Evaluation of servo, geometric and dynamic error sources on five axis high-speed machine tool

Many sources of errors exist in the manufacturing process of complex shapes. Some approximations occur at each step from the design geometry to the machined part. The aim of the paper is to present a method to evaluate the effect of high speed and high dynamic load on volumetric errors at the tool center point. The interpolator output signals and the machine encoder signals are recorded and compared to evaluate the contouring errors resulting from each axis follow-up error. The machine encoder signals are also compared to the actual tool center point position as recorded with a non-contact measuring instrument called CapBall to evaluate the total geometric errors. The novelty of the work lies in the method that is proposed to decompose the geometric errors in two categories: the quasi-static geometric errors independent from the speed of the trajectory and the dynamic geometric errors, dependent on the programmed feed rate and resulting from the machine structure deflection during the acceleration of its axes. The evolution of the respective contributions for contouring errors, quasi-static geometric errors and dynamic geomet- ric errors is experimentally evaluated and a relation between programmed feed rate and dynamic errors is highlighted.Comment: 13 pages; International Journal of Machine Tools and Manufacture (2011) pp XX-X

Adaptive Monte Carlo applied to uncertainty estimation in a five axis machine tool link errors identification

Knowledge of a machine tool axis to axis location errors allows compensation and correcting actions to be taken to enhance its volumetric accuracy. Several procedures exist, involving either lengthy individual test for each geometric error or faster single tests to identify all errors at once. This study focuses on the closed kinematic Cartesian chain method which uses a single setup test to identify the eight link errors of a five axis machine tool. The identification is based on volumetric error measurements for different poses with a non-contact measuring instrument called CapBall, developed in house. In order to evaluate the uncertainty on each identified error, a multi-output Monte Carlo approach is implemented. Uncertainty sources in the measurement and identification chain - such as sensors output, machine drift and frame transformation uncertainties - can be included in the model and propagated to the identified errors. The estimated uncertainties are finally compared to experimental results to assess the method. It shows that the effect of the drift, a disturbance, must be simulated as a function of time the Monte Carlo approach. The machine drift is found to be an important uncertainty in sources for the machine tested

Toward design optimization of a Pelton turbine runner

International audienceThe objective of the present paper is to propose a strategy to optimize the performance of a Pelton runner based on a parametric model of the bucket geometry, massive particle based numerical simulations and advanced optimization strategies to reduce the dimension of the design problem. The parametric model of the Pelton bucket is based on four bicubic Bézier patches and the number of free parameters is reduced to 21. The numerical simulations are performed using the finite volume particle method, which benefits from a conservative, consistent, arbitrary Lagrangian Eulerian formulation. The resulting design problem is of High-dimension with Expensive Black-box (HEB) performance function. In order to tackle the HEB problem, a preliminary exploration is performed using 2’000 sampled runners geometry provided by a Halton sequence. A cubic multivariate adaptive regression spline surrogate model is built according to the simulated performance of these runners. Moreover, an original clustering approach is proposed to decompose the design problem into four sub-problems of smaller dimensions that can be addressed with more conventional optimization techniques

Automated hill chart modeling procedure to estimate the performance of double regulated units

The work presented in this paper details an original procedure developed in order to automatically build on-cam surfaces for double-regulated hydropower units such as Kaplan or bulb turbines. The proposed method allows a sparse exploration of the operating domain to identify cam points of the machine. The automated approach enhance the reliability of performance hill charts obtained from simulation or model testing. The software implementation of the method is described, together with its application to the case of Priest Rapid hydropower plant

Monitoring a Francis Turbine Operating Conditions

Francis turbines are designed for a specific set of operating conditions that is particular to each hydropower plant site. It allows this type of turbine to extract as much hydraulic power as possible, as long as they are operating in the right conditions. For this reason, power plant operators must know in advance what are the best conditions for operating their generating units and, naturally, in which exact conditions these units are actually operating. Detailed information about the turbine behavior in any operating condition can be obtained by performing measurements in a reduced scale physical model of the turbine prototype. These tests provide what is known as the turbine hill chart: a two-dimensional graphical representation of the most relevant turbine properties showing, for instance, the power output, the discharge, the efficiency and the cavitation conditions. This paper presents a method to monitor the operating conditions of a Francis turbine by locating it on the hill chart. To do so, it requires the generation of polynomial bi-variate functions based on Hermite polynomials that can calculate the turbine discharge and efficiency from its guide vanes angle and power output. A test case is presented with a turbine prototype of 444 MW of rated power operating through a wide range of operating conditions. The validation is done by comparisons between the measured and estimated values of gross head, leading to similar values

