Optical lens assembly quality detection method and device based on ultrasonic signal analysis

Abstract

The application relates to the technical field of optical lens detection, in particular to an optical lens assembly quality detection method and device based on ultrasonic signal analysis, the optical lens assembly quality detection method based on ultrasonic signal analysis comprising the following steps: emitting ultrasonic waves to an optical lens and acquiring echo signals; dividing the echo signals into multiple frequency range sections; calculating characteristic values of each frequency range section; when the characteristic value is greater than a set threshold value, determining that the optical lens has defects, and determining the defect type according to the current frequency range. According to the technical scheme, ultrasonic waves are used for detection, a complex detection scene does not need to be built, there is no radiation, the detection operation is simpler, the cost is lower, and in the detection process, manual intervention is not needed, the misjudgment caused by manual intervention is avoided or reduced, the quality of the lens assembly can be quickly and efficiently judged, and the defects can be located when there is a quality problem.

Description

Technical Field

[0001] This application relates to the field of optical lens inspection technology, and in particular to an optical lens assembly quality inspection method and apparatus based on ultrasonic signal analysis. Background Technology

[0002] Optical lenses are widely used in products such as microscope objectives, eyepieces, mobile phone camera modules, automotive camera modules, projection lenses, and astronomical telescopes. With the increasing demands for lens manufacturing quality, the assembly quality of lenses needs to be guaranteed, and inspection efficiency needs to be improved. Optical lenses are generally assembled from several groups of optical glass, resin, and mechanical structural components (pressure rings, spacers). Lens assembly is a complex and delicate process involving multiple stages, and good installation between the various components is necessary to ensure product quality.

[0003] After assembly, the following problems are inevitable for lenses: air bubbles at the bonding interface, delamination, missing or discontinuous adhesive layers, etc.; cracks, impurities, and air bubbles inside the lens; gaps, insufficient pressure, stress concentration, loose pressure rings, and loose threaded connections between the lens and the mount. To address these issues, product quality can be detected during lens assembly using optical transfer function (MTF) and X-ray inspection, or after lens assembly, through manual screening and observation, or by inspecting the optical imaging quality.

[0004] However, the optical transfer function (OTF) method requires a complex optical measurement setup and can only evaluate the overall lens quality, resulting in high costs. It cannot pinpoint the cause of poor lens quality, only assess image quality, and cannot locate assembly defects. X-ray inspection is costly and carries radiation risks, making it unsuitable for rapid deployment on production lines. It also cannot effectively separate noise from high-frequency defect signals, especially in multi-layered bonded structures where sensitivity is insufficient. Manual screening can, to some extent, identify quality issues such as bubbles, cracks, or looseness, but manual interpretation relies on experience and has low repeatability, easily leading to missed detections. Summary of the Invention

[0005] To address at least the above-mentioned technical problems in the prior art, this application provides a method and apparatus for inspecting the assembly quality of optical lenses based on ultrasonic signal analysis.

[0006] This application provides a method for inspecting the assembly quality of an optical lens based on ultrasonic signal analysis. The method includes: emitting ultrasonic waves to the optical lens and acquiring echo signals; dividing the echo signals into multiple frequency range segments; calculating a characteristic value for each frequency range segment; determining that the optical lens has a defect when the characteristic value is greater than a set threshold, and determining the defect type according to the current frequency range.

[0007] In some embodiments, before the step of dividing the echo signal into multiple frequency range segments after acquiring the echo signal, the method further includes: performing gain compensation on the echo signal; the gain compensation calculation formula is:

[0008] G(t) = G g +K×t

[0009] in, G(t) The total gain (dB) is the value at time t (μs). G g The initial fixed gain (dB) K The attenuation compensation slope (dB / μs) t The transit time (μs) of the ultrasound in the material.

[0010] In some embodiments, the method of dividing the echo signal into multiple frequency range segments includes: the formula for calculating the number J of frequency range segments is:

[0011] J=log2( )+1;

[0012] in, The center frequency of the ultrasonic signal. The sampling frequency of the ultrasonic signal.

[0013] In some embodiments, the method for calculating characteristic values ​​for each of the frequency range segments includes: the characteristic values ​​including kurtosis, energy entropy, peak factor, or energy ratio.

[0014] In some embodiments, the kurtosis value KU The calculation formula is:

[0015]

[0016] in, This represents the sample size for the current frequency range. For i observations, The sample mean. It is the sample standard deviation.

[0017] In some embodiments, the energy entropy E is calculated using the following formula:

[0018]

[0019] in, This represents the sample size for the current frequency range. Let be i observations, and ε be a set value.

[0020] In some embodiments, the peak factor C is calculated using the following formula:

[0021]

[0022]

[0023] in, This represents the sample size for the current frequency range. This represents the root mean square value of the echo signal within the current frequency range.

[0024] In some embodiments, the energy ratio R is calculated using the following formula:

[0025]

[0026] in, The total energy across multiple frequency ranges. , This represents the total energy within the current frequency range.

[0027]

[0028]

[0029] in, For the energy of multiple frequency ranges other than the current frequency range, For the coefficients of multiple frequency ranges other than the current frequency range, The coefficients for the current frequency range. This represents the number of the k-th sample point in each frequency range segment, where J is the number of frequency range segments and j is the sequence number of the current frequency range segment.

[0030] In some embodiments, the method further includes: establishing a good product baseline database, the good product baseline database including a threshold range of feature values, the threshold range of feature values ​​being the set threshold.

[0031] This application also provides an optical lens assembly quality inspection device based on ultrasonic signal analysis, including a motion platform, a scanning probe, and a control device. The motion platform and the scanning probe are respectively connected to the control device. The motion platform is used to carry the optical lens under test and drive the optical lens under test to move along a set path. The scanning probe is used to emit ultrasonic waves to the optical lens under test and receive echo signals. The control device realizes the inspection of the optical lens under test based on the above-mentioned optical lens assembly quality inspection method based on ultrasonic signal analysis.

[0032] This application provides a method and apparatus for inspecting the assembly quality of optical lenses based on ultrasonic signal analysis. During inspection, an ultrasonic signal is emitted to the optical lens under test, and the echo signal is acquired. The echo signal is processed and analyzed, and characteristic values ​​are calculated for different frequency ranges. These characteristic values ​​are compared, and if the calculated characteristic value exceeds a set threshold, a defect in the optical lens can be determined, and the type of defect can be identified. This technical solution utilizes ultrasonic signals for inspection, eliminating the need for complex inspection setups, eliminating radiation, simplifying the inspection operation, reducing costs, and eliminating the need for human intervention. This avoids / reduces false positives caused by human intervention, enabling rapid and efficient assessment of the quality of the assembled lens, and allowing for the location of defects when quality problems exist. Attached Figure Description

[0033] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of this application are illustrated in the drawings by way of example and not limitation, in which:

[0034] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0035] Figure 1 A flowchart of an optical lens assembly quality inspection method based on ultrasonic signal analysis provided in an embodiment of this application;

[0036] Figure 2 A flowchart illustrating the determination of the threshold range of feature values ​​in the optical lens assembly quality inspection method based on ultrasonic signal analysis provided in this application embodiment;

[0037] Figure 3 This is a flowchart illustrating the process of determining defect classification in an optical lens assembly quality inspection method based on ultrasonic signal analysis, as provided in an embodiment of this application. Detailed Implementation

[0038] To make the objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0039] This application provides a method for inspecting the assembly quality of optical lenses based on ultrasonic signal analysis. During the inspection process, an ultrasonic signal is emitted to the optical lens under test. The support structure of the optical lens under test is described below. Then, the echo signal returned by the optical lens under test is acquired. By analyzing the echo signal, it is determined whether there are defects in the optical lens under test, the type of defects is determined, and the location of the defects can be located.

[0040] The detection method for optical lenses provided in the embodiments of this application will be described in detail below.

[0041] like Figure 1 As shown in the figure, this application provides a method for inspecting the assembly quality of an optical lens based on ultrasonic signal analysis. The method includes the following steps:

[0042] Step S10: The ultrasonic generator, in conjunction with the testing equipment, emits ultrasonic signals point by point to the optical lens under test and acquires the echo signals.

[0043] For example, the optical lens to be tested is placed on the testing device, which can move along a set path. The ultrasonic generator is pressed against the surface of the optical lens to be tested, and the ultrasonic generator emits ultrasonic signals to the optical lens to be tested point by point.

[0044] The acquired echo signal is amplified by an echo signal amplifier, and then converted into a digital signal by an A / D signal acquisition device. Data processing of the echo signal can complete the optical lens inspection.

[0045] Step S20: Perform gain compensation and filtering on the echo signal.

[0046] In this embodiment of the application, by processing the echo signal, the cost quality of the optical lens under test can be finally determined. Before performing data processing on the echo signal after it is acquired, the echo signal is first subjected to gain compensation and filtering to obtain a high-quality echo signal.

[0047] Gain refers to the degree to which an ultrasonic instrument amplifies the received echo signal, in order to address the issue of missed detections caused by energy attenuation when ultrasonic waves propagate through different materials.

[0048] For example, the formula for calculating gain compensation is:

[0049] G(t) = G g +K×t

[0050] in, G(t) The total gain (dB) is the value at time t (μs). G g The initial fixed gain (dB)K The attenuation compensation slope (dB / μs) t This represents the transit time (μs) of the ultrasound wave in the material. Specifically:

[0051] G g The initial value can be a certain percentage of the saturation amplitude of the echo signal; by measuring the surface of a good product (a defect-free optical lens), the signal gain is then adjusted so that the echo signal reaches a certain percentage of the saturation amplitude, for example, 80%.

[0052] Attenuation compensation slope K It can be calculated using the following formula:

[0053]

[0054] in, The material attenuation coefficient (dB / mm / MHz) The speed of sound (m / s) The ultrasonic frequency (MHz);

[0055] Crossing Time It can be calculated using the following formula:

[0056]

[0057] in, To detect thickness, The speed of sound.

[0058] By performing gain compensation processing on the echo signal, weak signals can be enhanced, ensuring the comprehensiveness of the analysis in subsequent data processing stages and avoiding / reducing missed detections. After completing the gain compensation processing, the echo signal is further filtered using a digital filter. The filtered echo signal can effectively suppress noise, thereby improving detection sensitivity. In this embodiment, the filtering method of the digital filter is not limited.

[0059] Step S30: Divide the echo signal into multiple frequency range segments. The optical lens under test has various defects, such as internal cracks, impurities, and bubbles in the lens; gaps, pressure issues, stress concentrations, loose pressure rings, and loose threaded connections between the lens and the mount. The echo signal will differ depending on the specific defect; therefore, the echo signal can be segmented according to the frequency range of the defect.

[0060] For example, when it is determined that the echo signal fed back by the optical lens under test has a defect in the frequency band of 25MHz to 50MHz, the specific defect can be identified as surface scratches or coating peeling; or, for example, when it is determined that the echo signal fed back by the optical lens under test has a defect in the frequency band of 12.5MHz to 25MHz, the specific defect can be identified as bubbles, delamination / delamination, or missing or discontinuous adhesive layer at the bonding interface.

[0061] The frequency range values ​​for each frequency range segment, as well as the corresponding specific defect types, are obtained through verification. For example, a frequency range may correspond to multiple defect types. When a defect exists in that frequency range, it can be matched with the corresponding defect type, but it is not possible to pinpoint which specific defect it is. If the frequency range is further refined, i.e., the frequency range segment is narrowed, a more precise comparison of defect types can be obtained.

[0062] In this embodiment of the application, the formula for calculating the number of frequency range segments J is as follows:

[0063] J=log2( +1;

[0064] in, The center frequency of the ultrasonic signal. The sampling frequency of the ultrasonic signal.

[0065] by =5MHz, Taking 50MS / s as an example, J = ≈4. Therefore, the echo signal can be divided into 4 frequency ranges.

[0066] Step S40: Calculate the characteristic value for each frequency range segment;

[0067] For example, eigenvalues ​​include kurtosis, energy entropy, peak factor, or energy ratio, where the type of eigenvalue for each frequency range is determined based on the defect type.

[0068] The characteristic values ​​are obtained through calculation and used as the basis for subsequent judgment on whether defects exist.

[0069] For example, kurtosis value KU The calculation formula is:

[0070]

[0071] in, This represents the sample size for the current frequency range. For i observations, The sample mean. It is the sample standard deviation.

[0072] For example, the formula for calculating energy entropy E is:

[0073]

[0074] in, This represents the sample size for the current frequency range. Let be i observations, and ε be a set value, which is a small value used to avoid mathematical errors caused by taking the logarithm of zero.

[0075] For example, the formula for calculating the peak factor C is:

[0076]

[0077]

[0078] in, This represents the sample size for the current frequency range. This represents the root mean square value of the echo signal within the current frequency range.

[0079] For example, the formula for calculating the energy ratio R is:

[0080]

[0081] in, The total energy across multiple frequency ranges. , This represents the total energy within the current frequency range.

[0082]

[0083]

[0084] in, For the energy of multiple frequency ranges other than the current frequency range, For the coefficients of multiple frequency ranges other than the current frequency range, The coefficients for the current frequency range. This represents the number of the k-th sample point in each frequency range segment, where J is the number of frequency range segments and j is the sequence number of the current frequency range segment.

[0085] Step S50: When the feature value is greater than the set threshold, it is determined that there is a defect in the optical lens, and the defect type is determined according to the current frequency range.

[0086] In this embodiment of the application, after determining that the feature value exceeds a set threshold, the corresponding defect type can be determined based on the current frequency range (refer to step S60). For example, when the kurtosis value... KUWhen the set threshold is exceeded, it can be determined that there is a defect in the frequency band of 25MHz to 50MHz. The specific defect type corresponding to this frequency band is surface scratches or coating peeling. Through detection, it can be found that the optical lens under test has surface scratches or coating peeling problems.

[0087] In this embodiment of the application, the optical lens assembly quality inspection method based on ultrasonic signal analysis further includes step S60: comparing and determining the defect classification. In the comparison step, it is necessary to obtain feature value information from the good product baseline database.

[0088] The baseline database for good products includes threshold ranges for feature values, which are set thresholds. That is, after calculating the actual feature value, this feature value is compared with the feature values ​​of good products (defect-free optical lenses). If the feature value is within the threshold range, it indicates that the actual feature value is normal or has no obvious abnormalities, and it can be determined that there are no problems or defects in that frequency range. Conversely, if the actual feature value is greater than the threshold range, it indicates that the actual feature value is abnormal, and a defect is determined. Furthermore, the defect type can be further determined based on that frequency range.

[0089] After the comparison is completed, the defect type of the optical lens under test can be determined, and a quality scoring report can be generated based on the test results. In this embodiment of the application, the form and content of the quality scoring report are not limited; for example, it may include defect type information, the number of defect types, etc.

[0090] The following example illustrates the optical lens assembly quality inspection method based on ultrasonic signal analysis provided in the embodiments of this application.

[0091] After gain compensation and filtering of the echo signal, the test results of the optical lens under test are determined by four-level wavelet decomposition.

[0092] For example, =5MHz, =50MS / s, then J=≈4. Therefore, the echo signal can be divided into 4 frequency ranges:

[0093] The frequency range of the first layer CD1, f4~f5, is: The defect types characterized are surface scratches and coating peeling;

[0094] The frequency range of the second layer CD2, f3~f4, is: The defect types characterized are bubbles at the adhesive interface, delamination (delamination), missing or discontinuous adhesive layers;

[0095] The frequency range f2~f3 of the third layer CD3 is: The defect type characterized is internal cracks in the mirror surface;

[0096] The frequency range of the profile coefficients is f1~f2: The defect types characterized are gaps between the lens and the lens mount / pressure ring, false pressure, and stress concentration areas.

[0097] After determining the four frequency ranges, based on the method in step S40 above, the characteristic values ​​of each layer are calculated, including the kurtosis value KUr of the first layer CD1, the energy entropy Er of the second layer CD2, the peak factor Cr of the third layer CD3, and the energy ratio Rr of the fourth layer CA4.

[0098] After calculating the actual feature values, compare them with the threshold range of the feature values.

[0099] like Figure 2 As shown, m groups of good products were used in the experiment, and the feature values ​​KU, E, C, and R were obtained respectively. The average value and threshold range of the m groups of sample values ​​were calculated. The threshold range can be expressed as:

[0100] KU_th

[0101] E_th ± E

[0102] C_th= ±

[0103] R_th=

[0104] in, Indicates the nth time, Indicates the total number of times. The standard deviation of kurtosis measured for 10 good products. E The standard deviation of the energy entropy measured for 10 good products. The standard deviation of the peak factor from 10 good product measurements. This represents the standard deviation of the energy ratio from 10 good product measurements. The calculation method is as follows:

[0105]

[0106] in, This represents the i-th data point. This represents the mean of the data. This indicates the total number of sampling points.

[0107] If KUr > KU_th, mark the surface defect; otherwise, there is no surface defect.

[0108] When Er > E_th, mark the adhesive layer bubble defect; otherwise, there is no adhesive layer bubble defect.

[0109] When Cr > C_th, mark the internal lens crack defect; otherwise, there is no lens crack.

[0110] When Rr > R_th, mark virtual pressure and stress concentration defects; otherwise, there are no virtual pressure and stress concentration defects.

[0111] For example, in the good product baseline database, the value of KU_th is 3.5, the value of E_th is 4.2, the value of C_th is 5.3, and the value of R_th is 80%, while the calculated actual feature values ​​are KUr=2.9, Er=4.28, Cr=4.2863, and Rr=19%.

[0112] Where: KUr>KU_th; Er>E_th; Cr <C_th;Rr<R_th;

[0113] The comparison shows that both KUr and Er exceed the threshold range of the feature values. Therefore, the reference... Figure 3 As shown, it can be determined that the optical lens under test has surface defects and adhesive layer bubbles.

[0114] This application provides an optical lens assembly quality inspection device based on ultrasonic signal analysis, including a motion platform, a scanning probe, and a control device. The motion platform and the scanning probe are respectively connected to the control device. The motion platform is used to carry the optical lens under test and drive the optical lens under test to move along a set path. The scanning probe is used to emit ultrasonic waves to the optical lens under test and receive echo signals. The control device realizes the inspection of the optical lens under test based on the above-mentioned optical lens assembly quality inspection method based on ultrasonic signal analysis.

[0115] The motion platform includes a three-dimensional moving module and a circumferential moving module, which can move in the X, Y, Z and Rz directions. The optical lens under test is fixedly mounted on the motion platform so that the optical lens under test can meet the position requirements in the X, Y, Z and Rz directions. During the test, multiple points of the optical lens under test need to be detected. The relative position of the optical lens under test and the scanning probe (ultrasonic generator) can be adjusted using the motion platform.

[0116] The scanning probe can also be configured to be movable, moving synchronously with the motion platform to acquire echo signals. There can be one or more scanning probes. In this embodiment, the moving structure of the three-dimensional moving module, the circumferential moving module, and the scanning probe is not limited; it can be a lead screw linear moving module, a rotary platform, etc.

[0117] When using the scanning probe, the probe is pressed against the surface of the optical lens under test and ultrasonic waves are emitted point by point into the optical lens under test. Then, the echo signal is acquired, and the data of the echo signal is processed to determine whether there is a defect in the optical lens under test and the type of defect.

[0118] In this embodiment, the type of scanning probe is not limited; it can generate ultrasonic signals and acquire echo signals.

[0119] This application provides a method and apparatus for inspecting the assembly quality of optical lenses based on ultrasonic signal analysis. During inspection, an ultrasonic signal is emitted to the optical lens under test, and the echo signal is acquired. The echo signal is processed and analyzed, and characteristic values ​​are calculated for different frequency ranges. These characteristic values ​​are then compared; if the calculated characteristic value exceeds a set threshold, a defect in the optical lens can be determined, and the type of defect can be identified. This technical solution utilizes ultrasonic signals for inspection, eliminating the need for complex inspection setups, eliminating radiation, simplifying the inspection operation, reducing costs, and eliminating the need for human intervention. This avoids / reduces false positives caused by human intervention, enabling rapid and efficient assessment of the quality of the assembled lens and locating defects when quality problems exist.

[0120] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0121] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0122] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An optical lens assembly quality detection method based on ultrasonic signal analysis, characterized in that, The method comprises: ultrasonic waves are emitted to the optical lens, and echo signals are acquired; dividing the echo signal into a plurality of frequency range segments, = 5 MHz, = 50 MS / s, wherein, is the center frequency of the ultrasound waves, is the sampling frequency of the ultrasound waves, the echo signal is divided into 4 frequency range segments, respectively: the frequency range f4~f5 of the first layer CD1 is: , the defect type represented is surface scratch and coating peeling; the frequency range f3~f4 of the second layer CD2 is: , the defect type represented is air bubble, debonding, missing or discontinuous of the glue layer at the glue interface; the frequency range f2~f3 of the third layer CD3 is: , the defect type represented is internal crack of the mirror surface; the frequency range f1~f2 of the fourth layer CD4 is: , the defect type represented is the gap between the lens and the mirror seat or the compression ring, the virtual compression or the stress concentration area; a characteristic value of each of the frequency range segments is calculated, a kurtosis value KUr of a first layer CD1 is calculated, an energy entropy Er of a second layer CD2 is calculated, a peak factor Cr of a third layer CD3 is calculated, and an energy ratio Rr of a fourth layer CD4 is calculated; when the characteristic value is greater than a set threshold value, it is determined that the optical lens has a defect, and a defect type is determined according to the current frequency range.

2. The optical lens assembly quality detection method based on ultrasonic signal analysis according to claim 1, characterized in that, Before the step of dividing the echo signals into multiple frequency range segments, the method further comprises: gain compensation is performed on the echo signals; the gain compensation calculation formula is: G(t) = G g + K x t wherein, G(t) Gtotai is the total gain value at time t, the unit of time t is μs, G(t) Gtotai is the total gain value at time t, the unit of time t is μs, G g Gini is the initial fixed gain, the unit is dB; K Gdec is the decay compensation slope, the unit is dB / μs; t T is the transit time of the ultrasonic wave in the material, the unit is μs.

3. The optical lens assembly quality detection method based on ultrasonic signal analysis according to claim 1, characterized in that, The method of dividing the echo signals into multiple frequency range segments comprises: the number J of the frequency range segments is calculated according to the formula: J = log2( )+ 1; wherein is the center frequency of the ultrasound signal, is the sampling frequency of the ultrasound signal.

4. The optical lens assembly quality detection method based on ultrasonic signal analysis according to claim 1, characterized in that, The method further comprises: a good product baseline database is established, and the good product baseline database comprises a threshold range of the characteristic value, and the threshold range of the characteristic value is the set threshold value.

5. An optical lens assembly quality detection device based on ultrasonic signal analysis, characterized in that, The motion platform, the scanning probe and the control device are connected with the control device respectively; The motion platform is used for carrying the optical lens to be tested and driving the optical lens to be tested to move along a set path; The scanning probe is used for emitting ultrasonic waves to the optical lens to be tested and receiving echo signals; The control device realizes the detection of the optical lens to be tested based on the optical lens assembly quality detection method based on ultrasonic signal analysis according to any one of claims 1 to 4.

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