An online inspection system for optical component manufacturing

Abstract

The present invention discloses an on-line detection system for the production of optical elements. The present invention relates to the technical field of optical element production and manufacturing. In the present invention, a laser level is used to irradiate a test target plate to form a light spot, and a thermal imager is used to capture images of the light spot at 4 different time points and 8 different angles of the light spot at the first time point to obtain thermal imaging pictures. The temperature interval area change calculation is performed on the thermal imaging pictures of adjacent time points obtained, and the temperature stability of the laser level is judged according to the total temperature interval area change rate S total. If the temperature stability of the laser level meets the standard, the color and area consistency of the thermal imaging images at 8 angles collected at time point t are judged. If both the temperature stability and energy uniformity of the laser level meet the standards, it can be determined that the laser level passes the detection; otherwise, it is determined that the detection fails. The present invention can effectively detect unqualified products, ensuring the quality of the products and the actual experience of users.

Description

Technical Field

[0001] This invention relates to the field of optical component manufacturing technology, specifically to an online inspection system for optical component production. Background Technology

[0002] In the production process of optical components, quality control is a crucial step. Laser levels, as common optical instruments widely used in construction, decoration, and engineering surveying, directly impact the quality of measurement work. Currently, most laser levels are tested offline, which has several drawbacks. It significantly reduces production efficiency, increases labor and time costs, and makes it difficult to detect problems in real time, potentially leading to batches of defective products, wasting resources and increasing costs. Furthermore, existing testing methods are insufficiently comprehensive and accurate in evaluating key performance indicators such as stability and energy uniformity. Some methods can only assess certain aspects of the laser level's performance, failing to comprehensively consider its performance under different operating conditions. This makes it difficult to detect potential quality problems in a timely manner, resulting in defective products entering the market, causing inconvenience to users and potential safety hazards. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides an online inspection system for optical component manufacturing, which solves the problems of insufficient comprehensiveness and low accuracy of existing laser levels during the production stage.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an online inspection system for optical component manufacturing, comprising:

[0005] Energy uniformity analysis module. This module pre-divides RGB values into certain intervals, with each interval corresponding to a specific color. For each thermal imaging picture, all pixels are traversed to count the number of pixels in each color interval, thereby obtaining the color set of the picture. Calculate the intersection C12 = C1 ∩ C2 and union C12u = C1 ∪ C2 of the color sets of two thermal imaging pictures, and obtain the cross-color ratio mixture. If mixture >= 0.8, it means the colors of the two pictures are the same. Compare the 8 pictures pairwise and record the number of times Num when the colors are the same. If Num >= 27, the color consistency meets the standard; otherwise, the color consistency does not meet the standard. For each color area in the thermal imaging picture, calculate its area by counting the number of pixels of that color. If the actual area of each pixel is area, then the area A of the color area is A = n × area, where n is the number of pixels of that color. Confirm the intersection color of the two pictures, calculate the sum of the areas occupied by the intersection of Picture 1 and Picture 2 as Q1 and Q2 respectively, and then calculate the sum of the areas occupied by the difference-set colors of Picture 1 and Picture 2 as Q3. If (Q1 / Q2) > 0.9 and Q3 < Qth, it means the areas of the two pictures are the same. Record the number of times Num1 when the areas are the same. If Num1 >= 27, the area consistency meets the standard; otherwise, the area consistency does not meet the standard.

[0006] Detection result determination module. If the temperature stability and energy uniformity of the laser level are all up to standard, it can be determined that the laser level passes the detection; otherwise, it is determined that the detection fails.

[0007] As a further solution of the present invention, before the energy uniformity analysis module, there are also a picture data acquisition module and a temperature stability analysis module. The picture data acquisition module aims at the light spot formed by the laser level irradiating the test target plate, uses a thermal imager to perform thermal imaging shooting on the light spot at 4 time points of t minutes, t + △t minutes, t + 2△t minutes, and t + 3△t minutes, and at time point t, continues to perform thermal imaging shooting from 8 angles respectively, and transmits the collected picture data to the temperature stability analysis module and the energy uniformity analysis module. The temperature stability analysis module calculates the change in the area of the temperature interval for each pair of adjacent time point thermal imaging pictures, and judges the temperature stability of the laser level according to the total change rate S of the temperature interval area. 总 Judge the temperature stability of the laser level.

[0008] As a further solution of the present invention, the resolution of the thermal imager is not less than 640 × 480 pixels, the accuracy reaches ±0.1 °C, and the response band range is 2.5 - 8.5 μm.

[0009] As a further solution of the present invention, the material of the selected test target plate is copper alloy, the thermal conductivity is maintained within the range of 300 - 400 W / m·K, and the surface roughness does not exceed Ra0.8 μm.

