Surface coating process for optical element product

Abstract

The invention relates to the technical field of surface coating, and particularly discloses a surface coating process of an optical element product, which comprises the following steps: acquiring an effective array in historical data, training a temperature prediction model in a temperature rise stage based on the effective array, acquiring a real-time temperature value in the temperature rise stage, and substituting the real-time temperature value into the temperature prediction model. Calculating to obtain a predicted temperature value and a predicted time point, calculating a predicted temperature deviation value based on the predicted temperature value and a standard temperature value of the predicted time point, comparing the predicted temperature deviation value with a temperature deviation threshold value, judging the deviation degree, and if a large deviation signal is generated, indicating that the predicted temperature value is in an abnormal state. Therefore, the temperature can be predicted through the temperature prediction model, the deviation of the temperature can be known in time, advanced adjustment is carried out, and then the curing effect of the film layer material is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of surface coating, and in particular to a surface coating process for an optical element product. Background Art

[0002] With the development of science and technology, the popularity of cameras, mobile phones and tablet computers has provided a lot of convenience for people. Among them, optical lenses are these devices and their important components. These are collectively referred to as optical component products. In the production and processing of optical lenses, their surfaces usually need to be coated. Among the process steps of coating materials, curing is a crucial step. Curing usually includes a heating stage, a high-temperature curing stage and a cooling stage. The temperature control of each stage directly affects the performance of the film material.

[0003] During the film curing process, the temperature of the equipment is usually adjusted by a temperature-controlled air mixer. However, the heating stage is to raise the temperature to the temperature required for curing, and it takes a certain amount of time for the temperature to reach the curing temperature. If the temperature reaches the preset curing temperature ahead of time, it may have the following effects: When the temperature reaches the curing temperature ahead of time or delayed, the imidization reaction rate between the precursors of the film material will be affected, affecting production efficiency. At the same time, too fast or too slow a reaction rate will lead to uneven mixing between the reactants, resulting in incomplete reaction in some areas, affecting the uniformity and consistency of the film material;

[0004] In view of this, we propose a surface coating process for optical component products. Summary of the Invention

[0005] The purpose of the present invention is to provide a surface coating process for optical element products to solve the technical problems in the above background.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] The present invention provides a surface coating process for optical element products, which specifically includes the following steps: obtaining temperature value data of a heating stage in historical data, and comparing it with a standard temperature value to obtain a valid array; training a model through the valid array to obtain a temperature prediction model for the heating stage; obtaining a real-time temperature value in the heating stage, calculating a predicted temperature value based on the real-time temperature value, and calculating a predicted temperature deviation value, comparing the predicted temperature deviation value with a temperature deviation threshold, and generating a large deviation signal; obtaining gas flow rate data based on the generated large deviation signal, and processing the data to obtain a gas flow rate anomaly coefficient; wherein the gas flow rate anomaly coefficient is calculated by the proportion of gas flow rate anomaly duration and the gas flow rate anomaly degree ratio; obtaining the gas flow rate anomaly coefficient and the predicted temperature deviation value, calculating the gas flow rate influence coefficient, and evaluating the coefficient to generate a related influence signal; and regulating the gas flow rate based on the generated related influence signal.

[0008] As a further solution of the present invention: the process of obtaining the valid array is:

[0009] With time as the X-axis and temperature as the Y-axis, a two-dimensional model is established, and the standard temperature value is substituted into the two-dimensional model to draw a standard temperature curve.

[0010] Obtain temperature value data of the heating stage of several groups of qualified processes in the historical data, and mark the temperature value data of the same group of heating stage as an analysis array;

[0011] In an analysis array, the total time of the heating stage is divided into a number of monitoring time points, and the temperature value corresponding to each monitoring time point is compared with the temperature standard range corresponding to each monitoring time point;

[0012] If the temperature value is not within the temperature standard range, an abnormal signal is generated;

[0013] In the same analysis array, if there is a monitoring time point that generates an abnormal signal, the analysis data is marked as an invalid array; if there is no monitoring time point that generates an abnormal signal, the analysis array is marked as a valid array.

