Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Damage Detection in Flexible Plate Using Lamb Waves

This paper presents an experimental technique for structural health monitoring (SHM) based on Lamb waves approach in an aluminum plate using piezoelectric material as actuators and sensors. Lamb waves are a form of elastic perturbation that remains guided between two parallel free surfaces, such as the upper and lower surfaces of a plate, beam or shelf. Lamb waves are formed when the actuator excites the surface of the structure with a pulse after receiving a signal. Two PZTs were placed in the plate surface and one of them was used to send a predefined wave through the structure. Thus, the other PZT (adjacent) becomes the sensor. Using this methodology, this paper presents one case of damage detection considering the aluminum plate in the free-free-free-free boundary condition. The damage was simulated by adding additional mass on the plate. It is proposed two damage detection indexes obtained from the experimental signal, involving the Fast Fourier Transform (FFT) and the power spectral density (PSD) that were computed using the output signal. The results show the viability of the presented methodology to damage detection in smart structures

Detection of turkey coronavirus in commercial turkey poults in Brazil

Poult enteritis complex has been incriminated as a major cause of loss among turkey poults in other countries. We have observed this in Brazil, associated with diarrhoea, loss of weight gain and, commonly, high mortality In this study, we have used the reverse transcriptase polymerase chain reaction (RT-PCR) to detect turkey coronavirus (TCoV) in sick poults 30 to 120 days of age from a particular producer region in Brazil. The RT-PCR was applied to extracts of intestine tissue suspensions, and the respective intestinal contents, bursa of Fabricius, faecal droppings and cloacal swabs. Primers were used to amplify the conserved 3' untranslated region of the genome, and the nucleocapsid protein gene of TCoV Histo pathological and direct immunohistochemical examinations were performed to detect TCoV antigen in infected intestine and bursa slides. All the results from stained tissues revealed lesions as described previously for TCoV infection. The direct immunohistochemical positive signal was present in all intestine slides. However, all bursa of Fabricius tissues analysed were negative. RT-PCR findings were positive for TCoV in all faecal droppings samples, and in 27% of cloacal swabs. Finally, the best field material for TCoV diagnosis was faecal droppings and/or intestine suspensions.

Why are fruits colorful? The relative importance of achromatic and chromatic contrasts for detection by birds

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detection of cracks in scratching tests in ceramic materials through acoustic emission

The mechanisms of material removal and the interactions among scratches performed in ceramic materials were investigated using acoustic emission signals, and scanning electron microscopy, in scratching experiments. Several testing conditions were used to produce different types of removing mechanism on a glass as well as on a polycrystalline alumina sample composed by heterogeneous grain size. It is known that the material removing process on a polycrystalline ceramic involves intergranular microfracture and grain dislodgement, unlike the chipping produced by the extension of lateral cracks in non-granular materials, such as glass. Distinct settings for velocities, loads, and two types of diamond indenter were tested. The material removal was carried out by three different methods of scratching: single passes, repeated overlapping passes, and parallel scratches. As a general result, there was a clear relationship between the acoustic emission signals and the damage intensity occurred in the material removal. More specifically, there were differences in the acoustic emission signal levels in the scratches made on the alumina and on the glass owing to the material removal mechanisms associated with the structure of these materials. A gradual increase in the acoustic emission levels was observed when the number of repeated passes was increased as a result of the damage accumulation process followed by severe material removal. It was also noticed that the acoustic emission signals were capable of reflecting the interactions between two parallel scratches.

Application of rotor response analysis to fault detection in hydro powerplants.

In this article some considerations obtained during the utilization of rotor response analysis techniques in hydraulic powerplants are discussed. An applied research work was carried out in two hydraulic turbines analysing the rotor response both theoretically and experimentally. A developed mathematical model was used to simulate the rotordynamic behaviour of Francis and Kaplan turbines. The main dynamical effects that appear during the operation of the machines are discussed too. A series of measurements were carried out in the turbines using impact hammers to determine the modal behaviour of the units. The tests were carried out with the machine still and in operation. Some results and the comparison with the theory is presented in this article. The improved theoretical model was used for a sensitivity analysis of the different bearings to the main excitations that fake place during the machine operation. From this analysis, the best measuring points for condition monitoring were determined.

