Method and device for measuring interfaces of an optical element

Abstract

The invention relates to a method (100) for measuring interfaces of an optical element to be measured based on signals measured by an interferometry system, the method being characterised in that it comprises the following steps: a) receiving (102) a plurality of measured peaks relating to beams reflected by the optical element when it is illuminated by an optical beam emitted by the interferometry system, b) receiving (104) a model comprising a plurality of modelled positions, each modelled position corresponding to one interface of the optical element to be measured encountered by the optical beam, c) automatically associating (106), among the measured peaks, so-called useful peaks, with corresponding modelled positions, d) determining (108) one or more thicknesses of the optical element based on the so-called useful peaks associated with these modelled positions.

Description

DESCRIPTION TITLE: Method and device for measuring interfaces of an optical element Technical field.

[0001] The present invention relates to a method for measuring interfaces of an optical element, in particular one that is part of a plurality of substantially identical optical elements. It also relates to a measuring device implementing such a method. Prior art

[0002] During the manufacture of optical elements, such as lenses or objectives with multiple lenses, it may be necessary to control or measure the thicknesses or positions of component elements, or the spaces between component elements, along a measurement axis such as the optical axis of an optical element.

[0003] For this purpose, low-coherence interferometry techniques are commonly used. A measurement optical beam from a broad-spectrum optical source is propagated through the surfaces of the optical element. The reflections of the beam from these surfaces are collected and analyzed by making them interfere with each other and / or with a reference beam to determine the differences in optical path lengths between interfering beams, and from this, to deduce the positions and / or distances between corresponding surfaces or interfaces. This allows, for example, the determination of lens thicknesses, distances between lenses, and / or lens positions in an optical assembly. The interferences result in peaks that include spurious peaks, called ghost peaks, which are inserted between the interface peaks, corresponding to a surface of the optical element.Indeed, the reflection signals on the interfaces to be observed are likely to be reflected several times between the interfaces, causing additional returns, which are a kind of echo, producing the ghost peaks in the measured signal to be analyzed.

[0004] It is possible to manually select the so-called useful peaks, that is, via a user-controlled software interface. However, this solution is time-consuming, unreliable, and difficult to implement.

[0005] The aim of the present invention is to resolve at least one of the aforementioned drawbacks. Description of the invention

[0006] At least one of these goals is achieved with a method for measuring the characteristics of an optical element to be measured from signals measured by an interferometry system; the method is characterized in that it comprises the following steps: a) receive a plurality of measured peaks relating to beams reflected by the optical element when it is illuminated by an optical beam emitted by the interferometry system, b) receive a model comprising a plurality of modeled positions, each modeled position corresponding to an interface of the optical element to be measured encountered by the optical beam, c) automatically associate, among the measured peaks, so-called useful peaks, with corresponding modeled positions, d) determine one or more thicknesses of the optical element from the so-called useful peaks associated with these modeled positions.

[0007] The process allows for the automatic detection of useful peaks and thus distinguishes parasitic peaks, due to noise and measurement echoes, from peaks corresponding to an interface measurement.

[0008] According to one embodiment, step c) may include the following steps: cl) extract, for each measured peak, a measured position, c2) determine distances between each measured position and each modeled position, c3) for each of the distances, determine a deviation score, said deviation score decreasing as the distance increases in absolute value, c4) select useful peaks as corresponding to the measured positions exhibiting the highest score in relation to the corresponding modeled position.

[0009] Advantageously, the distance can be, for example, the absolute value of the difference or the gap between two positions.

[0010] According to a particular embodiment, the process may include a step to add a tolerance to each measured position, or to each modeled position.

[0011] Advantageously, step c2) can be performed using the following formula: D[c2(i,j) ] = pos_meas[i] — pos_Mdl[j] with pos_meas[ï] being the measured position of index i between 1 and I the number of measured positions, pos_Mdl[j] being the modeled position of index j between 1 and J the number of positions of the provided model and [c2(i,y)] being the distance for the candidate pair (i,y).

[0012] According to another embodiment, step c2) can be carried out by the following formula: D[c2(i, j, k)] = pos_meas[i] — pos_Mdl[j] — e[k] * TOL[j] with pos_meas[i] being the measured position with index i between 1 and I the number of measured positions, pos_Mdl[j] being the modeled position with index j between 1 and J the number of positions of the provided model, D[c2(i,j)] being the distance for the candidate pair (i,j), TOL[j] being the tolerance of the modeled position and e[k] being a weighting factor, and k a weighting index between 1 and K.