[0014] As a further solution of the present invention: the process of obtaining the predicted temperature deviation value is:

[0015] During the temperature rise phase of the film material curing step, the real-time temperature value of each monitoring time point in the temperature rise phase is obtained, and the time period between two adjacent monitoring time points is marked as a prediction period;

[0016] Mark the real-time monitoring time point as the calculation time point, substitute the real-time temperature value at the calculation time point into the temperature prediction model, calculate the theoretical time value corresponding to the real-time temperature value, and sum the theoretical time value with the prediction period to obtain the analysis time value;

[0017] Substitute the analysis time value into the temperature prediction model to obtain the predicted temperature value corresponding to the analysis time value;

[0018] The predicted temperature value at the predicted time point is calculated to be different from the standard temperature value corresponding to the predicted time point, and the absolute value of the difference is taken to obtain the predicted temperature deviation value.

[0019] As a further solution of the present invention: the process of generating the large deviation signal is:

[0020] Obtain a predicted temperature deviation value, and compare the predicted temperature deviation value with a temperature deviation threshold; if the predicted temperature deviation value is greater than the temperature deviation threshold, generate a large deviation signal.

[0021] As a further solution of the present invention: the process of obtaining the gas flow rate anomaly coefficient is:

[0022] Substitute the ratio of gas flow rate abnormality duration and gas flow rate abnormality degree ratio into the formula The gas flow rate anomaly coefficient XS is calculated, where SC represents the proportion of gas flow rate anomaly duration, CD represents the gas flow rate anomaly degree ratio, and s1 and s2 are preset proportional coefficients.

[0023] As a further solution of the present invention: the process of obtaining the abnormal duration ratio of the gas flow rate is as follows:

[0024] Obtain the predicted time point and calculation time point corresponding to the generation of the large deviation signal, define the time point from the start of the heating phase to the calculation time point as the judgment period, and divide the judgment period into several sub-judgment periods;

[0025] Acquire real-time gas flow rate value data for each sub-judgment period in the film material curing step;

[0026] Compare the gas flow rate value with the gas flow rate standard range;

[0027] If the gas flow rate value is not within the gas flow rate standard range, a gas flow rate abnormality signal is generated;

[0028] Within the sub-judgment period, the duration of the generated gas flow rate abnormal signal is obtained and marked as the abnormal period. All abnormal periods are summed up to obtain the total abnormal duration. The total abnormal duration is calculated by ratio with the duration of the sub-judgment period to obtain the proportion of the gas flow rate abnormal duration.

[0029] As a further solution of the present invention: the process of obtaining the gas flow rate abnormality ratio is:

[0030] In the sub-judgment period, the gas flow rate value corresponding to the abnormal period is obtained, and the relationship between the gas flow rate value of each abnormal period and the gas flow rate standard range is determined;

[0031] If the gas flow rate value during the abnormal period is greater than the maximum value of the gas flow rate standard range, the maximum value of the gas flow rate value during the abnormal period is extracted and marked as the abnormal maximum value. The difference between the abnormal maximum value and the gas flow rate standard value is calculated, and the ratio of the difference to the gas flow rate standard value is calculated to obtain the abnormal deviation ratio.

[0032] If the gas flow rate value during the abnormal period is less than the minimum value of the gas flow rate standard range, the minimum value of the gas flow rate value during the abnormal period is extracted and marked as the abnormal minimum value. The difference between the abnormal minimum value and the gas flow rate standard value is calculated, and the absolute value of the difference is taken and the ratio is calculated with the gas flow rate standard value to obtain the abnormal deviation ratio;

[0033] All abnormal deviation ratios are summed to obtain the gas flow rate abnormality degree ratio.

[0034] As a further solution of the present invention: the process of obtaining the gas flow rate influence coefficient is:

[0035] Obtaining the gas flow rate anomaly coefficient for each sub-judgment period and the predicted temperature deviation value at the end time of the sub-judgment period;

[0036] Calculate the difference between the gas flow rate anomaly coefficients of adjacent sub-judgment periods to obtain a change value of the gas flow rate anomaly coefficient;

[0037] Calculate the difference between the predicted temperature deviation values at the end time points of adjacent sub-judgment periods to obtain a predicted temperature deviation change value;

[0038] The change value of the gas velocity anomaly coefficient and the change value of the predicted temperature deviation at the same time point are marked as a comparison array;

[0039] In a comparison array, if the change value of the gas flow rate anomaly coefficient and the change value of the predicted temperature deviation value change synchronously, the comparison array is marked as a synchronous change comparison array; otherwise, the comparison data is marked as an asynchronous change comparison array;

[0040] Get the number of synchronous change arrays, perform ratio processing on the synchronous change comparison array and the total number of comparison arrays to obtain the proportion of the synchronous change array, which is marked as the gas flow rate influence coefficient.