Label-free DNA detection based on modified conducting polypyrrole films at microelectrodes

A label-free electrochemical detection method for DNA hybridization based on electrostatic modulation of the ion-exchange kinetics of a polypyrrole film deposited at microelectrodes is reported. Synthetic single-stranded 27-mer oligonucleotides (probe) have been immobilized at 2,5-bis(2-thienyl)-N-(3-phosphorylpropyl)pyrrole film formed by electropolymerization on the previously formed polypyrrole layer. The 27- or 18-mer target oligonucleotides were monitored via the electrochemically driven anion exchange of the inner polypyrrole film. The performance of the miniaturized DNA biosensor system was studied in respect to selectivity, sensitivity, reproducibility, and regeneration of the sensor. Control experiments were performed with a noncomplementary target of 27-mer DNA and 12 base-pair mismatched 18-mer sequences, respectively, and did not show any unspecific binding. Under optimized experimental conditions, the label-free electrochemical biosensor enabled the detection limits of 0.16 and 3.5 fmol for the 18- and 2 7-mer DNA strand, respectively. Furthermore, we demonstrate reusability of the electrochemical DNA biosensor after successful recovery of up to 100% of the original signal by regenerating the DNA label-free electrode with 50 mM HCl at room temperature.

Surface-enhanced resonance Raman scattering as an analytical tool for single molecule detection

A perylene derivative, n-(n-butyl)-n'-(4-aminobutyl) perylene-3,4,9,10-tetracarboxylic acid diimide (simplified as nBu-PTCD-(CH2)(4)-NH2) has been chosen as the target molecule for studies involving single molecule detection (SMD) using Raman scattering. The enhancement of the Raman signal is the result of the multiplicative effects of two phenomena, resonance Raman scattering (RRS) and surface-enhanced Raman scattering (SERS), which leads to the resulting surface-enhanced resonance Raman scattering (SERRS) process. The SERRS spectra from a single molecule have been collected using both silver and gold colloids. The SMD detection of the fundamental vibrational frequencies characteristic of nBu-PTCD-(CH2)(4)-NH2 is complemented with the detection of some overtones and combinations from ring stretching modes at the single molecule level. The background characterization of the ensemble vibrational spectroscopy of the target perylene and its SERRS is also presented, which includes the UV-vis absorption, experimental and calculated Raman scattering and infrared absorption, and molecular organization using reflection-absorption infrared spectroscopy (RAIRS).

Determination of low-aliphatic aldehydes indoors by micellar electrokinetic chromatography using sample dissolution manipulation for signal enhancement

This work describes a novel approach for the analysis of selected aldehydes (formaldehyde, acetaldehyde, propionaldehyde, and acrolein) and acetone in environmental samples using micellar electrokinetic chromatography (MEKC). The method is based on the reaction of carbonyl compounds with 3-methyl-2-benzothiazoline hydrazone (MBTH) that gives an azine intermediate with maximum absorbance at 216 nm. A systematic evaluation of sample dissolution medium was conducted as a means to enhancing sensitivity. In the best condition, samples were dissolved in 0.030 mol.L-1 tetraborate solution. This condition presented enhancement factors in the range of 35-54 for the aldehydes under investigation, computed as the improvement of the concentration limits of detection (LODs) with reference to the sample dissolved in pure water. The running buffer was 0.020 mol.L-1 tetraborate, pH 9.3, containing 0.050 mol-L-1 sodium dodecyly sulfate (SIDS). The overall methodology presented several advantages over established methods for aldehydes. Worthy mentioning that MBTH is available in high purity degree, dispensing laborious reagent purification procedures. A few method validation parameters were determined revealing good migration time repeatability (< 2.5% coefficient of variation, CV) and area repeatability (< 4% CV), excellent linearity (20-120 mug/L, r > 0.995) and adequate sensitivity for environmental applications. The LODs with respect to each single aldehyde were in the range of 0.54-4.0 mug.L-1 and 11 mug.L-1 for acetone. The methodology was applied to the determination of aldehydes indoors. Samples were collected in an impinger flask containing 0.05% MBTH solution, at a flow rate of 0.80 L.min(-1), during 2.5 h, at different times during the day. The most abundant carbonyls in the samples were acetone, followed by formaldehyde and acetaldehyde, with estimate peak concentrations of 452, 5.2 and 2.2 ppbv, respectively.

