Optimal Frequency Range Selection for PZT Transducers in Impedance-Based SHM Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dressing monitoring with a digital signal processor

Grinding is a finishing process in machining operations, and the topology of the grinding tool is responsible for producing the desired result on the surface of the machined material The tool topology is modeled in the dressing process and precision is therefore extremely important This study presents a solution in the monitoring of the dressing process, using a digital signal processor (DSP) operating in real time to detect the optimal dressing moment To confirm the monitoring efficiency by DSP, the results were compared with those of a data acquisition system (DAQ) and offline processing The method employed here consisted of analyzing the acoustic emission and electrical power signal by applying the DPO and DPKS parameters The analysis of the results allowed us to conclude that the application of the DPO and DPKS parameters can be substituted by processing of the mean acoustic emission signal, thus reducing the computational effort

Monitoring the dressing operation in the grinding process

This work was based on a methodology of development and experimentation, and involved monitoring the dressing operation by processing the acoustic emission and electric power signals to detect the optimal dressing moment. Dressing tests were performed in a surface grinding machine with an aluminium grinding wheel. Dressing analysis software was developed and used to process the signals collected earlier in order to analyse not only the dressing parameters but also the software's ability to indicate the instant when the dressing operation could be concluded. Parameters used in the study of burn in grinding were implemented in order to ascertain if they would also prove efficient in monitoring dressing. A comparative study revealed that some parameters are capable of monitoring the dressing operation. It was possible to verify the parameters effectiveness that today are utilised in burning to monitor dressing as well as to create new parameters for monitoring this operation. Copyright © 2009, Inderscience Publishers.

Optimal single-embryo mass spectrometry fingerprinting

In pre-implantation embryos, lipids play key roles in determining viability, cryopreservation and implantation properties, but often their analysis is analytically challenging because of the few picograms of analytes present in each of them. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) allows obtaining individual phospholipid profiles of these microscopic organisms. This technique is sensitive enough to enable analysis of individual intact embryos and monitoring the changes in membrane lipid composition in the early stages of development serving as screening method for studies of biology and biotechnologies of reproduction. This article introduces an improved, more comprehensive MALDI-MS lipid fingerprinting approach that considerably increases the lipid information obtained from a single embryo. Using bovine embryos as a biological model, we have also tested optimal sample storage and handling conditions before the MALDI-MS analysis. Improved information at the molecular level is provided by the use of a binary matrix that enables phosphatidylcholines, sphingomyelins, phosphatidylserines, phosphatidylinositols and phosphoethanolamines to be detected via MALDI(±)-MS in both the positive and negative ion modes. An optimal MALDI-MS protocol for lipidomic monitoring of a single intact embryo is therefore reported with potential applications in human and animal reproduction, cell development and stem cell research. Copyright © 2013 John Wiley & Sons, Ltd. Copyright © 2013 John Wiley & Sons, Ltd.

Cultivation of PCV2 in swine testicle cells using the shell vial technique and monitoring of viral replication by qPCR and RT-qPCR

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

Economic design of Shewhart control charts for monitoring autocorrelated data with skip sampling strategies

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)