Effects of parameter uncertainties on longitudinal web dynamics

Web handling systems are very common in industry for metal, paper, textile and polymer material treatments. The key variables to monitor and control are the web speed and web tension in each span. The objective is to reach the expected web speed while maintaining web tension in an acceptable range around the tension reference. Nevertheless, the longitudinal web dynamic behavior is sensitive to parameter variations or parameter uncertainties, as for example the web elasticity, the web speed, the roll radius.The implemented control strategy is a classical one: a first loop ensures roller speed control whereas the external loop ensures web tension control. The web tension controllers are automatically synthesized using an optimization approach. The influences of parameter variations are studied firstly on the open-loop system and then on the closed-loop behavior

Control design for longitudinal web dynamics: Benefits and drawbacks of robust control approaches

Web tension and speed are two key variables to be monitored and controlled in order to achieve the expected final product quality. One of the main objectives in web handling plants is to reach an expected web speed while maintaining the web tension within an acceptable range around the tension reference in the entire processing line. In the recent years, many works have focused on the topic of web tension control and have proposed various ways to enhance the performance: H-infinity, optimal state feedback, neural network, etc. But the common practice in industrial web transport systems remains the use of decentralized PI-type controllers.An improved design methodology of these PI controllers with fixed -order and -structure synthesis approaches has been made. Nevertheless, despite high performances for a nominal working point, it has been noticed that the closed-loop system performances depend on the web elasticity since the dynamic behavior is strongly affected by the Young's modulus. Consequently the emphasis of this contribution is on the automatic tuning of PID (or PI) controllers for web processing plants that guaranty good performances of the closed-loop system

Frottement dans les systèmes de déroulement enroulement de surfaces textiles

Les systèmes déroulement / enroulement de bandes doivent faire défiler la bande à vitesse maximale pour lui faire subir un traitement tout en maîtrisant sa tension. Les phases critiques sont le démarrage et l'arrêt du système. Le frottement bande / rouleau est un élément important pendant ces phases où la bande peut glisser sur les rouleaux. Un banc de mesure de frottement ad'hoc a été développé. L'influence de l'angle, de la tension, de la bande et du diamètre du rouleau sur le frottement statique et dynamique est étudiée et comparée à la littérature existante

Gauge optimization of the reference tension and nip-load in winding systems using wound internal stresses calculation

In the winding process, the quality of the roll is directly related to its stress state. The winding tension and nip-load are the most significant parameters which play an important role in the stresses generated within a roll during winding. If the stresses exceed a critical value, defects can appear in the roll and make the web non usable.This work concerns the optimization of the maximal dispersion of the tension and nip load references. It consists to find automatically the maximum and minimum limits for the tension and nip load references, so that all curves ranging between these two limits or thresholds generate radial and tangential stresses located in another gauge fixed in advance, in accordance with the mechanical behavior of the material. The results lead to a practical gauge optimization of the reference tension and nip load for industrial applications

Contribution a l'etude des grands systemes thermiques: modelisation et identification du broyeur de charbon du type a galets

SIGLEINIST T 73435 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Milling diagnosis using machine learning approaches

International audienceThe Industry 4.0 framework needs new intelligent approaches. Thus, the manufacturing industries more and more pay close attention to artificial intelligence (AI). For example, smart monitoring and diagnosis, real time evaluation and optimization of the whole production and raw materials management can be improved by using machine learning and big data tools. An accurate milling process implies a high quality of the obtained material surface (roughness, flatness). With the involvement of AI-based algorithms, milling process is expected to be more accurate during complex operations.In this work, a smart milling diagnosis has been developed for composite sandwich structures based on honey-comb core. The use of such material has grown considerably in recent years, especially in the aeronautic, aerospace, sporting and automotive industries. But the precise milling of such material presents many difficulties. The objective of this work is to develop a data-driven industrial surface quality diagnosis for the milling of honey-comb material, by using supervised machine learning methods. Therefore, cutting forces and workpiece material vibrations are online measured in order to predict the resulting surface flatness.The workpiece material studied in this investigation is Nomex® honeycomb cores with thin cell walls. The Nomex® honeycomb machining presents several defects related to its composite nature (uncut fiber, tearing of the walls), the cutting conditions and to the alveolar geometry of the structure which causes vibration on the different components of the cutting effort.Given the low level of cutting forces, the quality of the obtained machined surface allows to establish criteria for determining the machinability of the honeycomb structures. Nearly 40 features are calculated in time domain and frequency domain from the raw signal in steady state behavior (transient zones are not taken into account). The features are then normalized. The input parameters for each experiment are: the tool rotation speed, the cutting speed and the depth of cut. It is then necessary to make a dimensional reduction of that feature table in order to avoid overfitting and to reduce the computing time of the learning algorithm.In this work, several classification algorithms have been implemented such as : k-nearest neighbor (kNN), Decision trees (DT), Support Vector Machine (SVM). The different supervised learning algorithms have been implemented and compared. Each AI-based model has been applied to a set of features. From the prediction results, SVM algorithm seems to be the most efficient algorithm in this application

Detection of Noncircularity and Eccentricity of a Rolling Winder by Artificial Vision

A common objective in the web transport industry is to increase the velocity as much as possible. Some disturbances drastically limit this velocity. Time-varying eccentricity of the rolling winder is one of the major disturbances which affect the quality of the rolling winder. This unsuitable factor can lead to a web break for a high-speed winding process. The main contribution of this work is to offer a new measurement technique that is able to provide on-line the estimation of the roll radius and its variations with a subpixel accuracy. A key feature within this work is the contour curvature classification by means of wavelets decomposition of the edge orientation function. We also propose a new model accounting for the increasing radius of the rolling winder, which confirms the experimental results and the reliability of the proposed approach

Systèmes d'entraînement de bandes flexibles (optimisation multicritère des performances dynamiques par approche évolutionnaire)

La conception des systèmes d'entrainement de bande est étudiée depuis de nombreuses années. Ces systèmes sont très répandus dans l'industrie puisque le conditionnement sous forme de bobines simplifie le traitement de nombreux matériaux tels que le papier, le carton, les polymères, ... Ces systèmes regroupent un grand nombre de difficultés : ils sont de grande dimension, un fort couplage existe entre les grandeurs et de nombreux paramètres varient au cours du temps. La méthode d optimisation classique consiste à considérer chaque partie du système sans tenir compte des autres. De plus, au sein d'un même sous-ensemble, l optimisation est réalisée discipline par discipline. Une nouvelle approche est proposée et appliquée à la synthèse de la commande : il s agit de considérer le système global en prenant en compte la robustesse paramétrique. Ensuite, le choix optimal du tracteur maître et de la technologie d'asservissement de la tension de bane associée sont étudiées.The design of roll-to-roll systems is studied for several years. This kind of system is very common in industry because the wound roll packaging simplify the treatment of material such as paper, cardboard, polymers, metal ... The studied systems have a high number of difficulties: they are large scale systems, a high coupling between physical values exists and several parameters are time dependent. The classical optimisation method consists in considering separately each subsystem without taking into account interactions. Moreover, the classical optimisation is made for each scientific field. A new approach is developed and applied to controller synthesis: the controllers are synthesized considering the global system with parametric uncertainties. The optimal choice of the master roller position and the technology used to control web tension are then studied.STRASBOURG-Bib.electronique 063 (674829902) / SudocSudocFranceF