Tool Wear Classification Using Fuzzy Logic for Machining of Al/SiC Composite Material

Tool wear state classification has good potential to play a critical role in ensuring the dimensional accuracy of the work piece and prevention of damage to cutting tool in machining process. During machining process, tool wear is an important factor which contributes to the variation of spindle motor current, speed, feed and depth of cut. In the present work, online tool wear state detecting method with spindle motor current in turning operation for Al/SiC composite material is presented. By analyzing the effects of tool wear as well as the cutting parameters on the current signal, the models on the relationship between the current signals and the cutting parameters are established with partial design taken from experimental data and regression analysis. The fuzzy classification method is used to classify the tool wear states so as to facilitate defective tool replacement at the proper time.

Analysis of vibrational spectra of nano-bio molecules: Application to metalloporphrins

In this paper, we have applied the Lie algebraic model to nano-bio molecules to determine the vibrational spectra of different stretching and bending vibrational modes. The determined vibrational energy levels by the Lie algebraic model are compared with the experimental data. The results from the theoretical mode[ are consistent with the experimental data. The vibrational energy levels are clustering in the excited states.

Resonance Raman spectroscopy of red blood cells using lie algebraic technique

Raman spectra of oxygenated and deoxygenated functional erythrocytes are calculated by using Lie algebraic technique. The results are obtained by this method is accuracy with the experimental data. So, the algebraic techniques are appropriate to the Raman spectra of red blood cells.

Design of Low Power and High Speed CMOS Comparator for A/D Converter Application

This paper presents an improved method for design of CMOS comparator based on a preamplifier-latch circuit driven by a clock. Design is intended to be implemented in Sigma-delta Analog-to-Digital Converter (ADC). The main advantage of this design is capable to reduce power dissipation and increase speed of an ADC. The design is simulated in 0.18 μm CMOS Technology with Cadence environment. Proposed design exhibits good accuracy and a low power consumption about 102 μW with operating sampling frequency 125 MHz and 1.8 V supply. Simulation results are reported and compared with earlier work done and improvements are observed in this work.

Design of a CMOS Optical Receiver Front-End Using 0.18 μm Technology

This paper reports design of a CMOS optical receiver front-end using 0.18 μm technology. Design process is current associated with photodiode using trans-impedance amplifier (TIA) for wide bandwidth, high gain, low input referred noise and wide dynamic range. The Automated Gain Control (AGC) voltage is used to provide variable gain for multilevel signals. This design is simulated in 0.18 μm UMC technology for the performance analysis. The best simulation results are reported the maximum TIA gain of 67.26 dB? at 0 V AGC followed by a post amplifier gain of 86.70 dB?. The bandwidth range is 7.03 GHz to 11.5 GHz corresponding to 0 - 3 V AGC respectively. The input referred noise level value is 43.86 pA/√Hz up to 10 GHz frequency. In addition authors have obtained the common mode rejection ratio (CMRR) is 72.42 dB and rectified group delay is 144.48 ps. Verification of the design, reported results are compared with earlier published work and improvements obtained in the present results.

A Study on Vibrational Spectra of PH3 and NF3: An Algebraic Approach

With the new theoretical approach i.e. lie algebraic approach, we have calculated the infrared spectra of Phosphine in the range from 3000 cm-1 to 9500 cm-1 and Nitrogen Trifluoride in the range from 900 cm-1 to 4500 cm-1. The model Hamiltonian, so constructed, seems to describe the P-H and N-F stretching modes accurately with only four numbers of parameters.

Fuzzy Based Intelligent Monitoring of Critical Lines in the Restructured Power Market

Restructured electric market environment allows the power wheeling transactions between the power producers and customers to meet the growing load demand. This will lead to the possible of congestion in the transmission lines. The possible contingencies of power components further worsen the scenario. This paper describes the methodology for the identification of critical transmission line by computing the real power and reactive power performance indices. It also demonstrates the importance of fuzzy logic technique used to rank the transmission lines according to the severity and demonstrated on IEEE-30 bus system.

Classification Using Two Layer Neural Network Back Propagation Algorithm

Worldwide breast cancer is the most common form of cancer death occurring in 12.6% of women. This paper presents a cost effective approach to classify the normal, malignant and benign tumor using two layer neural network back propagation algorithm. Back propagation algorithm is used to train the neural network. Parallelization techniques speed up the computation process and as a result two layer neural networks outperform the previous work in terms of accuracy. Breast cancer tumor database used for the testing purpose is from the CIA machine learning repository. The highest accuracy of 97.12% is achieved using the two layer neural network back propagation algorithm.