[0010] As a further embodiment of the present invention, the value range of t is [3,5], and the value range of Δt is [2,3].

[0011] As a further aspect of the present invention, the specific steps for calculating the area change of the temperature interval in thermal imaging images at adjacent time points are as follows:

[0012] Based on all temperature data at two time points, p minutes and q minutes, take the lowest and highest temperatures at the two time points to determine a total interval containing all temperature values, and then divide this total interval into equal intervals.

[0013] For each uniformly divided temperature range, calculate its area percentage in the thermal imaging images at p minutes and q minutes respectively. Area percentage = (area of ​​the range ÷ total area of ​​the thermal imaging images) × 100%;

[0014] The change in area percentage is obtained by subtracting the area percentage of a certain temperature range at time q minutes from the area percentage of that range at time p minutes.

[0015] Adding the absolute values ​​of the changes in the area percentage of all temperature ranges yields the comprehensive value Spq of the temperature range area change.

[0016] As a further aspect of the present invention, the comprehensive value of the change in the area of ​​the temperature interval from time point t minutes to t+Δt minutes is S. t,t+△t The comprehensive change in the area of ​​the temperature range from time point t+Δt to t+2Δt minutes is S. t+△t,t+2△t The comprehensive change in the area of ​​the temperature interval from time point t+2△t to t+3△t minutes is S. t+2△t,t+3△t The combined changes in the area of ​​the temperature intervals at the four time points are used to calculate the result using the formula S. 总 =a1×S t,t+△t +a2×S t+△t,t+2△t +a3×S t+2△t,t+3△t Calculate the total rate of change of the area of ​​the temperature interval, where a1, a2, and a3 are the weights of the comprehensive change in the area of ​​the temperature interval at different time points.

[0017] As a further aspect of the present invention, the cross-color ratio is calculated according to the formula mixture = |C12| / |C12u|, where |C12| and |C12u| represent the number of elements in C12 and C12u, respectively.

[0018] As a further aspect of the present invention, the difference set of colors between Image 1 and Image 2 specifically includes colors that belong to Image 1 but not to Image 2 and colors that belong to Image 2 but not to Image 1.

[0019] As a further aspect of the present invention, in the test result determination module, the specific test conclusion can be displayed through indicator lights, display screen, sound prompts, printouts, or mobile devices.

[0020] This invention provides an online inspection system for optical component manufacturing. Compared with existing technologies, it has the following advantages:

[0021] (1) The present invention can perform real-time detection directly on the laser level production line without removing the product from the production line for offline detection, which greatly shortens the detection time, improves production efficiency, facilitates timely detection and adjustment of quality problems during the production process, and effectively avoids batches of unqualified products.

[0022] (2) By comprehensively detecting and analyzing the temperature changes of the laser level at different time points and the energy distribution from multiple angles, this invention can accurately assess the stability and energy uniformity of its long-term operation. This multi-dimensional detection method greatly improves the accuracy and reliability of the detection, effectively prevents unqualified products from entering the market, and ensures the quality of the product and the actual user experience. Attached Figure Description

[0023] Figure 1 This is a block diagram illustrating the system principle of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] like Figure 1 This invention provides an online inspection system for optical component manufacturing, comprising:

[0026] The image data acquisition module uses a thermal imager to capture thermal images at four time points: t minutes, t+Δt minutes, t+2Δt minutes, and t+3Δt minutes, when the laser level illuminates the test target plate. At time point t, thermal images are captured from eight angles, such as 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°, to ensure that clear thermal images of the light spot can be captured from different angles.

[0027] In order to accurately capture the minute temperature changes of the laser beam spot when the laser level illuminates the test target, the selected thermal imager must have high resolution and high precision. The resolution requirement should be no less than 640×480 pixels. This resolution can clearly reflect the subtle features of the laser beam spot and ensure that the captured thermal image contains enough effective information. For example, when there is an uneven temperature distribution in the laser beam spot, high resolution can clearly show these subtle differences in the image.

[0028] For accuracy requirements, the error must reach ±0.1℃. This is because the laser energy emitted by the laser level may fluctuate slightly during operation, resulting in subtle changes in the temperature of the laser spot. A high-precision thermal imager can accurately measure the specific temperature changes in each area, providing a reliable basis for subsequent data analysis.

