Method and control device for detecting thermal anomalies in additive manufacturing processes

Abstract

Method and control device for detecting thermal anomalies in a laser powder bed fusion process. One aspect of the invention relates to a method for detecting a thermal anomaly in a manufacturing process for a test part (4), the manufacturing process being carried out using an additive manufacturing machine (1) by melting each deposit of a plurality of successive deposits of a powder bed. Figure to be published with the abbreviation: Figure 2

Description

Title of the invention: Method and control device for detecting thermal anomalies in additive manufacturing processes. TECHNICAL FIELD OF THE INVENTION

[0001] The technical field of the invention is that of non-destructive testing for additive manufacturing by powder bed fusion.

[0002] In particular, the invention relates to a method and a device for detecting a thermal anomaly in an additive manufacturing process. TECHNOLOGICAL BACKGROUND OF THE INVENTION

[0003] In additive manufacturing, processes based on powder bed fusion, such as Laser Powder Bed Fusion (LPBF), Electron Beam Melting (EBM), Binder Jetting (BJ), and Multi Jet Fusion (MJF), consist of applying energy locally to the powder bed to fuse (LPBF, EBM, MJF) or polymerize (BJ) at least a portion of the powder bed and form, layer by layer, a desired part. These processes allow for great manufacturing flexibility but are also subject, at various timescales, to manufacturing process anomalies, particularly those related to the power received by the parts. Therefore, to guarantee the quality of the manufactured parts and the repeatability of the process, it is essential to be able to evaluate these fluctuations in situ and in real time. In particular, this continuous monitoring must make it possible to detect rapid variations (e.g.power jumps) or slow (drifts) in process parameters.

[0004] It is known to use infrared radiation during manufacturing to detect manufacturing defects. For example, it is known to use photodiodes to acquire an intensity emitted by the melt pool environment and detect a defect by analyzing this signal and comparing it to reference values ​​(K. Taherkhani et al., Development of a defect-detection platform using photodiode signal collected from the melt pool of laser powder-bed fusion, Additive Manufacturing, vol. 46, 102152, 2021). One drawback of this approach is that the exercise must be performed for each additive manufacturing setup, each part geometry, each process parameter configuration, and each part material, since detection performance is highly dependent on manufacturing conditions. This approach is therefore difficult to implement in a high-speed industrial environment.

[0005] Alternatively, it is known to detect this infrared radiation by means of an infrared camera sensitive in the so-called "mid-wave" range, i.e. between 2 and 5.7 pm (G. Mohr et al., In-Situ Defect Detection in Laser Powder Bed Fusion by Using Thermography and Optical Tomography—Comparison to Computed Tomography, Metals, vol. 10, 103, 2020), or sensitive to the far-infrared, i.e., between 8 and 14 pm (JL Bartlett, In situ defect detection in selective laser melting via full-field infrared thermography, Additive Manufacturing, vol. 24, p. 595-605, 2018). One advantage of these approaches is acquiring an image covering a significant surface area of ​​the part being manufactured, at the expense of a large volume of data to acquire, store, and analyze. Another major drawback is that these approaches are unreliable because they have a significant number of false positives (defects detected when the part is sound) and false negatives (defects not detected when the part is defective).

[0006] Furthermore, it is known to detect a manufacturing anomaly by analyzing ultrasonic signals acquired during manufacturing (EP3658377A1 and H. Rieder et al., On- and offline ultrasonic characterization of components built by SLM additive manufacturing, 42nd Annual Review of Progress in Quantitative Nondestructive Evaluation, AIP Conf. Proc., vol. 1706, p. 130002-1-130002-7, 2016). These approaches aim to identify defects on parts during manufacturing and not to detect defects in the manufacturing process itself.

[0007] There is therefore a need for a reliable, in-situ and rapid means of detecting variations or anomalies in an additive manufacturing process by powder bed fusion. Summary of the invention

[0008] The invention provides a solution to the problems mentioned above by enabling the detection of a thermal anomaly in an additive manufacturing process through the evaluation of a cooling characteristic of a test part during its manufacture. This characteristic can be a kinetic or amplitude of a signal acquired from a sensor during the cooling phase.

[0009] One aspect of the invention thus relates to a method for detecting a thermal anomaly in a manufacturing process, the manufacturing process being implemented by means of an additive manufacturing machine by consolidating each deposit of a plurality of successive deposits of a powder bed, in particular for the production of a part, called a test part, said method comprising, after the consolidation of at least one deposit of the plurality of deposits: • Obtain a signal sensitive to a temperature variation of the consolidated deposit of the test piece, the signal being acquired during the manufacture of the test piece by the manufacturing process; • Determine, from a metric determined from the signal obtained, a cooling data, the cooling data being a quantifiable characteristic of the cooling dynamics of the consolidated deposit before the next deposit of the plurality of deposits; • Compare the cooling data to a reference value; and • Detect the thermal anomaly in the manufacturing process when the data The cooling value is far from the reference value.

[0010] Additive manufacturing refers to the production of a part by assembling one or more materials deposited in successive layers or passes. Among additive manufacturing processes, particular interest lies in those based on the principle of melting and cooling the material, the deposit of which in powder form is called a "powder bed." In the case of Laser Powder Bed Fusion (LPBF) and Electron Beam Fusion (EBM) processes, a pass or layer comprises the deposition of the powder bed and the melting of this deposit at the locations where the powder must be consolidated. In the case of the Multi-Jet Fusion (MJF) process, a layer comprises the deposition and melting of a specific fusible agent deposited at the locations where the fusible agent must be consolidated.Similarly, in the case of the Binder Jetting (BJ) process, a layer involves the deposition and heat-curing of a binder deposited in areas where the binder needs to be consolidated. A manufacturing process is therefore associated with a specific manufacturing technology (FLLP, EBM, MJF, BJ, etc.) and a set of parameters defining the manufacturing implementation for one or more specific parts.

[0011] A "thermal anomaly in the manufacturing process" is defined as a malfunction of one of the components of the additive manufacturing machine used in the manufacturing process. This malfunction is caused, for example, by a change in an operating parameter of one of these components. For example, it could be a variation in the power delivered by the melting source, such as a short-term variation resulting in an over- or under-input of energy for melting, compared to the nominal operation of the source when no thermal anomaly occurs. Such a power variation is also possible over a long timescale where the power delivered by the source and received by the part gradually decreases due to the machine's operation itself, for example, if smoke deposits occur on the optics; this is referred to as power "drift."Another example of malfunction is a variation in the speed of the laser spot movement mechanism on the workpiece during fusion, also resulting in an over- or under-input of energy. An over- or under-input of energy leads to a modification of the cooling mechanisms of the fused layer of the workpiece before deposition. The next layer, compared to a reference value of the cooling characteristic when the source is in nominal operation. Other examples of malfunction involve the random failure to execute one or more passes, or vectors, which are then not fused or are poorly fused.

[0012] A "test piece" means a piece manufactured alone or in parallel with one or a plurality of pieces to be manufactured, said test piece being of simple geometry and of geometric characteristics allowing a quick, simple and reliable detection of a thermal anomaly of the manufacturing process.

