Method for testing and manufacturing watch hairsprings

Abstract

1. A method for testing a hairspring or a hairspring blank configured to form a hairspring, the hairspring having to have at least one predetermined expected resonant frequency, the test method comprising the steps of: a. applying a vibrational excitation to the hairspring or hairspring blank, the vibration excitation varying over time to cover a predetermined frequency range; b. identifying at least one characteristic of a resonant frequency of the hair spring or hair spring blank, such as a resonant peak, during or in response to vibrational excitation over a predetermined frequency range; c. subjecting the resonant frequency characteristic determined in step b to a prediction machine to determine whether the hair spring or hair spring blank is affected by a defect.

Description

[Technical field]

[0001] The present invention relates to the field of testing and manufacturing of timepiece components, more specifically to a method for testing and manufacturing hairsprings, also known as oscillators, for timepieces. [Background technology]

[0002] The movement of a mechanical watch is regulated by a mechanical governor comprising an oscillator, in other words an elastically deformable component, whose oscillations determine the behavior of the watch. Many watches include a governor with a hairspring as an oscillator, for example, mounted on the axis of the balance wheel and set into oscillation by the escapement. The natural frequency of the balance wheel and hairspring pair allows the watch to be regulated and depends in particular on the stiffness of the hairspring.

[0003] More specifically, the frequency f of the regulating mechanism formed by a hairspring of stiffness R coupled to a balance wheel of inertia I is given by the following equation:

number

[0004] The stiffness of the hairspring also defines its natural vibration characteristics, such as the natural frequency and the resonant frequency. In this application, the natural frequency of an elastic system (oscillator alone or oscillator-balance wheel pair) is the frequency at which this system oscillates when it operates freely, in other words in the absence of an exciting force. Furthermore, the resonant frequency of an elastic system subjected to an exciting force is the frequency at which a local maximum can be measured in the amplitude of the displacement for a given point of the elastic system. In other words, if the elastic system is excited by an excitation source with a frequency that varies over time, the displacement amplitude will, at any point that does not correspond to a vibration node, follow an upward slope before this resonant frequency and a downward slope after it. Typically, during such tests, the recording of the amplitude of the displacement as a function of the excitation frequency has a peak or resonant peak in the amplitude of the displacement that is associated with or characterizes the resonant frequency.

[0005] The stiffness of a hairspring oscillator typically depends on the properties of the material from which it is made, as well as on its dimensions, in particular the thickness (or width) of its coils along the bar. More specifically, the stiffness is given by the following formula:

number

number

[0006] The natural frequency of a regulating mechanism formed by a hairspring of stiffness R coupled to a balance wheel of inertia I is in particular proportional to the square root of the stiffness of the hairspring. The main specification of a hairspring is its stiffness, which must be within a well-defined interval so that it can be paired with the balance wheel, which forms the inertia element of the oscillator. This pairing is essential to accurately regulate the frequency of a mechanical oscillator.

[0007] It is very important that the oscillator characteristics are as stable as possible in order to ensure an equally stable operation of the watch. The importance of magnetic fields in the modern environment has driven watchmakers over the years to use silicon balance springs, which are less sensitive to magnetic disturbances than metal balance springs.

[0008] Very advantageously, by using micromachining techniques, it is possible to produce hundreds of silicon balance springs on a single wafer. In particular, it is known to produce multiple silicon oscillators with very high precision by using photolithography and machining / etching methods in silicon wafers. The methods for producing these mechanical oscillators usually use monocrystalline silicon wafers, but it is also possible to use wafers made of other materials, such as polycrystalline or amorphous silicon, other semiconductor materials, glass, ceramics, carbon, carbon nanotubes, or composites containing these materials. On the other hand, monocrystalline silicon belongs to the cubic class m3m, whose coefficient of thermal expansion (alpha) is isotropic.

[0009] Silicon has a highly negative value for its first thermoelastic coefficient, as a result of which the stiffness of an oscillator made of silicon, and therefore its natural frequency, varies greatly with temperature. To at least partially compensate for this drawback, documents EP 1 422 436, EP 2 215 531 and WO 2016128694 describe hairspring-type mechanical oscillators that are generated from a core (or in the case of WO 2016128694, two cores) made of monocrystalline silicon, so that the temperature variation in Young's modulus is compensated by a layer of amorphous silicon oxide (SiO2) surrounding the core (or cores), the latter being one of the few materials with a positive thermoelastic coefficient.

[0010] When the hairsprings are produced from silicon or another material by collective manufacturing on a wafer, the final functional yield is obtained by dividing the number of hairsprings whose stiffness corresponds to the pairing interval by the total number of hairsprings on the wafer.

[0011] However, the micromachining steps, more specifically the etching, used in the manufacture of hair springs on wafers typically result in a significant contour variance in the dimensions of hair springs on the same wafer, and therefore in their stiffness, even though the etching pattern is the same for each hair spring. The measured variance in stiffness usually follows a Gaussian distribution. Therefore, in order to optimize the manufacturing yield, it is also considered to center the mean of the Gaussian distribution on the nominal stiffness value and to reduce the standard deviation of that Gaussian distribution.

[0012] Furthermore, the dispersion of stiffness is even larger between hair springs of two wafers etched at different times according to the same method specifications. This phenomenon is shown in Figure 1, which illustrates the stiffness dispersion curves Rd1, Rd2 and Rd3 of hair springs on three different wafers. In general, for each wafer, the distribution of stiffness R (with respect to the number N of hair springs with this stiffness) follows a normal or Gaussian law, with each dispersion curve centered on its respective mean value Rm1, Rm2 and Rm3.

[0013] Documents WO 2015113973 and EP 3181938 propose to solve this problem by forming a hairspring with dimensions greater than those necessary to obtain a hairspring with a given stiffness, measuring the stiffness of this hairspring formed by coupling with a balance wheel with a given inertia, calculating the thickness of material to be removed to obtain the dimensions necessary to obtain a hairspring with a given stiffness, and removing this thickness from the hairspring. Similarly, document EP 3181939 proposes to solve this problem by forming a hairspring with dimensions less than those necessary to obtain a hairspring with a given stiffness, determining the stiffness of this hairspring formed by coupling with a balance wheel with a given inertia, calculating the thickness of material to be added to obtain the dimensions necessary to obtain a hairspring with a given stiffness, and adding this thickness of material to the hairspring.

[0014] In this way, as illustrated in FIG. 2, regardless of the average stiffness Rm1, Rm2, etc. on a given wafer, the stiffness distribution curves Rd1, Rd2, etc. can be re-centered about a nominal stiffness value, Rnom.

[0015] In contrast, it can be observed that the manufacture of hairsprings on wafers may generate defects across some hairsprings, which defects lead to large variations in the oscillatory behavior with respect to the normally expected behavior. In particular, it can occur that the coils remain in contact or are joined to each other. Bridging phenomena can also be observed between the coils due to impurities, or that parts of the hairspring remain in contact with other parts of the wafer. Obviously, these phenomena can be considered as manufacturing defects that strongly affect the oscillatory behavior and make one or more hairsprings of the same wafer unsuitable for use in a watch mechanism. Furthermore, it is noted that these defects are not easy to correct and usually lead to the part in question having to be discarded. In particular, the micro-corrections mentioned above (making oxide layers, adding or removing material across the part) cannot be used to correct such point-joint defects or bridge defects of the part or its coils to each other or to the wafer supporting the part.

[0016] The object of the present invention is to propose a technique which does not have the above mentioned drawbacks and which allows a faster production flow and / or less risk of contamination and / or more sampling and / or easier or faster detection of hairsprings of wafers with defects which are prohibitive for use in a watch mechanism. Summary of the Invention

[0017] More specifically, a first aspect of the invention relates to a method for testing a hair spring or a hair spring blank adapted to form a hair spring, the hair spring having to have at least one predetermined expected resonant frequency, the testing method comprising the steps of: a. applying a vibrational excitation to the hairspring or hairspring blank, the vibration excitation varying over time to cover a predetermined frequency range; b. identifying at least one characteristic of a resonant frequency of the hair spring or hair spring blank, such as a resonant peak, during or in response to vibrational excitation over a predetermined frequency range; c. subjecting the resonant frequency characteristic determined in step b to a prediction machine to determine whether the hair spring or hair spring blank is affected by a defect.