Determination of acetaldehyde in fuel ethanol by high-performance liquid chromatography with electrochemical detection

The cyclic voltammetric behavior of acetaldehyde and the derivatized product with 2,4-dinitrophenylhydrazine (DNPHi) has been studied at a glassy carbon electrode. This study was used to optimize the best experimental conditions for its determination by high-performance liquid chromatographic (HPLC) separation coupled with electrochemical detection. The acetaldehyde-2,4-dinitrophenyl.hydrazone (ADNPH) was eluted and separated by a reversed-phase column, C-18, under isocratic conditions with the mobile phase containing a binary mixture of methanol/LiCl(aq) at a concentration of 1.0 x 10(-3) M (80:20 v/v) and a flow rate of 1.0 mL min(-1). The optimum condition for the electrochemical detection of ADNPH was +1.0 V vs. Ag/AgCl as a reference electrode. The proposed method was simple, rapid (analysis time 7 min) and sensitive (detection limit 3.80 mu g L-1) at a signal-to-noise ratio of 3:1. It was also highly selective and reproducible [standard deviation 8.2% +/- 0.36 (n = 5)]. The analytical curve of ADNPH was linear over the range of 3-300 mg L-1 per injection (20 mu L), and the analytical recovery was > 99%.

Determination of rice herbicides, their transformation products and clofibric acid using on-line solid-phase extraction followed by liquid chromatography with diode array and atmospheric pressure chemical ionization mass spectrometric detection

A simultaneous method for the trace determination of acidic, neutral herbicides and their transformation products in estuarine waters has been developed through an on-line solid-phase extraction method followed by liquid chromatography with diode array and mass spectrometric detection. An atmospheric pressure chemical ionization (APCI) interface was used in the negative ionization mode after optimization of the main APCI parameters. Limits of detection ranged from 0.1 to 0.02 ng/ml for 50 mi of acidified estuarine waters preconcentrated into polymeric precolumns and using time-scheduled selected ion monitoring mode. Two degradation products of the acidic herbicides (4-chloro-2-methylphenol and 2,4-dichlorophenol) did not show good signal response using APCI-MS at the concentration studied due to the higher fragmentor voltage needed for their determination For molinate and the major degradation product of propanil, 3,4-dichloroaniline, positive ion mode was needed for APCI-MS detection. The proposed method was applied to the determination of herbicides in drainage waters from rice fields of the Delta del Ebro (Spain). During the S-month monitoring of the herbicides, 8-hydroxybentazone and 4-chloro-2-methylphenoxyacetic acid were successively found in those samples. (C) 2000 Elsevier B.V. B.V. All rights reserved.

A new technique for thermal neutron detection using pyroelectric ceramics

In this article a new technique for thermal neutron detection using pyroelectric ceramics is described. The detector system is basically constituted of a PZT (lead zirconate titanate) ceramic attached to an uranium disk. The energy released in the uranium fission gives rise to an electrical signal in the detector which is amplified by a lock-in system. The neutron beam impinging on the uranium disk was modulated with a cadmium chopper. Thermal neutron fluxes within the interval of 103 to 106 n/cm2 s have been detected using a U3O8 pellet with 20% enrichment in 235U. © 1992.

Automation in fault detection using neural network and model updating

In this article, an implementation of structural health monitoring process automation based on vibration measurements is proposed. The work presents an alternative approach which intent is to exploit the capability of model updating techniques associated to neural networks to be used in a process of automation of fault detection. The updating procedure supplies a reliable model which permits to simulate any damage condition in order to establish direct correlation between faults and deviation in the response of the model. The ability of the neural networks to recognize, at known signature, changes in the actual data of a model in real time are explored to investigate changes of the actual operation conditions of the system. The learning of the network is performed using a compressed spectrum signal created for each specific type of fault. Different fault conditions for a frame structure are evaluated using simulated data as well as measured experimental data.