[0013] A "temperature-sensitive signal" is defined as a signal measuring a physical property that depends, in particular, on the temperature of the reference part. The sensor used to acquire this signal is therefore capable of capturing such a signal.

[0014] The term "reference value" means a value of the same dimensions as the cooling data and which corresponds to a cooling data point of the cooling kinematics of the test part, such as the amplitude of variation of a signal metric or a characteristic cooling time, when no thermal anomaly occurs. The reference value may be, for example, obtained using a numerical simulation tool or derived from a measurement campaign on a plurality of sound test parts, i.e., reference parts for which no thermal anomaly of the manufacturing process has been detected. The absence of thermal anomalies for these reference parts is, for example, verified by a control method other than that proposed in this method, for example, by non-destructive or destructive testing post-manufacturing or during manufacturing

[0015] The cooling data is considered "far" from the reference value when the distance between the determined cooling data and the reference value is greater than or equal to a predetermined threshold. This predetermined threshold is defined by an operator based on their knowledge and / or manufacturing constraints, using data from previous manufacturing of other parts, such as other test parts, and / or data from a numerical simulation.

[0016] Thanks to the invention, it is possible to determine, on the test piece, a cooling value quantifying the cooling kinematics of the consolidated deposit following the melting of a powder layer and before the subsequent deposition of the plurality of deposits. This cooling value provides information on the energy dissipated by the test piece after melting, as well as on the amount of energy supplied by the source to the piece, since the signal obtained is sensitive to the temperature of said piece. Thus, thanks to the invention, it is possible to detect a thermal anomaly in the manufacturing process by determining the cooling value. In particular, the method makes it possible to detect a variation on a short or long time scale of the power received by the test piece which, in an ideal case, is constant throughout its manufacture.

[0017] It is possible to manufacture this test part in one or more copies, for example, for maintenance, certification, or operational testing of the additive manufacturing machine. Alternatively, this test part can be manufactured jointly, in one or more copies, with another part or several other parts. One advantage is to implement the proposed method in parallel with the manufacture of one or more other desired parts and to detect, for example in a production context, a thermal anomaly in the manufacturing process in order to take corrective action in near real-time to correct the thermal anomaly or a consequence thereof.One consequence of the thermal anomaly is, for example, a manufacturing defect in the part such as a defect in the fusion of a layer, high porosity due to an under-input of energy ("lack of fusion") or an over-input of energy ("keyhole").

[0018] The method is simple and quick to implement since it requires, at a minimum, only the fabrication of the test piece and the acquisition of a signal sensitive to a temperature variation in the test piece. As the test piece has a simple geometry, acquiring such a signal is also simple. Such a signal can come, for example, from an ultrasonic (US) sensor or an infrared (IR) sensor.

[0019] The method is also simple and quick to implement since it only requires determining a cooling value for the test part in order to then detect a thermal anomaly in the manufacturing process by a simple comparison to the reference value. Furthermore, the comparison allows for the almost instantaneous detection of the thermal anomaly since it only requires knowing the reference value.

[0020] Since the signal is acquired during the manufacturing of the test part, it is possible to implement the method in-situ, during this manufacturing process. The proposed method thus makes it possible to quickly detect the thermal anomaly and alert an operator or send a command to the additive manufacturing machine to correct the machine malfunction in order, for example, to apply a corrective action to the part or stop the part's manufacturing. Furthermore, it is possible to perform the corrective action only on the layer(s) affected by the thermal anomaly. It is also possible to anticipate manufacturing defects in a subsequently produced part, particularly when the detected thermal anomaly corresponds to a drift. Detecting the thermal anomaly therefore makes it possible to reduce, or even avoid, the loss of manufacturing material. in this case the powder, by discarding defective parts manufactured jointly or subsequently to the control part.

[0021] Most non-destructive testing techniques (US, IR, etc.) allow for the acquisition of high-resolution signals at high sampling frequencies, making it possible to detect the thermal anomaly in near real-time.

[0022] In addition to the characteristics just mentioned, the previous method may have one or more complementary characteristics from among the following, considered individually or according to all technically possible combinations.

[0023] In one embodiment, the cooling data is a characteristic cooling time and the reference value is a reference duration.

[0024] The term “reference duration” means a cooling time of the control part not subject to a thermal anomaly.

[0025] In one embodiment, the cooling data is an amplitude of variation of the metric determined from the signal obtained and the reference value is a reference amplitude.

[0026] The term "reference amplitude" means a variation in amplitude of the metric determined from the signal during the cooling phase under nominal conditions.

[0027] In one embodiment, the cooling data is averaged over several deposits of the plurality of successive deposits, the steps of the method being implemented after the consolidation of each of the several deposits of the plurality of successive deposits.

[0028] Averaging makes it possible to smooth and / or mitigate the variability of the cooling data, in particular due to measurement uncertainties.

[0029] In one embodiment, the steps of the method are implemented after the consolidation of each deposit of the plurality of successive deposits of the powder bed.

[0030] The method thus makes it possible to detect the thermal anomaly early during a particular pass. It is then possible to alert the operator to the pass affected by the thermal anomaly and therefore to apply corrective action to that pass, for example by applying a new melt.

[0031] In one embodiment, the melting of each deposit of the plurality of successive deposits leads to the fabrication of the test piece, the test piece comprising a body such that the body is solid and includes, after the melting of each deposit of the plurality of successive deposits of the powder bed, a top surface whose geometry is invariant during the fabrication.

[0032] The test piece according to the invention is of a simple shape and quick to manufacture, such as a cylinder, with a top surface whose dimensions are constant in order to to minimize the variability of the energy dissipated by the control piece from one layer to another, after the melting of the deposit.

[0033] In one embodiment, the test piece further comprises a base such that the base is integral with an upper face of a plate and is flared from the body to the plate, and such that the body is integral with the base.

[0034] In this particular embodiment, the geometry of the base of the test piece includes, in its lower part, a "skirt" which ensures continuity of the mechanical coupling of the test piece with the platform without stress concentration, while also ensuring the stability of the piece on the platform. In this particular embodiment, the manufacturing surface of the test piece is therefore only constant after the skirt has passed over it.

[0035] The use of a simple geometry test piece makes it possible to link any variations in the thermal properties of the part to fluctuations in the manufacturing process and thus provide useful information for manufacturing control. The use of a complex geometry test piece, such as those typically produced by additive manufacturing, would be difficult to exploit because, in this case, the variations in the thermal properties of the part also depend on variations in the surface area produced for each layer. It would therefore not be possible to directly deduce that a thermal anomaly in the process is occurring from a measurement on such a piece.

[0036] In one embodiment, the cooling data is a difference between a value at an initial time, called the initial value, and a value at a final time, called the final value, of the metric determined from the signal obtained, the initial time being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit, the final time being strictly greater than the initial time and less than or equal to a time of start of the next deposit.

[0037] The cooling data is therefore directly linked to the cooling of the test part between the melting of two successive deposits. It is therefore possible to associate the thermal anomaly with a layer of the manufactured part.