[0018] The method according to the above embodiment includes a step consisting of identifying characteristics indicative of significant defects affecting the hairspring or blank in question. For example, if the divergence identified in the spectrum of vibration frequencies obtained is greater than a predefined threshold, the hairspring or blank in question is determined to be usable in a watch mechanism. The method can therefore detect, with a simple measurement of the vibration spectrum obtained in response to a vibration excitation, whether a defect significantly affects the hairspring or hairspring blank to such an extent that it renders the part unusable and unreworkable. Such a measurement (performed on a single or "bare" or "unworked" finished or blank part, in other words, for example, without a finishing surface treatment and / or not yet assembled) allows to identify defects on the part without an analysis of appearance or a single measurement, even before removing the part from the wafer and mounting it on the vibration mechanism, allowing to save time and resources. In other words, it is possible to categorize the hairspring or blank while still at the wafer stage, for example, into a first category of usable parts or parts for possible reworking, and a second category of defective parts to be discarded.

[0019] The method according to the above embodiment comprises a step of vibration excitation of the hairspring or hairspring blank and then a step of identification of the resonant frequency to estimate by prediction whether a defect affects the hairspring or blank. There is no assembly of a balance wheel or another component, saving time. Furthermore, measurements are performed only on the hairspring or blank, which limits the possibility of errors and contamination induced by other components or assemblies of components. The measurement accuracy is improved since there are fewer sources of variation due to other components or contamination. In other words, only the hairspring or hairspring blank is tested. The vibration excitation is applied to the part or single blank, without being coupled to either a balance wheel, a weight or an oscillating system. The method allows the testing of a single free part, offering advantages in terms of increased productivity (no assembly with an oscillating system), increased quality (no contamination of the part) and increased precision (no errors linked to other components of the oscillating system).

[0020] According to one embodiment, the defect is: One or more coils bonded or bridged to adjacent coils or to the remainder of the wafer, e.g., an insulating support; localized or non-localized porosity of the material or oxide; The interface between the silicon core and the oxide layer, which has voids, delaminations, irregularities, etc. Irregular or discontinuous thickness of oxides etc. Material defects or localized shortages, e.g. penetration defects, For example, excess material associated with masking defects, Inhomogeneity of materials (silicon, silicon oxide), Flatness defects (smoothing) of the transverse slices of the bars forming the hairspring, Vertical imperfections in the transverse slices of the bars forming the hairspring (tapering or undercutting of the faces), It may be a coil that is deformed, wavy, or off-center compared to its theoretical position. It should be noted that all the above defects are generally not correctable and no subsequent processing or correction can be envisaged in an industrial context that must be profitable. As a consequence, the detection of such defects leads to the discarding of the identified parts. In particular, the above defects cannot be compensated, masked or corrected at the oscillator level, for example by adjusting the mounting length of the hairspring in the oscillator, at the hairspring stud. It should be noted that these defects are not intentionally obtained and therefore cannot be compared or assimilated, and do not include, for example, producing a part (e.g., a silicon hairspring) with intentionally higher or lower overall and / or uniform dimensions to allow for overall modification of stiffness and / or subsequent oxidation to obtain a part with a target stiffness and / or thermal compensation of the part. In other words, it should be noted that these defects are not and do not encompass stiffness defects of the hair spring or hair spring blank, especially if such defects are caused by parts that are intentionally too thick or too thin, so that a part (or all parts of the same silicon wafer) can be modified, for example, as a function of a specific measurement of stiffness.

[0021] According to one embodiment, a vibrational excitation is applied to a hairspring or hairspring blank with a free end (typically the central collet). From a mechanical point of view, the vibrational excitation can be roughly considered as being applied to a mass (located at the center of gravity of the hairspring) connected by a spring (the elastic part of the hairspring) to a reference (the gripping pliers for a single hairspring or the remainder of a substrate or wafer for blanks that are not removed, e.g. made of silicon). The vibrational excitation sets the suspended mass in motion.

[0022] Also, note that if it is determined that a tested part must be separated or discarded due to defects, this can be done on a single part without disassembling anything.

[0023] The method according to the above embodiment therefore makes it possible to test the hairspring blank during production, limiting the risk of contamination or installation errors. Defects can be identified at an advanced stage of production. The method according to the above embodiment also makes it possible to test the finished hairspring, for example to perform a final conformity check.

[0024] Naturally, the frequency range of the spectrum obtained depends on the vibration excitation source as well as on the sensor of the measuring instrument used. The frequency range is therefore linked both to the frequency range of the excitation and to the frequency range to which the instrument for measuring the amplitude of the oscillations (such as a vibrometer) is sensitive. However, the frequency range of the excitation is chosen so as to include at least one resonant frequency of the hairspring or blank to be tested.

[0025] The predetermined resonant frequency that the finished hair spring should have can be a target natural or resonant frequency, or a target natural or resonant frequency range, defined by a tolerance around a target value.

[0026] In the above method, the characteristic of the resonant frequency is a characteristic of the oscillatory response measured over a predetermined frequency range that includes at least one resonant frequency. Such a characteristic is typically determined after processing the raw measurement signal (e.g. measurement of the amplitude, velocity or acceleration of the displacement of a particular point of the hairspring or hairspring blank), which may for example include a Fourier transformation to identify the resonant peak and thus the resonant frequency.

[0027] In particular, the identified characteristics may be the resonant frequency value, the width of the resonant peak, the amplitude of the resonant peak, the presence or absence of the resonant peak, the shape of the resonant peak (such as closely spaced peaks with several slope reversals). the characteristics obtained from this spectrum of vibration frequencies of the hairspring or blank obtained in response to a vibration excitation (resonance frequency, width of the resonance peak, amplitude of the resonance peak, presence or absence of a resonance peak, shape of the resonance peak, etc.); -based on a comparison between the same characteristics (resonant frequency, width of the resonant peak, amplitude of the resonant peak, presence or absence of the resonant peak, shape of the resonant peak, etc.) obtained from a reference spectrum, which may be a spectrum constructed from calibrated parts, test averages and / or simulations or numerical calculations.

[0028] According to one embodiment, step c. comprises at least one step of comparing the spectrum of vibration frequencies of the hairspring or hairspring blank obtained in response to step a. with a reference spectrum so as to determine whether the characteristic identified in step b. is an anomalous characteristic that deviates from the same characteristic of a predetermined expected resonance by a predetermined difference.

[0029] According to the above described embodiment, by measuring the vibration response of the hair spring or the hair spring blank in response to a vibration excitation step of the hair spring or the hair spring blank and detecting anomalous characteristics of the resonant frequencies by comparison with the spectrum of vibration frequencies obtained in a reference spectrum, it is possible to estimate by prediction whether a defect affects the hair spring or the blank.

[0030] According to one embodiment, in step a, the frequency range is applied simultaneously to several hair springs or hair spring blanks. The vibratory excitation can typically be imposed on a wafer supporting, for example, several hundred hair spring blanks still attached to the wafer, thus improving rapidity.

[0031] According to one embodiment, the frequency range is: -Centered on a given resonant frequency, and -predetermined to encompass at least one frequency range having a range of at least 30% of the predetermined resonant frequency, in other words ±15% of the predetermined resonant frequency, for example, if the predetermined resonant frequency is 1 kHz, the frequency range is 850 Hz to 1150 Hz.

[0032] According to one embodiment, the hairspring has at least two predetermined expected resonant frequencies and the frequency range is predetermined to cover the at least two predetermined expected resonant frequencies. By covering or scanning a wide range of frequencies, multiple resonant peaks (or resonant frequencies) can be measured, which can provide greater accuracy.

[0033] According to one embodiment, step a. comprises the use of a source such as a piezoelectric source making it possible to induce or impose an acoustic excitation on a slice of the wafer supporting the hairspring blank, or preferably above or even below the hairspring or hairspring blank to be excited in particular.

[0034] According to one embodiment, the acoustic source can be coupled to an excitation cone selected to excite at least one hairspring or hairspring blank. Preferably, if the wafer supports multiple hairspring blanks, the acoustic source can be coupled to an excitation cone selected to excite at least a portion, preferably all, of the hairspring blanks.

[0035] According to one embodiment, the acoustic source is a predefined frequency range: - have an amplitude sufficient to generate vibrations of the balance spring or of the balance spring blank sufficient to be detected by means for measuring the displacement amplitude, velocity or acceleration of at least one point of the balance spring or of the balance spring blank; and / or - can be selected and / or adjusted to generate a vibration excitation that varies over time to cover a range of frequencies over a duration sufficient to estimate the vibration spectrum of the hairspring or of the hairspring blank.

