Revista global de tecnología y optimización

The traditional regression model in machining process neglects nonlinear influence of machining parameters on process response, which causes the analyses to have a low accuracy. The primary objective of this study is to propose an optimal regression model to analyze the material removal rate in ultrasonic machining through the experimental tests, statistical analyses and regression modeling. Three main factors affecting the machining process response, namely abrasive granularity, feed pressure and feed speed, were selected for this purpose, and the experiments were performed in accordance with an L16 orthogonal array using Taguchi method. Analysis of variance (ANOVA) was used to investigate the statistical significance of the parameters at 95% confidence level and to determine the percentage contribution of the parameters to the process response. On this basis, the optimal regression model was proposed. Compared with traditional regression model, the analytical precision of the optimal regression model is quite higher than that of traditional regression model. The results obtained from the new experimental conditions show that the optimal regression model can correctly reflect the influence of machining parameters on process response, which can provide a theoretical basis for selection of machining parameters to improve its machining efficiency.

Wireless monitoring and control is the new technology that most of the nations are interested in since majority of the people are now using the cellular phone. Smart phone can now control many of the appliances of electric goods or lights as well as the motor speeds at the factories or workshops. The phone can also monitor the values of most of electrical or mechanical variables or even the human body functions like blood pressure, heart beat or oxygen. This technology is based on an automatic electronic and programming switch that can be built in a receiving circuit connected to any load, which detect the wireless transmitted signal and translated into an operating signal. The transmitted signal is generated from the mobile phone either by push button (touching a key) using DTMF (Dual-Tone Multi-Frequency) or by SMS (Short Messaging Service). This is preceded by dialling the number of the SIM card (Subscriber Identity Module) of the receiving circuit. This circuit consists of GSM board (Global System for Mobile Communications) and Arduino Uno microcontroller board plus other components such as resistances, capacitances, inductances, relays, transformer, decoder, transistors and converters. These electronic circuits are supplied by 3 to 5 volt or sometimes 12 volt, so adapter device is also involved with the components. This technology is only used the mobile functions, not the internet features, but depends on the mobile networks which allow the objects to be controlled from very far distance (from country to another country, from home to workshop or hospital). Unlike the other technology which works at small distance such as remote infrared Bluetooth, Wi-Fi, or line communication. In this paper, this technology will be highlighted showing the hardware circuits of light and speed control of AC and DC motors with their process and security system on the phone keys.

This paper proposes a novel optimization which named as Swarm based Mean-variance mapping optimization (MVMOS) for solving the economic dispatch. The proposed optimization algorithm is the extension of the original single particle mean-variance mapping optimization (MVMO). The novel feature is the special mapping function applied for the mutation base on the mean and variance of n-best population.The MVMOS outperforms the classical MVMO in global search ability due to the improvement of the mapping. The proposed MVMOS is investigated on four test power systems, including 3-, 13- , 20- thermal generating units and large-scale system 140 units with quadratic cost function and the obtained results are compared with many other known methods in the literature. Test results show that the proposed method can efficiently implement for solving economic dispatch.

With rising fuel costs and new emissions standards for automobiles, automotive manufacturers are turning to new ways to decrease engine size and emissions while still maintaining high power operation. This can be accomplished through the use of turbochargers. The aim of this study is to analyze what is currently being done with turbocharger compressor technology to meet these requirements. This analysis will focus on different impeller blading designs including splitter bladed impellers, tandem bladed impellers, and tandem bladed impellers with a casing blade. There are different advantages associated with each impeller design. The tandem bladed impeller designs are shown to have decreased efficiency and pressure ratios as compared with the backswept and/or splitter bladed designs. It is also shown that the operating range is increased with the tandem design due to a lower surge margin. Further analysis needs to be conducted on refining the tandem bladed and tandem bladed with a casing blade designs to truly see if these designs have the potential for greater performance improvements. Keywords: Centrifugal compressor impeller; Turbocharging; Turbomachinery; Tandem-blading; Compressor surge; Compressor performance; Impeller designs Introduction With rising fuel costs and the depletion of natural resources, automotive manufacturers have been looking for ways to increase fuel economy without significantly decreasing an engine’s power output. Many engine manufactures have turned to the use of turbochargers to meet this need. A turbocharger is able to increase an engine’s power by forcing more air into the combustion chamber thus also allowing it take in more fuel as well. The mass of air entering the combustion chamber can increase the power output as well as allow for leaner combustion. These are an attractive option for modern cars because they allow manufacturers to use smaller engines for the same output power. This can increase fuel economy at idling stages as well as reduce the overall weight of the vehicle. They also function as a way to reduce emissions since a majority of modern turbochargers are driven by an exhaust gas turbine. The turbine is connected to the compressor via a common shaft so when it pulls in the exhaust gases, it generates the rotation necessary for the compressor to operate. A major component of the turbocharger is the compressor which is generally a centrifugal compressor. Flow generally enters the compressor in axial direction. The rotating impeller blades then accelerate the fluid before discharging it radially. This increase in velocity will generally lead to an increase in pressure as well. The accelerated fluid can then be discharged into a collector and then on to a diffuser where the fluid velocity is decreased allowing further conversion of velocity into pressure. Generally, a centrifugal compressor is designed for optimal operation at a single speed. This can be problematic as compressors need to be able to function at off-design speeds, especially in the case of automotive turbochargers which have highly transient operation. Due to the transient nature of engine operation, a turbocharger ideally has a large operating range. Bounding the operating range at low speeds with high pressure ratios is the surge limit. Surge occurs when there is a low flow rate at a relatively high pressure ratio causing flow reversal. This causes fluctuations in the flow resulting in unstable operation. Surge that results in a flow reversal over almost the entire fluid flow, also known

The main purpose of this paper is to investigate the multi-criteria decision making (MCDM) under the completely unknown attributes weights. As the information collected from the various resources related to different criteria for assessing the best alternatives is always imprecise in nature. Thus, to handle the impreciseness in the data, fuzzy set theory has been used during the analysis and representation each attribute in the form of triangular fuzzy numbers. Moreover, the attribute weight vectors, used for aggregating the decision maker’s preferences, are found by using an entropy function. Finally, a house selection example, has been taken for demonstrating the approach.

This paper proposes a pseudo-gradient based particle swarm optimization with constriction factor (PG-PSOCF) method for solving multiobjective optimal power flow (MOOPF) problem. The proposed PG-PSOCF is the conventional particle swarm optimization based on constriction factor based on pseudo gradient to enhance its search ability for optimization problems. The proposed method is to deal with the MOOPF problem by minimizing the total cost and emission from generators while satisfying various constraints of real and reactive power balance, real and reactive power limits, bus voltage limits, shunt capacitor limits and transmission limits. Test results on the IEEE 30-bus system have indicated that the proposed method is more efficient than many other methods in the literature. Therefore, the proposed PG-PSOCF can be an effectively alternative method for solving the MOOPF problem.