MANUFACTURING A 3D WOVEN PIECE WITH LOCAL REGULARIZATION OF THE TEXTILE STRUCTURE

Abstract

MANUFACTURING A 3D WOVEN PART WITH LOCAL REGULARIZATION OF THE TEXTILE STRUCTURE One aspect of the invention relates to a method for controlling the manufacture, by a manufacturing machine, of a 3D woven part in a composite material. Figure to be published with the abbreviation: Figure 3

Description

Title of the invention: MANUFACTURE OF A 3D WOVEN PIECE WITH LOCAL REGULARIZATION OF THE STRUCTURE TEXTILE TECHNICAL FIELD OF THE INVENTION

[0001] The technical field of the invention is that of parts manufactured from woven composite material, in particular aeronautical parts such as aircraft engine blades.

[0002] In particular, the invention relates to the manufacture of a preform of a woven composite part by defining manufacturing parameters as a function of the desired properties of said part. TECHNOLOGICAL BACKGROUND OF THE INVENTION

[0003] A woven composite material is an assembly comprising at least one woven textile framework called reinforcement and a binder called matrix. The reinforcement comprises strands, also called "threads", woven using a loom according to a theoretical weaving topology per layer, defined according to at least two orientations also called reinforcement axes. Each layer comprises different types of threads woven according to the two reinforcement axes and forms the elementary structure of the reinforcement. The reinforcement axes are conventionally called "warp" and "weft". In general, the warp corresponds to the main weaving direction, and the weft corresponds to the transverse direction, orthogonal to the warp. The way in which the strands are interwoven, i.e. the pattern according to which said strands are woven, is conventionally called "weave" and is defined on one or more layers.

[0004] The design of a 3D woven composite part requires precise control of its properties, which result from the structure of the weave as well as the type of material, the type of reinforcement and the manufacturing process. The development of such a part is therefore complex and begins with the design and manufacturing of a preform. The design of the preform, i.e. the 3D woven reinforcement, is then a tedious process involving numerous back-and-forths in order to find the best compromise between the mechanical characteristics (warp-weft ratio, volume fraction of fibers, etc.) imposed and the manufacturing constraints (weaves, count of available threads, position in the harness, etc.) of the department responsible for manufacturing.

[0005] Convergence towards the optimal compromise is conventionally carried out by an operator specialized in the weaving of composites and responsible for guaranteeing the regularity of the designed preform. In particular, the operator seeks to minimize the number of warp or weft threads which are woven (i.e. woven at the level of the columns of the preform) and floated (i.e. not woven at the level of the columns of the preform) on a small number of insertions, generally less than ten insertions. For example, a floated yarn on less than ten columns and a woven yarn on less than 10 columns are considered defects. In this case, the search for the compromise is made with the support of a digital weaving model and by visualization of the programmed preform.

[0006] Defining a textile part is time-consuming, with a processing time of around several months, depending on the complexity of the part. This long duration therefore has a major impact on the iterations between the specifier and the manufacturing department and, consequently, on the development times of the parts.

[0007] Several digital textile programming weaving models are known from the prior art, such as: • General tools, for example NedGraphics™, do not allow for taking into account the specified parameters or constraints related to the weaving of a 3D preform. In addition, these weaving models are not suitable for defining large parts and / or parts of high complexity; • Tools dedicated to programming 3D woven preforms, for example 3D Composite Structures™, which take into account the specifications and properties of 3D textile preforms such as the number of layers, the spacing of wefts between two columns of weft yarns, the weave characteristics, etc. These weaving models include a textile layer optimization algorithm but do not take into account manufacturing constraints or weave optimization. • Tools dedicated to the programming of 3D woven preforms and allowing to optimize locally, i.e. cell by cell, the definition of the textile preform, by means of heuristic techniques, in order to respect the constraints imposed by the specifier, for example by adding or removing layers and / or choice of weaves. However, these weaving models do not allow to regularize the numerical definition of the preform during optimization, thus producing discontinuities between cells and increasing the number of anomalies.

[0008] Thus, even if there are digital tools to automatically determine the compromise, these tools are not able to regularize the solution found.

[0009] There is therefore a need for an automatic means of determining a definition of a preform of a 3D woven composite part without over-regularization. Summary of the invention

[0010] The invention provides a solution to the problems mentioned above, by allowing a fine regularization of the preform, by the use of a plurality of regularization terms.

[0011] A first aspect of the invention relates to a computer-implemented method for controlling the manufacture, by a manufacturing machine, of a 3D woven part in a composite material, comprising: • Obtain a target value of a volume fraction of a textile preform of the 3D woven part and a sequence of modifications, each modification of the modification sequence being associated with a range of values; • Obtaining a plurality of regularization terms, each of the plurality of regularization terms corresponding to one of the modifications in the sequence of modifications; • Modify the textile preform by applying the sequence of modifications to conform the textile preform to the target value of the volume fraction, each modification being carried out in the associated range of values ​​taking into account a modeled value of the volume fraction and the regularization term corresponding to said modification; • Control the machine to manufacture the 3D woven part from the modified textile preform.

[0012] The term "preform" means a three-dimensional woven reinforcement blank of the part to be manufactured. The preform is characterized by one or more properties, which may be geometric and / or mechanical properties, such as a thickness, a volume fraction, a surface density, etc. The terminology "target value" of the property of the preform therefore designates the value of one of the properties of the preform which is predetermined, for example by the specifier. This target value meets a specific need and application for which the composite part is intended. The target value can therefore be defined according to the specifications of the part.

[0013] The term "regularization term" means a weighting coefficient that imposes regularity on the digital definition of the preform when adjusting the parameter of the preform. In other words, the regularization term is used to control the incidence of anomalies in the digital definition of the preform arising from the compromise between the target value of the volume fraction of the digital definition of the preform and the manufacturing constraints.

[0014] By "modification" of the preform parameter is meant an adjustment of the value of the parameter to be set in order to achieve the optimal compromise. For example, the modification of the preform parameter is a modification of the number of wires.

[0015] The term “maximum value” means the maximum value of the volume fraction of the textile preform reached by a modification of the parameter, said modification corresponding to one of the values ​​among a range of values ​​associated with said modification. fication.