[0036] According to one embodiment, the defect affecting the hairspring or the hairspring blank is a defect that alters the expected resonance mode, Step c. comprises a step consisting of searching for an anomalous resonance peak between two expected normally adjacent or consecutive resonance peaks. The applicant has realized that defects in the joined coils, shortages of material, impurities linking the coils together, or other defects can cause the hairspring or blank to have resonance modes that are not observed in a compliant hairspring. The method is therefore intended to identify the presence of resonance peaks that are not normally present in the expected frequency spectrum. If a defect causes the emergence of a new resonance mode, the method makes it possible to detect the defect even if the other resonance peaks are correct.

[0037] According to one embodiment, the defect affecting the hairspring or the hairspring blank is a damping or amplification defect of an expected resonant mode, Step c. comprises a step consisting of searching for anomalous resonant peaks having an amplitude that differs from the expected amplitude of the expected resonant peak by at least 30%. The applicant has realized that defects in the joined coils, shortages of material, or impurities linking the coils together can cause the hairspring or blank to have a resonant mode that is significantly different from the resonant mode that can be observed in a compliant hairspring. The method is therefore interested in quantifying the difference between the amplitude of a resonant peak in the obtained frequency spectrum and the amplitude of the same resonant peak in the reference spectrum. Alternatively, the area under the obtained resonant peak can be calculated and compared with the area under the peak in the reference spectrum, and if the area has a difference of, for example, 30%, it is possible to declare a defect.

[0038] According to one embodiment, the method includes a step d. consisting of categorizing the defects identified in step c. For example, if the abnormal characteristic is the presence of an unexpected resonant peak, or if the abnormal characteristic is a strong attenuation of the expected resonant peak, the prediction machine can identify one defect and distinguish it from another in order to categorize the defective part. The category of defects can be, for example, a bonded coil, a material defect, or else an unintended contact between the blank and the rest of the wafer.

[0039] According to one embodiment, step b is based on measuring over time the amplitude or velocity or acceleration of the displacement of at least one point of the hair spring or hair spring blank, preferably at least in part carried out during step a.

[0040] According to one embodiment, step b comprises: - determining the resonant frequency of the hairspring or hairspring blank as a function of the operating or modal deformation of at least one point of the hairspring or hairspring blank, the operating or modal deformation being typically defined by the displacement amplitude or velocity, or acceleration and oscillation direction (outside a particular plane or within a particular plane) as a function of the excitation frequency.

[0041] According to one embodiment, the hairspring or hairspring blank is contained within a base plane, and step b. comprises the steps of: - a step b' of measuring the amplitude, velocity or acceleration of the displacement of at least one point of the hairspring or of the hairspring blank in a direction perpendicular to the base plane, and / or - a step b'' of measuring the amplitude, velocity or acceleration of the displacement of at least one point of the hair spring or of the hair spring blank in a direction contained in the base plane.

[0042] Measuring displacement or velocity in several directions allows for better identification of peaks and resonant frequencies.

[0043] According to one embodiment, - for a first predetermined resonance frequency, only a step b' of measuring the displacement or velocity of at least one point of the hairspring or of the hairspring blank in a direction perpendicular to the base plane is carried out, and / or - for a second predetermined resonance frequency, only step b'' is carried out of measuring the displacement or velocity of at least one point of the hair spring or hair spring blank in a direction contained in the base plane.

[0044] Depending on the resonant frequency, a choice may be made to measure in one direction or another to measure the greatest possible displacement or velocity in order to minimize measurement errors. More specifically, as a function of the geometry of the hairspring or hairspring blank, the mode of vibration (typically the direction of vibration) in response to a vibration excitation may vary.

[0045] According to one embodiment, step b. comprises: determining a resonance peak of the hair spring or of the hair spring blank as a function of the displacement amplitude or velocity of at least one point of the hair spring or of the hair spring blank.

[0046] According to one embodiment, the resonant frequency characteristic is determined based on the width of the resonant peak at the mid-height of its maximum, this processing method making it possible to limit the calculation errors that may be made if based only on determining the frequency location of the peak defined by its maximum.

[0047] According to one embodiment, the prediction machine may be a device that makes it possible to predict, and therefore pre-empt or calculate, the presence of a defect based on one or more measured resonant frequencies, without coupling the hairspring to the balance wheel and without performing any other tests alone than the vibration excitation of the part. The output obtained by the user is information on the presence / nature or suitability / non-suitability of the defect that can be displayed or transmitted to the user of the test method. The prediction machine may be provided as follows: - based on a mathematical model (e.g. a polynomial relating one or more resonant frequencies to specific parameters such as stiffness), using a neural network to receive as input values ​​or graphs obtained from a vibration measurement spectrum to give as output the presence of defects, -Use artificial intelligence to enforce the system. In other words, the predictor machine is not a tuning or self-tuning or feedback loop system for adjusting the resonant frequency in response to a comparison of the measured value with a target value during the tuning process of the oscillator.

[0048] According to one embodiment, the prediction machine performs a classification, for example carried out by a neural network, to predict whether a defect affects the hairspring or the hairspring blank.

[0049] According to one embodiment, the method comprises a preliminary step consisting of taking into account the material of the hairspring or of the hairspring blank and adjusting the maximum amplitude of the vibration excitation and / or the frequency range of the predetermined frequency range as a function of the material of the hairspring or of the hairspring blank.

[0050] According to one embodiment, the frequency range spans a frequency range of 0 Hz to 100 kHz, preferably 0 Hz to 50 kHz, more preferably 0 Hz to 40 kHz, and very preferably 10 kHz to 35 kHz. The applicant has observed that the prediction accuracy is better for peaks or resonance frequencies located in the high frequency range. More specifically, focusing on stiffness, its effect on resonance frequency is stronger in the high frequency range (e.g. 10 kHz to 35 kHz), so the sensitivity and accuracy are better over this particular range.

[0051] According to one embodiment, steps a. and b. are synchronized. Such synchronization gives the possibility to detect phase shifts, or damping, or couplings, taking into account which can improve the accuracy of the prediction, or make it possible to adjust or recalibrate the vibration excitation source.

[0052] According to one embodiment, if step c. determines that the defect affects the hair spring or the hair spring blank, the method comprises at least one step of identifying, or separating, or reworking, or discarding the hair spring or the hair spring blank.

[0053] A second aspect of the invention relates to a method for manufacturing a hair spring having at least one predetermined expected resonant frequency, the method comprising the steps of: A / forming at least one hairspring or hairspring blank having dimensions within predetermined tolerances necessary to obtain a predetermined expected resonant frequency; B / testing the hairspring or a hairspring blank according to the test method of the first aspect.

[0054] According to one embodiment, the method of manufacture comprises the steps of: C / identifying, or separating, or reworking, or discarding the hair spring or hair spring blank formed during step A / in accordance with the defect identification of step c. of the first embodiment.

[0055] According to one embodiment, the hair spring blank is formed on a wafer along with a plurality of other hair spring blanks.

[0056] A third aspect of the invention relates to a method for training a prediction machine implementing step c. of the testing method of the first aspect of the invention, the method comprising the steps of: i—forming the hairspring or hairspring blank, ii- applying to each of the hair springs or to each of the hair spring blanks a vibration excitation which varies over time to cover a predetermined frequency range; iii- determining at least one characteristic of the resonant frequency of each hair spring or each hair spring blank during or in response to the application of the predetermined frequency range; iv' - mounting a plurality of hairsprings or hairspring blanks in an oscillating mechanism having a predetermined inertia so as to measure the free oscillation frequency for each hairspring or hairspring blank; and / or iv'' - modelling, in a simulation tool, a number of hairsprings or hairspring blanks in an oscillating mechanism having a given inertia, so as to calculate the free oscillation frequency for each hairspring or hairspring blank, v - estimating at least one expected resonant frequency of the resonant frequencies determined in step iii and / or the free oscillation frequencies measured in step iv' and / or calculated in step iv'', vi-The prediction machine, for each hairspring or blank: - the characteristics of the resonant frequency determined in step iii-, providing the same characteristics of expected resonant frequency.

