Evaluation-based closed-loop errors using principal component analysis and self-organisation map with an application to a pickling process

Closed-loop control is a basic technology in control engineering. Its role is to avoid the tracking error between set points and real variables. The evaluation of plant performance can be based on multivariate statistical process control connected to closed-loop errors behaviour. Due to its practicality, this approach has found many applications in several industries. This paper suggests a combined use of principal component analysis (PCA) and self-organisation map (SOM) algorithms to evaluate the process on the basis of closed-loop errors dynamic. Generally, it is possible to evaluate a product quality in the basis of the dynamic changes of the closed-loop control errors. In this paper, a new method based on the analysis of the control errors is proposed; it is carried out by a combined use of the PCA-SOM algorithm. Comparatively to the conventional PCA method, this new technique is characterised by the performant indexes that give an accurate evaluation of the process variability and its impact on the product quality. As shown in the different simulation results, the proposed approach gives a global evaluation and improves considerably the performance of computed indexes used for the evaluation of the controlled process.     

Adaptive support vector machine-based surface quality evaluation and temperature monitoring. Application to billet continuous casting process

A method for surface quality evaluation and temperature monitoring of the billet in continuous casting is considered in this paper. This method uses the difference between the measured and the filtered temperature computed using an adaptive support vector machine method. The temperature field, measured by an infrared camera, is affected by an important noise called calamine (a metal oxide generated during the cooling process). The quality of the billet’s surface temperature is connected to the secondary cooling behavior, and therefore an evaluation of the calamine effect is needed. Methods such as soft sensing and adaptive support vector machine are used for a global evaluation of calamine intensity on the monitored area of the billet in continuous casting. This kind of approaches is applied in continuous casting process for constructing a complementary condition monitoring system, which allows an online calamine evaluation. Simulation results, based on the measured surface temperature and the adaptive support vector machine analysis, showed that this new combined approach is easily implementable and gives good results when applied online.     

Phase noise modeling in LC oscillators implemented in SiGe technology

This paper addresses phase noise analysis of a radiofrequency LC oscillator built around a SiGe het- erojunction bipolar transistor(HBT) realized in a 0.35μm BiCMOS process,as an active device.First,we give a brief background to SiGe HBT device physics.The key point is to initiate quantitative analysis on the influence of defects induced during extrinsic base implantation on electric performances of this device.These defects are responsible for the current fluctuations at the origin of low frequency noise in BiCMOS technologies.Next,we investigate the effect of implantation defects as a source of noise in semiconductors on the phase noise of a radiofrequency LC oscillator.We observe their influence on the oscillator phase noise,and we quantify the influence of their energy distribution in the semiconductor gap.Second,we give a behavioral model of an LC oscillator containing a SiGe HBT as an active device.The key goal is to study the susceptibility of a radiofrequency oscillator built around a SiGe HBT to phase noise disturbance sources.Based on the time variance behavior of phase noise in oscillators,transient simulations(in the time domain) were used to analyze the time-dependent noise sensitivity of the oscillator.     

Mixed‐mode analysis of the sensitivity of a radiofrequency oscillator disturbed by parasitic signals

The first step of this work is to study the susceptibility of a radiofrequency oscillator to deterministic disturbance sources. A Colpitts oscillator, working around a 4 GHz frequency, contains a heterojunction bipolar transistor with a silicon–germanium base as an active device. A mixed‐mode analysis is involved, applying a microscopic drift diffusion model to the device, whereas the rest of the circuit used is governed by Kirchhoff's laws. We assume that this tool is very relevant to grasp the influence of intrinsic or extrinsic noisy sources of the oscillator. Our first simulation raw results motivate us to discuss, and perhaps extend, via some analytical models, the so‐called impulse sensitivity function model. In this paper, we try to develop quantitative predictions about the phase noise of such oscillators, and to give some new tracks on this field. Copyright © 2008 John Wiley & Sons, Ltd.     