Comprehensive power loss modelling to improve the performance of an Energy Recovery Station for water utility networks

The work presented in this paper details the methodology applied to inventory and estimate the power losses in a micro-turbine with counter-rotating runners. The separation between the impact of design parameters and operational parameters on each identified source of power loss provides an efficient framework for optimal design of a family range of standard turbines. The qualitative inventory can be used at early stage of the design for specification purpose while the quantitative aspect can serve for optimizing the system accounting for all the loss sources

Assisted innovative assembly process planning for composite structures

Ces travaux proposent une méthode d’assistance à la sélection des techniques d’assemblage et à l’allocation de tolérances sur les écarts géométriques des composants dans le cadre de l’assemblage de structures aéronautiques composites. Cette méthode consiste à formuler et à résoudre un problème d’optimisation multiobjectif afin de minimiser un indicateur de cout et un indicateur de non-conformité des structures assemblées. L’indicateur de coût proposé prend en compte le coût associé à l’allocation des tolérances géométriques ainsi que le coût associé aux opérations d’assemblage. Les indicateurs de non-conformités proposés sont évalués à partir des probabilités de non-respect des exigences géométriques sur les structures assemblées. Ces probabilités sont évaluées en propageant les tolérances géométriques allouées et les dispersions des techniques sélectionnées au travers d’une fonction appelée Relation de Comportement de l’assemblage (RdCa). Dans le cas de l’assemblage de structures aéronautiques composites, des exigences peuvent porter sur les jeux aux interfaces entre composants. Dans ce cas, la RdCa est évaluée par la résolution d’un problème mécanique quasi-statique non-linéaire par la méthode des éléments finis. Un méta-modèle de la RdCa est construit afin de la rendre compatible avec les méthodes probabilistes utilisées pour évaluer la non-conformité. Finalement, la définition d’un modèle structuro-fonctionnel du produit et d’une bibliothèque de techniques d’assemblage permet de construire un avant-projet de gamme d’assemblage paramétrique. Ce paramétrage permet de formuler le problème d’optimisation multiobjectif résolu à l’aide d’un algorithme génétique.The purpose of this PhD is to develop a method to assist assembly technique selection and component geometrical tolerance allocation in the context of composite aeronautical structure assembly. The proposed method consists in formulating and solving a multiobjective optimisation problem aiming at minimising a cost indicator and a non-conformity indicator. The cost indicator account for both the cost involved by the geometrical tolerance allocation and the cost associated with the assembly operations. The proposed non-conformity indicators are evaluated according to the probabilities of non-satisfied requirements on the assembled structures. These probabilities are computed thanks to Geometrical Variation Propagation Relation (GVPR) that expresses the characteristics of the product as a function of the geometrical deviation of the components and the dispersion occurring during the assembly. In the case of composite aeronautical structures, the product characteristics can be gaps at interfaces between components. In this case, the GVPR is evaluated by solving a non-linear quasi-static mechanical problem by the mean of the finite element method. A metamodel of the GVPR is built in order to reduce the computing time and to make it compatible with the probabilistic methods used to evaluate the non-conformity. Finally, the use of a structure-functional model of the product together with an assembly technique library allows defining a parametric assembly process plan. The multiobjective optimisation problem built thanks to set of parameters defining the assembly process plan is solved using a genetic algorithm

Assistance à l'élaboration de gammes d'assemblage innovantes de structures composites