[0041] As a further solution of the present invention: the process of generating the relevant influence signal is:

[0042] obtaining a gas flow rate influence coefficient, and comparing the gas flow rate influence coefficient with a gas flow rate influence coefficient threshold;

[0043] If the gas flow rate influence coefficient is greater than the gas flow rate influence coefficient threshold, then a related influence signal is generated.

[0044] As a further solution of the present invention: the process of regulating the gas flow rate is:

[0045] Obtain the gas flow rate values of all abnormal periods, sum and average all the gas flow rate values to obtain the gas flow rate mean;

[0046] Obtain the air supply power value during the non-abnormal period, sum up all the air supply power values and take the average value to obtain the air supply power average value and substitute it into the formula The target value of air supply power PY is calculated, where VB represents the standard value of gas flow rate, VY represents the average gas flow rate, and PB represents the average air supply power.

[0047] Beneficial effects of the present invention:

[0048] (1) The present invention obtains a valid array in historical data, trains a temperature prediction model in the heating stage based on the valid array, obtains the real-time temperature value in the heating stage, substitutes the real-time temperature value into the temperature prediction model, calculates the predicted temperature value and the predicted time point, calculates the predicted temperature deviation value based on the predicted temperature value and the standard temperature value at the predicted time point, compares the predicted temperature deviation value with the temperature deviation threshold, and judges the degree of deviation. If a large deviation signal is generated, it indicates that the predicted temperature value is in an abnormal state, so that the temperature can be predicted by the temperature prediction model, the temperature deviation can be timely understood, and advance adjustment can be made, thereby optimizing the curing effect of the film material;

[0049] (2) When generating a large deviation signal, the present invention obtains the corresponding calculation time point and prediction time point, and obtains the gas flow rate data during the process from the start time point of the film material curing temperature rise stage to the calculation time point, calculates the gas flow rate anomaly coefficient based on the gas flow rate data, calculates the gas flow anomaly coefficient based on the calculated gas flow rate anomaly coefficient and the predicted temperature deviation ratio, compares the gas flow anomaly coefficient with the gas flow anomaly coefficient threshold, generates a relevant influence signal or generates an irrelevant influence signal, and when generating a relevant influence signal, regulates the gas flow rate by adjusting the air supply power value, so that when the predicted temperature value deviates greatly from the standard temperature value, the influencing factors causing the deviation can be understood through analysis, and timely adjustments can be made based on the influencing factors, thereby reducing the problem of abnormal curing reaction of the film material due to temperature deviation, which affects the curing effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention will be further described below with reference to the accompanying drawings.

[0051] Figure 1This is a flowchart of calculation and judgment of predicted temperature deviation value in a surface coating process of an optical component product of the present invention;

[0052] Figure 2 It is a flow chart of a surface coating process for an optical component product of the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] Example 1:

[0055] Reference Figure 2 As shown, based on the above embodiment, this embodiment provides a surface coating process for an optical element product, comprising the following steps:

[0056] Step 1: Optical component preparation and cleaning: Use ultrasonic waves combined with organic solvents (such as acetone, alcohol) to clean the surface of the optical component to thoroughly remove grease, dust and impurities, then rinse with deionized water and dry to ensure that the film layer is firmly attached and free of contamination;

[0057] Step 2: Applying the functional coating liquid: The prepared functional coating liquid is evenly applied to the component surface. Common methods include spin coating, dip coating or spray coating to control the initial thickness and uniformity of the film layer, providing a foundation for the subsequent formation of a complete film layer.

[0058] Step 3: Pre-drying by standing: After coating, the film needs to be left standing at room temperature or low temperature for a few minutes to allow the solvent to evaporate naturally and form a preliminary gel-like wet film, thus creating a stable physical structure and solvent control conditions for formal curing;

[0059] Step 4: Curing: Use thermal curing method according to the film material to make the coating undergo cross-linking reaction or polymerization transformation to form a dense, stable and functional film layer;

[0060] Step 5: Post-treatment of the film: Depending on the application requirements, thermal annealing can be performed to improve the stability and heat resistance of the film, or surface modification methods (such as fluorosilane treatment) can be used to enhance its anti-fouling and anti-fingerprint properties.

[0061] Step 6: Testing and quality inspection: The coated optical components are subjected to multiple tests such as film thickness, optical performance, appearance and adhesion to ensure that the film quality is stable and meets the standards.

