Use of particle swarm optimization for machinery fault detection

A study is presented on the application of particle swarm optimization (PSO) combined with other computational intelligence (CI) techniques for bearing fault detection in machines. The performance of two CI based classifiers, namely, artificial neural networks (ANNs) and support vector machines (SVMs) are compared. The time domain vibration signals of a rotating machine with normal and defective bearings are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to the classifiers for detection of machine condition. The classifier parameters, e.g., the number of nodes in the hidden layer for ANNs and the kernel parameters for SVMs are selected along with input features using PSO algorithms. The classifiers are trained with a subset of the experimental data for known machine conditions and are tested using the remaining set of data. The procedure is illustrated using the experimental vibration data of a rotating machine. The roles of the number of features, PSO parameters and CI classifiers on the detection success are investigated. Results are compared with other techniques such as genetic algorithm (GA) and principal component analysis (PCA). The PSO based approach gave a test classification success rate of 98.6–100% which were comparable with GA and much better than with PCA. The results show the effectiveness of the selected features and the classifiers in the detection of the machine condition.     

A reliable and accurate calculation of excitation capacitance value for an induction generator based on interval computation technique

A squirrel cage induction generator (SCIG) offers many advantages for wind energy conversion systems but suffers from poor voltage regulation under varying operating conditions. The value of excitation capacitance (C exct ) is very crucial for the selfexcitation and voltage build-up as well as voltage regulation in SCIG. Precise calculation of the value of C exct is, therefore, of considerable practical importance. Most of the existing calculation methods make use of the steady-state model of the SCIG in co...     

Inhaled benzene increases the frequency and length of lacI deletion mutations in lung tissues of mice

This study investigated the frequency and pattern of mutations that arose in lacI transgenes in lung tissues of mice exposed to 300 p.p.m. of benzene for 6 h/day x 5 days/week for 12 weeks. The nucleotide sequence changes in 86 lacI- transgenes from lung tissues of eight benzene-exposed mice (BEM) and 78 spontaneous lacI- transgenes from lung tissues of eight unexposed control mice (UCM) were identified and compared. A total of 31% (27/86) of the lacI mutations in BEM are deletions compared with 9% (7/78) deletions in UCM. In BEM, 44% (12/27) of the deletions were longer than 10 bp, whereas only 14% (1/7) of the deletions in UCM exceeded 10 bp in length. Statistical tests supported the hypothesis that benzene exposure resulted in significant increases in both the frequency and length of deletions. Based on the lacI mutant frequency and fraction of unique mutations, lung tissues of BEM were estimated to have a 1.8-fold increase in lacI mutation frequency compared with lung tissues of UCM. The results presented in this paper demonstrate that inhaled benzene is a gene mutagen in lung tissues of mice.     

A New Subdivision Algorithm for the Bernstein Polynomial Approach to Global Optimization

In this paper,an improved algorithm is proposed for unconstrained global optimization to tackle non-convex nonlinear multivariate polynomial programming problems.The proposed algorithm is based on the Bernstein polynomial approach.Novel features of the proposed algorithm are that it uses a new rule for the selection of the subdivision point,modified rules for the selection of the subdivision direction,and a new acceleration device to avoid some unnecessary subdivisions.The performance of the proposed algorithm is numerically tested on a collection of 16 test problems.The results of the tests show the proposed algorithm to be superior to the existing Bernstein algorithm in terms of the chosen performance metrics.     

Computation of QFT bounds for robust tracking specifications

An algorithm is proposed for generation of QFT controller bounds to achieve robust tracking specifications. The proposed algorithm uses quadratic constraints and interval plant templates to compute the bounds, and presents several improvements over existing QFT tracking bound generation algorithms. The proposed algorithm (1) guarantees robustness against template inaccuracies, (2) guarantees robustness against phase discretization, (3) provides a posteriori error estimates, (4) is computationally efficient, achieving a reduction in flops and execution time, typically by 1-2 orders of magnitude. The algorithm is demonstrated on an aircraft example having five uncertain parameters.     

