is based on the sliding mode concept. Unlike the existing algorithms, the adaptive learning algorithm developed does not require a prioriknowledge of upper bounds of bounded signals. The convergence of the algorithm is established and conditions given. Simulations are presented to show the effectiveness of the algorithm.     

Development and implementation of a hybrid intelligent controller for interior permanent-magnet synchronous motor drives

A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) controller for an interior permanent-magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN-based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1102 for a laboratory 1-hp IPMSM. The effectiveness of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications in an IPMSM drive.     

EFFECTS OF COOLANT SUPPLY METHODS AND CUTTING CONDITIONS ON TOOL LIFE IN END MILLING TITANIUM ALLOY

Titanium machining poses a great challenge to cutting tools due to its severe negative influence on tool life primarily due to high temperature generated and strong adhesion in the cutting area. Thus, various coolant supply methods are widely used to improve the machining process. On account of this, tool life and cutting force are investigated based on dry cutting, flood cooling, and minimum quantity lubrication (MQL) techniques. The experimental results show that MQL machining can remarkably and reliably improve tool life, and reduce cutting force due to the better lubrication and cooling effect.     

Product-cost modelling approach for the development of a decision support system for optimal roofing material selection

Selection of optimal roofing materials is very important but it is a complex and onerous task as varieties of materials are available for housing roof construction. In order to select suitable materials, an extensive range of criteria would need to be considered. This paper presents the framework and the development of a knowledge-based decision support system for material selection implemented in roofing material selection domain, called ‘Knowledge-based Decision Support system for roofing Material Selection and cost estimating’ (KDSMS). It was developed to facilitate the selection of optimal materials for different roof sub elements. The system consists of a database and knowledge base that is equipped with an inference engine. The former is used to store different types of roofing materials with assigned attribute values. The later is used to hold qualitative and quantitative knowledge which were collected from domain experts and other technical literatures such as building regulations, price guide book and product catalogues. The proposed system employs the TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution) multiple criteria decision making method to solve materials selection and optimisation problem. This study utilised the available roofing materials in the UK housing market in developing the system reported. The main contribution of the developed system is that it provides a tool for the architects, quantity surveyors or self house builder to select optimal materials from a wide array of possibilities for different roof sub elements and also to estimate the conceptual cost for the roof element in the early stage of building design.     

Visualization and concentration measurement of a direct-injection hydrogen jet in a constant-volume vessel using spark-induced breakdown spectroscopy

In this work, spark-induced breakdown spectroscopy (SIBS) was employed to investigate the mixing process of a hydrogen jet in a constant-volume vessel. The local fuel concentration of the hydrogen jet was measured at several locations, using a SIBS sensor. A high-speed camera was used to visualize spark discharge fluctuations, and hydrogen jet concentration measurements were conducted simultaneously. Spectrally resolved atomic emissions from the plasma generated by the spark plug were examined to determine the local equivalence ratio. Direct visualization of the spark discharge provided useful information about the influence of spark discharge characteristics related to the spark timing. Using the developed SIBS sensor, atomic emission spectra were obtained from hydrogen H_α at 656 nm and nitrogen N (I) at 501 nm. Comparison of the intensity peaks of atomic emissions from hydrogen and nitrogen allows the local hydrogen concentration in a measured volume to be determined, and hence also the local equivalence ratio. The measurement results demonstrate the local variation in the equivalence ratio throughout the jet and along its axis. From the results, the spatial structure of the hydrogen jet affects the hydrogen/nitrogen mixing and could be clarified with SIBS technique when the spark is discharged.     

An experimental investigation on the effects of exponential window and impact force level on harmonic reduction in impact-synchronous modal analysis

A novel method called Impact-synchronous modal analysis (ISMA) was proposed previously which allows modal testing to be performed during operation. This technique focuses on signal processing of the upstream data to provide cleaner Frequency response function (FRF) estimation prior to modal extraction. Two important parameters, i.e., windowing function and impact force level were identified and their effect on the effectiveness of this technique were experimentally investigated. When performing modal testing during running condition, the cyclic loads signals are dominant in the measured response for the entire time history. Exponential window is effectively in minimizing leakage and attenuating signals of non-synchronous running speed, its harmonics and noises to zero at the end of each time record window block. Besides, with the information of the calculated cyclic force, suitable amount of impact force to be applied on the system could be decided prior to performing ISMA. Maximum allowable impact force could be determined from nonlinearity test using coherence function. By applying higher impact forces than the cyclic loads along with an ideal decay rate in ISMA, harmonic reduction is significantly achieved in FRF estimation. Subsequently, the dynamic characteristics of the system are successfully extracted from a cleaner FRF and the results obtained are comparable with Experimental modal analysis (EMA).     