[0062] This process can be used to process optical lenses such as camera lenses, telescopes and microscopes, and can also be used to produce display screen protective covers. The coating process can effectively improve the transmittance of the lens, and at the same time, the coating process can effectively improve the scratch resistance, fingerprint resistance and hydrophobicity of the mirror surface.

[0063] Example 2:

[0064] Based on the above examples, please refer to Figure 1 As shown, a thermal curing method is used to cause the coating to undergo a cross-linking reaction or polymerization transformation to form a dense, stable, and functional film layer. The surface coating process of an optical component product described in an embodiment of the present invention ensures that the curing efficiency is improved during the curing process, specifically including:

[0065] During the curing process, the temperature value data of the heating stage in the historical data is obtained and compared with the standard temperature value to obtain a valid array;

[0066] With time as the X-axis and temperature as the Y-axis, a two-dimensional model is established, and the standard temperature value is substituted into the two-dimensional model to draw a standard temperature curve.

[0067] Among them, the standard temperature value is set by those skilled in the art based on historical experience and film curing production specifications;

[0068] It should be noted that the time range of the standard temperature curve is the temperature rise stage in the curing step of the film material;

[0069] In some embodiments, temperature value data of a plurality of groups of qualifying processes in the heating stage are obtained from the historical data, and the temperature value data of the same group of heating stage are marked as an analysis array;

[0070] It should be noted that the qualified process refers to the process in which the temperature reaches the preset curing temperature value at the preset time point in the heating stage, wherein the preset time point is the end point of the standard time of the heating stage, and the end point of the standard time of the heating stage is set by those skilled in the art based on historical experience and production specifications, and the preset curing temperature value is the standard temperature value of the standard temperature curve at the preset time point;

[0071] In an analysis array, the total time of the heating stage is divided into a number of monitoring time points, and the temperature value corresponding to each monitoring time point is compared with the temperature standard range corresponding to each monitoring time point;

[0072] The maximum value of the temperature standard range is the sum of the standard temperature value and the temperature deviation threshold, and the minimum value of the temperature standard range is the difference between the standard temperature value and the temperature deviation threshold. The temperature deviation threshold is set by those skilled in the art based on historical experimental data.

[0073] If the temperature value is within the temperature standard range, it means that the temperature value at the monitoring time point is within the standard range and a normal signal is generated;

[0074] If the temperature value is not within the temperature standard range, it means that the temperature value at the monitoring time point is not within the standard range, and an abnormal signal is generated;

[0075] In the same analysis array, if there is a monitoring time point that generates an abnormal signal, the analysis data is marked as an invalid array; if there is no monitoring time point that generates an abnormal signal, the analysis array is marked as a valid array;

[0076] Obtain a valid array and obtain the temperature prediction model for the heating stage through training;

[0077] In some embodiments, all valid arrays, the timestamp of each set of data and the corresponding temperature value are obtained, specifically:

[0078] The time set of the heating stage is: T = {t1, t2, t3, ..., tn}, where t represents the time of the heating stage, and n is the number of the monitoring time point in the heating stage;

[0079] The temperature set in the heating stage is: C = {c1, c2, c3, ..., cn}, where c represents the temperature value in the heating stage, and n is the number of the monitoring time point in the heating stage;

[0080] It should be explained that each time value in the heating stage time set corresponds to each temperature value in the heating stage temperature set one by one, for example, t1 corresponds to c1, t2 corresponds to c2, and tn corresponds to cn;

[0081] A temperature prediction model is constructed based on the heating stage time set T and the heating stage temperature set C in combination with the LSTM model;

[0082] Exemplarily, the process of building a temperature prediction model is as follows:

[0083] Data preprocessing: Based on the temperature set C in the heating stage, the element data of the time period T is normalized so that the temperature value falls within a specific range, such as between 0 and 1;

[0084] Build an LSTM model and input the number of LSTM layers and the number of neurons in each layer.

[0085] For example, a model with 2 LSTM layers and 64 neurons in each layer is set up;

[0086] The constructed LSTM model is trained using the heating stage time set and the heating stage temperature set to obtain a temperature prediction model;

[0087] It should be noted that LSTM is a variant of recurrent neural networks (RNNs) and is particularly good at processing time-dependent sequence data. In temperature forecasting, the current temperature is often closely related to the temperatures at previous moments. This time dependency is captured and effectively utilized by the LSTM model.