[0057] This learning phase can build calibrated reference data for later comparison during the prediction / generation phase with defect search. In particular, learning makes it possible to obtain test data of a reference part or a part that is tested / simulated in parallel, for example, to build a reference spectrum. [Brief description of the drawings]

[0058] Other details of the invention will emerge more clearly from reading the following description, made with reference to the accompanying drawings, in which: [Figure 1] The uncorrected stiffness dispersion curves of the hairspring on three different wafers are shown. [Diagram 2] The centering of the average stiffness on one wafer around the nominal value is shown. [Figure 3A] FIG. 1 is a simplified diagram of a method for manufacturing a mechanical oscillator, here a hairspring, on a wafer. [Figure 3B] FIG. 1 is a simplified diagram of a method for manufacturing a mechanical oscillator, here a hairspring, on a wafer. [Figure 3C] FIG. 1 is a simplified diagram of a method for manufacturing a mechanical oscillator, here a hairspring, on a wafer. [Figure 3D] FIG. 1 is a simplified diagram of a method for manufacturing a mechanical oscillator, here a hairspring, on a wafer. [Figure 3E] FIG. 1 is a simplified diagram of a method for manufacturing a mechanical oscillator, here a hairspring, on a wafer. [Figure 3F] FIG. 1 is a simplified diagram of a method for manufacturing a mechanical oscillator, here a hairspring, on a wafer. [Figure 4] Represents a device that allows evaluation of the torque of a hairspring. [Diagram 5] 1 illustrates a schematic representation of an embodiment of the assessment of the stiffness of a hairspring by vibration analysis. [Figure 6] 1 represents an example of a frequency applied to a silicon wafer supporting a hairspring blank to impose a vibrational excitation. [Figure 7] FIG. 6 shows an example of measuring the amplitude of the displacement of a point of a hairspring blank as a function of an imposed frequency range. [Figure 8] 8 details resonant peaks identified at particular frequencies in FIG. 7; [Figure 9] For a defect-free part, FIG. 8 shows the resonant peaks measured and superimposed for a particular frequency. [Figure 10] 10 illustrates an example of a predictive model built from data extracted from FIG. 9 for defect-free parts. [Figure 11] 1 illustrates a first example of measurements performed on a set of parts, including non-defective and defective parts. [Figure 12] 4 illustrates a second example of measurements performed on non-defective and defective parts. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0059] 3A to 3F are simplified diagrams of a method for manufacturing a mechanical oscillator 100 on a wafer 10. The oscillator is intended in particular to equip the regulating mechanism of a watch component, and according to this example is in the form of a silicon hairspring 100 intended to equip the balance wheel of a mechanical watch movement.

[0060] Wafer 10 is illustrated in FIG. 3A as a silicon on insulator (SOI) wafer and includes a substrate or "handler" 20 having a sacrificial layer 30 of silicon oxide (SiO2) and a layer of single crystal silicon 40. By way of example, substrate 20 may have a thickness of 500 μm, sacrificial layer 30 may have a thickness of 2 μm, and silicon layer 40 may have a thickness of 120 μm. Layer 40 of single crystal silicon may have any crystal orientation.

[0061] The lithography process is illustrated in Figures 3B and 3C. The term "lithography" refers to a series of operations that allow to transfer an image or pattern on or above the wafer 10 backwards. With reference to Figure 3B, in this exemplary embodiment, the layer 40 is covered with a protective layer 50, for example of a polymerizable resin. This layer 50 is typically structured by a photolithography process using an ultraviolet light source and, for example, a photomask (or other type of exposure mask) or a stepper-reticle system. This lithographic structuring forms a pattern for a number of transducers in the layer 50, as illustrated in Figure 3C.

[0062] 3D, the pattern is then machined, in particular etched, to form a number of transducers 100 in layer 40. Etching can be performed by deep reactive ion etching (DRIE) techniques. After etching, the remaining parts of protective layer 50 are subsequently removed.

[0063] In Fig. 3E, the transducer is released from the substrate 20 by locally removing the sacrificial layer 30 or also by etching all or part of the silicon of the substrate or the handler 20. Smoothing of the etched surface (not shown) may also be performed before the release step, for example by a thermal oxidation step followed by a deoxidation step consisting of a wet etch using, for example, hydrofluoric acid (HF).

[0064] In the final step of the manufacturing method of FIG. 3F, the coil 110 of the silicon oscillator 100 is covered with a layer 120 of silicon oxide (SiO2), typically through a thermal oxidation step, in order to produce a temperature-compensated oscillator. The formation of this layer 120, which generally has a thickness of 2 to 5 μm, also influences the final stiffness of the oscillator and must therefore be taken into account during the preceding steps in order to obtain the vibration characteristics of the hairspring that allow to obtain a specific natural frequency of the hairspring-balance wheel pair in a given watch mechanism.

[0065] As mentioned above, in the preceding stages of temperature compensation layer creation, the various resonators formed in the wafer generally have a large variation in geometry among the resonators and therefore in their stiffness, despite the fact that the steps of forming patterns and machining / etching through these patterns are the same for all resonators.

[0066] Moreover, this dispersion in stiffness is even greater between the hairsprings of two etched wafers at different times, even when the same method specifications are used.

[0067] Finally, it should be noted that during manufacturing, more point-like manufacturing defects can occur. For example, during the machining process in FIG. 3D, material can remain between two adjacent coils. In contrast to what is shown in FIG. 3E, it is possible to see parts where material residues are still present between the coils or the substrate. Material bridges can also form between two adjacent coils during oxidation, represented in FIG. 3F. Finally, contamination can also occur by debris or particles attached between the two coils or between the coil and the substrate. All these defects strongly affect the vibration behavior and cannot be corrected by adding or removing material over a set of parts, as known in the prior art.

[0068] The above description relates to a silicon oscillator 100, but glass, ceramic, carbon nanotube or even metal oscillators are also possible. In particular, a conventional steel hairspring can be tested. In this case, the metal hairspring is clamped or sampled with reference to a tool that positions the metal hairspring opposite a radiation source and a displacement measuring device.

[0069] In a known manner, the stiffness measurement of the hairspring can be carried out in a so-called static manner, that is to say by determining its torque without causing the hairspring to oscillate, see for example document EP 3 654 111.

[0070] An alternative to the method described in this last document consists in carrying out the torque measurements using a rheometer such as that marketed by Anton Paar. The device provided for this purpose is illustrated in FIG. 4. Advantageously, it makes it possible to place the hair spring 200 to be evaluated on a mounting 202 and position it in such a way that the hair spring can be fixed with its last coil by a holding member 204. Once the last coil is fixed, the mounting 202 moves away from the hair spring 200, which thus completely releases the hair spring from any elastic constraint. A rheometer head 206 is then positioned facing the collet of the hair spring. It has a counter shape of the non-circular collet, but of reduced size, allowing the rheometer head to engage in the collet with controllable precision without coming into contact with the hair spring. The rheometer head is then rotated in the direction of contraction of the hair spring. When the head comes into contact with the collet, it drives the collet and the rheometer measures the torque exerted by the elastic return of the hairspring over a given angle. However, such measurements remain unitary measurements and involve many risks such as breakage, contamination, etc., and require long processing times.

[0071] The invention proposes in step 3E to determine the resonant frequency of a sample of transducers 100 on the wafer based on at least one characteristic, and whether defects are present on the components, in which case the invention proposes to identify the components in question without disassembly or measurements on a test subassembly, according to a more efficient method than the prior art methods.

[0072] Therefore, the invention proposes determining at least one characteristic of the resonant frequency of a sample of oscillators by vibration measurements and applying predictive methods (e.g. numerical models or classification or categorization methods) in order to link the results of said vibration measurements to the identification of possible defects present.

[0073] For this purpose, the stylistic properties of the hairsprings mounted on the wafer are utilized. During the learning phase, it is possible to arrange a predictive machine by establishing, through analytical and numerical methods, a predictive model that links manufacturing defects (bonds, bridges, contamination, etc.) to certain specifically selected frequencies (eigenfrequencies or resonant frequencies associated with the resonant peak or width at mid-height).

[0074] Once the learning phase is complete (the modes and excitation frequencies to be utilized have been determined), it is possible to move to a prediction phase in which the transducers on the generated wafer are tested and a prediction machine is used to predict whether some parts are defective or not by utilizing a prediction model, and, if appropriate, to identify defects in order, for example, to discard the parts.