[0029] The response band range should match the thermal radiation band generated by the laser emitted by the laser level. In this case, the thermal imager can more effectively acquire the temperature information of the laser spot. Within this band, the thermal radiation generated by the laser can be efficiently captured by the thermal imager and converted into accurate temperature data. For example, infrared lasers have relatively high energy and generate a wide thermal radiation band after interacting with objects, mainly concentrated in the mid-infrared band, approximately between 3-8 μm. In this case, an infrared thermal imager with a response band of 2.5-8.5 μm can be selected.

[0030] Before using a thermal imager, it needs to be calibrated using a standard blackbody furnace. First, point the thermal imager at the standard blackbody furnace and set its temperature to several different values, such as 20℃, 30℃, and 40℃. The thermal imager measures the standard blackbody furnace at each set temperature and records the measured values. The measured values ​​are compared with the previously set temperatures of the standard blackbody furnace to obtain the error between the two data. The thermal imager is then adjusted based on the error, and the measurement results are corrected using a calibration algorithm until the error between the measured temperature and the set temperature is maintained within ±0.1℃.

[0031] For the selected test target plate, both thermal conductivity and surface flatness should be considered. Copper alloy can be selected as the material, as it has good thermal conductivity and uniformity. In practical applications, special proportioning and treatment of this copper alloy are required to maintain its thermal conductivity coefficient within the range of 300-400 W / m·K. This range allows the heat generated by laser irradiation to spread rapidly and evenly. For example, when a laser level emits a laser beam onto the test target plate, the heat will be evenly distributed on the surface of the target plate in a short time, avoiding large local temperature deviations due to uneven thermal conduction. This effectively ensures that the thermal imager can accurately measure the temperature distribution of the laser spot.

[0032] The surface roughness of the test target plate should not exceed Ra0.8μm. A flat surface can ensure that the laser can be uniformly irradiated onto the target plate, avoiding laser reflection or scattering caused by uneven surface, which would affect the temperature measurement of each part. At the same time, the size of the test target plate should be approximately 200mm×200mm×10mm. This size range can not only meet the coverage of the laser spot emitted by the laser level, but also take into account issues such as thermal conductivity and manufacturing cost.

[0033] The initial value of t should ensure that the laser level has finished warming up and the production rhythm of the production line products. If t is set too small, the laser level will start testing before it has been fully warmed up, and the obtained thermal imaging data will not reflect its performance under normal working conditions. If t is set too large, it will slow down the production rhythm and affect production efficiency.

[0034] In one embodiment of the present invention, the value of t is in the range of [3,5];

[0035] If Δt is too large, it will miss information about the performance changes of the laser level in a short period of time, and it will be impossible to comprehensively and accurately assess its stability. If Δt is too small, it will not be effective for laser levels that require long-term observation to obtain effective information.

[0036] In one embodiment of the present invention, the value range of △t is [2,3].

[0037] The temperature stability analysis module analyzes the temperature range area changes in thermal imaging images acquired by the image data acquisition module at each time point, thereby demonstrating the long-term stability of the laser level.

[0038] The specific operation method for calculating the area change of the temperature range between two time points is as follows: (1) Unify the temperature range division. To avoid difficulties in comparison caused by differences in range division, based on all temperature data at two time points, p minutes and q minutes, re-divide a unified temperature range. Take the lowest and highest temperatures at the two time points to determine a total range that includes all temperature values, and then perform equally spaced division within this total range; (2) Calculate the actual area ratio of each unified range at different time points. For each uniformly divided temperature range, calculate its area ratio in the thermal imaging pictures at p minutes and q minutes respectively. The area ratio = (the area of this range ÷ the total area of the thermal imaging picture) × 100%. Through the area ratio, the possible measurement error of the total area of the thermal imaging picture can be eliminated, making the data at different time points more comparable; (3) Calculate the change amount of the area ratio. Subtract the area ratio of a certain temperature range at p minutes from the area ratio of this range at q minutes to obtain the change amount of the area ratio. The change amount of the area ratio reflects the actual change situation of this temperature range during this period. A positive value indicates an increase in the area ratio, and a negative value indicates a decrease in the area ratio; (4) Add up the absolute values of the change amounts of the area ratios of all temperature ranges to obtain the comprehensive value Spq of the area change of the temperature range;

[0039] The comprehensive value of the area change of the temperature range from time point t minutes to t + △t minutes is calculated as S t,t+△t , and the comprehensive value of the area change of the temperature range from time point t + △t to t + 2△t minutes is S t+△t,t+2△t , and the comprehensive value of the area change of the temperature range from time point t + 2△t to t + 3△t minutes is S t+2△t,t+3△t , combine the comprehensive values of the area changes of the temperature ranges at the 4 time points. According to the formula S 总 = a1×S t,t+△t + a2×S t+△t,t+2△t + a3×S t+2△t,t+3△t Calculate the total change rate of the area of the temperature range, where a1, a2, and a3 are the weights of the comprehensive values of the area changes of the temperature ranges at different time points.

[0040] Energy uniformity analysis module. If S 总 < Sth, it is necessary to perform color consistency judgment and area consistency judgment on the thermal imaging images at 8 angles collected at time point t;

[0041] The specific steps for color consistency judgment are as follows:

[0042] Since the colors in thermal images are essentially determined by the RGB or HSV values ​​of pixels, these continuous values ​​need to be quantized, i.e., converted into a statistically discrete set of colors. For example, RGB values ​​can be divided into certain intervals, with each interval corresponding to a specific color. For each thermal image, all pixels are traversed, and the number of pixels in each color interval is counted to obtain the color set of the image. If the quantized color set of image 1 is C1 = {red, blue, green, gray}, and the color set of image 2 is C2 = {red, blue, green}, then the color set of image 2 is C2 = {red, blue, green}. Calculate the intersection C12 = C1 ∩ C2 and the union C12u = C1 ∪ C2 of the color sets of two images. Based on the above example, we get the intersection C12 = {red, blue, green, gray} and the union C12u = {red, blue, green, gray, orange}. Calculate the percentage of colors in the intersection using the formula mixture = |C12| / |C12u|, where |C12| and |C12u| represent the number of elements in C12 and C12u, respectively. In the above example, mixture = 4 / 5 = 0.8. If mixture >= 0.8, it means that the colors of the two images are consistent. Perform pairwise comparisons on the 8 images, requiring a total of 28 comparisons. After each comparison, record the number of times the colors are consistent, i.e., Num, where mixture >= 0.8. If Num >= [28 × 0.95] = 27, then the color consistency is achieved.

[0043] The specific steps for determining area consistency are as follows:

[0044] For each color region in the thermal imaging picture, its area can be calculated by counting the number of color pixels. If the actual area of each pixel is area, then the area A of the color region is A = n × area, where n is the number of color pixels. For example, in the above Picture 1, the number of red pixels is n1, so the area of the red region is A1 = n1 × area. Similarly, the areas occupied by each color in Picture 1 can be calculated as A1 - red, A2 - blue, A3 - green, A4 - gray, and the areas occupied by each color in Picture 2 are B1 - red, B2 - blue, B3 - green, B4 - gray, B5 - orange; confirm the intersection colors of the two pictures, and then calculate the sum of the areas occupied by the intersections of Picture 1 and Picture 2 respectively as Q1 = A1 + A2 + A3 + A4 and Q2 = B1 + B2 + B3 + B4, and then find the sum of the areas occupied by the difference sets of Picture 1 and Picture 2 as Q3 = B5. The above-mentioned difference set is actually a color difference set that combines the colors that belong to Picture 1 but not to Picture 2 and the colors that belong to Picture 2 but not to Picture 1. Since there is only 1 difference set in the above example, its area can be directly obtained; if (Q1 / Q2) > 0.9 and Q3 < Qth, it means that the areas of the two pictures are the same; when comparing 8 pictures pairwise, a total of 28 comparisons need to be made. After each comparison, record the number of times Num1 when the areas are the same. If Num1 >= [28 × 0.95] = 27, the area consistency meets the standard.

[0045] The detection result determination module comprehensively determines whether the laser level is qualified according to the stability and energy stability results of the laser level during continuous operation obtained by the temperature stability analysis module and the energy uniformity analysis module, that is, to meet the total change rate S of the temperature interval area 总 <Sth, color consistency, and area consistency meet the standards to determine that the laser level is qualified; otherwise, it is determined as unqualified. The detection result determination module will display the final detection result in an intuitive way, such as through an indicator light: a green light indicates qualified, and a red light indicates unqualified; display the specific detection conclusion on the display screen; sound prompt: use a speaker or buzzer to emit sounds with different frequencies and rhythms to represent different detection results; print output: connect to a printer and print the detection result in the form of a paper report; mobile device:借助蓝牙、Wi-Fi或移动网络,将检测结果推送到操作人员的手机、平板电脑等移动设备上,方便操作人员及时了解产品的质量情况。

[0046] Some of the data in the above formula are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0047] It should be noted that there is an unclear part in the original text for item where "借助蓝牙、Wi-Fi或移动网络,将检测结果推送到操作人员的手机、平板电脑等移动设备上,方便操作人员及时了解产品的质量情况。" is in Chinese. I have translated it as best as possible based on the context, but it would be better if the complete English expression for this part was provided for a more accurate translation.The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An online inspection system for optical component manufacturing, characterized in that, including: An image data acquisition module. For the light spot formed by the laser level irradiating the test target board, use a thermal imager to perform thermal imaging on the light spots at 4 time points of t minutes, t+△t minutes, t+2△t minutes, and t+3△t minutes, and continue to perform thermal imaging from 8 angles at time point t, and transmit the collected image data to the temperature stability analysis module; The temperature stability analysis module calculates the change in temperature range area based on the thermal imaging images acquired at adjacent time points, and then calculates the total rate of change S of the temperature range area. 总 The specific steps for determining the temperature stability of a laser level and calculating the change in the area of ​​the temperature range in thermal images at adjacent time points are as follows: Based on all the temperature data at two time points of p minutes and q minutes, take the lowest temperature and the highest temperature at the two time points to determine a total interval containing all temperature values, and then perform equally spaced division within this total interval; For each uniformly divided temperature interval, calculate its area proportion in the thermal imaging pictures at p minutes and q minutes respectively. Area proportion = (area of this interval ÷ total area of the thermal imaging picture) × 100%; Subtract the area proportion of a certain temperature interval at p minutes from the area proportion of this interval at q minutes to obtain the change amount of the area proportion; Add up the absolute values of the change amounts of the area proportions of all temperature intervals to obtain the comprehensive value Spq of the area change of the temperature interval; An energy uniformity analysis module. This module pre-divides the RGB values according to a certain interval, and each interval corresponds to a specific color. For each thermal imaging picture, traverse all pixels, count the number of pixels in each color interval, so as to obtain the color set of this picture, calculate the intersection C12 = C1∩C2 and union C12u = C1∪C2 of the color sets of the two thermal imaging pictures, and calculate the cross-color proportion according to the formula mixture = |C12| / |C12u|. If mixture >= 0.8, it means that the colors of the two pictures are the same. Compare the 8 pictures pairwise and record the number of times Num when the colors are the same. If Num >= 27, the color consistency meets the standard, otherwise, the color consistency does not meet the standard; For each color area in the thermal imaging picture, calculate its area by counting the number of pixels of this color. If the actual area of each pixel is area, the area A of the color area = n×area, where n is the number of pixels of this color. Confirm the intersection color of the two pictures, and calculate the sum of the areas occupied by the intersection of Picture 1 and Picture 2 as Q1 and Q2 respectively, and then calculate the sum of the areas occupied by the difference set colors of Picture 1 and Picture 2 as Q3. If (Q1 / Q2) > 0.9 and Q3 < Qth, it means that the areas of the two pictures are the same. Record the number of times Num1 when the areas are the same. If Num1 >= 27, the area consistency meets the standard, otherwise, the area consistency does not meet the standard; A detection result determination module. If the temperature stability and energy uniformity of the laser level both meet the standards, it can be determined that the laser level passes the detection, otherwise, it is determined that the detection fails.

2. The online inspection system for optical component manufacturing according to claim 1, characterized in that, The resolution of the thermal imager is not less than 640×480 pixels, the accuracy reaches ±0.1℃, and the response band range is 2.5 - 8.5μm.

3. The online inspection system for optical component manufacturing according to claim 1, characterized in that, The material of the selected test target board is copper alloy, the thermal conductivity coefficient is maintained within the range of 300 - 400W / m・K, and the surface roughness does not exceed Ra0.8μm.

4. The online inspection system for optical component manufacturing according to claim 1, characterized in that, The value range of t is [3,5], and the value range of △t is [2,3].

5. The online inspection system for optical component manufacturing according to claim 1, characterized in that, The comprehensive value of the area change in the temperature range from time point t minutes to t+Δt minutes is S. t,t+△t The comprehensive change in the area of ​​the temperature range from time point t+Δt to t+2Δt minutes is S. t+△t,t+2△t The comprehensive change in the area of ​​the temperature interval from time point t+2△t to t+3△t minutes is S. t+2△t,t+3△t The combined changes in the area of ​​the temperature intervals at the four time points are used to calculate the result using the formula S. 总 =a1×S t,t+△t +a2×S t+△t,t+2△t +a3×S t+2△t,t+3△t Calculate the total rate of change of the area of ​​the temperature interval, where a1, a2, and a3 are the weights of the comprehensive change in the area of ​​the temperature interval at different time points.

6. The online inspection system for optical component manufacturing according to claim 1, characterized in that, The difference set of colors between Image 1 and Image 2 specifically includes colors that belong to Image 1 but not Image 2, and colors that belong to Image 2 but not Image 1.

7. The online inspection system for optical component manufacturing according to claim 1, characterized in that, In the test result determination module, specific test conclusions can be displayed via indicator lights, screens, sound prompts, printouts, and mobile devices.

Images