[0013] Thus, it is possible to take into account the errors related to the measurement process of the measured peaks. For example, the tolerance sequence e[k] can vary as follows: for example e[l] = -1; e[2] = 0; e[3] = +1, or e[l] = -1.2; e[2] = -0.6; e[3] = 0; e[4] = +0.6; e[5] = +1.2.

[0014] Tolerances on modeled and / or measured positions may depend on tolerances on the thicknesses of the model layers.

[0015] The process may further include, following step c2), a step to reorder the distances determined in step c2). In particular, the process then generates an ordered, for example, ascending, list of distances D[c2(i,j)] or distances D[c2(i,j,k)], which are renumbered as D[c], with indices c from 1 to C. The number C may correspond to the maximum number of different possible offsets between the measured and modeled positions in order to align the model peaks with the measured peaks. Preferably, for each c, the indices i[c], j[c], (k[c]) at the origin of index c may be stored.

[0016] According to one embodiment, the gap score can be determined in step c3) by the following formula: SC(c) = P(pos meas[ic] - pos Mdl[jc]- D[c]), for (ic,jc) in 1, 1 x I with SC(c) being the index deviation score c corresponding to this index c2(ic,jc) after its ordering, and D[c] the distance determined at step c2) and P being a function which has a maximum of 1 when its argument tends towards 0 and a minimum of 0 when its argument is greater than a given threshold, the function P varying inversely to the absolute value of its argument.

[0017] For example, the gap score can be between 0 and 1. Thus, the gap score can be a maximum of 1 and a minimum of 0; and can be maximum when the value of pos meas [ ic ] - pos Md i[ jc ] -£>[c] is equal to 0. The gap score can decrease when the value of pos meas [ ici - pos Mdl [ jci - D[c] is close to 0. Finally, the gap score can be 0 when pos meas [ ic ] - pos Md i[j C] ~ D[c] is large or very large, for example greater than a threshold. In particular, the function P can be a Gaussian function.

[0018] Furthermore, the P-function can depend on other parameters. In particular, the P-function can depend on the amplitudes of the measured peaks. In this case, this allows the deviation score to be higher when the amplitude of the measured peak is greater, which helps to choose a useful peak over another potentially similar one that is due to measurement aberrations such as a ghost or spurious peak. This allows the selection of the most probable peak to associate with the model.

[0019] According to one embodiment, step c4) may include the following substeps: c4-l) compare the gap scores and select one or more indices c0 giving the highest gap score(s), or greater than a threshold; and for each index c0 select the indices cl neighboring or close to c0 whose associated indices il and jl correspond to associations between measured peak and modeled peak complementary to i0 and j0, increasing the number of associated pairs (i, j), c4-2) determine a relevance criterion for each index c0 selected in the previous step, such as the number of pairs selected and an overall score on the selected pairs, and c4-3) select the useful peaks as the measured peaks associated with the index(es) c0 for which the relevance criterion is satisfied.

[0020] These sub-steps allow us to consider cases where an optimized number of modeled peaks are matched with the measured peaks.

[0021] In particular, step d) may include the following steps: dl) determining so-called optical distances calculated as the differences in the positions of each of the previously selected useful peaks, d2) divide optical distances by optical refractive indices in order to obtain so-called physical thicknesses.

[0022] Preferably, the model in step b) can correspond to a model of the thicknesses of the layers to be measured. For example, the model can be decomposed into corresponding interface positions.

[0023] In the context of the present invention, an "optical element to be measured" can refer to any type of object having optical properties, intended, for example, to be inserted into an optical beam, to shape an optical beam, and / or to produce an image. It can refer, for example a unique optical component such as a lens or a plate or a substrate exhibiting, for example, surface patterns, an assembly of lenses and / or other optical components, such as an imaging lens, camera lens, or optical beam shaping device.

[0024] An optical element to be measured may consist of, or include, refractive or diffractive elements such as lenses. The distances determined by the method may correspond to the thicknesses of the lenses.

[0025] According to the invention, the optical element to be measured can be a stack of optical elements, such as for example an optical lens comprising several optical elements stacked according to a stacking direction.

[0026] According to the invention, the optical element to be measured can be a lens array, or a microlens array.