[0075] Therefore, once each oscillator has been coupled to the balance wheel of a given watch mechanism, it is possible, if necessary, to incorporate testing methods into the manufacturing process in order to separate defective parts from non-defective parts and parts suitable for obtaining a particular, predetermined natural vibration frequency. Vibrational Excitation

[0076] Measurement of the vibration response of the oscillator makes it possible to deduce at least one characteristic of the resonant frequency, for example the value of the resonant frequency. In detail, it is first necessary to apply a vibration excitation to the wafer. Several options are offered: a. Frequency domain measurements: 1- Use a piezoelectric source (or any other source making it possible to induce or apply an acoustic excitation) on a slice of a wafer, specifically above or below the (preferably) excited hairspring blank 200, which excites with a specific frequency f0 (continuous single frequency excitation). In this alternative, the excitation is maintained. 2-Alternatively, it is also possible to use a piezoelectric source (or any other source allowing to induce or impose an acoustic excitation) on a slice of a wafer, specifically above or below the (preferably) excited hairspring blank 200, exciting with a frequency that varies over time to cover a given frequency range, for example 0-100 kHz, preferably 0-75 kHz, preferably 0-50 kHz, preferably 5 kHz-50 kHz, and preferably 10-35 kHz. The entire frequency range can be scanned or covered in a time interval ranging from a fraction of a second to a few seconds. For example, the range of frequencies in the frequency range can be scanned or covered in less than 0.5 seconds, less than 1 second, or less than 1.5 seconds. In this alternative, the excitation frequency varies continuously. b. Measurement in the time domain: An excitation hammer (or any other source capable of inducing a pulsed acoustic excitation) is used on a slice of the wafer, specifically above or below the hairspring to be excited (preferably), to give the shortest possible acoustic pulse (multi-frequency pulse excitation). In this alternative, the excitation is temporary and not sustained.

[0077] Furthermore, the measurements can be carried out by following a specific sampling, for example according to a sampling range of 4, 2 or 1 Hz. More specifically, the resolution for processing the acquired data, for example according to a Fourier transformation, depends directly on the duration of this acquisition.

[0078] Furthermore, if the frequency range extends, for example, up to 50 kHz, a sampling frequency of the signal of at least 100 kHz can be chosen.

[0079] Generally, it may also be provided to finally vary the direction of excitation, in other words the direction of the motion imposed by the source (the vibrations may be imposed in one or more axial directions and this or these directions may be varied over time). In case a wafer comprising multiple transducers is excited, the direction of vibration may be adjusted towards one or the other of the transducers depending on the displacement amplitude measurements described below.

[0080] Finally, it may be provided to couple an acoustic source to a divergence cone directed towards the transducers to be excited, and in turn tune the acoustic source to emit an excitation signal having a sufficient amplitude to impose vibrational excitation of one or more transducers and to be accurately detected and measured by a selected measurement device. Measurement of displacement amplitude, velocity or acceleration

[0081] During excitation, the amplitude (relative to the excitation source) and phase of the oscillations in the three directions X, Y (in-plane) and Z (out-of-plane) of the specifically excited hairspring are recorded via suitable measuring means. Without being limiting, the following possible measuring means can be cited: - Optical methods using interferometry: a.3D Doppler effect (laser Doppler vibrometer), b. Holography, - Strobe optical methods, -High resolution first order chromatic confocal profilometry, -Optical reflectance measurements, a. Vibration analysis by beam deflection with a multi-dial detector or camera; b. Analysis by time-correlated TCSPC analysis; -Acoustic method by Doppler ultrasonography.

[0082] 5 shows a schematic representation of a silicon wafer 25 on which a number of hair spring blanks 200 have been formed. A vibration excitation source 400 is coupled to the wafer 25 in order to impose a vibration excitation. As a result, each hair spring blank 200 vibrates and a laser vibrometer 300, here focused on a point on the right-hand hair spring blank 200, can measure the vibration amplitude of the measurement point over time. Displacements can be measured in a direction perpendicular to the plane of the wafer 25, but also in one or more directions contained in the plane of the wafer 25.

[0083] Once a particular point has been investigated, the laser vibrometer 300 can be moved onto another measurement point of the hair spring blank 200 or to another hair spring blank 200 of the wafer 25. Of course, the hair spring blank 200 can alternatively be displaced relative to the laser vibrometer.

[0084] 6 represents an exemplary vibration excitation over time. In the given example, the excitation frequency varies over time between 0 Hz and 50 kHz, and a series of rising edges can be imposed, each rising edge being separated by a rest period without excitation. For each measurement point on the hairspring blank 200, multiple rising fronts (between 2 rising fronts and 60 rising fronts) can be imposed, each lasting, for example, 0.5 seconds to 2 seconds. Selecting the reference point to be measured

[0085] With regard to the displacement amplitude measurements, during the learning phase, a step may be provided consisting of identifying points of the oscillator at which the vibration response is significant. More specifically, in the case of a hairspring subjected to vibrations, especially if the frequency varies over time, the vibration response causes nodes to appear on the hairspring, in other words at specific points of the hairspring at which the displacement amplitude is low or zero. If the displacement measurements are carried out at points of the hairspring known to be nodes at one or more specific frequencies, the identification of the characteristics of the resonant frequencies will be adversely affected.

[0086] It is therefore advantageous to provide a preliminary step of measuring the displacement at a number of predetermined points of the hairspring, for example at least 10 predetermined points, preferably at least 20 predetermined points, very preferably at least 30 predetermined points. The predetermined points may be selected to be located on an orthonormal coordinate system XY in the plane of the hairspring.

[0087] At the end of the preliminary amplitude measurement step on the given points, a resonant frequency can be identified for each measurement point, and then a step of selecting reference points for the measurement of the displacement amplitude during excitation indicates that no nodes of these resonant frequencies are present. In other words, the identified nodes have at least one resonant frequency, a displacement amplitude of zero or less than a first threshold peak value, and these points forming nodes are away from the reference points considered for the subsequent measurements. It can also be noted that the reference points differ as a function of the position of the hairspring blank 200 on the wafer 25.

[0088] Typically, it is contemplated that at least two reference points are selected, and preferably at least four reference points are selected. If the transducer has a radius Ra and is fixed or embedded on the wafer by its externally pinned end, preferably four reference points may be selected and positioned: Within the first zone (e.g., on the central bead) below -0.20 × Ra, or Within the second zone between -0.05 × Ra and 0.30 × Ra (for example, on the second coil starting from the whisker head), or Within the third zone between -0.35 × Ra and 0.65 × Ra (for example, on the coil located in the middle of the hairspring), or -In the fourth zone from 0.65×Ra to 0.85×Ra (for example, on a coil located three-quarters of the way along the hairspring). Therefore, the reference point is separated from the part fixed on the wafer and necessarily has a significant capacitance to the oscillatory displacement, ensuring better accuracy of the displacement measurement.

[0089] Additionally, the displacement can also be measured relative to a point on the body of the wafer and / or a point on the excitation source, for example to identify or measure phase shifts or vibration damping, or even vibration coupling or resonance resulting from the wafer. These complementary measurements can ensure that the identified peaks are in fact peaks of the hairspring only. The displacement amplitude measurements and vibration excitation can also be synchronized.

[0090] Alternatively, it is possible to measure only the displacements / movements / vibrations at specific points, preferably located on zones of the part that do not deform. In particular, it may be provided to aim at measurements on points of the collet of the hairspring or the hairspring blank. More specifically, the collet can be considered as not deformable during vibration excitation, all points of the collet having similar displacements / movements / vibrations. As a result, small errors in the location of the measurement points on the collet have little effect on the final result. Furthermore, the selection of specific measurement points on the part makes it possible to identify and select a specific frequency range for making the stiffness prediction.

[0091] An embodiment in which multiple parts are tested in succession while still attached to the substrate or tool includes the following: - capturing an image of the part to be tested; - analyzing the images, for example to identify each part type and / or each part position, - selecting one or more points to be measured for each part and / or selecting a vibrational excitation spectrum to be imposed for each part and / or each selected point, For each part to be tested, it may include a step of positioning the substrate or tool supporting the part to be tested in the vibration excitation and measurement device. According to this embodiment, in the case of a wafer still carrying the hairspring blank, the excitation and measurement can be automated: - one or more images of the wafer are taken; - an automatic image analysis is carried out in order to know at least the XY position of each part (part type or model recognition may also be performed), - specific pre-established measurement points are identified or selected (e.g. on the eyeball) as a function of the position and / or the recognized part type; specific excitation cycles can also be selected as a function of the part type or specific points; For example, using a tool with a table capable of carrying the wafer and moving in XY, each hair spring blank is automatically and successively positioned opposite an excitation source and measuring device to be tested by aiming at the correct measuring point and applying the correct excitation specifications.