[0016] The claimed invention therefore makes it possible to determine a textile preform, via the adjustment of a digital definition of the preform, allowing the manufacture of the preform when the digital definition is supplied to a preform manufacturing machine, the characteristics of which correspond to the properties supplied by the specifier, and which is regular, thus minimizing the number of anomalies in the digital definition of the preform. It is therefore a regulated digital definition. The balance between compliance with the theoretical criteria, taking into account the manufacturing constraints, and minimizing the number of anomalies is obtained by taking into account the regularization term when adjusting the parameter of the preform.

[0017] Thanks to the invention, the regularization of the definition of the preform is carried out without over-regularization. The proposed approach therefore has better robustness than the approaches of the art.

[0018] The adjustment of the digital definition of the preform is, moreover, entirely automated and does not require the intervention of the operator to be carried out, nor to correct the regularity of said digital definition.

[0019] The claimed invention also makes it possible to obtain this adjusted digital definition of the preform, by adjusting the parameter of the preform, in a short time which makes it possible to accelerate the development of new parts. This is particularly advantageous in the case of preforms of high complexity and / or large size.

[0020] Advantageously, the approach proposed in this first aspect can be applied to the entirety or a portion of the part to be manufactured; the preform will then only concern the part concerned.

[0021] Advantageously, the adjustment of the parameter of the preform is entirely controlled by the plurality of regularization terms.

[0022] Advantageously, the proposed approach can be applied to any woven composite part, regardless of its particularities which are taken into account by the numerical model of the preform used to determine the modeled value of the volume fraction. In particular, the invention is not restricted to parts and / or portions of parts where the material thickness is small (i.e., less than 20 mm), but can be applied to parts and / or portions of parts where the material thickness is greater, in particular at least up to 60 mm. Typically, in the case of a blade, the proposed invention can be applied to the entire structure of the blade and not only to the portions where the thickness is small (i.e., less than 20 mm).

[0023] In addition to the characteristics which have just been mentioned, the method according to the first aspect of the invention may have one or more complementary characteristics among the following, considered individually or in all combinations: technically possible.

[0024] In one embodiment, the method according to the first aspect is a computer-implemented method of manufacturing a 3D woven part in a composite material comprising a textile preform of the part, comprising: • Obtain a target value of a volume fraction of the textile preform; • Obtain a plurality of regularization terms; • Adjusting at least one parameter of the textile preform to conform a definition of the textile preform to the target value of the volume fraction, the adjustment comprising at least one sequence of modifications, each modification of the sequence of modifications being a modification of one of the at least one parameter of the definition of the textile preform, each modification of the sequence of modifications being associated with a range of values, and each of the regularization terms of the plurality of regularization terms corresponding to one of the modifications of the sequence of modifications, each regularization term being a weighting coefficient imposing a regularity on the definition of the preform, and each modification being implemented from: • A cancellation of a difference between a modeled value of the volume fraction of the textile preform, obtained using a numerical model and taking into account the regularization term corresponding to said modification, and: • The target value of the volume fraction; or • A maximum value of the volume fraction corresponding to a maximum value of the volume fraction, obtained by modifying the parameter of the textile preform in the range of values ​​associated with said modification; • The regularization term corresponding to said modification; • Issue a command including the definition of the textile preform for the manufacture of the textile preform by a manufacturing machine, the definition of the textile preform including the set parameter.

[0025] The term “numerical definition” or more simply “definition” of the preform means the set of properties of the preform, each of which has a value associated with it. The numerical definition therefore describes a specific draft of the woven reinforcement. In other words, it is a categorical variable, for example defined by an elementary weaving pattern such as a plain weave, a twill weave, etc. The numerical definition is in a digital format allowing it to be read by a computer and transmitted, for example via a hardware medium such as a hard disk. externally or via a wired or wireless connection device. The digital format is, for example, a table including the properties associated with their respective value and / or a plan of the preform. The plan includes one or more one-dimensional, two-dimensional and / or three-dimensional schematic representations of the preform.

[0026] The term "preform parameter" means a physical characteristic of said preform, the adjustment of which makes it possible to conform the definition of the preform with the target value of the volume fraction of the preform. For example, the preform parameter is a number of wires, a number of layers, a number of cells per layer, etc.

[0027] The term “digital model of the preform” means a model that allows the calculation of a volume fraction of the preform, of the same magnitude as the target value of the volume fraction of the preform, in order to compare the target value of the volume fraction of the preform and the modeled volume fraction value with each other. This model calculates the volume fraction from the manufacturing constraints of the preform, for example those of the manufacturing machine and / or linked to its environment, and from the parameter of the preform. The digital model of the preform can also take into account other predetermined parameters and / or properties, in particular those imposed by the specifications, such as a preform armor, a preform thickness, a surface density of the preform, etc.The digital model of the preform is, for example, a digital model dedicated to the programming of 3D woven preforms and allowing local optimization, i.e. cell by cell, of the definition of the textile preform, subsequently called “digital model with local optimizer”, or a meta-model of this model.

[0028] In one embodiment, modifying the preform comprises adjusting at least one parameter of the textile preform to conform a definition of the textile preform to the target value of the volume fraction, the adjustment comprising: • Initializing the at least one parameter of the definition of the textile preform; and • For each of the modifications in the sequence of modifications: • Determine, by means of a first iterative search algorithm, a set value of the at least one parameter of the definition of the textile preform corresponding to said modification, said set value being determined by canceling a difference between the modeled value of the volume fraction, obtained using a numerical model and taking into account the regularization term corresponding to said modification, and: • The target value of the volume fraction; or • A maximum value of the volume fraction cor corresponding to a maximum value of the volume fraction, obtained by modifying the parameter of the textile preform in the range of values ​​associated with said modification; the first iterative search algorithm searching for a value, among the range of values ​​associated with said modification, which allows said cancellation.

[0029] In one embodiment, the first iterative search algorithm is configured to solve, for each modification of the sequence of modifications, max(VFtarget f (IT, A”iax))-f(IT, A,-) + fiAAj = 0, with VFcihle the target value of the volume fraction; / the digital model of the textile preform; IT a target value of a thickness of the textile preform; Ai = ..., ci} the sequence of modifications from the first modification to said modification, noted i-th modification ai, the modifications to being associated with the values ​​which allow said cancellation, determined by the first iterative search algorithm, for the modifications preceding said modification aî; the sequence of modifications from the first modification to said modification a>, where is the modification ai, in the associated range of values, which corresponds to the maximum value of the volume fraction; / 1 the regularization term corresponding to said modification ai; and Ad,- a Laplacian of the sequence of modifications A, from the first modification to said modification ai.