[0038] In one embodiment, the cooling data is a characteristic cooling time and in which the final instant is an instant for which the final value is equal to a predefined value.

[0039] The characteristic cooling time therefore corresponds to the time required for the part for the metric to reach the predefined value from the initial instant, i.e., the end of the melting of the layer in question or an instant separated by the predefined duration. The predefined value is, for example, defined by an operator based on their knowledge and / or manufacturing constraints based on manufacturing processes. previous data from other parts, such as other reference parts, and / or data from a numerical simulation.

[0040] In one embodiment, the predefined value is equal to the initial value reduced by a predefined factor.

[0041] The cooling time is determined without resorting to an imposed initial temperature that would be artificially predefined and case-dependent. On the contrary, the characteristic cooling time is determined as the time required for the temperature of the reference part to decrease by the predefined factor. The determination of the characteristic cooling time is therefore relative to the acquired signal and not absolute with respect to an imposed reference. The predefined factor is defined by an operator based on their knowledge and / or manufacturing constraints, using data from previous manufacturing of other parts, such as other reference parts, and / or data from a numerical simulation.

[0042] In one embodiment, the cooling data is a characteristic cooling time and is determined from a ratio between a value at an initial instant, called the initial value, of the metric determined from the signal obtained and a time derivative of said metric in the vicinity of the initial instant, the initial instant being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit.

[0043] Alternatively, the characteristic cooling time is continuously calculated from the values ​​of the metric and its derivative. Therefore, there is no need to use an imposed, artificially predefined, and case-dependent initial temperature. Nor is it necessary to determine the characteristic time based on a parameter provided by the operator. The determination of the characteristic cooling time is thus free from any preconceptions about the manufacturing process and / or the part being manufactured.

[0044] In one embodiment, the cooling data is determined from a time derivative in the vicinity of an initial instant of the metric determined from the signal obtained, the initial instant being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit.

[0045] The use of the derivative of the metric makes it possible to increase the sensitivity of the cooling data to the cooling dynamics of the part.

[0046] In one embodiment, the initial instant is the instant of the end of heat input due to at least one deposit of the plurality of successive deposits or an instant following the instant of the end of heat input of a predefined duration

[0047] The initial moment therefore corresponds to the moment when the source ceases to supply energy to fuse / solidify the powder and when the cooling of the part is initiated. Alternatively, the initial instant corresponds to an instant spaced from the predefined duration of the end of the melting to limit the sensitivity of the calculation to noise generated by the transient nature of the stop of the melting / solidification.

[0048] In one embodiment, the signal obtained is a signal of light radiation from the witness piece captured by a photodiode, a plurality of photodiodes or an infrared camera.

[0049] Signal acquisition therefore relies on a non-intrusive, non-destructive sensor technology, requiring minimal instrumentation and adaptation to ensure compatibility between the measurement implementation and the additive manufacturing machine and the associated process. Furthermore, the signal acquired by such sensors is particularly sensitive to the surface temperature of the reference part facing the camera, and not to a temperature gradient along the height of the part. The information contained in the acquired signal is thus essentially characteristic of the properties of the surface facing the camera.

[0050] In one embodiment, the signal obtained is a signal of light radiation from the test piece captured by the plurality of photodiodes or the infrared camera and comprises a plurality of images of the test piece acquired during manufacturing, each image of the plurality of images comprising a plurality of pixels, each pixel of the plurality of pixels being associated with a value of light amplitude radiated by the test piece, and in which the metric is an average for each image of the plurality of images of the values ​​of light amplitude radiated from the plurality of pixels.

[0051] The light energy radiated by the reference part depends on the surface temperature of the part. The captured signal is therefore sensitive to variations in the surface temperature of the reference part. Furthermore, averaging the values ​​of each pixel for each image reduces the information to be processed per image to a single scalar, limiting the amount of data to be stored in memory, at least temporarily, while also reducing the sensitivity of the cooling data calculation to measurement noise.

[0052] In one embodiment, the signal obtained is a signal of an ultrasonic wave propagating in the witness piece, the ultrasonic wave being emitted and captured by an ultrasonic sensor positioned opposite the witness piece.

[0053] The signal acquisition therefore relies on a non-intrusive, non-destructive sensor technology, requiring minimal instrumentation to ensure that the measurement implementation is compatible with the additive manufacturing machine and the associated process. Furthermore, the signal acquired by such a sensor is sensitive to the temperature within the volume of the test part. The information contained in the acquired signal is richer than those of the signal captured by the infrared camera and are therefore characteristic of both the volumetric and surface properties of the part.

[0054] In one embodiment, the ultrasonic signal comprises a variation of an acoustic field caused by the propagation of the ultrasonic wave in the witness piece after reflection on a surface formed by the melting of at least one deposit, and in which the metric is a propagation time of the ultrasonic wave from a generation instant to a capture instant.

[0055] The propagation time of a mechanical wave in a material depends on the temperature field present within the volume of said material. The signal captured and the propagation time determined from this captured signal are therefore sensitive to a variation in temperature in the reference part.

[0056] In one embodiment, the method according to the first aspect includes the issuance of an alert relating to the detected thermal anomaly.

[0057] Another aspect of the invention relates to a device for detecting a thermal anomaly in a manufacturing process for a test part configured to implement the method according to the first aspect.

[0058] The implementation of this method in such a device requires few resources for its implementation, such as a processor and a memory comprising instructions which, when executed by the processor, allow the implementation of the method described above.

[0059] Another aspect of the invention relates to a device for detecting a thermal anomaly to implement the method in the first aspect, comprising an ultrasonic sensor intended to emit and capture the ultrasonic wave, the ultrasonic sensor being positioned opposite the test piece under a platform, said platform being configured to protect the ultrasonic sensor from an atmosphere generated by the manufacturing process and to ensure mechanical continuity between the ultrasonic sensor and the test piece.

[0060] The platform therefore serves to ensure the seal between the atmosphere of the additive manufacturing chamber and the location of the sensor while ensuring the proper propagation of the ultrasonic wave through its thickness, from the ultrasonic sensor to the test piece.

[0061] A computer program, implementing all or part of the method described above, installed on pre-existing equipment, is in itself advantageous.

[0062] Thus, the present invention also relates to a computer program product comprising instructions for the implementation of certain steps of the process described above, when this program is executed by a processor.

[0063] This program may use any programming language (for example, an object-oriented language or other), and may be in the form of interpretable source code, partially compiled code or fully compiled code.

[0064] Another aspect of the invention relates to a computer-readable recording medium comprising instructions which, when executed by a computer, lead the computer to carry out the steps of the method described above.

[0065] The invention and its various applications will be better understood by reading the following description and examining the accompanying figures. BRIEF DESCRIPTION OF THE FIGURES

[0066] Other features and advantages of the invention will become apparent from the description, which can be read in conjunction with the figures. These figures are provided for illustrative purposes only and are not intended to limit the scope of the invention: • The [Fig. 1] is a synoptic diagram illustrating the sequence of steps of a method according to the invention. • Fig. 2 is a schematic representation of an additive manufacturing machine equipped with an external infrared camera. • Fig. 3 is a schematic representation of a variant of the additive manufacturing machine of Fig. 2 with an internal infrared camera. • Fig. 4 is a schematic representation of the additive manufacturing machine equipped with an ultrasonic sensor. • Fig. 5 is a schematic representation of the additive manufacturing machine equipped with thermocouples. • Fig. 6 is a schematic representation of the additive manufacturing machine equipped with thermocouples according to a variant compatible with the embodiment of Fig. 4. • Fig. 7 is a schematic representation of a test piece according to the invention comprising a base, or skirt, used to highlight the effect of a change in parameters. • Fig. 8 is an example of a signal from an infrared camera capture. • Fig. 9 is an example of a signal from a capture by an ultrasonic translator. • The [Fig. 10] is an example of the evolution of a characteristic cooling time in the test piece following an evolution of the manufacturing parameters at the level of the skirt passage according to the [Fig.7] determined by the implementation of the method according to the [Fig.1]. • The [Fig. 11] is an example of variation of an amplitude of the propagation time of an ultrasonic wave in the control part following an evolution of the manufacturing parameters according to the [Fig.7]. DETAILED DESCRIPTION

[0067] The invention relates to a method for detecting a thermal anomaly in a powder bed fusion additive manufacturing process. The proposed approach is based on the implementation in the additive manufacturing machine of sensors capable of measuring signals sensitive to temperature variations, such as an infrared (IR) camera or an ultrasonic transducer (US), which can deliver a signal whose variations depend on the power received by a part during its manufacture. These variations in the signals, acquired in situ and in real time during manufacturing, provide information on the energy received by the part and therefore on the stability of the process, as well as on the presence of a thermal anomaly in said process.To this end, the method relies on the fabrication of a simple geometric sample, for which a signal is acquired via one of the aforementioned sensors and then analyzed to evaluate the cooling dynamics of this sample after the melting of one of the deposited powder bed layers. The proposed method makes it possible, in particular, to detect fluctuations or instabilities in the source used for melting, leading to manufacturing defects such as the random failure of one or more melts, or even longer-term drifts in the power delivered by the source.

[0068] The thermal anomaly can be caused by a short- or long-term malfunction of one or more machine components. A "short-time-scale phenomenon" and a "long-time-scale phenomenon" are defined as phenomena occurring over a short or long period, respectively, relative to the complete manufacturing of a part by the additive manufacturing machine. Short-time-scale phenomena are most often punctual or transient fluctuations whose duration is shorter than the duration of a pass but long enough to be detected by a control method, such as the method proposed here. In contrast, long-time-scale phenomena are fluctuations with slow variations of varying amplitude that are detectable after the manufacturing of several layers, or even after several uses of the machine.

[0069] The process in question is based on the melting of a powder bed, which is deposited by a plurality of successive deposits. The melting is carried out after each deposit of the powder bed.

[0070] As illustrated in [Fig. 1], the method 100 for detecting a thermal anomaly in the additive manufacturing process comprises several steps. The method The steps involved can be implemented by a device for detecting a thermal anomaly in the additive manufacturing process, configured to implement the method. That is, this device includes hardware and software means to implement Method 100. For example, the device in question is a computer comprising a processor and volatile or non-volatile memory, which contains instructions that, when executed by the processor, lead to the implementation of Method 100.

[0071] Since the objective of the method is to determine a thermal anomaly of the process from a cooling data of the part after the melting of one of the powder bed deposits, these steps are successively implemented once the melting of the deposit in question has taken place.

[0072] In one embodiment, these steps are implemented for each powder bed deposit made, after the powder bed has melted. Alternatively, these steps are implemented after the melting of some powder bed deposits, for example, after the melting of each deposit in a number N of powder bed deposits, where N is an integer greater than 1.

[0073] By way of illustration, the method is subsequently implemented for the analysis of a signal acquired via an infrared (IR) camera and a laser heat input method. Such an embodiment is illustrated in [Fig. 2]. However, this illustration does not detract from the general applicability of the method to other heat input technologies and sensors capable of producing a signal sensitive to a temperature variation in the reference part.

[0074] The additive manufacturing machine 1 includes a heat source 2, for example a laser, an electron beam source, or a set of infrared lamps. The source emits energy towards the test part 4 and, optionally, towards another part to be manufactured 5. The machine 1 also includes a platform 6 suitable for supporting the manufacturing of the test part 4 and the other part 5.

[0075] The IR camera 3 is positioned outside the machine so that its lens faces a window 3' of the machine 1 that is non-opaque to IR radiation, for example, made of germanium or sapphire. In an alternative embodiment, illustrated in [Fig. 3], the IR camera 3 is inside the machine 1. In this case, the IR camera 3 is positioned so as not to alter or hinder the operation of the machine 1. The IR-non-opaque window 3' is not required here.

[0076] The IR camera 3 is oriented so that its lens is directed towards the test piece 4 and so that no other element of the machine 1 screens between the IR camera 3 and the test piece 4. The IR camera 3 can, for example, operate either in the mid-wave range, with wavelengths between 2 and 6 pm, or in the far infrared with wavelengths between 8 and 14 pm. Alternatively, the camera can be replaced by one or more photodiodes, called measurement photodiodes.

[0077] The test piece 4 is manufactured, by means of the fusion of successive deposits, so as to be solid, that is to say without cavity or hollowness, and to have a simple geometry.

[0078] The geometry, and the related dimensions, of the upper surface constructed pass after pass, of the test piece 4, are preferably constant throughout the manufacturing process.

[0079] The test piece is, for example, cylindrical or parallelepiped-shaped, such as a rectangular prism. The width, or diameter, of the test piece is between 0.5 and 5 cm, preferably between 0.5 and 2 cm. The piece is therefore sufficiently narrow so as not to require too much material in its manufacture, but large enough for a thermal fluctuation to be detectable by the sensor.

[0080] In a particular embodiment illustrated in [Fig. 7], the test piece 4 comprises a body 4-1 and a base 4-2 joined together. The body 4-1 of the test piece is cylindrical or parallelepiped in shape as previously described. The body 4-1 therefore has an invariant geometry throughout the manufacturing process. The base 4-2 is flared from the body to the base plate 6. The base 4-2 thus has a width that gradually increases from the body to the base plate 6.

[0081] The 4-2 base can be a polyhedron or be of concave or convex annular shape. The base is fixed to the plate.

[0082] The upper surface of the test piece 4 is also parallel to the upper face of the plate 6.

[0083] The test part 4 can be manufactured anywhere on the platform 6 or at a specific location on the platform to control the manufacturing process at that specific location. The test part 4 is positioned on the platform so as not to interfere with the manufacturing of another part, for example, by selecting the location of the test part 4 on the platform after having selected the location(s) for manufacturing the other parts.

[0084] The camera 3 is used to capture light radiation emitted by the test piece 4. This radiation is produced by the thermal dissipation of the test piece 4 linked to the energy input from the source 2.

[0085] The camera is connected to a device 20 used for acquiring signals via the IR camera 3. The acquisition device can be the device configured to implement method 100.

[0086] Method 100 therefore includes a step 110 of obtaining a signal acquired by means of the IR camera 3. By acquiring a signal is understood the acquisition of digital samples of a physical quantity to which the sensor is sensitive. The acquisition is performed by the device 20 at a predefined sampling frequency. The predefined sampling frequency is set by an operator and is high enough to provide a sufficient number of samples to analyze the cooling dynamics. In practice, this number of samples is greater than 10, preferably greater than 100, and even more preferably greater than 1000. "Acquisition" therefore means that the signal is transmitted in digital format to the device implementing method 100 via a transmission medium, for example, a wired or wireless connection.

[0087] In this embodiment, the acquired signal comprises a plurality of IR images acquired at the predefined sampling frequency. Each image is formed from a plurality of pixels. Each pixel of the image is associated with a luminous amplitude of the light radiation equal to a number of photons captured for said pixel.

[0088] The signal acquisition is done continuously during the manufacture of the test piece 4.

[0089] Alternatively, the acquisition is triggered by means of a photodiode, called a detection photodiode, which is used to detect the instant at which the deposit melts. The instant at which melting ceases is the instant at which the source stops emitting the energy necessary to melt the powder bed. In other words, it is the instant at which the heat input ends.

[0090] Acquisition can also be stopped at the start time of the next deposition or at the start time of melting of that next deposition, also detected by means of the detection photodiode. The start time of deposition is the moment when the next deposition begins to be deposited. The start time of melting is the moment when the source begins to emit the energy necessary to melt the powder bed.

[0091] Method 100 then includes a step 120 of determining a cooling datum, in particular for the surface of the test part 4 that has just been manufactured. This cooling datum is characteristic of the cooling dynamics of the part. The cooling datum makes it possible to quantify the cooling of the surface that has just been consolidated. The cooling datum is therefore a quantifiable characteristic of the cooling kinematics of this surface due to the cessation of energy emission by the source 2. As such, the cooling datum may be an amplitude of variation of a signal metric or a characteristic cooling time.

[0092] In the embodiment presented, the cooling data is determined from the light signal acquired by the IR camera 3, forming an image referred to as an IR image. Preferably, the cooling data is determined by analyzing a metric calculated from the obtained signal. In the case where the signal is acquired via the IR camera 3, the metric in question is an average amplitude calculated by averaging, for each IR image, the light amplitude values ​​of all the pixels of the image. In some embodiments, the average is applied to a subset of the plurality of pixels. The plurality of images is thus averaged into a plurality of scalars, the value of each of which is equal to the average of the amplitudes of the corresponding image. The cooling data is therefore determined as a function of the variation of the average amplitude calculated for each image.

[0093] In an alternative embodiment, the cooling data is determined from the light signal acquired by the measuring photodiode. In this case, the metric in question is the light amplitude captured by the measuring photodiode.

[0094] In one embodiment, the cooling data is determined from the light signals acquired by the plurality of measurement photodiodes. The concatenation of the light signals forms an image, each pixel of the image being associated with one of the photodiodes of the plurality of measurement photodiodes. Each pixel of the image is therefore associated with the light amplitude captured by the associated photodiode. As with the thermal camera 3, an averaging of the light amplitude is performed over all or part of the set of pixels. The metric is then, at each instant, the average of the light amplitudes captured by each of the measurement photodiodes.

[0095] The cooling data is determined from the difference between a value of the metric taken at an initial time and a value of the metric taken at a final time. This data can be, if necessary, dimensionless and / or normalized.

[0096] The initial time is, for example, the time of completion of the merge of the repository for which method 100 is implemented.

[0097] Alternatively, the initial instant is a subsequent instant close to the instant of the end of melting. In this case, the initial instant is, for example, offset from the instant of the end of melting by a duration equal to the predefined duration, for example, between 0.1 s and 2 s. The predefined duration is, for example, chosen by the operator based on their knowledge and manufacturing constraints. Preferably, the predefined duration is defined so as to minimize the sensitivity of the signal obtained to measurement noise generated by transient phenomena due to the near-instantaneous interruption of the energy supplied by the source.

[0098] The final instant is a time subsequent to the initial instant, strictly greater than the initial instant. The final instant is less than or equal to the start time of the next deposition. The notion of quasi-real time is thus relative to the manufacturing time of a layer, since it is necessary to wait until the final instant is reached to determine the cooling data, which can be the time at which the layer's consolidation is complete.

[0099] In the case where the cooling data is the amplitude of variation of the metric, the cooling data is equal to a difference between the value of the metric at the initial time and the value of the metric at the final time.

[0100] In a preferred embodiment of the invention, the cooling kinematics are measured by determining the characteristic cooling time, which is determined from the signal obtained in the previous step. The characteristic cooling time corresponds to the cooling duration of the part, in particular the surface of the test part 4 that has just been manufactured. The characteristic cooling time therefore corresponds to the duration during which the layer whose deposit has just been fused undergoes a temperature decrease.

[0101] The characteristic cooling time is equal to the difference between the initial time and the final time.

[0102] Alternatively, the final instant is an instant at which the value of the metric, called the final value, is equal to a predefined value. The characteristic cooling time is then the time required for the surface of the test piece to cool down to the predefined value.

[0103] The predefined value is, for example, an average amplitude value of luminous amplitude defined by the operator. The amplitude value can be an absolute value or a value relative to another value.

[0104] Preferably, the predefined value is defined relative to the value of the metric at the initial instant, called the initial value, in this case the average value of the light amplitude captured by the IR camera 3. For example, the predefined value is lower than the initial value by a predefined factor. As an example, the predefined factor is strictly greater than 0 and strictly less than 1; for example, it is between 0.1 and 0.9. The predefined value is therefore proportional to the initial value, and the final instant is the instant after the initial instant at which the final value is equal to the initial value reduced by the predefined factor. The predefined factor is, for example, defined by the operator. The characteristic cooling time is then the time required for the surface of the test piece to cool by the predefined factor.

[0105] Method 100 then includes a step 130 of comparing the cooling data determined in the previous step with a reference value.

[0106] The reference value is defined by the operator or by means of a digital simulation tool and corresponds to a nominal value of the cooling data, i.e. a cooling data value for which no thermal anomaly has occurred.

[0107] The comparison is implemented by calculating a distance, for example in the form of a difference, between the reference value and the determined cooling data.

[0108] The smaller this distance, the closer the cooling data is to the reference value and the lower the risk of a thermal anomaly occurring. The energy dissipated by the test part during its cooling therefore corresponds well to the energy it is supposed to dissipate when the manufacturing process is implemented without thermal anomaly.

[0109] On the contrary, the greater this distance, the higher the risk of a thermal anomaly occurring. The energy dissipated by the control part during its cooling is therefore abnormally high or abnormally low.

