A novel direct torque control for interior permanent-magnet synchronous machine drive with low ripple in torque and flux-a speed-sensorless approach

A novel direct torque control (DTC) scheme for an interior permanent magnet synchronous machine (IPMSM) is proposed in this paper, which features low torque and flux ripple and almost fixed switching frequency. The torque and flux ripples have been significantly reduced compared with those of the basic DTC reported in the literature. A speed estimation scheme is integrated with the proposed DTC scheme in order to achieve a fully sensorless high-performance IPMSM drive.     

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.     

Wear characteristics of commercial gas turbine components

Wear is one of the common degradations in a commercial gas turbine. A stainless steel grade 304 (SS 304) fuel nozzle and its collar made of nickel-based superalloy (Hastelloy X) are two vital components that normally suffer from rapid wear. During an installation, the fuel nozzle is slotted into the collar of the combustion liner. In operation, these two surfaces are subjected to high pressure from the fuel combustion, hence continuously rubbing against each other causes vibrations. During the start–stop operation, these surfaces had undergone a large relative motion. The vibration is the main cause of the wear occurrence on the surfaces. Physical properties of the worn surfaces were obtained through visual observations: wear measurement, hardness and microstructure examination. Through visual observations, fretting wear was mainly suspected as the dominant wear mode, particularly after 8,000 of running hours at high temperature and vibration. In short, this paper discusses the preliminary findings of wear on the fuel nozzle and its collar. It also discusses the changes in the mechanical properties before and after the operation. Solutions for mitigating the problem were discussed.     

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.     

Hierarchical steganography using novel optimum quantization technique

Security and imperceptibility are fundamental issues for steganography. This paper presents a multi-level steganography system based on concealing and deception. Basically, the secret image is embedded in a cover image, which in turn is embedded in another higher-level cover image. Each steganography level provides additional security, with lower levels implemented using stronger steganography methods. Furthermore, in the event that the higher level steganography is compromised, it would include misleading information to deceive the attacker that he/she is successfully eavesdropping. One challenge of hierarchical system is retaining hidden data in lower level in a higher level stenographic technique. To mitigate this issue, we designed a novel technique which combines discrete cosine transform and least significant bit (LSB). The technique objective is to maximize the capacity and invisibility of the secret image with minimal modification to the cover image (at most k-bits per block). The performance (capacity and peak signal-to-noise ratio) of the proposed method has superior performance compared with LSB since it combines the benefits of 1-bit and 3-bit LSBs. Furthermore, the paper demonstrates that the secret message is successfully embedded and extracted in two-level steganography system with peak signal-to-nose ratio greater than 20 dB.     

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.     

Static and dynamic compressive properties of polypropylene/zinc oxide nanocomposites

The effect of strain rate is widely recognized as an essential factor that influences the mechanical properties of polymer matrix composites. Despite its importance, no previous work has been reported on the high‐strain rate behavior of polypropylene/zinc oxide nanocomposites. Based on this, static and dynamic compression properties of polypropylene/zinc oxide nanocomposites, with particle contents of 1%, 3%, and 5% by weight, were successfully studied at different strain rates (i.e., 0.01 s^?1, 0.1 s^?1, 650 s^?1, 900 s^?1, and 1100 s^?1) using a universal testing machine and a split Hopkinson pressure bar apparatus. For standardization, approximately 24 nm of zinc oxide nanoparticles were embedded into polypropylene matrix for each of the tested polypropylene/zinc oxide nanocomposites. Results show that the yield strength, the ultimate strength, and the stiffness properties, of polypropylene/zinc oxide nanocomposites, were greatly affected by both particle loading and applied strain rate. Furthermore, the rate sensitivity and the absorbed energy of all tested specimens showed a positive increment with increasing strain rate, whereas the thermal activation volume showed a contrary trend. In addition, the fractographic analysis and particle dispersion of all composite specimens were successfully obtained using a field emisission scanning electron microscopy. POLYM. ENG. SCI., 54:949–960, 2014. © 2013 Society of Plastics Engineers