[0030] These embodiments make it possible to regularize the definition of the technical preform sequentially, by applying several modifications ordered successively. Each modification will therefore be dependent on the modifications previously made in the sequence. The order of the modifications in the sequence must therefore be suitably predefined according to the application in question and the desired properties of the preform. In other words, the sequence of modifications makes it possible to take into account the textile strategy for the manufacture of the preform when determining its definition.

[0031] Furthermore, the alternative to the target value, proposed by the maximum value, makes it possible to obtain a satisfactory preform, without over-regularization of its definition, while having a value of the volume fraction of the textile preform close to the target value. It is noted that, in these embodiments, the maximum value is less than or equal to the target value.

[0032] The regularization of the definition of the preform is thus improved and more robust, compared to known approaches.

[0033] Thanks to these characteristics, the parameter of the preform is easy to adjust since it It is sufficient, for each modification, to solve the defined equation to determine it. This equation being, moreover, a simple cancellation, it can be easily solved using any algorithm for finding the poles of a function. These algorithms allow, in particular, to solve this type of equation very quickly and with great precision. Preferably, the Krylov-Newton algorithm is used to solve this equation.

[0034] Furthermore, the proposed adjustment makes it possible to refine the automatic regularization of the digital definition of the preform, by applying the regularization terms corresponding to each of the modifications, improving the granularity of the regularization at each modification, which makes it possible to minimize the number of anomalies of the preform, including when the latter is divided into cells.

[0035] Furthermore, the plurality of regularization terms makes it possible to select the optimal solution on the Pareto front of the adjustment problem to be solved, i.e. to weight the error on the volume fraction of the textile preform by the regularity of the solution.

[0036] The regularity of the solution is ensured if the second-order derivatives of the modification field of the parameter to be adjusted are canceled. The Laplacian of the modification of the parameter to be adjusted serves this purpose and makes it possible to detect anomalies of the preform, in particular discontinuities and regions of strong degression of the active layers. By "region of strong degression" we mean regions of the part where the thickness decreases rapidly from one cell to another by shrinkage of several layers in these cells. A layer is active when a wire is woven into it; otherwise, the layer is inactive.

[0037] The independence of the equation of each modification, with respect to the following modifications in the sequence of equations, means that the computational cost for determining the definition of the preform is not of the order of ( nxj ) 2 but rather of the order of Q x D2, where Q is the number of modifications in the sequence of modifications and d is the dimension of the textile preform, (typically D — N x M, where N is the number of cells along the weft reinforcement axis and M is the number of cells along the warp reinforcement axis).

[0038] In one embodiment, the method according to the first aspect comprises: • Comparing a final value of the volume fraction or other property of the textile preform to a tolerance, the final value of the volume fraction or other property of the textile preform being obtained by using the digital model of the textile preform with the set value of the parameter of the textile preform, and: • When the final value of the volume fraction or other property of the textile preform meets the tolerance, issue the order including the definition of the textile preform; • Otherwise, modify the plurality of regularization terms, by means of a second iterative search algorithm, and implement again the adjustment of the parameter of the textile preform with the modified plurality of regularization terms.

[0039] It is thus possible to verify that the definition of the textile preform complies with one or more requirements of the specifications. If this is not the case, it is possible to repeat the adjustment of the at least one parameter of the preform by implementing the method according to the first aspect again, taking into account the modified regularization terms in place of the regularization terms used previously.

[0040] In one embodiment, the at least one parameter of the textile preform is initialized to a maximum value.

[0041] In one embodiment, the definition of the textile preform comprises a plurality of superimposed layers, each of the layers of the plurality of layers comprising a plurality of cells and each cell of the plurality of cells corresponding to one or more threads of said composite material woven along the weft and / or warp reinforcement axes of the textile preform, and the at least one parameter of the textile preform is: • a number of layers, and the modification of the parameter of the textile preform is an increase or a decrease in the number of layers of the preform; • a number of cells, and the modification of the parameter of the textile preform is an increase or a decrease in the number of cells of one or more layers of the preform; • a weft spacing and / or a warp spacing, and the modification of the parameter of the textile preform is an increase or a decrease in the weft spacing and / or an increase or a decrease in the warp spacing between two or more cells of one or more layers; • a number of warp threads and / or a number of weft threads, and the modification of the parameter of the textile preform is an increase or a decrease in the number of warp threads and / or an increase or a decrease in the number of weft threads, of one or more cells of one or more layers of the preform; • is a warp yarn count and / or a weft yarn count, and the modification of the parameter of the textile preform is an increase or a decrease in the warp yarn count and / or an increase or a decrease in the weft yarn count, of one or more cells of one or more layers of the preform.

[0042] The term “weft (or warp) spacing” means the distance between two successive weft (or warp) threads, along the weft (or warp) reinforcement axis.

[0043] The term “count” of yarn means the type of yarn, characterized by its linear mass, which depends in particular on the number of fibers that compose it. For example, the available yarn counts may be 12k, 24k, 36k, 48k, 72k, etc., where a count “Xk” corresponds to a yarn comprising Xk X1000 fibers per yarn. The list of available yarn counts may differ between the warp and the weft.

[0044] In one embodiment, the digital model of the textile preform is a meta-model modeling a digital weaving model, the meta-model taking as input the modification of the parameter of the textile preform or the sequence of modifications, and producing as output the modeled value of the volume fraction.

[0045] Thanks to the use of this meta-model, the adjustment of the preform parameter is almost instantaneous or very fast since the meta-model is an analytical function which replaces the numerical model of the preform. In addition, the use of the meta-model makes it possible to make the adjustment problem continuous. That is to say that if the modification of the preform parameter has discrete values, for example the number of threads to be removed, then the meta-model makes it possible to make these values ​​continuous, for example to achieve additions / removals of a positive real and not an integer of threads, thus simplifying and accelerating the adjustment. Furthermore, when the regularization term is zero, the optimal solution coincides with the solution obtained by the optimization algorithm of the weaving model, but with much shorter calculation times.

[0046] The meta-model can advantageously be configured to estimate the modeled value by taking into account the entire sequence of modifications, in particular, at each modification, said modification as well as the previous modifications in the order of the sequence of modifications.

[0047] A second aspect of the invention relates to a device comprising a computer configured to implement the method according to the first aspect.

[0048] A third aspect of the invention relates to a computer program product comprising instructions which, when the program is executed on a computer, cause the latter to implement the steps of the method according to the first aspect.