[0027] According to another aspect of the invention, a device is proposed for measuring the interfaces of an optical element to be measured from signals measured by interferometry, comprising: a measurement channel configured to produce a measurement beam at a determined position relative to the element's field of view and comprising an optical sensor configured to acquire signals reflected by the optical element, and a processing module configured to process the signals acquired by the optical sensor, the processing module being configured to implement the process as described above.

[0028] For example, the optical element comprises a stack of optical lenses. Description of the figures and methods of implementation

[0029] Other advantages and features of the invention will become apparent upon reading the detailed description of implementations and embodiments, which are by no means limiting, and the following attached drawings: [Fig. 1] schematically represents examples of objects or optical elements to be measured that can be used in the present invention. [Fig. 2] illustrates a schematic representation of an example of a measured signal used in an example of the method according to the invention. [Fig. 3] illustrates an example of a modeled peak pattern. [Fig. 4] illustrates an example of an embodiment of the method according to the invention, [Fig. 5] illustrates an example of a gap score determination function implemented by the method of Figure 4.

[0030] These embodiments are not exhaustive; in particular, variants of the invention may be considered that comprise only a selection of features described or illustrated hereafter, isolated from the other described or illustrated features (even if this selection is isolated within a sentence including these other features), provided that this selection of features is sufficient to confer a technical advantage or to differentiate the invention from the prior art. This selection includes at least one preferably functional feature without structural details, and / or with only a portion of the structural details if this portion alone is sufficient to confer a technical advantage or to differentiate the invention from the prior art.

[0031] Figure 1 illustrates examples of objects or optical elements to be measured 5. These are objectives each consisting of several lenses or microlenses 35 mounted in a barrel 36 and stacked along a common optical axis 23.

[0032] The purpose of method 100 in Figure 4 is to determine characteristics of the optical element 5, for example the thicknesses of the lenses or microlenses 35.

[0033] The method 100 includes a first step 102 of measuring a measurement signal 51, shown in Figure 2. For example, the measurement signal 51 can be obtained by a low-coherence interferometry system based on a double Michelson interferometer using single-mode optical fibers. The interferometry system may include: - a light source capable of emitting a measurement beam to illuminate the optical element 5, and - an optical delay line to produce a reference beam.

[0034] The retro-reflections from the optical element 5 are collected and analyzed by interfering with each other and / or with the reference beam, which produces the measurement signal 51.

[0035] The measurement signal 51 in Figure 2 is an example of an interferometric measurement for element 5. The microlenses 35 have respective thicknesses d1, d2, d3 and d4 and are separated by spacings 11, 12 and 13. The continuous curve illustrates a measurement signal 51 with useful peaks 52 corresponding to interferogram envelopes, and representative of reflections of the measurement beam on interfaces of the microlenses of the optical element 5.

[0036] In the example in Figure 2, the respective positions of the expected microlens surfaces, as identified on the measurement signal 51, are indicated by crosses, corresponding to the peaks 52. However, the measurement signal 51 also includes so-called ghost peaks 53 which are intercalated between the useful peaks 52.

[0037] To identify the real interfaces, represented by the useful peaks 52, and distinguish them from the ghost peaks 53, the method 100 includes steps 104 and 106 consisting of selecting the useful peaks 52 of the measurement signal 51 using a known model of the microlens stacking 35. An example of model 200 is shown in Figure 3 where the symbols dl' to d4' and el' to e3' are respectively associated by the method with the intervals dl to d4 and el to e3 of Figure 2.

[0038] In step 104, the model 200 corresponding to the optical element 5 is provided. The model 200 comprises lines 202, where each line corresponds to the position of an interface or surface of one of the microlenses 35 of the optical element 5. This correspondence means that the position can be shifted by a certain distance (positive or negative), and that since the thicknesses of the measured elements are generally different from the thicknesses of the model, there is no simple correspondence with, for example, a single shift for all the lines of the model and the lines of the measurement.

[0039] Model 200 depends on the composition and arrangement of the optical element 5. For example, process 100 includes a communication step with a database containing several models and a step of selecting the model corresponding to the optical element to be measured.