Copper substituted nickel ferrite nanoparticles anchored onto the graphene sheets as electrode materials for supercapacitors fabrication

Nickel ferrites with high theoretical capacitance value as compared to the other metal oxides have been applied as electrode material for energy storage devices i.e. batteries and supercapacitors. High tendency towards aggregation and less specific surface area make the metal oxides poor candidate for electrochemical applications. Therefore, the improvements in the electrochemical properties of nickel ferrites (NiFe₂O₄) are required. Here, we report the synthesis of graphene nano-sheets decorated with spherical copper substituted nickel ferrite nanoparticles for supercapacitors electrode fabrication. The copper substituted and unsubstituted NiFe₂O₄ nanoparticles were prepared via wet chemical co-precipitation route. Reduced graphene oxide (rGO) was prepared via well-known Hummer's method. After structural characterization of both ferrite (Ni_1-xCu_xFe₂O₄) nanoparticles and rGO, the ferrite particles were decorated onto the graphene sheets to obtain Ni_1-xCu_xFe₂O₄@rGO nanocomposites. The confirmation of preparation of these nanocomposites was confirmed by scanning electron microscopy (SEM). The electrochemical measurements of nanoparticles and their nanocomposites (Ni_0.9Cu_0.1Fe₂O₄@rGO) confirmed that the nanocomposites due to highly conductive nature and relatively high surface area showed better capacitive behavior as compared to bare nanoparticles. This enhanced electrochemical energy storage properties of nanocomposites were attributed to the graphene and also supported by electrical (I-V) measurements. The cyclic stability experiments results showed ~65% capacitance retention after 1000 cycles. However this retention was enhanced from 65% to 75% for the copper substituted nanoparticles (Ni_0.9Cu_0.1Fe₂O₄) and 65–85% for graphene based composites. All this data suggest that these nanoparticles and their composites can be utilized for supercapacitors electrodes fabrication.     

Assessment of organic acid-rich bio-sap to generate electricity

The study has focused on electricity generation from organic acid-rich bio-substrate like star fruit (Averrhoa carambola). The sap of star fruit was selected as an electrolyte due to the presence of significant amounts of organic acids such as citric acid and ascorbic acid. To preserve the sap, 2% phenol by volume was used to reduce the growth of microorganisms, and the addition of phenol did not affect the initial pH. It was observed that due to an increase in the electrode surface area, reaction rate and current generation had been amplified. Internal resistance also decreased rapidly because of the large electrode surface area. Furthermore, internal resistance was the significant barrier in electricity generation, which was also successfully controlled by the baffle flow agitation system. Moreover, the baffle flow agitation system reduces the formation of dead zones and increases the total dissolved solids inside the electrochemical cell compartments during operation.     

Formulation and characterisation of nanosuspension of herbal extracts for enhanced antiradical potential

Nanotechnology is a promising technique to increase the bioavailability of herbal medicines. This paper presents the nanosuspension approach for increasing the aqueous solubility and thereby bioactivity of important herbal extracts. Nanosuspensions of the seeds of three plants extract (Silybum marianum, Elettaria cardamomum and Coriandrum sativum) were prepared by using polyvinyl alcohol (1.5% w/v) as a stabiliser. Prepared nanoparticles were characterised by scanning electron microscope. Activity of nanosuspension formulation was assessed by using four in vitro antioxidant assays. S. marianum, E. cardamomum and C. sativum particle size was observed to fall in range of 446.1 ± 112.6, 456.63 ± 339.2 and 432.1 ± 172.8 nm, respectively, most of the particles were having spherical shape and smooth topology. These synthesised nanoparticles were found to be more effective against quenching free radical than their crude extracts and standards [butylated hydroxyl toluene and ascorbic acid]. C. sativum nanosuspension showed most free radical scavenging potential against 2,2-diphenyl-1-picrylhdrazyl (DPPH) and superoxide free radical scavenging assays (IC₅₀ 0.59 ± 0.01 and 0.81 ± 0.11 mg/ml). S. marianum nanosuspension was found to be most effective against DPPH radicals scavenging (IC₅₀ 0.34 ± 0.02 mg/ml). It was concluded that nanosuspension of herbal medicines potentiates the antioxidant potential.     

Modeling the response of Listeria monocytogenes at various storage temperatures in pork with/without electrolyzed water treatment

The objective of this study was to develop a model of the growth of Listeria monocytogenes in pork untreated or treated with low concentration electrolyzed water (LcEW) and strong acid electrolyzed water (SAEW), as a function of temperature. The experimental data obtained under different temperatures (4, 10, 15, 20, 25, and 30°C) were fitted into the modified Gompertz model to generate the growth parameters including specific growth rate (SGR) and lag time (LT) with high coefficients of determination (R² >0.97). The obtained SGR and LT were employed to develop square root models to evaluate the effects of storage temperature on the growth kinetics of L. monocytogenes in pork. The values of bias factor (0.924–1.009) and accuracy factor (1.105–1.186), which were regarded as acceptable, demonstrated that the obtained models could provide good and reliable predictions and be suitable for the purpose of microbiological risk assessment of L. monocytogenes in pork.