[0088] Obtaining the real-time temperature value during the heating phase, calculating the predicted temperature value based on the real-time temperature value, calculating the predicted temperature deviation value, and evaluating the predicted temperature deviation value;

[0089] In some embodiments, during the temperature rise phase in the film material curing step, the real-time temperature value of each monitoring time point in the temperature rise phase is obtained, and the time period between two adjacent monitoring time points is marked as a prediction period;

[0090] The real-time monitoring time point is marked as the calculation time point, the real-time temperature value at the calculation time point (i.e., the value at the calculation time point) is substituted into the temperature prediction model, the theoretical time value corresponding to the real-time temperature value is obtained, and the theoretical time value is summed with the prediction period to obtain the analysis time value;

[0091] Substitute the analysis time value into the temperature prediction model to obtain the predicted temperature value corresponding to the analysis time value;

[0092] It should be noted that the predicted temperature value is the temperature value at one monitoring time point after the calculation time point, and the monitoring time point after the calculation time point is marked as the predicted time point;

[0093] Calculate the difference between the predicted temperature value at the predicted time point and the standard temperature value corresponding to the predicted time point, take the absolute value of the difference, and obtain the predicted temperature deviation value;

[0094] comparing the predicted temperature deviation value with a temperature deviation threshold;

[0095] If the predicted temperature deviation value is less than or equal to the temperature deviation threshold, it means that the deviation between the predicted temperature value and the standard temperature is within the process range, and a small deviation signal is generated;

[0096] If the predicted temperature deviation value is greater than the temperature deviation threshold, it means that the deviation between the predicted temperature value and the standard temperature is not within the process range, and a large deviation signal is generated;

[0097] It should be explained that when a large deviation signal is generated, the predicted temperature value is in an abnormal state, which may cause the film material to fail to reach the preset curing temperature at the preset time point, affecting the curing process of the film material;

[0098] The technical solution of the embodiment of the present invention is mainly as follows: first, by obtaining the valid array in the historical data, the temperature prediction model of the heating stage is trained based on the valid array, and then the real-time temperature value of the heating stage is obtained, the real-time temperature value is substituted into the temperature prediction model, and the predicted temperature value and the predicted time point are calculated, and the predicted temperature deviation value is calculated based on the predicted temperature value and the standard temperature value at the predicted time point, and the predicted temperature deviation value is compared with the temperature deviation threshold to judge the degree of deviation. If a large deviation signal is generated, it indicates that the predicted temperature value is in an abnormal state, so that the temperature can be predicted through the temperature prediction model, and the temperature deviation can be understood in time, and advance adjustment can be made, thereby optimizing the curing effect of the film material.

[0099] Example 3:

[0100] On the basis of Example 1, the surface coating process of an optical element product according to the embodiment of the present invention further includes the following steps:

[0101] Based on the generated large deviation signal, gas flow rate data is obtained and processed to obtain a gas flow rate anomaly coefficient;

[0102] Among them, the gas flow rate anomaly coefficient is calculated by the gas flow rate anomaly duration ratio and the gas flow rate anomaly degree ratio;

[0103] In some embodiments, the predicted time point and the calculation time point corresponding to the generation of the large deviation signal are obtained, the time point from the start of the heating phase to the calculation time point is defined as the judgment period, the judgment period is divided into a number of sub-judgment periods, and the gas flow rate abnormality duration ratio and the gas flow rate abnormality degree ratio of each sub-judgment period are obtained;

[0104] For example, the process of obtaining the abnormal gas flow rate duration ratio is as follows:

[0105] Acquire real-time gas flow rate value data for each sub-judgment period in the film material curing step;

[0106] Comparing the gas flow rate value with a standard range of gas flow rates, wherein the standard range of gas flow rates is set by those skilled in the art based on production specifications and historical experience;

[0107] If the gas flow rate value is within the gas flow rate standard range, it means that the gas flow rate meets the production specifications and a gas flow rate normal signal is generated;

[0108] If the gas flow rate value is not within the gas flow rate standard range, it means that the gas flow rate does not meet the production specifications and a gas flow rate abnormality signal is generated;

[0109] Within the sub-judgment period, the duration of the abnormal gas flow rate signal is obtained and marked as the abnormal period. All abnormal periods are summed to obtain the total abnormal duration. The total abnormal duration is calculated by ratio with the duration of the sub-judgment period to obtain the proportion of the abnormal gas flow rate duration.