[0049] A fourth aspect of the invention relates to a computer-readable recording medium comprising instructions which, when executed by a computer, cause the computer to carry out the steps of the method according to the first aspect.

[0050] The invention and its various applications will be better understood upon reading the following description and examining the accompanying figures. BRIEF DESCRIPTION OF THE FIGURES

[0051] The figures are presented for information purposes only and in no way limit the invention. • [Fig.l] is a block diagram representing a method according to the invention, according to one embodiment. • [Fig.2] represents an adjustment of a regularization term of the process, according to one embodiment. • [Fig.3] is a diagram illustrating the implementation of the method of [Fig.l], according to an example of implementation. DETAILED DESCRIPTION

[0052] Unless otherwise specified, the same element appearing in different figures has a single reference.

[0053] The invention relates to a method for manufacturing a 3D woven part in a composite material comprising a textile preform of the part, for a specific application and having to meet a certain number of requirements of a specification specifying in particular the properties that the manufactured part must have to be suitable for its use. Tolerances can be defined in the specification, the characteristics of the part thus being able to support a margin of approximation with respect to the imposed requirements. The characteristics of the textile preform must therefore also meet these requirements. In the following, the term "preform" means "textile preform".

[0054] Unlike the known approaches of the prior art, the method described herein makes it possible to find a regulated digital definition of the preform by taking into account the regularity of said digital definition. The search for the regulated digital definition thus takes into account the requirements of the specifications, the manufacturing constraints and the regularity of the digital definition. The method according to the invention thus makes it possible to minimize the number of anomalies in the preform, such as discontinuities, non-monotony or a strong degressivity of the active layers. The regularity is taken into account by introducing a plurality of regularization terms into the adjustment problem to be solved.

[0055] As described below, several variants can be implemented, independently or jointly, in order to improve the regularity of the definition of the preform which is determined.

[0056] The definition of the preform can be in the format of a digital document, for example a plan, a table, a text, etc.

[0057] As illustrated in [Fig.l], the method 100 for manufacturing a 3D woven part in a composite material comprising a textile preform of the part, in other words the method for controlling a manufacturing by a machine for manufacturing a part woven 3D in a composite material, comprises five steps numbered from 110 to 150. The method 100 is implemented by a computer (not shown). The computer comprises a processor and a memory. The computer includes in its memory instructions which, when executed by the processor, allow the implementation of the steps of the method 100.

[0058] The definition of the preform comprises a plurality of superimposed layers, corresponding to the layers according to which the preform is manufactured. Each layer comprises a plurality of cells and each cell corresponds to one or more threads of said woven composite material, according to the weft and / or warp reinforcement axes of the preform. That is to say that the definition of the preform is subdivided into several portions, called "cells", which may be of the same size or of different sizes relative to each other. Each cell corresponds to an element of the weaving pattern. Typically, a cell corresponds to a volume comprising the intersection of a weft thread and a warp thread. There may therefore be as many cells as there are intersections of these threads for each layer.

[0059] A cell has dimensions between 0.1 mm and 20 mm in width and 0.1 mm and 20 mm in height. For example, each cell has a width of 2 mm and a height of 10 mm.

[0060] The first step 110 is a step of obtaining a target value of the property of the preform. In this case, the property of the preform is a volume fraction of the preform. The target value of the volume fraction is obtained by the computer. The target value of the volume fraction is, for example, provided in the specifications.

[0061] For this purpose, the computer comprises a device for obtaining the target value of the volume fraction. This device is, for example, a port for connecting an external device to the computer, a device for connecting to a communication network through which the data can pass or a human-machine interface allowing the interaction of an operator such as a graphical interface.

[0062] The target value of the volume fraction may be the same over the entire preform or may vary over all or part of the definition of the preform. For example, the target value may be the same for one or more layers and / or different for one or more layers. Similarly, the target value may be the same for one or more cells of a layer and / or different for one or more cells of a layer.

[0063] The adjusted digital definition of the preform is therefore sought so as to respect the target value of the volume fraction.

[0064] The second step 120 is then a step of obtaining the plurality of regularization terms. Each regularization term is, for example, a scalar or a set of scalars. The number of regularization terms depends on the application considered. Typically, this number can depend on one or more of the following conditions: • the number of layers, for example to have one regularization term per layer or one regularization term for several layers; • the number of cells per layer, for example to have several regularization terms per layer, typically one term for several cells of the layer or one term per cell; • the total number of cells in the preform definition, typically to have a regularization term for one or more cells of different layers; • a number of modifications applied to the preform, typically to have one or more regularization terms per modification; • the independence of the weft and warp axes, typically so that the regularization terms are different and independent along these two axes.

[0065] The regularization terms are produced by a dedicated algorithm or are provided by an operator. This involves initializing the regularization terms so that the computer can implement the adjustment. Each regularization term is, for example, initialized to a positive or zero value.

[0066] The regularization terms may be modified subsequently, for example by incrementation, to progressively reduce the number of irregularities linked to the definition of the preform produced by the process.

[0067] The third step 130 is then a step of adjusting at least one parameter of the preform to conform the preform, in particular its numerical definition, to the target value of the volume fraction. This step 130 is therefore a step of modifying the textile preform by applying the sequence of modifications to conform the textile preform to the target value of the volume fraction.

[0068] The adjustment takes into account the target value of the volume fraction, the manufacturing constraints and the regularization term to determine the adjusted numerical definition. The adjusted numerical definition is determined by adjusting the at least one parameter of the preform. For this purpose, the adjustment comprises a sequence of modifications, each of which serves to modify one of the at least one parameters of the preform, i.e. to modify its value. Each modification therefore corresponds to at least one of the parameters of the definition of the preform. In other words, each modification of the modification sequence is a modification of one of the at least one parameter of the definition of the textile preform.

[0069] The modifications are made in an order defined by the sequence. Each modification is therefore dependent on the modifications already made in the sequence. The sequence is defined by the operator or specifier. The sequence of modifications includes at least two modifications.

[0070] Each modification of the sequence of modifications corresponds to one or more of the plurality of regularization terms.

[0071] Each modification of the sequence of modifications is associated with a range of values. Each modification of the parameter of the preform is therefore carried out in a range of values ​​associated with this modification. That is to say that the possible modifications of the parameter of the preform are restricted to a range of actions, for example defined according to the manufacturing constraints and / or the requirements of the specifications. The value range can be defined by the operator or the specifier and / or automatically from the manufacturing constraints and / or the specifications.