Distillery wastewater treatment by the membrane-based nanofiltration and reverse osmosis processes

A hybrid nanofiltration (NF) and reverse osmosis (RO) pilot plant was used to remove the color and contaminants of the distillery spent wash. The feasibility of the membranes for treating wastewater from the distillery industry by varying the feed pressure (0-70 bar) and feed concentration was tested on the separation performance of thin-film composite NF and RO membranes. Color removal by NF and a high rejection of 99.80% total dissolved solids (TDS), 99.90% of chemical oxygen demand (COD) and 99.99% of potassium was achieved from the RO runs, by retaining a significant flux as compared to pure water flux, which shows that membranes were not affected by fouling during wastewater run. The pollutant level in permeates were below the maximum contaminant level as per the guidelines of the World Health Organization and the Central Pollution Control Board specifications for effluent discharge (less than 1,000 ppm of TDS and 500 ppm of COD).     

A novel approach to multiparametric quadratic programming

Multiparametric (mp) programming pre-computes optimal solutions offline which are functions of parameters whose values become apparent online. This makes it particularly well suited for applications that need a rapid solution of online optimization problems. In this work, we propose a novel approach to multiparametric programming problems based on an enumeration of active sets and use it to obtain a parametric solution for a convex quadratic program (QP). To avoid the combinatorial explosion of the enumeration procedure, an active set pruning criterion is presented that makes the enumeration implicit. The method guarantees that all regions of the partition are critical regions without any artificial cuts, and further that no region of the parameter space is left unexplored.     

Downregulation of T cell receptor expression by CD8(+) lymphocytes in kidney allografts

Allospecific CD8(+) T lymphocytes are an important component of the cellular response in allograft rejection. These cells recognize and engage MHC class I antigens, leading to allospecific cytolytic responses and graft rejection. In mouse kidney allografts that survive to 3 wk after transplantation, we noted that the majority of CD8(+) cells do not express surface alpha/beta T cell receptor alpha/beta(TCR), gamma/deltaTCR, or CD3. However, these CD8(+)TCR- cells did express surface markers characteristic of T cells, including Thy1.2, CD2, and CD5. In addition, the CD8(+)TCR- cells expressed mRNA for TCR Vbeta gene families, and nearly half stained positive for cytoplasmic Vbeta8 protein, suggesting that they are T cells that have downregulated alpha/betaTCR protein expression from their cell surfaces. When these surface TCR- cells were isolated from kidney allografts by flow cytometry and cultured in the presence of either allogeneic or syngeneic stimulators, nearly 100% of cells reacquired normal levels of alpha/betaTCR expression with disproportionate usage of Vbeta8 chains. After recovery of their surface TCR expression, the CD8(+)TCR- population demonstrated strong alloreactivity in culture. These results suggest that the substantial number of CD8(+)TCR- cells found in long-term surviving mouse kidney allografts are alpha/beta-T cells that have downregulated their cell surface expression of TCR. While in other systems this phenotype may identify cells that have engaged antigen, our results indicate that loss of TCR expression by CD8(+) kidney graft-infiltrating cells may not depend on antigen engagement and that elements in the microenvironment of the kidney graft play a key role in this process. Factors that modulate expression of TCR by graft-infiltrating lymphocytes may have an important role in regulating rejection responses.     

A New Subdivision Strategy for Range Computations

We present a new subdivision strategy in interval analysis for computing the ranges of functions. We show through several real-world examples that the proposed subdivision strategy is more efficient than the widely used uniform and adaptive subdivision strategies of Moore (Methods and Applications of Interval Analysis, SIAM, Philadelphia, 1979).     

Interval QFT: a mathematical and computational enhancement of QFT

The paper presents an overview of a mathematical and computational enhancement of Horowitz's QFT design procedure. The enhancement uses methods of interval analysis and is called as interval QFT, or IQFT. IQFT addresses and solves some of the fundamental issues in QFT, concerning selection of design frequencies, selection of controller phases in bound generation, approximation of plant templates with finite plant sets, and generation of plant templates and controller bounds with reliability and to a prescribed accuracy. An example is presented to illustrate the key features of IQFT. Copyright © 2002 John Wiley & Sons, Ltd.