[0110] Exemplarily, the process of obtaining the gas flow rate abnormality ratio is as follows:

[0111] In the sub-judgment period, the gas flow rate value corresponding to the abnormal period is obtained, and the relationship between the gas flow rate value of each abnormal period and the gas flow rate standard range is determined;

[0112] If the gas flow rate value during the abnormal period is greater than the maximum value of the gas flow rate standard range, the maximum value of the gas flow rate value during the abnormal period is extracted and marked as the abnormal maximum value. The difference between the abnormal maximum value and the gas flow rate standard value is calculated, and the ratio of the difference to the gas flow rate standard value is calculated to obtain the abnormal deviation ratio.

[0113] If the gas flow rate value during the abnormal period is less than the minimum value of the gas flow rate standard range, the minimum value of the gas flow rate value during the abnormal period is extracted and marked as the abnormal minimum value. The difference between the abnormal minimum value and the gas flow rate standard value is calculated, and the absolute value of the difference is taken and the ratio is calculated with the gas flow rate standard value to obtain the abnormal deviation ratio;

[0114] It should be noted that the standard value of gas flow rate is the average of the maximum and minimum values of the standard range of gas flow rate;

[0115] All abnormal deviation ratios are summed to obtain the gas flow rate abnormality degree ratio;

[0116] The calculation process of the gas flow rate anomaly coefficient is:

[0117] The gas flow rate anomaly coefficient XS is calculated, where SC represents the proportion of gas flow rate anomaly duration, CD represents the gas flow rate anomaly degree ratio, and s1 and s2 are preset proportional coefficients;

[0118] It should be explained that the meaning of the gas flow rate anomaly coefficient is as follows: the gas flow rate anomaly coefficient is calculated by the ratio of the gas flow rate anomaly duration to the gas flow rate anomaly degree ratio, that is, the longer the gas flow rate anomaly duration, the larger the gas flow rate anomaly coefficient, and the higher the degree of gas flow rate anomaly, that is, the larger the gas flow rate anomaly degree ratio, the greater the deviation of the abnormal maximum value from the gas flow rate standard value or the deviation of the abnormal minimum value from the gas flow rate standard value, the larger the gas flow rate anomaly coefficient, and the higher the degree of gas flow rate anomaly;

[0119] Obtain the gas flow rate anomaly coefficient and the predicted temperature deviation value, calculate the gas flow rate influence coefficient, and determine whether the gas flow rate is an influencing factor of the predicted temperature deviation;

[0120] In some embodiments, obtaining the gas flow rate anomaly coefficient of each sub-judgment period and the predicted temperature deviation value at the end time of the sub-judgment period;

[0121] Calculate the difference between the gas flow rate anomaly coefficients of adjacent sub-judgment periods to obtain a change value of the gas flow rate anomaly coefficient;

[0122] Calculate the difference between the predicted temperature deviation values at the end time points of adjacent sub-judgment periods to obtain a predicted temperature deviation change value;

[0123] The change value of the gas velocity anomaly coefficient and the change value of the predicted temperature deviation at the same time point are marked as a comparison array;

[0124] In a comparison array, if the change value of the gas flow rate anomaly coefficient and the change value of the predicted temperature deviation value change synchronously, the comparison array is marked as a synchronous change comparison array; otherwise, the comparison data is marked as an asynchronous change comparison array;

[0125] It should be noted that the synchronous changes in the gas flow rate anomaly coefficient change value and the predicted temperature deviation value change value indicate that the gas flow rate anomaly coefficient change value and the predicted temperature deviation value change value are both positive, both negative, and both 0.

[0126] Get the number of synchronous change arrays, perform ratio processing on the synchronous change comparison array and the total number of comparison arrays to obtain the proportion of the synchronous change arrays, and mark it as the gas flow rate influence coefficient;

[0127] Comparing the gas flow rate influence coefficient with a gas flow rate influence coefficient threshold, wherein the gas flow rate influence coefficient threshold is set by a person skilled in the art based on historical multiple experimental data;

[0128] If the gas flow rate influence coefficient is greater than the gas flow rate influence coefficient threshold, it means that the gas flow rate is an influencing factor of the predicted temperature deviation, and a related influence signal is generated;

[0129] If the gas flow rate influence coefficient is less than or equal to the gas flow rate influence coefficient threshold, it means that the gas flow rate is not an influencing factor of the predicted temperature deviation, and an irrelevant influence signal is generated;

[0130] Based on the generated relevant influence signal, the gas flow rate is regulated;

[0131] In some embodiments, the gas flow rate values of all abnormal periods are obtained, and all the gas flow rate values are summed and averaged to obtain the gas flow rate average;