The role of quinine chlorhydrate in the conditioned inhibition of the tarsal reflex in Drosophila melanogaster

The proboscis extension reflex (PER) can be elicited by applying a sucrose stimulation to the tarsus of a walking fly. This reflex decreases in frequency with repetition, presumably habituation, a nonassociative learning. If each sucrose stimulation is followed by a bitter stimulation, quinine chloride, the PER declines more rapidly, probably the result of conditioning, an associative learning. The present work shows that quinine chloride does not always inhibit PER suppressions but depends on the moment of delivery, being most effective when presented immediately after a sucrose stimulation. A bitter stimulus presented before, or simultaneously with a sucrose stimulation is less effective than habituation to sucrose alone. This experiment provides evidence for an interpretation in terms of cognitive association. The model of learning is not a Pavlovian conditioning as advanced by Medioni and Vaysse (1975), but corresponds to the punishment paradigm of Dyal and Corning (1973).     

Inferential sensor – Based adaptive principal components analysis for mechanical properties prediction and evaluation

This paper is concerned with a method for on-line quality prediction and evaluation of mechanical properties in metal testing. This method uses an Adaptive Principal Component Analysis (APCA) as a multi predictor of different sub-models defining the mechanical properties such as constraints limits and elongation. The PCA technique, characterized by its multivariate component, is strongly recommended to model a multi-input-multi-output system. The complex system is generally known as a non-linear and unsteady state process. The PCA method is a linear projection. To adapt it and to improve the prediction accuracy, a variant of this method is considered based on iteratively using a specific algorithm. This kind of approaches is applied for constructing an inferential model, which allows a reliable and accurate predictor. Simulation results, based on the measured and computed data using the above-cited method, show that the proposed approach is easily implementable and give an accurate prediction.     

The molecular chaperone Hsp90 can negatively regulate the activity of a glucocorticosteroid-dependent promoter

Hsp90, a molecular chaperone required for the functioning of glucocorticosteroid receptor (GR), ensures, by direct interaction, the conformational competence of the steroid-binding pocket. In addition to having this positive function, Hsp90 maintains steroid receptors in an inactive form in the absence of hormone. However, neither the participation of Hsp90 once the pathway has been activated by the ligand nor the importance of increased Hsp90 levels in determining the amplitude of the response has ever been assessed directly. Here, by increasing the Hsp90/GR ratio in the nuclear compartment, we found an attenuation of the response to glucocorticosteroids that was not due to a nonspecific or toxic effect of the Hsp90 modified by nuclear targeting. Since this negative effect was more pronounced at high levels of hormone, when receptor and Hsp90 are maximally dissociated, the possibility of an interaction between Hsp90 and GR, already activated to a DNA-binding form, was directly investigated. Indeed GR, after in vivo activation by ligand, was still able to reassociate with Hsp90, suggesting that this interaction plays a role in vivo, possibly in receptor recycling. Moreover, the GR binding to its DNA response element was inhibited by an excess of Hsp90, pointing to a function of Hsp90 in the nuclear compartment. It is thus proposed that an increased Hsp90/GR ratio influences the responsiveness to ligand at a step that is after receptor activation. This increased ratio may be of pathophysiological relevance in the different circumstances that lead to an elevated level of nuclear Hsp90.     

Le r?le du chlorhydrate de quinine dans l'inhibition conditionnée du réflexe tarsal chez Drosophila melanogaster.

The proboscis extension reflex (PER) can be elicited by applying a sucrose stimulation to the tarsus of a walking fly. This reflex decreases in frequency with repetition, presumably habituation, a nonassociative learning. If each sucrose stimulation is followed by a bitter stimulation, quinine chloride, the PER declines more rapidly, probably the result of conditioning, an associative learning. The present work shows that quinine chloride does not always inhibit PER suppressions but depends on the moment of delivery, being most effective when presented immediately after a sucrose stimulation. A bitter stimulus presented before, or simultaneously with a sucrose stimulation is less effective than habituation to sucrose alone. This experiment provides evidence for an interpretation in terms of cognitive association. The model of learning is not a Pavlovian conditioning as advanced by Médioni and Vaysse (1975), but corresponds to the punishment paradigm of Dyal and Corning (1973). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluation using online support-vector-machines and fuzzy reasoning. Application to condition monitoring of speeds rolling process

A method for process condition monitoring and evaluation, which combines the online support vector machine (SVM) regression and the fuzzy sets methods, is proposed. To account for the time dependence, the proposed approach is based on moving windows in order to take into account the past and new data for the model’s adaptation. The fuzzy analysis is then applied to the generated residual data to give an evaluation of the condition monitoring. The proposed approach is applied to hot rolling for constructing a complementary condition monitoring system, which permits an online quality evaluation in the rolling process. Simulation results based on residual data show that the new approach is easily implementable.