[0072] "Manufacturing constraints" means constraints imposed by the conditions under which the manufacturing of the part takes place. These are typically constraints of the machine used to manufacture the part or of the environment in which said machine is located. Manufacturing constraints are, for example, a space limit, a load limit, a machine force limit, a woven / floated length restriction, a maximum layer limit linked to the depth of the harness, a maximum / minimum weft spacing, a homogeneous and gradual layer output, etc.

[0073] The sequence of modifications is, for example, obtained during the first step 110, in addition to the target value of the volume fraction.

[0074] Each modification is carried out, in the associated range of values, taking into account a modeled value of the volume fraction and the regularization term corresponding to said modification.

[0075] In particular, the adjustment problem is based, for each modification of the modification sequence, on a comparison between a modeled value of the volume fraction obtained using a digital model of the preform and • the target value of the volume fraction; or • a maximum value of the textile volume fraction.

[0076] The maximum value of the textile volume fraction corresponds to the maximum value of this property, which can be obtained by the relevant modification of the parameter of the preform in the range of values ​​associated with the modification.

[0077] The adjustment problem also takes into account the plurality of regularization terms applied to the successive modifications of the parameters of the preform which are to be adjusted. In particular, for each modification of the modification sequence, the adjustment is carried out taking into account the regularization term(s) corresponding to said modification, among the plurality of regularization terms.

[0078] The parameter of the preform may be at least one of: a number of layers, a number of cells, a weft spacing, a warp spacing, a number of weft threads, a number of warp threads, a count of weft threads, a count of warp threads.

[0079] Respectively, the modification of the parameter of the preform may be at least one of an increase or a decrease: • The number of layers of the preform, for example the addition or removal of one or more layers, or even the division of a layer into several layers; • The number of cells in one or more layers, for example the addition or removal of one or more cells in one or more layers; • The frame spacing between two or more cells of one or more layers; • Chain spacing between two or more cells of one or more layers; • The number of weft threads, of one or more cells of one or more layers, for example the addition or removal of one or more ream threads from one or more cells of one or more layers; • The number of warp threads, of one or more cells of one or more layers, for example the addition or removal of one or more warp threads from one or more cells of one or more layers; • The title of weft threads, of one or more cells of one or more layers; • From the warp thread count, of one or more cells of one or more layers.

[0080] The possible modifications are dependent on the armor of the preform.

[0081] For each modification, the digital model of the preform makes it possible to calculate the modeled value, as well as the maximum value, if applicable, of the volume fraction from the manufacturing constraints, the parameter of the preform and, possibly, other properties of the preform imposed by the specifications. For example, the digital model of the preform determines a value of the volume fraction from the modification of the parameter, for example the modification of the number of weft and / or warp threads, taking into account the manufacturing constraints and possibly properties other than the volume fraction of the preform, for example the thickness of the preform, the weave of the preform, etc.

[0082] The digital model of the preform may be the digital model with local optimizer. Preferably, the digital model of the preform is a meta-model, also called a substitution model, constructed from the digital model with local optimizer. The meta-model replaces the digital model with local optimizer. to estimate the modeled value of the volume fraction from the modifications of the sequence of modifications already made. The meta-model is therefore constructed in such a way as to estimate the modeled value from any admissible combination of modifications. The meta-model therefore models the solver included in the numerical model with local optimizer. The interest is to significantly reduce the calculation times since once the meta-model is constructed, it behaves like an analytical function and the estimation by its means is almost instantaneous.

[0083] Another advantage is that the meta-model allows, through its extrapolation capacity, to make the adjustment problem continuous. Indeed, the numerical model can only take into consideration properties and parameters of the preform which are physically realistic. For example, the numerical model can only consider an integer number of wires and / or layers, constraining the adjustment to a search among discrete values ​​for these parameters. The meta-model, acting as an interpolation or regression function, resolves this drawback by allowing continuous extrapolation to intermediate solutions with discrete values. This makes it possible to reduce the complexity of the adjustment problem linked to the discretization of the preform parameter.

[0084] The meta-model is constructed from a database using a linear, non-linear, kernel, etc. regression or interpolation mechanism. The meta-model can alternatively use a more sophisticated learning mechanism, for example that of a neural network.

[0085] In an exemplary embodiment, each admissible modification is modeled, in the meta-model, by a polynomial regression, typically a polynomial regression of order 3, of the database. Each regression thus associates the volume fraction with the corresponding modification of the parameter to be adjusted. The meta-model then includes all of these regressions, which are combined with a decision tree.

[0086] The database used by the meta-model comprises a plurality of samples determined by the digital model to be substituted. Each sample associates a value of the volume fraction with one or more modifications, or combination of admissible modifications, of at least one parameter of the preform and / or one or more constraints, which made it possible to determine said value of the volume fraction via the digital model to be substituted. The plurality of samples therefore forms a search space for the volume fraction, the different dimensions of which are the modifications made to the parameter(s) of the preform and used as input to the digital model.

[0087] To produce a modeled value, the meta-model therefore requires as input data, at a minimum, the modification(s) of the sequence of modifications already ef made during the adjustment, as well as the modification. The meta-model therefore takes into account, as input, all the modifications admissible for the application concerned.

[0088] The samples are, for example, defined randomly or pseudo-randomly, such as by Latin hypercube sampling. Alternatively, the samples may be defined as being regularly distributed within each range of values ​​associated with one of the modifications made.

[0089] Preferably, the samples in the database associate a volume fraction VF with a thickness 1T and one or more modifications a admissible for each of the parameters of the preform which are considered. The meta-model is then such that f{IT, A): IT. A~^ VF, where A includes all the admissible modifications.

[0090] Thus, for one of the modifications in the sequence of modifications, the meta-model must be informed of the modifications already made as well as those not yet made and, where applicable, those which are not part of the sequence although they are admissible. In other words, up to the current modification, the meta-model is informed of the sequence A^ which includes: • The modifications already made, each of which is assigned the value from at least one value range associated with this modification; • Changes not yet made, each of which is assigned a zero value; • Changes that are admissible in the meta-model but are not part of the sequence of changes, if any, and each of which is assigned a null value.

[0091] The database includes at least 100 samples, preferably at least 1000 samples, for each modification of each parameter considered.