[0092] According to an embodiment, a step may be provided consisting of providing a specific orientation to the excitation direction and / or the measurement direction as a function of the measurement point selected on the part to be tested and / or as a function of the excitation frequency and / or as a function of the model of the part to be tested. For this purpose, the excitation direction (or the axial direction of the excitation source) may be selected to be perpendicular to the part to be tested in order to maximize the displacement perpendicular to the plane formed by the stationary part. The excitation direction (or the axial direction of the excitation source) may be selected to be inclined with respect to the part to be tested in order to maximize the displacement included in the plane formed by the stationary part. With regard to the measurement, the measurement direction (or the axial direction of the laser beam of the measuring device) may be selected to be perpendicular to the part to be tested in order to maximize the measurement accuracy of the displacement perpendicular to the plane formed by the stationary part. The measurement direction (or the axial direction of the laser beam of the measuring device) may be selected to be inclined with respect to the part to be tested in order to maximize the measurement accuracy of the displacement included in the plane formed by the stationary part.

[0093] According to embodiments in which several components are attached to a substrate such as a wafer, sampling can be performed by removing one or more components in order to test them alone, and by introducing specific excitation frequencies to be applied and / or specific measurement points to be used and / or specific ranges of the vibration spectrum to be considered. In other words, this pre-sampling makes it possible to test the single components under good conditions (measurement errors and interferences are limited) in order to select the best test conditions for the components that remain integrated with the substrate. Vibration characteristics determination

[0094] Depending on the range preselected for the excitation, there are several scenarios: a. Measurement in the frequency domain 1-An alternative example that maintains excitation: i. Integrating the amplitude and oscillation phase over time long enough to have good spectral resolution at the excitation frequency f0; ii. offset the oscillation frequency by delta f to excite at frequency f0+Δf and repeat integration step i; iii. Reconstruct the amplitude and oscillation phase spectrum as a function of excitation frequency (possibly with multiple peaks at multiple frequencies). 2-An alternative example with excitation whose frequency varies over time: i. recording vibration amplitude and phase versus time over the course of a frequency scan of a range of frequencies; ii. repeating step i- at ​​least once, preferably at least three times; iii. Reconstruct the amplitude and oscillation phase spectrum as a function of excitation frequency (possibly with multiple peaks at multiple frequencies). b. Time domain measurements: i. Record the displacement of the coil over time in X, Y, and Z for a duration long enough to obtain a sufficiently representative signal, for example a few seconds. ii. One can choose to record the signal in order to create a reference signal to be compared with other signals measured on other components. One can also choose to perform a Fourier transform type of processing of the signal in order to identify resonant frequencies in the recorded signal.

[0095] As a result, at least one resonant peak can be identified for each excited oscillator, and it is proposed to determine the resonant frequency not based on the tip of the resonant peak, in other words the maximum amplitude, but rather on the area of ​​the curve located between 25% and 75% of the maximum amplitude value of the resonant peak, for example on its width at mid-height. More specifically, this processing method, focusing on the part of the curve between 25% and 75% of the maximum amplitude value of the resonant peak, makes it possible to limit the errors due to approximation calculations for reconstructing the singular points of the maximum amplitude and the tip part of the resonant peak. The area of ​​the curve located between 25% and 75% of the maximum amplitude value of the resonant peak has better accuracy than the part larger than 75% (typically the peak), providing better accuracy with regard to the exact resonant frequency determined. For example, it is possible to take the middle of the segment connecting two points at the mid-height of the resonant peak in order to determine the resonant frequency associated with the peak in question.

[0096] FIG. 7 represents an example of a vibration spectrum of a point of the hairspring blank 200 of FIG. 5, without defects and reconstructed from measurements of the displacement amplitude of the considered measurement point in response to the vibration excitation of FIG. 6 from 10 kHz to 15 kHz. The presence of three amplitude peaks at approximately 11 kHz, 12.3 kHz and 13.7 kHz can be noted. Although not shown, when the vibration excitation scans the frequency range from 0 Hz to 50 kHz, it is typically possible to identify 10 to 30 amplitude peaks. Each amplitude peak has a resonant frequency, the maximum amplitude of which varies strongly.

[0097] FIG. 8 details a process that can be performed on an amplitude peak of a non-defective part, for example an amplitude peak at 11 kHz. The objective is to find the resonant frequency and give it as accurate a value as possible. Instead of basing this process on the maximum value of the peak, the applicant has realized that better accuracy can be achieved by determining the length of the segment that connects the ascending and descending parts of the curve at the mid-height of the peak. The resonant frequency is typically the mid-value of this segment. However, an interpolation can be performed on points in the vicinity of the resonant peak to improve the accuracy and to shift the selected point on the segment that is not the mid-point, especially if the actual position of the resonant peak is shifted, for example, due to the selected sampling frequency.

[0098] FIG. 9 represents the amplitude peaks constructed for approximately ten tested and defect-free hairspring blanks 200 for an example of an amplitude peak at approximately 10 kHz. It can be noted that for each hairspring blank, the frequency location of the amplitude peaks varies (approximately 9.8 kHz to 10.02 kHz) and the maximum displacement amplitude varies in a ratio of approximately 1 to 5. Since the tips of the amplitude peaks are not actually symmetrical, it may be prudent to determine the resonant frequency based on the width of the peak at mid-height. The width of the peak at mid-height can also be used to determine the damping and compare this damping to a reference value.

[0099] In these tests of FIG. 9 it was possible to deduce the following resonant frequencies: [Table 1] Determination of the stiffness and / or actual dimensions of the bars of the tested transducer

[0100] During the learning phase, it is necessary to provide data on the actual stiffness and / or dimensions of the bars of the tested oscillator in order to establish a predictive model capable of receiving as input the vibration characteristics (typically the resonant frequencies) and giving as output stiffness and / or dimensional corrections. For this purpose, the natural frequency of the hairspring-balance wheel system can be virtually measured in an environment similar to that of the particular watch mechanism.

[0101] Two alternatives can be implemented. According to a first alternative, it is possible to couple a given balance wheel onto the oscillator still attached to the wafer and measure the natural frequency of oscillation of the oscillator-balance wheel pair in order to compare the natural frequency with the expected natural frequency and, inter alia, to calculate the actual stiffness or the actual dimensions based on the above equations 1-3. According to a second alternative, the manufacture of the oscillator to be tested can be completed in order to individually attach or couple the oscillator to the balance wheel in order to now again measure the natural frequency of oscillation of the oscillator-balance wheel pair.

[0102] In the two alternatives above, an intermediate step may be included to determine the stiffness of each oscillator and then the actual dimensions of the bars of the oscillator being tested. In other words, by analyzing the free oscillations of the hairspring coupled to a reference balance wheel, it is possible to determine the natural or resonant frequency and then the stiffness or dimensions of the bars of the oscillator. In this approach, a laser aimed at the arms of the balance wheel or the hairspring carrier records the passage times of the arms of the balance wheel or the arms of the locating pin. From this the period is then estimated, then the frequency and finally the stiffness. The collected data is essentially a point cloud of passage times.

[0103] More specifically, to evaluate the stiffness of the hairspring on the wafer, several solutions are proposed, in particular those described in Traite de construction horlogere (2011) by M. Vermot et al., pages 178-179. For example, a dynamic evaluation can be carried out by coupling the hairspring to a reference balance wheel whose inertia is known. Measuring the frequency of the assembly allows to accurately estimate the stiffness of the hairspring. This evaluation can be carried out on the wafer or by removing the hairspring from the wafer. The above references and prior art provide details about this method.

[0104] Similarly, the stiffness can also be estimated from the measurement of the reaction torque on the hairspring using a rheometer. The required signal represents the change over time in the torque as a function of the amplitude. Analysis of the slope of this curve at low amplitudes (linear part) makes it possible to estimate the stiffness and then the dimensions of the bar of the oscillator. The dimensions of the bar of the hairspring can then be determined.

[0105] On the other hand, the natural and / or resonant frequencies and / or stiffness can be inferred by simulation for each resonator tested on the wafer. For this purpose, the resonator can be reconstructed by numerical modeling, its vibration response to an imposed spectrum can be simulated by numerical calculations, and dimensional measurements can be made for each resonator tested in order to find the stiffness of the resonator.

[0106] High-resolution 3D X-ray tomography techniques allow a point cloud to be extracted, giving the 3D material density of the hairspring and, using appropriate image reconstruction, a mapping of the hairspring's sections. These different types of data make it possible to estimate the dimensions of the bars and, by geometrical methods, to infer the stiffness of the hairspring.