The purpose of this PhD is to develop a method to assist assembly technique selection and component geometrical tolerance allocation in the context of composite aeronautical structure assembly. The proposed method consists in formulating and solving a multiobjective optimisation problem aiming at minimising a cost indicator and a non-conformity indicator. The cost indicator account for both the cost involved by the geometrical tolerance allocation and the cost associated with the assembly operations. The proposed non-conformity indicators are evaluated according to the probabilities of non-satisfied requirements on the assembled structures. These probabilities are computed thanks to Geometrical Variation Propagation Relation (GVPR) that expresses the characteristics of the product as a function of the geometrical deviation of the components and the dispersion occurring during the assembly. In the case of composite aeronautical structures, the product characteristics can be gaps at interfaces between components. In this case, the GVPR is evaluated by solving a non-linear quasi-static mechanical problem by the mean of the finite element method. A metamodel of the GVPR is built in order to reduce the computing time and to make it compatible with the probabilistic methods used to evaluate the non-conformity. Finally, the use of a structure-functional model of the product together with an assembly technique library allows defining a parametric assembly process plan. The multiobjective optimisation problem built thanks to set of parameters defining the assembly process plan is solved using a genetic algorithm.Ces travaux proposent une méthode d’assistance à la sélection des techniques d’assemblage et à l’allocation de tolérances sur les écarts géométriques des composants dans le cadre de l’assemblage de structures aéronautiques composites. Cette méthode consiste à formuler et à résoudre un problème d’optimisation multiobjectif afin de minimiser un indicateur de cout et un indicateur de non-conformité des structures assemblées. L’indicateur de coût proposé prend en compte le coût associé à l’allocation des tolérances géométriques ainsi que le coût associé aux opérations d’assemblage. Les indicateurs de non-conformités proposés sont évalués à partir des probabilités de non-respect des exigences géométriques sur les structures assemblées. Ces probabilités sont évaluées en propageant les tolérances géométriques allouées et les dispersions des techniques sélectionnées au travers d’une fonction appelée Relation de Comportement de l’assemblage (RdCa). Dans le cas de l’assemblage de structures aéronautiques composites, des exigences peuvent porter sur les jeux aux interfaces entre composants. Dans ce cas, la RdCa est évaluée par la résolution d’un problème mécanique quasi-statique non-linéaire par la méthode des éléments finis. Un méta-modèle de la RdCa est construit afin de la rendre compatible avec les méthodes probabilistes utilisées pour évaluer la non-conformité. Finalement, la définition d’un modèle structuro-fonctionnel du produit et d’une bibliothèque de techniques d’assemblage permet de construire un avant-projet de gamme d’assemblage paramétrique. Ce paramétrage permet de formuler le problème d’optimisation multiobjectif résolu à l’aide d’un algorithme génétique

Model testing beyond the scope of International Standards: an outlook.

The roles of hydropower plants within the energy system has been evolving during the last two decades. The potential to provide ancillary services to the grid is often harnessed, leading to a major change in hydropower plants operations. Ancillary services provision can nowadays be considered as one of the main functions of the power plant during the design of greenfield and refurbishment projects. Reduced scale physical model testing of hydraulic machines are meant to experimentally determine their main hydraulic performances. Model testing also provides a valuable opportunity to accurately gather information and to build models of the machine behavior that are of critical importance to fuel the transition of hydropower into the digital era triggered by some of the major industrial actors of the hydropower market. The quantities of interest within the scope of the guaranteed hydraulic performance are likely to be enriched following the new needs and expectations of the hydropower plants operators. The manufacturers also intend to deliver innovative digital solutions aside with their machines. This contextual breakthrough leads to supplementary requirements for future model testing campaigns that are not necessarily fully addressed within the current International Standards corpus, especially within the IEC 60193 International Standard referring to hydraulic turbines, storage pumps and pump-turbines model acceptance test. The purpose of this paper is to propose an outlook of the model testing beyond the scope of the IEC 60193 International Standard. Activities and techniques aiming at the characterization of the stability of the units, their transient behaviors and the machine condition within various operating modes and regimes are described. The maturity of the described practices is considered according to multiple points of view ranging from instrumentation and procedures to model vs. prototype transposition. The potential impact on the units operation is also discussed. A review of the outcomes from recent research and development projects is proposed together with their transfer into industrial practices. A reflection is also conducted about the foreseeable needs for model testing in the coming years, the gap with the existing state of the art and the envisioned paths to close it