[0092] The meta-model is dependent on the armor considered for manufacturing. That is to say, the meta-model is built for a particular armor. A meta-model must therefore be built for each armor considered, in the case where the preform is built according to different armors, or if a change of armor is envisaged.

[0093] In the case where each parameter is initialized to a maximum value, the database associates a value of the volume fraction with a decrease in each parameter considered. One advantage is to simplify the construction of the meta-model since it is then not necessary to have samples for an increase in the number of threads but only for a decrease in the number of threads.

[0094] The adjustment step 130 comprises two sub-steps 131 and 132. These sub-steps can be successively carried out several times, if necessary, to find the de- digital finish set.

[0095] The first sub-step 131 is a step of initializing the parameter of the preform. The initialization can be done randomly, for example by following a normal distribution over an interval of values ​​comprising a predefined maximum value and a predefined minimum value. These two values ​​can be defined automatically by the computer according to the requirements of the specifications and / or manufacturing constraints. These two values ​​can also be defined by an operator.

[0096] Preferably, the parameter of the preform is initialized to a maximum admissible value for the application concerned. By “admissible” is meant that the maximum value assigned to the initialization of the parameter corresponds to the maximum value that can be assigned in accordance with the specifications and respecting the manufacturing constraints. The maximum value for initialization also depends on the armor of the preform.

[0097] The value at initialization of the preform parameter may be, relative to the parameter considered, one or more of: a maximum number of layers, a maximum number of cells, a maximum weft spacing, a maximum warp spacing, a maximum number of weft threads, a maximum number of warp threads, a maximum count of weft threads, a maximum count of warp threads.

[0098] Substep 132 is then a step for determining a set value of the parameter of the preform, implemented for each modification of the sequence of modifications, each corresponding to a different parameter.

[0099] The adjusted value of the parameter is obtained, taking into account the regularization term corresponding to the relevant modification of the parameter of the preform, by canceling a difference between the modeled value of the volume fraction and the target value of the volume fraction or the maximum value of the textile volume fraction.

[0100] The cancellation of the difference between the modeled value and the target value or the maximum value is therefore carried out for each of these modifications, taking into account the regularization term(s) corresponding to the modification concerned. For each modification, the maximum value corresponding to the maximum value of the textile volume fraction, obtained for said modification in the associated range of values.

[0101] Solving such an equation makes it possible to find a balance solution between the error of the modeled value of the volume fraction of the preform compared to the target value or the maximum value of the volume fraction, and the regularity of the solution.

[0102] Preferably, this search for the set value of the parameter is carried out by means of a first iterative search algorithm, implemented for each modi fication of the sequence of modifications. Thus, for each modification, the first iterative search algorithm performs its search in the range of values ​​associated with said modification.

[0103] The first algorithm has the function of searching, for a given modification, the modification of the parameter of the preform which allows said cancellation from the initialized parameter of the preform, that is to say from the initial value of the parameter determined in the previous sub-step 131, for example the maximum value of said parameter.

[0104] In other words, the algorithm searches for the modification of the parameter to be applied, among the range of values ​​associated with said modification, so that the defined preform complies with the requirements of the specifications.

[0105] In particular, the first iterative search algorithm is used to solve the following equation, for each modification of the sequence of modifications: ma^VFclWe, f(lT, f(IT, A^ + / LAA;- = 0- In this equation, VF cihle is the target value of the volume fraction of the textile preform; f is the numerical model of the textile preform; IT is a target value of a thickness of the textile preform; Ai = ..., a^, is the sequence of modifications since the first modification up to said modification, noted i-th modification ai, the modifications to ai-i being associated with the values ​​which allow said cancellation, determined by the first iterative search algorithm, for the previous modifications of said modification ai, that is to say that Aj corresponds to the modifications already carried out up to the current modification; A”™* = [a^ , a^, is the sequence of modifications from the first modification to said modification a', where is the modification ai, in the associated range of values, which corresponds to the maximum value of the textile volume fraction; fi. is the regularization term(s) corresponding to said modification ai; and AAZ is a Laplacian of the sequence of modifications At from the first modification a 1 to said modification ai.

[0106] The target value of the thickness of the preform is predefined in the specifications and / or manufacturing constraints. The target value of the volume fraction of the preform and the value modeled by the numerical model of the preform are adimensionalized. Each regularization term has a dimension equal to the inverse of the dimension of the Laplacian. The initialization of each regularization term, in the second iterative search algorithm, to a positive or zero value favors the adjustment of the volume fraction and does not take into account the Laplacian during the first iteration.

[0107] When the meta-model is used, A- = {tïj, ..., a^, a,, 0, ... 0} so that the size of A, equal to the total number of changes that the metamodel can take as input, for example the total number of changes in the sequence of changes. The total number of admissible changes can, if necessary, correspond to the admissible changes that are not part of the sequence of changes. There are therefore neither unmade changes (i.e. to come in the sequence or admissible but not included in the sequence) to which the value 0 is assigned in Ah

[0108] The uniqueness of the solution of the equation, with respect to the modification of the preform, is guaranteed by the monotonicity of the error on the target volume fraction. The monotonicity of the error is guaranteed by minimization of the Laplacian, when solving the equation.

[0109] The regularity of a cell is defined by the Laplacian of the modification of the parameter to be adjusted. The Laplacian is preferably determined by a numerical solver from the numerical model of the preform. For example, the solver is a finite difference model of order 2. When the Laplacian is zero, the optimal solution of the equation is monotonic.

[0110] The first iterative search algorithm is preferably an optimization algorithm such as gradient descent, simulated annealing or a Krylov-Newton method.

[0111] Each modification can be applied to the entire preform or to one or more portions of the preform. In other words, each modification can be applied globally to the preform or only to certain layers and / or in certain cells of certain layers. In the latter case, the adjustment problem amounts to solving the appropriate equation in each layer and / or cell concerned.

[0112] In the case where the preform is subdivided into the plurality of cells, the parameter of the preform is assigned to each cell, independently of each other. In other words, each cell is associated with a value of the parameter of the preform. The parameter of the preform is then set individually for each cell of the plurality of cells and the regularization term(s) corresponding to the modification guarantee the regularity of the definition of the preform at the global level of the preform, between adjacent cells.

[0113] Similarly, each cell is assigned the volume fraction. The target value of the volume fraction may be identical for the entire preform or may vary from one cell to another.