[0110] In one embodiment, the reference value is equal to the cooling data determined for a previous layer or to an average of cooling data determined for several previous layers, method 100 having been implemented for this or these previous layers. The previous layer(s) used to define the reference value are, preferably, layers built without modification of the manufacturing process compared to the layer being inspected.

[0111] Thus, when the cooling data is the amplitude of variation of the metric, the reference value is a reference amplitude of variation of the metric, obtained under nominal manufacturing conditions; and when the cooling data is the characteristic cooling time, the reference value is a reference duration, also obtained under nominal manufacturing conditions.

[0112] Method 100 then includes a step 140 for detecting the thermal anomaly based on the comparison in the previous step. The thermal anomaly is detected when the comparison between the cooling data and the reference value—that is, between the metric's variation amplitude and the reference metric variation amplitude, or between the characteristic cooling time and the reference duration—indicates an excessively large difference between these values. In particular, the thermal anomaly is detected when the distance calculated in the previous step exceeds a predefined threshold.

[0113] The threshold is for example defined as a function of a standard deviation of the cooling data calculated for a plurality of passes of a plurality of reference parts, for example other test parts or other copies of the test part 4, for which no thermal anomaly has been detected.

[0114] Alternatively, the threshold can be defined based on the cooling data and / or the average of the cooling data calculated for the preceding layer(s). For example, the threshold is proportional to the cooling data determined for the preceding layer or to the average of the cooling data of the preceding layer(s). For example, the threshold is equal to the standard deviation of this average.

[0115] The predefined threshold can, moreover, be defined by the operator.

[0116] Method 100 then includes a step 150 of issuing an alert. The alert relates to the detected thermal anomaly. For example, the alert may include one or more pieces of information concerning the layer for which the thermal anomaly is detected. The alert is, for example, a message sent to the operator in the form of alphanumeric characters. The alert may also include part or all of the signal obtained and relating to said alert, that is, all or part of the samples of said signal. The alert may, furthermore, include part or all of the metric calculated from the signal obtained, that is, all or part of the values ​​that the metric comprises.

[0117] When one or more other parts 5 are manufactured concurrently with the control part 4, this alert is used to implement corrective action, for example in the form of feedback. This makes it possible to correct the thermal anomaly in the manufacturing process and, potentially, to correct a manufacturing defect caused in the other parts 5 by the occurrence of the thermal anomaly.

[0118] In one embodiment, the sensor used to capture the signal is an ultrasonic (US) sensor. This sensor is preferably a single-element transducer, converting a mechanical deformation into an electrical voltage by piezoelectric effect. Alternatively, the sensor is a multi-element transducer.

[0119] Preferably, the US sensor is a single-element transducer, thus enabling signal acquisition at a high sampling frequency and propagation of an US wave at a high speed, allowing for near real-time evaluation of the cooling data. In an alternative embodiment, the generation / detection of ultrasonic waves is performed using a laser.

[0120] As illustrated in [Fig. 4], the transducer 7 is positioned under the platform 6, which supports the test piece 4 and the optional other or plurality of other pieces 5. This transducer is arranged opposite the test piece to maximize the transmission of ultrasound waves between the transducer and the test piece. The transducer 7 can be placed in contact with the underside of the platform 6, and a coupling can also be applied between the transducer and the platform 6.

[0121] In addition to supporting the manufactured parts and the transducer 7, for which it is chemically and thermo-mechanically compatible with the manufacturing material, the platform serves to protect the US sensor 7 from the atmosphere generated by the manufacturing process. To this end, the platform 6 is capable of protecting, or even isolating, the US sensor 7 from the additive manufacturing chamber 8 in which the additive manufacturing of the test part 4, and any other parts 5, takes place. It therefore ensures a seal between the additive manufacturing chamber 8 and the location of the US sensor 7. The platform is made of a material compatible with the parts to be manufactured, the choice of which is a matter of operator expertise.

[0122] The term "additive manufacturing chamber" refers to the part of the additive manufacturing machine 1 in which additive manufacturing takes place. The chamber 8 is isolated from the other parts of the additive manufacturing machine 1 to protect the inside of the machine from contact with the material in powder form. The chamber 8 contains, for example, the melting source 2, the test part 4, the other part(s) to be manufactured 5, a powder reservoir (not shown), and a powder bed deposition device (not shown).

[0123] The platform 6 is also suitable for ensuring mechanical continuity between the US sensor 7 and the witness piece 4 in order to reduce the acoustic impedance break for an US wave propagating between the US sensor 7 and the witness piece 4. The platform is also configured to be of low attenuation for mechanical waves. Advantageously, it can be machined to allow the integration of the transducer and optional thermocouples without modifying the machine architecture.

[0124] In one embodiment, this platform 6 has an opening allowing the passage of connecting supports, for example cables linking the US sensor 7 to the acquisition device 20 or to the thermal anomaly detection device.

[0125] The US 7 sensor is configured to generate an US wave around a center frequency between 1 MHz and 100 MHz, preferably between 2 MHz and 20 MHz, with a bandwidth between 50% and 95% at -6 dB, for example 80% at -6 dB.

[0126] The generated US wave then propagates from the US sensor 7 into the test piece 4 by passing through the thickness of the plate 6. The wave is then reflected by the upper surface of the test piece 4 and is back-propagated from this surface to the US sensor 7.

[0127] The US sensor 7 therefore detects the disturbance of the displacement field, at its surface in contact with the plate 6, generated by the propagation of the US wave, in particular after its reflection by the upper surface of the witness piece 4. Each sample of the plurality of samples of the acquired signal includes an amplitude value of the variation of said displacement field.

[0128] The US wave is emitted in the form of a continuous succession of pulses, in English "pumps", separated by a predefined time step, said time step being between 0.01 s and 1 s, preferably 0.02 s and 0.2 s. The pulses can also be emitted only between the time of the end of fusion and the time of the start of the next deposition.

[0129] Since the propagation speed of the US wave is sensitive to temperature variations in the test piece 4, this speed decreases significantly during the cooling of the test piece 4 between the respective meltings of two successive layers. This decrease allows the cooling data for the test piece 4 to be determined.

[0130] Consequently, we seek to extract the evolution of the propagation time of the US wave of the US signal captured by the sensor US 7, including the variations in the amplitude of the displacement field at its surface. For each emitted wave train, the propagation time is determined as the difference between the time of capture of the echo of the US wave by the sensor US 7 and the time of generation of the wave by the sensor US 7.

[0131] The metric used to determine the cooling data is therefore the round-trip propagation time of the wave from its generation until its capture by the US 7 sensor.

[0132] In this embodiment, when the cooling data is an amplitude of variation of the metric, the cooling data is a propagation time and is equal to the difference between the propagation time of the US wave at the initial instant and the propagation time of Fonde US at the final instant.

[0133] In this embodiment, when the cooling data is the characteristic cooling time, this is determined as the difference between the initial time and the final time, where the final time is the time when the propagation time reaches the predefined value, which is then a propagation time value. Again, the predefined value can be defined absolutely or relative to another value, such as relative to the initial value, for example, to be less than the initial value by a predefined factor. The initial value is defined in the same way as in the case of using the IR camera 3. The initial value is therefore the Fonde US propagation time at the initial time.