[0107] Another approach consists of analysing the forced oscillations of the hairspring on a reference balance wheel with the escapement. As mentioned above, laser measurements (point cloud) of the passage times of the arms of the balance wheel allow the frequency to be measured and the stiffness to be deduced from the frequency. An alternative is possible based on acoustic acquisition (Witschi type microphone) recording the impulses of the various operating phases of the escapement / anchor system. The data measured are either point clouds of the passage times of the arms of the balance wheel or the change over time in the level of sound pressure. These types of experimental data make it possible to deduce the period, then the frequency, then the stiffness and finally the dimensions of the bars of the oscillator.

[0108] Returning to the tests discussed above in FIG. 9, stiffness measurements were performed by coupling each hairspring blank 200 to a reference balance wheel, and it was possible to estimate the following stiffnesses: [Table 2] Establishing a predictive model

[0109] To be able to detect defects, firstly reference data must be established or constructed, for example reference spectra. During a learning phase, oscillation amplitude measurements are performed on the physical oscillator and the resonant frequencies are identified. Then, to be able to link the resonant frequencies measured on the oscillator to the stiffness and / or dimensional (thickness) corrections made, correlation phases must be provided on which a predictive model is constructed.

[0110] The above operations (vibration measurement, identification of the resonance peak, determination of the bandwidth at mid-height and its mean or modified value, stiffness and / or dimensions of the bar) make it possible to provide a database in which the position of the hairspring on the wafer, the spectrum or oscillation period or the bandwidth at mid-height and its mean or modified value can be related to the effective stiffness and / or dimensions of the bar of hairspring. As seen above, this database can be built from numerical simulations on a hairspring finite element model. These simulations can generate a spectrum or a reference oscillation period related to the stiffness. This database can also be supplemented by experimental measurements by measuring the vibration spectrum, the oscillation period and the position of the hairspring on the wafer and their associated stiffness. One of the advantages of this approach lies in the fact that the learning database is strengthened over the course of the test as the training database is strengthened. This makes it possible to have an adaptive model depending on the wafer and the hairspring, which can contribute to reducing the standard deviation in stiffness on the wafer.

[0111] This database can be used to build predictive models, providing multiple solutions.

[0112] A numerical model, for example a polynomial model, can be constructed to calculate the actual thickness, dimensional correction or actual stiffness as a function of the resonant frequency value.

[0113] It is also possible to perform categorization by performing a k-means partition of the input data (results of vibration measurements, typically the frequency of the resonant peaks) and the output data (stiffness and / or dimensions of the bars of the transducer) and linking them together to establish a match.

[0114] It may also be provided to process the images of the resonance peaks using a neural network, such as a perceptron, to perform a classification according to the stiffness or dimensions of the bar, the classes being defined by value increments.

[0115] In summary, the learning phase includes a testing phase (excitation of the transducer with measurement of vibration characteristics to reconstruct the vibration spectrum and identify the resonant frequencies). A measurement phase of the stiffness and / or dimensions of the transducer's bars is also performed. Once input data (resonant frequencies) and output data (stiffness and / or dimensions of the bars) for significant samples are available, a predictive model building phase can be performed.

[0116] Returning to the example discussed and described in relation to FIG. 9, the data collected is as follows: [Table 3] Linear regression modeling was performed on the above data for the first six lines and the following relationships could be established: R=0.0015F-10.894 Where: R is 10 -7 Stiffness in N.mm. F is the resonant frequency in Hz. Thus, stiffness can be predicted and compared to the actual stiffness measured as shown in the table below, for the first six lines this is the data used to build or train a linear regression, for the last four lines it is just a prediction. [Table 4] A maximum error of 4.40% can be measured and FIG. 10 shows the linear regression line for the values ​​from the first six lines.

[0117] It can be seen that it is advantageous to verify that the established prediction model has good sensitivity, in other words, for two different input values, the model gives two distinct output values. The applicant observed that the sensitivity of the prediction model was not the same for all resonance peaks. In particular, with reference to the prediction equation established and represented in FIG. 10, the leading coefficient is between 0.0015 and 10. -7N.mm / Hz. On the other hand, the applicant has observed that the leading coefficient may be larger for high resonance frequencies, providing a better prediction sensitivity to predict clear stiffness or dimensional correction values ​​even on the basis of close resonance frequency values. In order to verify / confirm that during the learning phase it is preferable to take into account and select specific resonance peaks at high frequencies (e.g. above 5 kHz), it is then advantageous to provide a step of comparing the prediction sensitivities p to predict, as precisely as possible, stiffness and / or dimensional corrections as a function of the measured vibration response.

[0118] On the other hand, the applicant has also observed that even if the resonant frequencies are close, the resonant modes (in particular the deformation and / or displacement modes of the oscillator) may differ significantly, which may also affect the sensitivity of the prediction of the stiffness and / or dimensional compensation. During the learning phase, it is advantageous to provide a step of comparing the sensitivity of the predictions in order to select to subsequently consider such a resonant frequency rather than another one in order to predict, as accurately as possible, the stiffness and / or dimensional compensation as a function of the vibration response.

[0119] From the above remarks on considering the sensitivity of predictions, it may be provided that during the learning phase, the various identified resonant peaks are classified according to their predicted sensitivity to stiffness and / or dimensional corrections. It may then be provided to define an excitation frequency range (applied during the pure prediction phase) to include at least one or more peaks or resonant frequencies that give the best sensitivity. Thus, imposing a variable vibration excitation over such a predetermined frequency range ensures that accurate predictions can be made for the identified resonant peaks, or for each of the identified resonant peaks that cross or reinforce each other.

[0120] In general, the learning phase makes it possible to select either resonant peaks at high frequencies and / or resonant peaks corresponding to specific resonant modes that make it possible to predict accurate and reliable values; a frequency range is predetermined to include at least one resonant peak, preferably multiple resonant peaks, so as to be able to make either a single prediction as precise as possible, or multiple predictions (one per resonant peak deemed relevant), and then to perform cross-checking, averaging or adjustment of the predicted values.

[0121] For example, a final value can be calculated by predicting multiple stiffness or dimensional correction values ​​based on multiple peaks or resonant frequencies, and then performing a weighted average by assigning a weight to each predicted value based on the predicted values, each weight being determined as a function of the sensitivity identified for each corresponding peak or resonant frequency.

[0122] Alternatively and preferably, it is possible to have just one model that takes all the peaks or resonant frequencies as input and returns the stiffness or dimensional corrections, and a learning phase of the model is used to precisely calculate the weightings for the input peaks or resonant frequencies. Predicted Phase

[0123] Once the learning phase is over, it is possible to proceed to a prediction phase, for example during a method for testing an oscillator. Typically, the testing method may be carried out on a hairspring blank produced on a wafer and still attached to this wafer, to infer the stiffness and / or dimensions of a sample hairspring bar in order to determine whether dimensional corrections should be applied or not.

[0124] Once the model is trained, the testing procedure implemented may be as follows. 1) Identifying the location of the hairspring on the wafer and making a vibration measurement of the spectrum or oscillation period (as described above); 2) predicting the stiffness and / or dimensions of the bars of the hairspring by application of a predictive model; 3) Determine whether a dimensional correction is necessary to reach a natural frequency or target stiffness.

[0125] During the test method it is also possible to quantify the exact correction to be applied, so that the manufacturing method can additionally include the above tests. 1) Knowing the effective stiffness of the hairspring, estimated according to the model and the target stiffness and / or target dimensions of the bar, and applying the necessary correction application. Repeat steps 1) and 2) of the test method to test the hairspring stiffness / dimension and verify that the target values ​​have been reached within the tolerance thresholds, or repeat these steps and dimensional corrections until the stiffness / dimension predicted by the model reaches the target values. sampling

[0126] It is known that several hundred hairsprings are produced on a wafer and that the dimensions of the produced hairspring bars may vary according to the area of ​​the wafer. If a stiffness evaluation could be carried out on a single hairspring, it is in fact carried out on a sample of hairsprings distributed on the wafer.

[0127] Starting from the evaluation carried out, if the results obtained vary from hairspring to hairspring, a correction can be carried out in a uniform manner for the whole wafer or differently for each area. It is thus possible to reduce the standard deviation of the distribution of the stiffness. Furthermore, if the stiffness is known for all hairsprings by application of a model, an optimal correction can be determined that allows to reduce the overall distribution.