[0114] Once the set parameter has been determined, the fifth step 150 of controlling the manufacturing machine is implemented to manufacture the 3D woven part from the modified textile preform.

[0115] For example, the fifth step 150 is a step of issuing a command to the manufacturing machine to manufacture said preform from the definition set digital. The command includes the digital definition of the preform including the set parameter of the preform, i.e. the set value of the parameter of the preform. For this purpose, the computer includes a device for transmitting the command to the manufacturing machine. When the machine receives the command, it manufactures the preform according to the specifications of the digital definition of the preform included in the command.

[0116] In an alternative, after the first iterative search algorithm has set the parameter of the preform, a comparison of the definition of the preform, in particular a final value of one of the properties of said definition, with one or more tolerances, is implemented in a step 140. The final value of one of the properties corresponds, for example, to the value of the volume fraction after setting the parameter. The final value of each property concerned is therefore associated with the set parameter of the preform.

[0117] The final value of each property concerned is obtained by using the numerical model of the preform with the set value of the parameter, i.e. the preform is modeled using the model with the set value of the parameter.

[0118] The tolerances may be those defined in the specifications. Comparison with the tolerances makes it possible to confirm or deny that the preform defined with the set parameter complies with the requirements of the specifications. These tolerances are, for example, defined in the form of thresholds or ranges of values.

[0119] Preferably, two tolerances are used: the first is a tolerance on a difference between the final value of the volume fraction and the target value of the volume fraction; the second is a tolerance with respect to a maximum number of anomalies, which is then another property of the preform.

[0120] The first tolerance is, for example, a range of values ​​defined by a minimum value lower than the target value of the volume fraction, and a maximum value higher than the target value of the volume fraction, so as to include the target value of the volume fraction in the value range. When the set value of the volume fraction is included in the value range, the preform obtained complies with the specifications.

[0121] The second tolerance is, for example, a predetermined threshold which indicates the maximum number of anomalies beyond which the preform does not conform to the specifications. When the number of anomalies of the preform is less than the predetermined threshold, the preform after adjustment conforms to the specifications. The number of anomalies is calculated from the distribution of the modifications of the parameter of the preform in the definition of the preform. In particular, an anomaly is a non-monotonicity of the solution of the equation on a plurality of consecutive cells; the plurality of consecutive cells comprises between 2 and 20 consecutive cells, for example example 10 cells.

[0122] When all tolerances are simultaneously met, the digital definition of the preform complies with all the requirements of the specification. This is then the adjusted digital definition of the preform. The preform can then be manufactured in compliance with the adjusted digital definition. The adjusted digital definition of the preform is generated using the digital model of the preform, or another digital weaving model, with the adjusted value of the preform parameter.

[0123] If the meta-model is used, the adjusted value of the preform parameter in the adjusted numerical definition can be rounded to the nearest integer. This approximation preserves the monotonicity and regularity of the solution.

[0124] The method comprises the step 150 of issuing the command to the manufacturing machine to manufacture the preform with the set digital definition.

[0125] When at least one of the tolerances is not met, the definition of the preform obtained by the adjustment is not compliant and is not manufactured. One or more regularization terms of the plurality of regularization terms must then be adjusted to iterate again the steps 120 to 140 of the method 100, until the definition of the preform after adjustment is compliant with the requirements. The adjustment 130 is therefore implemented again with the modified regularization terms, i.e. the modified values ​​of the regularization terms.

[0126] When the first tolerance is not respected, one or more of the regularization terms are reduced by a predetermined decrease. When the second tolerance is not respected, one or more of the regularization terms are increased by a predetermined increase. The predetermined increase and decrease are set by the operator depending on the application case.

[0127] When neither the first tolerance nor the second tolerance are met, no adjusted numerical definition can be found to conform the manufacture of the preform to the specifications. In this case, the target value of the volume fraction is modified, i.e. the specifications of the specifications concerning this property are adjusted. The method 100 is then implemented again.

[0128] The adjustment of the regularization terms can be done by means of a second iterative search algorithm. This second algorithm can be identical to the first algorithm, or another. For example, the second algorithm is an algorithm that does not impose an a priori on the nature of the problem, such as a genetic algorithm, a particle swarm, a Nelder-Mead method, a Broyden-Fletcher-Goldfarb-Shanno (BFGS) method, a greedy algorithm, etc. Preferably, the second algorithm does not require the calculation of a derivative.

[0129] This second algorithm makes it possible to iteratively adjust the plurality of regularization terms, from an initialization of the plurality of regularization terms, in implementing at each of its iterations the first algorithm which then searches for the adjusted digital definition of the preform using the plurality of regularization terms produced by the second algorithm. At the end of the first algorithm, the second algorithm compares the definition of the preform obtained with the tolerances and determines whether the values ​​of the regularization terms must be modified and repeat the adjustment of the first algorithm with adjustment of the plurality of regularization terms, or whether the preform complies with the requirements, in which case the manufacturing command is issued.

[0130] In other words, the second algorithm has the function of finding a minimum value for each regularization term of the plurality of regularization terms, such that all anomalies are resolved and / or the number of anomalies respects the tolerance.

[0131] The second algorithm can be applied following two approaches: a global approach and a local approach. The global approach consists of adjusting all the regularization terms, that is, modifying the regularization terms including for cells without anomalies. The local approach consists of adjusting only the regularization terms in the cells comprising anomalies. For example, in the local approach, the regularization term is progressively increased to regularize the cells with anomalies so as to preserve the spatial correlation between the cells.

[0132] For a cell, when the regularization term associated with it is zero, the set value of the preform parameter is such that the final value of the volume fraction is equal to the target value of the volume fraction. If the regularization term associated with a cell is very large, the solution becomes monotonic.

[0133] The adjusted regularization terms, obtained by the second iterative search algorithm, are case-dependent because an anomaly can be more or less critical depending on the part and the position of the anomaly on the part. The regularization terms can take this criticality into account.

[0134] Furthermore, it is possible to cancel certain regularization terms, in particular for cells without anomalies, and to make non-zero only the regularization terms for cells with anomalies, allowing a parsimonious regularization of the definition of the preform.

[0135] At the end of the search for the plurality of optimal regularization terms by the second iterative search algorithm, it is possible that the definition of the preform obtained via the adjustment does not respect the tolerances. In other words, no adjusted numerical definition is found to conform the manufacture of the preform to the specifications. In this case, the target value of the volume fraction is modified, that is to say that the specifications of the specifications concerning this property are adjusted. Optionally, the values ​​of other properties and / or parameters can be modified, such as preform thickness, preform areal density, preform armor, etc.

