In process laser beam diagnostics (403)

Laser beam diagnosis is usually carried out off-line in order to minimise the disruption to the process being carried out. This paper presents the results of a fractional sampling device for a high power beam diagnosis system capable of measuring in process beam properties such as beam diameter, intensity and beam position. The paper discusses the application of this sampling technique for monitoring beam properties during the laser materials processing operation.

In process laser beam diagnostics (403)

Laser beam diagnosis is usually carried out off-line in order to minimise the disruption to the process being carried out. This paper presents the results of a fractional sampling device for a high power beam diagnosis system capable of measuring in process beam properties such as beam diameter, intensity and beam position. The paper discusses the application of this sampling technique for monitoring beam properties during the laser materials processing operation.

processline: visualizing time-series data in process industry

In modern process industry, it is often difficult to analyze a manufacture process due to its umerous time-series data. Analysts wish to not only interpret the evolution of data over time in a working procedure, but also examine the changes in the whole production process through time. To meet such analytic requirements, we have developed ProcessLine, an interactive visualization tool for a large amount of time-series data in process industry. The data are displayed in a fisheye timeline. ProcessLine provides good overviews for the whole production process and details for the focused working procedure. A preliminary user study using beer industry production data has shown that the tool is effective.

The thermal fatigue resistance of vermicular cast iron coupling with H13 steel units by cast-in process

This paper focuses on improving the thermal fatigue resistance on the surface of vermicular cast iron coupling with inserted H13 steel blocks that had different cross sections, by cast-in processing. The microstructure of bionic units was examined by scanning electron microscope. Micro-hardness and thermal fatigue resistance of bionic samples with varied cross sections and spacings were investigated, respectively. Results show that a marked metallurgical bonding zone was produced at interface between the inserted H13 steel block and the parent material - a unique feature of the bionic structure in the vermicular cast iron samples. The micro-hardness of the bionic samples has been significantly improved. Thermal resistance of the samples with the circular cross section was the highest and the bionics sample with spacing of 2 mm spacing had a much longer thermal fatigue life, thus resulting in the improvement for the thermal fatigue life of the bionic samples, due to the efficient preclusion for the generation and propagation of crack at the interface of H13 block and the matrix. Crown Copyright (c) 2010 Published by Elsevier Ltd. All rights reserved.

Analysis for temperature and pressure fields in process of hydrate dissociation by depressurization

An improved axisymmetric mathematic modeling is proposed for the process of hydrate dissociation by depressurization around vertical well. To reckon in the effect of latent heat of gas hydrate at the decomposition front, the energy balance equation is employed. The semi-analytic solutions for temperature and pressure fields are obtained by using Boltzmann-transformation. The location of decomposition front is determined by solving initial value problem for system of ordinary differential equations. The distributions of pressure and temperature along horizontal radiate in the reservoir are calculated. The numeric results indicate that the moving speed of decomposition front is sensitively dependent on the well pressure and the sediment permeability. Copyright (C) 2010 John Wiley & Sons, Ltd.

Negative correlations between control performance and verbalizable knowledge: indicators for implicit learning in process control tasks?

Negative correlations between task performance in dynamic control tasks and verbalizable knowledge, as assessed by a post-task questionnaire, have been interpreted as dissociations that indicate two antagonistic modes of learning, one being “explicit”, the other “implicit”. This paper views the control tasks as finite-state automata and offers an alternative interpretation of these negative correlations. It is argued that “good controllers” observe fewer different state transitions and, consequently, can answer fewer post-task questions about system transitions than can “bad controllers”. Two experiments demonstrate the validity of the argument by showing the predicted negative relationship between control performance and the number of explored state transitions, and the predicted positive relationship between the number of explored state transitions and questionnaire scores. However, the experiments also elucidate important boundary conditions for the critical effects. We discuss the implications of these findings, and of other problems arising from the process control paradigm, for conclusions about implicit versus explicit learning processes.

Novel developments in process optimisation using predictive control

In industrial practice, constrained steady state optimisation and predictive control are separate, albeit closely related functions within the control hierarchy. This paper presents a method which integrates predictive control with on-line optimisation with economic objectives. A receding horizon optimal control problem is formulated using linear state space models. This optimal control problem is very similar to the one presented in many predictive control formulations, but the main difference is that it includes in its formulation a general steady state objective depending on the magnitudes of manipulated and measured output variables. This steady state objective may include the standard quadratic regulatory objective, together with economic objectives which are often linear. Assuming that the system settles to a steady state operating point under receding horizon control, conditions are given for the satisfaction of the necessary optimality conditions of the steady-state optimisation problem. The method is based on adaptive linear state space models, which are obtained by using on-line identification techniques. The use of model adaptation is justified from a theoretical standpoint and its beneficial effects are shown in simulations. The method is tested with simulations of an industrial distillation column and a system of chemical reactors.

In-process grinding monitoring by acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. Many statistics have shown effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS.