Actuator fault detection and isolation in linear systems

A scheme for the detection and isolation of actuator faults in linear systems is proposed. A bank of unknown input observers is constructed to generate residual signals which will deviate in characteristic ways in the presence of actuator faults. Residual signals are unaffected by the unknown inputs acting on the system and this decreases the false alarm and miss probabilities. The results are illustrated through a simulation study of actuator fault detection and isolation in a pilot plant doubleeffect evaporator.

Synthesis and Isolation of 5,6-Dihydro-4H-1,3-Oxazine Hydrobromides by Autocyclization of N-(3-Bromopropyl)amides

5,6-Dihydro-4H-1,3-oxazine hydrobromides have been synthesized by the nucleophilic autocyclo-O-alkylation of N-(3-bromopropyl)amides under neutral conditions in chloroform. It is found that electron-donating amide alpha-substituents influence the autocyclization efficiency.

Synthesis, Structures, and Magnetic Behavior of a Series of Copper(II) Azide Polymers of Cu-4 Building Clusters and Isolation of a New Hemiaminal Ether as the Metal Complex

Four new neutral copper azido polymers, Cu-4(N-3)(8)(L-1)(2)](n) (1), Cu-4(N-3)(8)(L-2)(2)](n) (2), Cu-4(N-3)(8)(L-3)(2)](n) (3), and Cu-9(N-3)(18)(L-4)(4)](n) (4) L1-4 are formed in situ by reacting pyridine-2-carboxaldehyde with 22-(methylamino)ethyl]pyridine (mapy, L-1), N,N-dimethylethylenediamine (N,N-dmen, L-2), N,N-diethylethylenediamine (N,N-deen, L-3), and N,N,2,2-tetramethylpropanediamine (N,N,2,2-tmpn, L-4)], have been synthesized by using 0.5 mol equiv of the chelating tridentate ligands with Cu-(NO3)(2)center dot 3H(2)O and an excess of NaN3. Single-crystal X-ray structures show that the basic unit of these complexes, especially 1-3, contains very similar Cu-4(II) building blocks. The overall structure of 3 is two-dimensional, while the other three complexes are one-dimensional in nature. Complex 1 represents a unique example containing hemiaminal ether arrested by copper(R). Complexes 1 and 2 have a rare bridging azido pathway: both end-on and end-to-end bridging azides between a pair of Cu-II centers. Cryomagnetic susceptibility measurements over a wide range of temperature exhibit dominant ferromagnetic behavior in all four complexes. Density functional theory calculations (B3LYP functional) have been performed on complexes 1-3 to provide a qualitative theoretical interpretation of their overall ferromagnetic behavior.

A study on fear memory retrieval and REM sleep in maternal separation and isolation stressed rats

As rapid brain development occurs during the neonatal period, environmental manipulation during this period may have a significant impact on sleep and memory functions. Moreover, rapid eye movement (REM) sleep plays an important role in integrating new information with the previously stored emotional experience. Hence, the impact of early maternal separation and isolation stress (MS) during the stress hyporesponsive period (SHRP) on fear memory retention and sleep in rats were studied. The neonatal rats were subjected to maternal separation and isolation stress during postnatal days 5-7 (6 h daily/3 d). Polysomnographic recordings and differential fear conditioning was carried out in two different sets of rats aged 2 months. The neuronal replay during REM sleep was analyzed using different parameters. MS rats showed increased time in REM stage and total sleep period also increased. MS rats showed fear generalization with increased fear memory retention than normal control (NC). The detailed analysis of the local field potentials across different time periods of REM sleep showed increased theta oscillations in the hippocampus, amygdala and cortical circuits. Our findings suggest that stress during SHRP has sensitized the hippocampus amygdala cortical loops which could be due to increased release of corticosterone that generally occurs during REM sleep. These rats when subjected to fear conditioning exhibit increased fear memory and increased, fear generalization. The development of helplessness, anxiety and sleep changes in human patients, thus, could be related to the reduced thermal, tactile and social stimulation during SHRP on brain plasticity and fear memory functions. (C) 2014 Elsevier B.V. All rights reserved.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

Bufferless lysis of erythrocytes for isolation of hemoglobin using modified cellulose acetate membranes

This paper presents a modified cellulose acetate membrane prepared using a dry casting technique that can be used to perform lysis of erythrocytes and isolation of hemoglobin. Isolation of hemoglobin is thus achieved without the use of lysis buffers. Cellulose acetate (CA) membranes are embedded with ammonium chloride (NH4Cl) and potassium bicarbonate (KHCO3), which act as lysing agents. The presence of embedded salts is confirmed using EDS analysis. The pores in the CA membrane act as filters. The average pore size in these membranes is designed to be 1.5 mu M, as characterized by SEM analysis, so that they allow hemoglobin to pass through and block all other cells and unlysed erythrocytes present in blood. When a drop of blood is added to the membrane, the NH4Cl and KHCO3 embedded in the membrane dissolve in plasma and lyse the erythrocytes. The filtered hemoglobin is characterized using UV-Vis Spectroscopy. The results indicate extraction of higher concentration of hemoglobin compared with conventional methods.