[0136] The method 100 is then implemented again in its entirety until the set digital definition of the preform is determined. The modification of the target value(s) of the property(ies) of the preform can be implemented automatically, by predefined increment or decrement, or by an operator.

[0137] An example of the evolution of the regularity of the definition of the preform by successive adjustment of the plurality of regularization terms is shown in [Fig.2]. It can be observed that the number of anomalies of the definition of the preform, both for the warp threads (corresponding to the continuous curve with the solid circles) and for the weft threads (corresponding to the dashed curve with the solid circles), decreases significantly with the successive adjustment of the regularization terms, represented by the evolution of the average value of these terms, along the weft axes (corresponding to the dashed curve with the solid triangles) and warp axes (corresponding to the solid curve with the solid triangles), with the increase in the number of iterations of the second iterative search algorithm. An optimum of the definition of the preform is reached from iteration 80.

[0138] An example of the operation of the method 100 is shown in [Fig. 3]. In this figure, the sequence of modifications comprises two modifications M1 and M2. Modification M1 is a modification of the weft yarn count and modification M2 is a modification of the number of layers. Before setting for modification M1, the preform definition is initialized with the maximum number of layers and yarn counts equal to 48 for the weft and warp yarns of each cell of the eight layers. The search by the first iterative algorithm determined that the optimal value in the range of values ​​associated with modification M1 is 4, i.e., the yarn count of 4 of four layers is modified in the preform definition.Then, for modification M2, the first iterative search algorithm determined that the optimal value in the value range associated with this modification is 2, two layers must then be removed from the preform definition.

Claims

1.

2. Claims A computer-implemented method (100) for controlling the manufacture, by a manufacturing machine, of a 3D woven part in a composite material, comprising: - Obtaining (110) a target value of a volume fraction of a textile preform of the 3D woven part and a sequence of modifications, each modification of the modification sequence being associated with a range of values; - Obtaining (120) a plurality of regularization terms, each of the plurality of regularization terms corresponding to one of the modifications of the sequence of modifications; - Modifying (130) the textile preform by applying the sequence of modifications to conform the textile preform to the target value of the volume fraction, each modification being carried out in the associated range of values ​​taking into account a modeled value of the volume fraction and the regularization term corresponding to said modification; - Order (150) the machine to manufacture the 3D woven part from the modified textile preform. The method (100) of claim 1, wherein modifying the preform comprises adjusting at least one parameter of the textile preform to conform a definition of the textile preform to the target value of the volume fraction, the adjusting comprising: - Initialize (131) the at least one parameter of the definition of the textile preform; and - For each of the modifications in the sequence of modifications: • Determine (132), by means of a first iterative search algorithm, a set value of the at least one parameter of the definition of the textile preform corresponding to said modification, said set value being determined by canceling a difference between the modeled value of the volume fraction, obtained using a numerical model and taking into account the regularization term corresponding to said modification, and: - The target value of the volume fraction; or - A maximum value of the volume fraction corresponding to a maximum value of the volume fraction, obtained by modifying the parameter of the textile preform in the range of values ​​associated with said modification; the first iterative search algorithm searching for a value, among the range of values ​​associated with said modification, which allows said cancellation.

3. The method (100) of claim 2, wherein the first iterative search algorithm is configured to resolve, for each modification of the sequence of modifications, max(VFcihl(? f (IT, A'"')) - f (IT, A,) + = 0, with VFcihle the target value of the volume fraction; f the digital model of the textile preform; IT a target value of a thickness of the textile preform; Ai = {«;, ..., a^, G,} 'a sequence of modifications from the first modification a< until said modification, noted i-th modification ai, the modifications ai to ai-i being associated with the values ​​which allow said cancellation, determined by the first iterative search algorithm, for the previous modifications of said modification ai; Az”“a = the sequence of modifications from the first modification to said modification ai, where is the modification ai, in the associated range of values, which corresponds to the maximum value of the volume fraction; / 1 the regularization term corresponding to said modification F; and AAZ a Laplacian of the sequence of modifications A, from the first modification to said modification a>.

4. Method (100) according to one of claims 2 and 3, comprising: - Comparing (140) a final value of the volume fraction or other property of the textile preform to a tolerance, the final value of the volume fraction or other property of the textile preform being obtained using the model

5.

6. digital of the textile preform with the set value of the textile preform parameter, and: • When the final value of the volume fraction or other property of the textile preform meets the tolerance, issue (150) the command including the definition of the textile preform; • Otherwise, modify the plurality of regularization terms, by means of a second iterative search algorithm, and implement again the adjustment (130) of the parameter of the textile preform with the modified plurality of regularization terms. Method (100) according to one of claims 2 to 4, in which the at least one parameter of the textile preform is initialized to a maximum value. Method (100) according to one of claims 2 to 5, wherein the definition of the textile preform comprises a plurality of superimposed layers, each of the layers of the plurality of layers comprising a plurality of cells and each cell of the plurality of cells corresponding to one or more threads of said composite material woven along the weft and / or warp reinforcement axes of the textile preform, and the at least one parameter of the textile preform is: - a number of layers, and the modification of the parameter of the textile preform is an increase or a decrease in the number of layers of the preform; - a number of cells, and the modification of the parameter of the textile preform is an increase or a decrease in the number of cells of one or more layers of the preform; - a weft spacing and / or a warp spacing, and the modification of the parameter of the textile preform is an increase or a decrease in the weft spacing and / or an increase or a decrease in the warp spacing between two or more cells of one or more layers; - a number of warp threads and / or a number of weft threads, and the modification of the parameter of the textile preform is a increase or decrease in the number of warp threads and / or an increase or decrease in the number of weft threads, of one or more cells of one or more layers of the preform; - is a warp thread count and / or a weft thread count, and the modification of the parameter of the textile preform is an increase or decrease in the warp thread count and / or an increase or decrease in the weft thread count, of one or more cells of one or more layers of the preform.

7. Method (100) according to one of claims 2 to 6, in which the digital model of the textile preform is a meta-model modeling a digital weaving model, the meta-model taking as input the modification of the parameter of the textile preform or the sequence of modifications, and producing as output the modeled value of the volume fraction.

8. Device comprising a calculator configured to implement the method (100) according to one of claims 1 to 7.

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