Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.

Monitoring the Tension and the Temperature in an Overhead Line

MELECON 2012 - 2012 16th IEEE Mediterranean Electrotechnical Conference, 25 Mar - 28 Mar 2012, Túnez

Optimization of the pyrolysis process for the production of a biomass derived reducing agent and hydrogen-rich gases

221 p.

Implementation of the nursing process in a health area: models and assessment structures used

Objective: to analyze what nursing models and nursing assessment structures have been used in the implementation of the nursing process at the public and private centers in the health area Gipuzkoa (Basque Country). Method: a retrospective study was undertaken, based on the analysis of the nursing records used at the 158 centers studied. Results: the Henderson model, Carpenito's bifocal structure, Gordon's assessment structure and the Resident Assessment Instrument Nursing Home 2.0 have been used as nursing models and assessment structures to implement the nursing process. At some centers, the selected model or assessment structure has varied over time. Conclusion: Henderson's model has been the most used to implement the nursing process. Furthermore, the trend is observed to complement or replace Henderson's model by nursing assessment structures.