[0134] During its manufacture, the test piece 4 is preferably manufactured so that its upper surface is flat and in a plane orthogonal to the direction of propagation of Fonde US, in order to maximize the energy of the specular echo captured by the sensor US 7.

[0135] In one embodiment, the cooling data is equal to a value of a derivative of the determined metric (the average amplitude per frame or the Fonde US propagation time). The derivative is, for example, a first-order time derivative of the metric whose value is evaluated in the vicinity of the initial time, for example, at the initial time. The derivative is, for example, calculated using a finite difference. The finite difference may be centered or non-centered. Thus, when the metric is derived from the IR camera 3, the cooling data is a derivative of the average amplitude per frame; and, when the metric is derived from the US sensor 7, the cooling data is a derivative of the Fonde US propagation time. The reference value is then the value of the derivative of the metric in the vicinity of the initial time, for example, at the initial time, when the metric is obtained under nominal manufacturing conditions.Therefore, there is no longer any need to determine the moment. final nor the final value to be compared to the predefined value to evaluate the cooling data.

[0136] In an alternative, the cooling data is a difference between the derivative of the metric in the vicinity of the initial time, for example at the initial time, and the derivative of the metric in the vicinity of the final time, for example at the final time.

[0137] In another embodiment, the characteristic cooling time is alternatively determined as being proportional to a division of the determined metric (the average amplitude per image or the US wave propagation time) by a value of the derivative of this metric with respect to time.

[0138] This division is, for example, evaluated in the vicinity of the initial time. That is to say, the value of the metric taken in the vicinity of the initial time is divided by its derivative calculated in the vicinity of the initial time. In particular, this division is evaluated at the initial time. The characteristic cooling time is therefore the value of the ratio between the metric and its derivative calculated at the initial time.

[0139] The derivative is, for example, determined in the same way as in the previous embodiment.

[0140] In this alternative, the characteristic cooling time is directly calculated around the initial instant without recourse to the final instant or the final value.

[0141] In another alternative, the characteristic cooling time is determined as being proportional to a division of a change in said metric by the value of the derivative of said metric with respect to time in the vicinity of the initial instant, for example at the initial instant. The change in said metric is determined as being equal to a difference between the value of the metric at the initial instant and the value of the metric at the final instant.

[0142] In this alternative, it is therefore not necessary to determine the final time relative to the initial time to evaluate the time required to reach the predefined value. The final time can therefore be any time subsequent to the initial time. Preferably, the final time is the start time of the next deposit or a time preceding the start time of the deposit by a short predefined duration, for example between 0.01 s and 1 s.

[0143] The reference value is then the value of the division of the metric, or of the variation of the metric, by the derivative of the metric in the vicinity of the initial instant, for example at the initial instant, when the metric is obtained under nominal manufacturing conditions.

[0144] In one embodiment, once the cooling data has been determined for a layer, it is advantageous to average the values ​​obtained over several layers. The duration of the averaging window is sufficiently long to smooth the signal and reduce its sensitivity to measurement uncertainties. as well as noise. The duration of said window is also short enough to limit the loss of information.

[0145] In the case of the US sensor 7, averaging is applied to the data over a number of layers between 3 and 10, preferably between 5 and 8. In the case of the IR camera 3, averaging is applied to the data over a number of layers between 2 and 8, preferably between 4 and 6.

[0146] In one embodiment, one or more thermocouples are instrumented in the machine 1, for example type K thermocouples. As illustrated in [Fig.5], the thermocouples 9 are arranged so as to be positioned under the tray 6, for example in contact with the lower surface of the tray 6. The thermocouples are connected to the acquisition device 20 and / or to the thermal anomaly detection device.

[0147] The thermocouples 9 can be placed anywhere under the plate 6 or at specific locations to collect temperature data at those specific locations. For example, as illustrated in Figure 6, the thermocouples can be arranged on either side of the sensor US 7 to precisely collect the temperature at the level of said sensor US7.

[0148] One advantage of using thermocouples 9 is the ability to build a database that can later be used to populate a thermal model in a numerical simulation. Another advantage is the ability to control temperature variations at the platform 6 during manufacturing.

[0149] In one embodiment, several copies of the test part 4 are manufactured simultaneously. Other test parts 4 of different dimensions or shapes can also be manufactured. Method 100 is then implemented for some or all of the parts or copies for one, several, or each deposit of the powder bed. One advantage is the ability to detect thermal anomalies over a longer period, particularly drift. Another advantage is the ability to evaluate the robustness of the process with respect to a thermal anomaly at several positions on the platform 6; indeed, the performance of the manufacturing process can depend on the position of the part relative to the heat source or other machine components.

[0150] Furthermore, several other optional parts 5 can be manufactured in conjunction with the control part 4 or with a plurality of copies of the control part 4 or a plurality of different control parts 4. The copies or different control parts 4 then serve to detect the thermal anomaly throughout the manufacture of the plurality of other parts 5, for example by alternating the manufacture of one of the control parts 4 with the manufacture of one or more of the other parts 5. This makes it possible to precisely identify the other parts 5 for which the thermal anomaly This may have degraded the manufacturing process and allow for better targeting of corrective action, for example, by correcting only the parts affected by the thermal anomaly. To this end, the alert may include information relating to the control part 4 and, possibly, to the other part(s) 5 affected by the thermal anomaly.

[0151] Advantageously, the proposed method can be used to evaluate changes in cooling dynamics during part manufacturing, or over several successive manufacturing runs of different parts. The part's cooling dynamics can thus be compared to one or more reference cooling trends. These reference trends are obtained, for example, from a previous measurement campaign or from a numerical simulation tool and represent the cooling dynamics for one or more passes with and / or without a thermal anomaly. Comparing the cooling dynamics with the reference trend(s) makes it possible to identify abnormal behavior in part cooling, without necessarily detecting or experiencing a thermal anomaly.On the contrary, and advantageously, this comparison allows us to predict a future thermal anomaly, for example, for a subsequent pass or for a subsequent manufacturing process. One benefit is therefore identifying a behavior that, in the short or long term, leads to the occurrence of the thermal anomaly. When such a behavior is identified, it is then possible to anticipate the thermal anomaly and prevent it, for example, by implementing corrective action.

[0152] The applicability of Method 100 was evaluated on two different additive manufacturing machines 1. Two powder materials were used: AlSi7Mg and IN 625. The method was implemented jointly using an IR camera and an ultrasonic sensor. In this case, an Optris™ PI 640i G7 thermal imaging camera was used, positioned above the machine 1 through a germanium viewing window. The ultrasonic sensor was a single-element ultrasonic transducer with a center emission frequency of 5 MHz, mounted under the build platform 6. The ultrasonic signal was acquired with a sampling frequency of 156 MHz. A photodiode was instrumented to detect the start and end times of melting.

[0153] Two type K thermocouples 9 were arranged under the tray, on either side of the transducer.

