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.

Constrained optimization model for the design of an adaptive (X)over-bar chart

An economic-statistical model is developed for variable parameters (VP) (X) over bar charts in which all design parameters vary adaptively, that is, each of the design parameters (sample size, sampling interval and control-limit width) vary as a function of the most recent process information. The cost function due to controlling the process quality through a VP (X) over bar chart is derived. During the optimization of the cost function, constraints are imposed on the expected times to signal when the process is in and out of control. In this way, required statistical properties can be assured. Through a numerical example, the proposed economic-statistical design approach for VP (X) over bar charts is compared to the economic design for VP (X) over bar charts and to the economic-statistical and economic designs for fixed parameters (FP) (X) over bar charts in terms of the operating cost and the expected times to signal. From this example, it is possible to assess the benefits provided by the proposed model. Varying some input parameters, their effect on the optimal cost and on the optimal values of the design parameters was analysed.

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 hierarchy of adaptive (X)over-bar control charts

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Harmonics filtering and detection of disturbances using wavelets

Traditional mathematical tools, like Fourier Analysis, have proven to be efficient when analyzing steady-state distortions; however, the growing utilization of electronically controlled loads and the generation of a new dynamics in industrial environments signals have suggested the need of a powerful tool to perform the analysis of non-stationary distortions, overcoming limitations of frequency techniques. Wavelet Theory provides a new approach to harmonic analysis, focusing the decomposition of a signal into non-sinusoidal components, which are translated and scaled in time, generating a time-frequency basis. The correct choice of the waveshape to be used in decomposition is very important and discussed in this work. A brief theoretical introduction on Wavelet Transform is presented and some cases (practical and simulated) are discussed. Distortions commonly found in industrial environments, such as the current waveform of a Switched-Mode Power Supply and the input phase voltage waveform of motor fed by inverter are analyzed using Wavelet Theory. Applications such as extracting the fundamental frequency of a non-sinusoidal current signal, or using the ability of compact representation to detect non-repetitive disturbances are presented.

Production grinding burn detection using acoustic emission and electric power signals

This work uses a monitoring system based on a PC platform, where the acoustic emission and electric power signals generated during the grinding process are used to investigate superficial burning occurrence in a surface grinding operation using two types of steel, three grinding conditions and an Al203 vitrified grinding wheel. Acoustic emission signals on the workpiece and grinding power were measured during a surface plunge operation until the grinding burn happened. From the results the standard deviation of the acoustic emission signal and the maximum electric power were calculated for each grinding pass. The proposed DPO parameter is the product between the power level and acoustic emission standard deviation. The results show that both signals can be used for burning detection, and the parameter DPO is the best indicator for the burning studied in this work. This can be explained by the high dispersion of the acoustic emission RMS level associated to the high power consumption when the grinding wheel lose its sharpness.

Neural network detection of grinding burn from acoustic emission

An artificial neural network (ANN) approach is proposed for the detection of workpiece `burn', the undesirable change in metallurgical properties of the material produced by overly aggressive or otherwise inappropriate grinding. The grinding acoustic emission (AE) signals for 52100 bearing steel were collected and digested to extract feature vectors that appear to be suitable for ANN processing. Two feature vectors are represented: one concerning band power, kurtosis and skew; and the other autoregressive (AR) coefficients. The result (burn or no-burn) of the signals was identified on the basis of hardness and profile tests after grinding. The trained neural network works remarkably well for burn detection. Other signal-processing approaches are also discussed, and among them the constant false-alarm rate (CFAR) power law and the mean-value deviance (MVD) prove useful.

In-process thermal damage detection in grinding with monitoring via Internet

This work aims the development of a dedicated system for detection of burning in surface grinding process, where the process will constantly be monitored through the acoustic emission and electric power of the induction motor drive. Acquired by an analog-digital converter, algorithms process the signals and a control signal is generated to inform the operator or interrupt the process in case of burning occurrence. Moreover, the system makes possible the process monitoring via Internet. Additionally, a comparative study between parameters DPO and FKS is carried through. In the experimental work one type of. steel (ABNT-1020 annealed) and one type of grinding wheel referred to as TARGA, model ART 3TG80.3 NVHB, were employed.

Adaptative techniques for the human faces detection

This paper presents results from an efficient approach to an automatic detection and extraction of human faces from images with any color, texture or objects in background, that consist in find isosceles triangles formed by the eyes and mouth.