[0132] Obtain the air supply power value during the non-abnormal period (excluding the abnormal period), and sum and average all the air supply power values to obtain the average air supply power;

[0133] Substitute into the formula The target air supply power value PY is calculated, where VB represents the standard value of gas flow rate, VY represents the average gas flow rate, and PB represents the average air supply power;

[0134] Adjust the air supply power value to the air supply power target value;

[0135] The technical solution of the embodiment of the present invention is mainly as follows: when generating a large deviation signal, the corresponding calculation time point and prediction time point are obtained, and the gas flow rate data in the process from the start time point of the film material curing temperature rise stage to the calculation time point is obtained, the gas flow rate anomaly coefficient is calculated based on the gas flow rate data, the gas flow rate anomaly coefficient is calculated based on the calculated gas flow rate anomaly coefficient and the predicted temperature deviation ratio, the gas flow anomaly coefficient is compared with the gas flow anomaly coefficient threshold, and a relevant influence signal or an irrelevant influence signal is generated. When generating a relevant influence signal, the gas flow rate is regulated by adjusting the air supply power value, so that when the predicted temperature value deviates greatly from the standard temperature value, the influencing factors causing the deviation can be understood through analysis, and timely adjustments can be made based on the influencing factors, thereby reducing the problem of abnormal curing reaction of the film material due to temperature deviation, which affects the curing effect.

[0136] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A surface coating process for an optical component product, characterized in that: The following steps are involved: Obtain the temperature value data of the heating stage in the historical data, and compare it with the standard temperature value to obtain a valid array; By training the model with valid arrays, a temperature prediction model for the heating stage is obtained; Obtain the real-time temperature value during the heating phase, calculate the predicted temperature value based on the real-time temperature value, calculate the predicted temperature deviation value, compare the predicted temperature deviation value with the temperature deviation threshold, and generate a large deviation signal; Based on the generated large deviation signal, gas flow rate data is obtained and processed to obtain a gas flow rate anomaly coefficient; Among them, the gas flow rate anomaly coefficient is calculated by the gas flow rate anomaly duration ratio and the gas flow rate anomaly degree ratio; Obtain the gas flow rate anomaly coefficient and predicted temperature deviation value, calculate the gas flow rate influence coefficient, and evaluate and generate relevant influence signals; The gas flow rate is regulated based on the generated relevant influence signal.

2. The surface coating process of an optical element product according to claim 1, characterized in that: The process of obtaining the valid array is as follows: With time as the X-axis and temperature as the Y-axis, a two-dimensional model is established, and the standard temperature value is substituted into the two-dimensional model to draw a standard temperature curve. Obtain temperature value data of the heating stage of several groups of qualified processes in the historical data, and mark the temperature value data of the same group of heating stage as an analysis array; In an analysis array, the total time of the heating stage is divided into a number of monitoring time points, and the temperature value corresponding to each monitoring time point is compared with the temperature standard range corresponding to each monitoring time point; If the temperature value is not within the temperature standard range, an abnormal signal is generated; In the same analysis array, if there is a monitoring time point that generates an abnormal signal, the analysis data is marked as an invalid array; if there is no monitoring time point that generates an abnormal signal, the analysis array is marked as a valid array.

3. The surface coating process of an optical element product according to claim 1, characterized in that: The process of obtaining the predicted temperature deviation value is as follows: During the temperature rise phase of the film material curing step, the real-time temperature value of each monitoring time point in the temperature rise phase is obtained, and the time period between two adjacent monitoring time points is marked as a prediction period; Mark the real-time monitoring time point as the calculation time point, substitute the real-time temperature value at the calculation time point into the temperature prediction model, calculate the theoretical time value corresponding to the real-time temperature value, and sum the theoretical time value with the prediction period to obtain the analysis time value; Substitute the analysis time value into the temperature prediction model to obtain the predicted temperature value corresponding to the analysis time value; The predicted temperature value at the predicted time point is calculated with the standard temperature value corresponding to the predicted time point, and the absolute value of the difference is taken to obtain the predicted temperature deviation value.

4. The surface coating process for an optical component product according to claim 1, characterized in that: The process of generating a large deviation signal is as follows: Obtain a predicted temperature deviation value, and compare the predicted temperature deviation value with a temperature deviation threshold; if the predicted temperature deviation value is greater than the temperature deviation threshold, generate a large deviation signal.