[0154] The cylindrical test piece 4 was manufactured to have a diameter of 20 mm and a post-manufacturing height of 15 mm. The base was formed on the first 65 layers, in the lower part of the cylinder.

[0155] For the base, the power delivered by the source, here a laser, was 240 W. The scanning speed of the source was 2000 mm / s.

[0156] For the body, the power delivered was 253 W and the scan speed was 900 mm / s.

[0157] The time during which fusion energy is emitted by the source decreases over the first 65 layers corresponding to the base, due to the flared shape. The energy emission time is then constant and at a higher value, since the scan speed is slower for the body than for the base and the surface area to be created is the same size from one pass to the next.

[0158] From the signal acquired by the IR camera 3, variations in the averaged radiated light amplitude during a portion of the manufacturing process are shown in [Fig. 8]. From the signal acquired by the US sensor 7, variations in the propagation time of the US wave during this first part of the manufacturing process are shown in [Fig. 9]. It is observed that these two metrics exhibit significant variations after each layer melting. The start time of each melting is represented by a dashed vertical line, and the end time of each melting is represented by a solid vertical line. These variations are related to the heat dissipation generated by the reference part 4. The analysis of these signals is therefore relevant for calculating the cooling data.

[0159] As illustrated in [Fig. 10], the calculation of the characteristic cooling time Tc, determined by analysis of the IR camera signal 3 on the first 500 layers, shows an increase in this characteristic cooling time during skirt fabrication, a jump at the C transition between the base and the body, and subsequent stabilization. The LT laser emission time for each layer during fabrication is also indicated.

[0160] As illustrated in [Fig. 11], the variations in the amplitude of the propagation time during the cooling phase between the time of the end of melting of one layer and the beginning of melting of the next layer, evaluated via the US sensor on the first 900 layers, show growth during the manufacturing of the skirt, a jump at the transition between the skirt and the cylinder, and a decrease before stabilization thereafter.

[0161] The characteristics of these signals therefore make it possible to identify changes in the power conditions received by the test piece during its manufacture, using both the IR camera 3 and the US sensor 7.

Claims

Demands

1. Method (100) for detecting a thermal anomaly in a manufacturing process, the manufacturing process being implemented by means of an additive manufacturing machine (1) by consolidating each deposit of a plurality of successive deposits of a powder bed for, in particular, the production of a part, referred to as a test part (4), said method (100) comprising, after the consolidation of at least one deposit of the plurality of deposits: - Obtaining (110) a signal sensitive to a temperature variation of the consolidated deposit of the test part (4), the signal being acquired during the manufacture of the test part (4) by the manufacturing process, the signal obtained being a signal of light radiation from the test part (4) captured by a photodiode, a plurality of photodiodes or an infrared camera, or a signal of an ultrasonic wave propagating in the test part (4),The ultrasonic wave is emitted and captured by an ultrasonic sensor (7) positioned opposite the test piece (4); - Determine (120), from a metric determined from the signal obtained, a cooling value, the cooling value being a quantifiable characteristic of the cooling dynamics of the consolidated deposit before the next deposit of the plurality of deposits; - Compare (130) the cooling value to a reference value; and - Detect (140) the thermal anomaly of the manufacturing process when the cooling value deviates from the reference value.

2. Method (100) according to claim 1 wherein the cooling data is a characteristic cooling time and the reference value is a reference duration.

3. Method (100) according to claim 1 wherein the cooling data is an amplitude of variation of the metric determined from the signal obtained and the reference value is a reference amplitude.

4. Method (100) according to claim 3, wherein the cooling data is a difference between a value at an initial time, referred to as initial value, and a value at a final time, referred to as final value, of the metric determined from the signal obtained, the initial time being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit, the final time being strictly greater than the initial time and less than or equal to a time of start of the next deposit.

5. Method (100) according to claim 2, wherein the cooling data is a characteristic cooling time, the characteristic cooling time being equal to a difference between an initial instant and a final instant, the initial instant being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit, the final instant being strictly greater than the initial instant and less than or equal to a time of start of the next deposit, and wherein the final instant is an instant for which the value of the metric, called final value, is equal to a predefined value.

6. Method (100) according to claim 5, wherein the predefined value is equal to the value of the metric at the initial time, referred to as the initial value, reduced by a predefined factor.

7. Method (100) according to claim 2, wherein the cooling data is determined from a ratio between a value at an initial time, called initial value, of the metric determined from the signal obtained and a time derivative of said metric in the vicinity of the initial time, the initial time being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit.

8. Method (100) according to any one of claims 1 to 3 wherein the cooling data is determined from a time derivative in the vicinity of an initial instant of the metric determined from the signal obtained, the initial instant being between the time of completion of consolidation of at least one deposit of the plurality of successive deposits and the time of start of the next deposit.

9. Method (100) according to any one of claims 4 to 8, wherein the initial time is the time of termination of heat input due to at least a deposit of the plurality of successive deposits or an instant following the instant of end of thermal input of a predefined duration.

10. Method (100) according to any one of the preceding claims, wherein the cooling data is averaged over several deposits of the plurality of successive deposits, the steps of the method (100) being implemented after the consolidation of each of the several deposits of the plurality of successive deposits.

11. Method (100) according to any one of the preceding claims wherein the steps of the method (100) are carried out after the consolidation of each deposit of the plurality of successive deposits of the powder bed.

12. Method (100) according to any one of claims 1 to 11, wherein the signal obtained is a signal of light radiation from the test piece (4) captured by the plurality of photodiodes or the infrared camera (3) and comprises a plurality of images of the test piece (4) acquired during manufacturing, each image of the plurality of images comprising a plurality of pixels, each pixel of the plurality of pixels being associated with a value of light amplitude radiated by the test piece (4), and wherein the metric is an average for each image of the plurality of images of the light amplitude values ​​radiated from the plurality of pixels.

13. Method (100) according to any one of claims 1 to 11, wherein the signal obtained is a signal of an ultrasonic wave propagating in the test piece (4), the ultrasonic wave being emitted and captured by an ultrasonic sensor (7), wherein the ultrasonic signal comprises a variation of an acoustic field caused by the propagation of ultrasonic waves in the test piece (4) after reflection on a surface formed by the melting of at least one deposit, and wherein the metric is a propagation time of the ultrasonic wave from a generation instant to a capture instant.

14. Method (100) according to any one of the preceding claims comprising the emission (150) of an alert relating to the detected thermal anomaly.

15. Device for detecting a thermal anomaly in a manufacturing process of a test part (4) configured to implement method (100) according to one of the preceding claims.

16. A device for detecting a thermal anomaly for implementing the method (100) according to any one of claims 1 to 11 or 13, comprising an ultrasonic sensor (7) for emitting and capturing the ultrasonic wave, the ultrasonic sensor (7) being positioned opposite the test piece (4) under a platform (6), said platform (6) being configured to protect the ultrasonic sensor (7) from an atmosphere generated by the manufacturing process and to ensure mechanical continuity between the ultrasonic sensor (7) and the test piece (4).

17. Product computer program comprising instructions to implement method (100) according to any one of claims 1 to 14 when this program is executed by a processor.

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