Smart structures health monitoring using artificial neural network

This paper presents a non-model based technique to detect and locate structural damage with the use of artificial neural networks. This method utilizes high frequency structural excitation (typically greater than 30 kHz) through a surface-bonded piezoelectric sensor/actuator to detect changes in structural point impedance due to the presence of damage. Two sets of artificial neural networks were developed in order to detect, locate and characterize structural damage by examining changes in the measured impedance curves. A simulation beam model was developed to verify the proposed method. An experiment was successfully performed in detecting damage on a 4-bay structure with bolted-joints, where the bolts were progressively released.

Influência do intervalo entre a inseminação artificial com sêmen diluído resfriado e transportado e a ovulação sobre a fertilidade de éguas

One hundred forty seven cycles of mares were allocated in a completely randomized experiment, with different number of replications and divided in four treatments (T1 = 24 hours preovulation; T2 = 48 hours preovulation; T3 = 48 hours preovulation and in tbe same day of ovulation; T4 = 72 hours preovulation and in the same day of ovulation), in order to study the effect of AI/ovulation interval on mare fertility. The mares were inseminated three times for wek (monday, wednesday and friday), with semen of only one stallion diluted in extender skim milk-glucose, using a volume of 15ml, with 400 x 10(6) sptz viable, cooled at 14 degrees C/3.6 hours, and transported in modified container Celle. Conception rates were not different according to the treatments. So, observed spermatic survival for 60 hours showed the practicability of the inseminations on monday, wednesday and friday.

Uterine leucocyte infiltration after artificial insemination in bitches

In the present study, polymorphonuclear neutrophils (PMN) were enumerated to evaluate acute uterine inflammation after artificial insemination in the bitch. It was concluded that the canine seminal plasma possessed an immunomodulating action. However, the most commonly used extender for freezing canine semen (Tris glucose with egg yolk and glycerol) was a potential inducer of uterine inflammation. (c) 2006 Published by Elsevier B.V.

Using artificial neural networks for identification of electrical losses in transformers during the manufacturing phase

The paper describes a novel neural model to estimate electrical losses in transformer during the manufacturing phase. The network acts as an identifier of structural features on electrical loss process, so that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through experimental data taking into account core losses, copper losses, resistance, current and temperature. The results obtained in the simulations have shown that the developed technique can be used as an alternative tool to make the analysis of electrical losses on distribution transformer more appropriate regarding to manufacturing process. Thus, this research has led to an improvement on the rational use of energy.

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Potentiometric determination of saccharin in commercial artificial sweeteners using a silver electrode

A simple, precise, rapid and low-cost potentiometric method for saccharin determination in commercial artificial sweeteners is proposed. Saccharin present in several samples of artificial sweeteners is potentiometrically titrated with silver nitrate solution using a silver wire as the indicator electrode, coupled to a titroprocessor. The best pH range was from 3.0 to 3.5 and the detection limit of sodium saccharin was 2.5 mg/ml. Substances normally found along with saccharin in several commercial artificial sweeteners such as maltodextrin, glucose, sucrose, fructose, aspartame, cyclamate, caffeine, sorbitol, lactose, nitrate, methyl- and n-propyl-p-hydroxybenzoate, benzoic, citric and ascorbic acids do not interfere even in significant amounts (e.g. 20 excess relative to saccharin). Chloride ion interferes when present in concentrations larger than 10 mg l(-1); this interference is eliminated with previous extraction of the sweetener from the aqueous medium with ethyl acetate. The results obtained by applying the proposed method compared very favorably with those given by the HPLC method recommended by the FDA. (C) 2003 Elsevier Ltd. All rights reserved.

Comparison of direct digital and conventional imaging with Ekta Speed Plus and INSIGHT films for the detection of approximal caries

Purpose: To evaluate the accuracy of approximal caries detection comparing enhanced and unenhanced Sidexis CCD-based digital image with Ektaspeed Plus and INSIGHT films. Methods: Fifty-two extracted premolars were imaged under identical standardized geometric and exposure conditions. Four observers, using five points confidence scale, rated 104 approximal surfaces for the presence or absence of carious lesions by means of four image modalities: (1) observer enhanced; (2) unenhanced Sidexis displays; (3) E speed films and (4) F speed film. Histologic sections served as validating criterion for the presence and depth of carious lesions. Diagnostic accuracy was measured as the area beneath the ROC curve. Results: Mean ROC (receiver operating characteristic) curve areas for approximal surfaces were 0.865 (E speed), 0.856 (F speed), 0.816 (unenhanced Sidexis) and 0.776 (observer enhanced). There were no significant differences between unenhanced digital Sidexis and films. Observer enhanced Sidexis images exhibited a statistically significant lower diagnostic accuracy than the film images for two of the observers.