[0128] It may also be envisaged to proceed to the evaluation of all the hairsprings of the wafer, in particular with vibration evaluation, as this can be done very quickly and allow the method to be automated.

[0129] Although the above examples are given mainly on the basis of the manufacture of hairsprings with a set bar dimension larger than that of the target bar, it may also be provided to produce hairsprings with initial bars with initial dimensions smaller than that of the target bar. The correction step consists, for example, in adding material as described in the aforementioned document EP 3 181 939.

[0130] The method consisting in identifying the resonant frequency by imposing a vibration excitation only on the hairspring blank makes it possible to obtain measurement data quickly, without the need to carry out any work, for example to mount the balance wheel, while limiting the measurement errors since only the hairspring blank is tested (there are no errors that can be linked to the balance wheel, such as its mass, its mounting position, etc.).

[0131] Applicant has also observed that, alternatively, the prediction step can be a method for detecting gross defects on components such as coils that are bonded or bridged together or on a substrate. Figure 11, for example, shows a frequency spectrum measured on a wafer blank, including a corrected portion (whose resonant peak is surrounded by a rectangle with a dash-dotted blending line and marked "OK") and inaccurate portions marked P1, P2, P3, P4, P5, and P6.

[0132] More specifically, during testing, each frequency spectrum obtained in response to a vibration excitation is connected by traceability to a specific component, and inspection of each of the components from which the resonant peaks P1-P6 occur is found to have a defect. Consequentially, by comparing each of these frequency spectra with the reference spectra previously established during the learning phase, it becomes possible to observe significant deviations or divergences, revealing defects that would cause the component in question to be scrapped.

[0133] In this example, the method includes a step of searching for and identifying excess resonant peaks with respect to the expected frequency spectrum. Such excess peaks can be detected if they exceed the expected noise level by at least 30%. In other words, the presence of a resonant peak between two normally adjacent or consecutive resonant peaks forms an anomalous characteristic of the resonant frequency and makes it possible to identify a hairspring or blank with a coupling coil defect. Since such defects cannot be easily corrected, the part is identified and, as a rule, discarded.

[0134] Figure 12 shows another example or type of anomalous characteristic with respect to the reference spectrum. More specifically, among the curves with a single resonant peak (marked "OK") at the expected resonant frequency at about 24.1 kHz, the presence of a curve shown in bold can be seen with a "double peak" resonance. In this case, to detect a defect, the method must look for two apexes or three slope change points in the portion of the curve located above the mid-height or mid-point of the recorded maximum (instead of a single maximum or a single slope change for a non-defective portion).

[0135] Therefore, by searching for peaks in the reference spectrum that are not normally present, as in Figure 11, or resonant peaks that are significantly different (have some change in slope or maximum, or even a significantly different amplitude) from the expected peaks, as in Figure 12, parts with defects can be identified, including bonded coils, bridges with the substrate, material inhomogeneities, residual deformations in the hairspring, microcracks, or even accidental contamination. Each frequency spectrum obtained can be assigned or linked to the part being tested with traceability, so that the problematic part can be identified and the part can be separated or discarded.

Claims

1. 1. A method for testing a hair spring or a hair spring blank configured to form a hair spring, the hair spring having to have at least one predetermined expected resonant frequency, the testing method comprising the following steps: a. applying a vibrational excitation to the hair spring or hair spring blank, the vibration excitation varying over time to cover a predetermined frequency range; b. identifying at least one characteristic of a resonant frequency of the hair spring or hair spring blank, such as a resonant peak, during or in response to the vibrational excitation over the predetermined frequency range; c) subjecting the resonant frequency characteristic determined in step b to a prediction machine in order to determine whether the hair spring or hair spring blank is affected by a defect.

2. 2. The method of claim 1, wherein step c. comprises at least one step of comparing the spectrum of vibration frequencies of the hairspring or hairspring blank with a reference spectrum so as to determine whether the characteristic identified in step b. is an anomalous characteristic that deviates from the same characteristic of the predetermined expected resonant frequency by a predetermined difference.

3. 3. The method of claim 1, wherein the hairspring has at least two predetermined expected resonant frequencies, and the frequency range is predetermined to cover the at least two predetermined expected resonant frequencies.

4. the defect affecting the hairspring or hairspring blank is a defect that changes an expected resonance mode, 4. The method of claim 1, wherein step c. comprises searching for an anomalous resonance peak between two expected normally adjacent or consecutive resonance peaks.

5. the defect affecting the hairspring or hairspring blank is a damping or amplifying defect of the expected resonance mode, 5. The method of claim 1, wherein step c. comprises searching for anomalous resonant peaks having an amplitude that differs from an expected amplitude of the expected resonant peak by at least 30%.

6. 6. A testing method according to any one of claims 1 to 5, wherein step b. is based on a measurement over time of the displacement amplitude or velocity or acceleration of at least one point of the hairspring or hairspring blank, preferably carried out at least in part during step a.

7. The hairspring or the hairspring blank is contained within a base plane, and step b. - a step b' of measuring the displacement amplitude or the velocity or the acceleration of at least one point of said hairspring or hairspring blank in a direction perpendicular to said base plane, and / or The method according to any one of the preceding claims, comprising a step b'' of measuring the displacement amplitude or the velocity or the acceleration of at least one point of the hair spring or hair spring blank in a direction contained in the base plane.

8. Step b. is A test method according to claim 6 or 7, comprising a step of identifying a resonance peak of the hair spring or hair spring blank as a function of the displacement amplitude or velocity of at least one point of the hair spring or hair spring blank.

9. 9. The method of claim 8, wherein the resonant frequency is characterized based on a width of the resonant peak at a mid-height of a maximum of the resonant peak.

10. Test method according to any one of claims 1 to 9, wherein the prediction machine performs a classification, for example carried out by a neural network, to predict whether a defect affects the hair spring or the hair spring blank or not.

11. 11. Test method according to any one of the preceding claims, comprising a preliminary step consisting of taking into account the material of the hair spring or hair spring blank and adjusting the maximum amplitude of the vibration excitation and / or the frequency range of the predetermined frequency range as a function of the material of the hair spring or hair spring blank.

12. A test method according to any one of the preceding claims, wherein the frequency range spans a frequency range of 0 Hz to 100 kHz, preferably 0 Hz to 50 kHz, more preferably 0 Hz to 40 kHz, and very preferably 10 kHz to 35 kHz.

13. 13. The method according to any one of claims 1 to 12, wherein if step c. determines that a defect affects the hair spring or the hair spring blank, the method comprises at least one of the steps of identifying, or separating, or reworking, or discarding the hair spring or the hair spring blank.

14. 1. A method for manufacturing a hair spring having at least one predetermined expected resonant frequency, comprising the steps of: A / forming at least one hairspring or hairspring blank having dimensions within predetermined tolerances necessary to obtain said predetermined expected resonant frequency; B / A method comprising a step consisting of testing the hair spring or the hair spring blank according to the test method according to any one of claims 1 to 13.

15. C / the manufacturing method according to claim 14, comprising a step of identifying, or separating, or reworking, or discarding the hair spring or hair spring blank formed during step A / in accordance with the defect identification in step c. according to claim 1.

16. 16. The method of claim 14 or 15, wherein the hairspring blank is formed on a wafer together with a plurality of other hairspring blanks.

17. A learning method for a predictive machine for carrying out step c. of the testing method according to any one of claims 1 to 13, comprising: i—forming the hairspring or hairspring blank, ii- applying to each of said hair springs or each of said hair spring blanks a vibrational excitation which varies over time to cover a predetermined frequency range; iii- determining at least one characteristic of the resonant frequency of each hairspring or each hairspring blank during application of said predetermined frequency range; iv' - placing a number of hairsprings or hairspring blanks in an oscillating mechanism having a given inertia so as to measure the free oscillation frequency for each hairspring or hairspring blank; and / or iv'' - modelling, in a simulation tool, a number of hairsprings or hairspring blanks in an oscillating mechanism with a given inertia, so as to calculate the free oscillation frequency for each hairspring or hairspring blank, v - estimating at least one expected resonant frequency of said resonant frequency determined in step iii and / or of the free oscillation frequency measured in step iv' and / or calculated in step iv'', vi--saying said prediction machine, for each hairspring or blank: -step iii-, the characteristic of the resonant frequency determined in a learning method comprising the steps of providing the same characteristics of said expected resonant frequency.

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