ABSTRACT
The aim of this article is to describe an application of acoustic emission to characterise a process of laser droplet formation from a metal wire. Laser droplet formation is a crucial process in new laser droplet welding technology, where parts are joined by means of the heat content of a liquid metal droplet deposited onto the parts to be joined. A laser beam is used for heating and melting the wire tip, and for detaching the molten pendant droplet. Depending on the process parameters, three different outcomes of the process can be observed: (1) no droplet formed; (2) a droplet formed but not detached; (3) a droplet formed and detached from the wire. It is shown that AE can be used to monitor the process and to indicate the different process outcomes.
ABSTRACT
Analysis of time series from stochastic processes governed by a Langevin equation is discussed. Several applications for the analysis are proposed based on estimates of drift and diffusion coefficients of the Fokker-Planck equation. The coefficients are estimated directly from a time series. The applications are illustrated by examples employing various synthetic time series and experimental time series from metal cutting.
ABSTRACT
Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.
ABSTRACT
The location of continuous acoustic emission sources is a difficult problem of non-destructive testing. This article describes one-dimensional location of continuous acoustic emission sources by using an intelligent locator. The intelligent locator solves a location problem based on learning from examples. To verify whether continuous acoustic emission caused by leakage air flow can be located accurately by the intelligent locator, an experiment on a thin aluminum band was performed. Results show that it is possible to determine an accurate location by using a combination of a cross-correlation function with an appropriate bandpass filter. By using this combination, discrete and continuous acoustic emission sources can be located by using discrete acoustic emission sources for locator learning.
ABSTRACT
A dental diagnostic system for patient database management, automated measurements, diagnostics and statistical estimation of health conditions is described. To increase the diagnosis quality various diagnostic tools are developed using several statistical methods. The analysis provides information about the importance of particular general, dental, and periodontal data which are further used in quantitative modeling of healing process in the oral cavity. The system supports clinician's diagnostic process and leads to improvement of decisions obtained by a conventional routine. Increased control and evaluation of different therapy types is enabled.
Subject(s)
Database Management Systems , Diagnosis, Computer-Assisted , Tooth Diseases/diagnosis , Computer Communication Networks , Computer Systems , Dental Records , Humans , Software , Tooth Diseases/therapyABSTRACT
In the article the relation between initial mobility of incisors of both jaws and the level of marginal alveolar bone is described. The regression lines representing the dependence of mobility on marginal bone level at various loading forces confirm stepwise the nature of the force transmission from tooth to periodontal support tissues. The dependence of regression line slope on increasing inflammatory periodontal pathology indicates increasing loading of alveolar bone over tension of connective tissue fibers as well as increasing of pressure. This can further accelerate alveolar bone resorption.