Mixed-ligand aroylhydrazone complexes of molybdenum: Synthesis, structure and biological activity

The reaction of the benzoylhydrazone of 2-hydroxybenzaldehyde (H2L) with MoO2(acac)(2)] proceeds smoothly in refluxing ethanol to afford an orange complex MoO2L(C2H5OH)] (1). The substrate binding capacity of 1 has been demonstrated by the formation and isolation of two mononuclear MoO2L(Q)] {where Q = imidazole (2a) and 1-methylimidazole (2b)} and one dinuclear (MoO2L)(2)(Q)] {Q = 4,4'-bipyridine (3)} mixed-ligand oxomolybdenum complex. All the complexes have been characterized by elemental analysis, magnetic and spectroscopic (IR, UV-Vis and NMR) measurements. The molecular structures of all the oxomolybdenum(VI) complexes (1, 2a, 2b and 3) have been determined by X-ray crystallography. In each complex, the dianionic planar ligand is coordinated to the metal centre via one enolate oxygen, one phenolate oxygen and an azomethine nitrogen atom. The complexes have been screened for their antibacterial activity against Escherichia coli, Bacillus and Pseudomonas aeruginosa. The minimum inhibitory concentration of these complexes and their antibacterial activity indicates that compounds 2a and 2b are potential lead molecules for drug designing. (C) 2012 Elsevier Ltd. All rights reserved.

Microprocessor Based Sinusoidal PWM Inverter by DMA Transfer

The implementation of three-phase sinusoidal pulse-width-modulated inverter control strategy using microprocessor is discussed in this paper. To save CPU time, the DMA technique is used for transferring the switching pattern from memory to the pulse amplifier and isolation circuits of individual thyristors in the inverter bridge. The method of controlling both voltage and frequency is discussed here.

Microprocessor Based Sinusoidal PWM Inverter by DMA Transfer

The implementation of three-phase sinusoidal pulse-width-modulated inverter control strategy using microprocessor is discussed in this paper. To save CPU time, the DMA technique is used for transferring the switching pattern from memory to the pulse amplifier and isolation circuits of individual thyristors in the inverter bridge. The method of controlling both voltage and frequency is discussed here.

Reliability analysis of torsional varactor

A torsional MEMS varactor with wide dynamic range, lower actuation voltage and isolation between actuation voltage and signal voltage has been proposed in C. Venkatesh et al. (2005). In this paper we address the effects of pull-in, residual stress and continuous cycling on the performance of torsional MEMS varactor.

A DC-to-Three-Phase-AC High-Frequency Link Converter With Compensation for Nonlinear Distortion

This paper focuses on a new high-frequency (HF) link dc-to-three-phase-ac power converter. The least number of switching devices among other HF link dc-to-three-phase-ac converters, improved power density due to the absence of devices of bidirectional voltage-blocking capability, simple commutation requirements, and isolation between input and output are the integral features of this topology. The commutation process of the converter requires zero portions in the link voltage. This causes a nonlinear distortion in the output three-phase voltages. The mathematical analysis is carried out to investigate the problem, and suitable compensation in modulating signal is proposed for different types of carrier. Along with the modified modulator structure, a synchronously rotating reference-frame-based control scheme is adopted for the three-phase ac side in order to achieve high dynamic performance. The effectiveness of the proposed scheme has been investigated and verified through computer simulations and experimental results with 1-kVA prototype.

The design of polyaniline based sensor for the qualitative estimation of malonaldehyde

The detection of contaminated food in every stage of processing required new technology for fast identification and isolation of toxicity in food. Since effect of food contaminant are severe to human health, the need of pioneer technologies also increasing over last few decades. In the current study, MDA was prepared by hydrolysis of 1,1,3,3-tetramethoxypropane in HCl media and used in the electrochemical studies. The electrochemical sensor was fabricated with modified glassy carbon electrode with polyaniline. These sensors were used for detection of sodium salt of malonaldehyde and observed that a high sensitivity in the concentration range similar to 1 x 10(-1) M and 1 x 10(-2) M. Tafel plots show the variation of over potential from -1.73 V to -3.74 V up to 10(-5) mol/L indicating the lower limit of detection of the system. (C) 2013 Elsevier Ltd. All rights reserved.