[0040] The process then includes a step 106 of associating the peaks of the model with corresponding useful peaks in the measurement signal. To this end, step 106 comprises the following substeps: a) extract, for each peak of the measurement signal, a measured position and, for each peak of the model, a modeled position, b) determine distances between each measured position and each modeled position according to the following formula: D[c2(i, j)] = pos_meas[i] — pos_Mdl[j] with pos_meas[i] being the measured position with index i between 1 and I the number of measured positions, pos_Mdl[j] being the modeled position with index j between 1 and J the number of positions in the provided model, and [c2(i,j)] being the distance for the candidate pair (i, j). The number J corresponds in this case to the number of lines 202. The number I corresponds to all the peaks represented by a cross and a plus sign in the measured signal 51. c) reorganize the previously determined distances in an ordered manner. At this stage, an ordered list of distances D[c2(i,j)] is generated, for example in ascending order, which are renumbered as D[c], with indices c between 1 and C. For each c, the indices i[c], j[c] at the origin of the index c are stored. d) For each distance, determine a gap score, for the plurality of measured and modeled positions, according to the following formula: SC(c) = P(pos meas[ic] - pos Mdl[jc]- D[c]), for (ic,jc) in 1, 1 x 1, / with SC(c) being the slack score of index c corresponding to this index c2(ic,jc) after its ordering, and D[c] the distance determined at step c2) and P being a function that has a maximum of 1 when its argument tends towards 0 and a minimum of 0 when its argument is greater than a given threshold, the function P varying inversely with the absolute value of its argument. For example, the slack score can be between 0 and 1. Thus, the slack score can be at most 1 and at least 0; and can be maximum when the value of pos meas [ ic ] - pos Md i[ jc ] ~ D[c] is equal to 0. The gap score can increase when the value of pos meas [ ici - pos Mdl [ jci -D[c] tends towards 0 (through positive values, or through negative values). Finally, the gap score can be 0 when pos meas [ ic ] - pos Md i[ jc] -£>[c] is large or very large, for example greater than a threshold. Figure 5 shows an example of the function P, which is a Gaussian function. The argument x corresponds to the value of pos meas [ ic ] - pos Md i[ jc ] - Furthermore, the function α can depend on other parameters. In particular, the function P can also depend on the amplitudes of the measured peaks. In this case, this allows the deviation score to be higher when the amplitude of the measured peak is greater, which helps to choose a useful peak over another potentially similar one that is due to measurement aberrations such as a ghost or spurious peak. This allows the selection of the most probable peak to associate with the model. e) compare the gap scores and select one or more indices c0 giving the highest gap scores; and for each index c0 select the neighboring or close indices cl whose associated indices il and jl correspond to associations between measured peak and modeled peak complementary to i0 and j0, increasing the number of associated (i,j) pairs, f) determine a relevance criterion for each index c0 selected in the previous step, such as the number of pairs selected and an overall score on the selected pairs, This overall score can be the product of the scores for each selected pair. g) Select the useful peaks as those measured peaks associated with the c0 index(es) for which the relevance criterion is satisfied.

[0041] Alternatively, in substep v), the distances can be determined taking into account measurement tolerances. The distances can be calculated using the following formula: D[c2(i,j, k) ] = pos_meas[i] — pos_Mdl[j] — e[k] * TOL[j] with pos_meas[i] being the measured position of index i between 1 and I the number of measured positions, pos_Mdl[j] being the modeled position of index j between 1 and J the number of positions of the provided model, D[c2(i,j)] being the distance for the candidate pair (i ), TOL[j] being the tolerance of the modeled position and e[k] being a weighting factor, and k a weighting index between 1 and K.

[0042] Thus, it is possible to take into account errors related to the measurement process of the measured peaks, and especially production deviations which produce a dispersion of the peak positions from the measurements, relative to the model. For example, the tolerance sequence e[k] can vary as follows: for example e

[0001] = -1; e[2] = 0; e[3] = +1, or even e[1] = -1.2; e[2] = -0.6; e[3] = 0; e[4] = +0.6; e[5] = +1.2.

[0043] Tolerances on modeled and / or measured positions may depend on tolerances on the thicknesses of the model layers.

[0044] The process 100 then includes a step 108 of extracting the thicknesses (dl-d4) and spacings (el-e3) from the selected useful peaks. For this, so-called optical distances are calculated as the differences between the positions of each of the previously selected useful peaks. These distances are divided by the optical refractive indices of the microlenses to obtain the thicknesses (dl-d4) and spacings (el-e3).

[0045] Of course, the invention is not limited to the examples just described and many modifications can be made to these examples without departing from the scope of the invention.