5. The surface coating process of an optical element product according to claim 1, characterized in that: The process of obtaining the gas flow rate anomaly coefficient is as follows: Substitute the ratio of gas flow rate abnormality duration and gas flow rate abnormality degree ratio into the formula The gas flow rate anomaly coefficient XS is calculated, where SC represents the proportion of gas flow rate anomaly duration, CD represents the gas flow rate anomaly degree ratio, and s1 and s2 are preset proportional coefficients.

6. The surface coating process for an optical component product according to claim 5, characterized in that: The process of obtaining the abnormal duration ratio of gas flow rate is as follows: Obtain the predicted time point and calculation time point corresponding to the generation of the large deviation signal, define the time point from the start of the heating phase to the calculation time point as the judgment period, and divide the judgment period into several sub-judgment periods; Acquire real-time gas flow rate value data for each sub-judgment period in the film material curing step; Compare the gas flow rate value with the gas flow rate standard range; If the gas flow rate value is not within the gas flow rate standard range, a gas flow rate abnormality signal is generated; Within the sub-judgment period, the duration of the generated gas flow rate abnormal signal is obtained and marked as the abnormal period. All abnormal periods are summed up to obtain the total abnormal duration. The total abnormal duration is calculated by ratio with the duration of the sub-judgment period to obtain the proportion of the gas flow rate abnormal duration.

7. The surface coating process of an optical component product according to claim 6, characterized in that: The process of obtaining the gas flow rate abnormality ratio is as follows: In the sub-judgment period, the gas flow rate value corresponding to the abnormal period is obtained, and the relationship between the gas flow rate value of each abnormal period and the gas flow rate standard range is determined; If the gas flow rate value during the abnormal period is greater than the maximum value of the gas flow rate standard range, the maximum value of the gas flow rate value during the abnormal period is extracted and marked as the abnormal maximum value. The difference between the abnormal maximum value and the gas flow rate standard value is calculated, and the ratio of the difference to the gas flow rate standard value is calculated to obtain the abnormal deviation ratio. If the gas flow rate value during the abnormal period is less than the minimum value of the gas flow rate standard range, the minimum value of the gas flow rate value during the abnormal period is extracted and marked as the abnormal minimum value. The difference between the abnormal minimum value and the gas flow rate standard value is calculated, and the absolute value of the difference is taken and the ratio is calculated with the gas flow rate standard value to obtain the abnormal deviation ratio; All abnormal deviation ratios are summed to obtain the gas flow rate abnormality degree ratio.

8. The surface coating process for an optical component product according to claim 1, characterized in that: The process of obtaining the gas flow rate influence coefficient is as follows: Obtaining the gas flow rate anomaly coefficient for each sub-judgment period and the predicted temperature deviation value at the end time of the sub-judgment period; Calculate the difference between the gas flow rate anomaly coefficients of adjacent sub-judgment periods to obtain a change value of the gas flow rate anomaly coefficient; Calculate the difference between the predicted temperature deviation values at the end time points of adjacent sub-judgment periods to obtain a predicted temperature deviation change value; The change value of the gas velocity anomaly coefficient and the change value of the predicted temperature deviation at the same time point are marked as a comparison array; In a comparison array, if the change value of the gas flow rate anomaly coefficient and the change value of the predicted temperature deviation value change synchronously, the comparison array is marked as a synchronous change comparison array; otherwise, the comparison data is marked as an asynchronous change comparison array; Get the number of synchronous change arrays, perform ratio processing on the synchronous change comparison array and the total number of comparison arrays to obtain the proportion of the synchronous change array, which is marked as the gas flow rate influence coefficient.

9. The surface coating process for an optical component product according to claim 1, characterized in that: The process of generating relevant impact signals is as follows: obtaining a gas flow rate influence coefficient, and comparing the gas flow rate influence coefficient with a gas flow rate influence coefficient threshold; If the gas flow rate influence coefficient is greater than the gas flow rate influence coefficient threshold, a related influence signal is generated.

10. The surface coating process for an optical component product according to claim 1, characterized in that: The process of regulating the gas flow rate is as follows: Obtain the gas flow rate values of all abnormal periods, sum and average all the gas flow rate values to obtain the gas flow rate mean; Obtain the air supply power value during the non-abnormal period, sum up all the air supply power values and take the average value to obtain the air supply power average value and substitute it into the formula The target value of air supply power PY is calculated, where VB represents the standard value of gas flow rate, VY represents the average gas flow rate, and PB represents the average air supply power.

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