Claims

DEMANDS 1. A method (100) for measuring the characteristics of an optical element (5) to be measured from signals measured by an interferometry system, the method is characterized in that it comprises the following steps: a) receive (102) a plurality of measured peaks relating to beams reflected by the optical element when it is illuminated by an optical beam emitted by the interferometry system, b) receive (104) a model (200) comprising a plurality of modeled positions, each modeled position corresponding to an interface of the optical element to be measured encountered by the optical beam, c) automatically associate (106), among the measured peaks, so-called useful peaks, with corresponding modeled positions, d) determine (108) one or more thicknesses of the optical element from the so-called useful peaks associated with these modeled positions.

2. A method (100) according to the preceding claim, wherein step c) comprises the following steps: cl) extract, for each measured peak, a measured position, c2) determine distances between each measured position and each modeled position, c3) For each of the distances, determine a gap score, said gap score decreasing as the distance increases in absolute value, c4) select useful peaks as corresponding to measured positions exhibiting the highest score in relation to the corresponding modeled position.

3. Method (100) according to the preceding claim, comprising a step for adding a tolerance to each measured position, or to each modeled position.

4. A method (100) according to any one of claims 2 or 3, wherein step c2) is carried out by the following formula: D[c2(i, f) ] = pos_meas[i] — pos_Mdl[j] with pos_meas[ï] being the measured position of index i between 1 and / the number of measured positions, pos_Mdl[j] being the modeled position of index j between 1 and J the number of positions of the provided model and D[c2(i,j)] being the distance for the candidate pair (i,j).

5. Method (100) according to claim 3, wherein step c2) is carried out by the following formula: D[c2(i,j,k) ] = pos_meas[i] — pos_Mdl[j] — e[k] * TOL\f] with pos_meas[i] being the measured position of index i between 1 and J the number of measured positions, pos_Mdl[j] being the modeled position of index j between 1 and J the number of positions of the provided model, D[c2(i,j)] being the distance for the candidate pair (i,j), TOL[j] being the tolerance of the modeled position and e[k] being a weighting factor, and k a weighting index between 1 and K.

6. Method (100) according to any one of claims 2 to 5, wherein the method comprises, following step c2), a step for rearranging the distances determined in step c2) in an orderly manner.

7. Method (100) according to claims 4 and 6, wherein the deviation score is determined in step c3) by the following formula: S C(c) = p(pos meas[ici - pos Md i[j C ] - D [c]), for (ic,jc) in l, I x 1, J with SC(c) being the index deviation score c corresponding to this index c2(ic,jc) after its ordering, and D[c] the distance determined at step c2) and P being a function which has a maximum of 1 when its argument tends towards 0 and a minimum of 0 when its argument is greater than a given threshold, the function P varying inversely to the absolute value of its argument.

8. Method (100) according to the preceding claim, wherein the function P further depends on the amplitudes of the measured peaks.

9. A method (100) according to any one of the preceding claims, wherein step c4) comprises the following substeps: c4-1) compare the gap scores and select the index(es) c0 giving the highest gap score(s); and for each index c0 select neighboring or close indices cl whose associated indices il and jl correspond to associations between measured peak and modeled peak complementary to i0 and j0, increasing the number of associated (i, j) pairs; c4-2) determine a relevance criterion for each index c0 selected in the previous step, such as the number of pairs selected and an overall score on the selected pairs, and c4-3) select the useful peaks as the measured peaks associated with the index(es) c0 for which the relevance criterion is satisfied.

10. A method (100) according to any one of the preceding claims, wherein step (d) comprises the following steps: d1) determine so-called optical distances calculated as the differences in the positions of each of the previously selected useful peaks, d2) divide the optical distances by optical refractive indices in order to obtain so-called physical thicknesses.

11. Method (100) according to any one of the preceding claims, wherein in step b) the model corresponds to a thickness model of the layers to be measured, which model is decomposed into corresponding interface positions.

12. Method (100) according to any one of the preceding claims taken in combination with claim 3, wherein the tolerances on the modeled and / or measured positions depend on tolerances on the thicknesses of the model layers.

13. Device for measuring interfaces of an optical element (5) to be measured from signals measured by interferometry, comprising a measurement channel configured to produce a measurement beam at a determined position relative to a field of view of the optical element and comprising an optical sensor configured to acquire signals reflected by the optical element, a processing module configured to process the signals acquired by the optical sensor, the processing module being configured to implement the process (100) according to one of the preceding claims.

14. Device according to the preceding claim, wherein the optical element (5) comprises a stack of optical lenses.

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