A method, equipment and system for testing the sealing performance of an antireflective adhesive mixing tank.

Abstract

This invention relates to the field of equipment testing technology, specifically to a method, equipment, and system for testing the sealing performance of an antireflective adhesive mixing vessel. The method involves collecting pressure data, temperature data from different locations, and historical normal data from the antireflective adhesive mixing vessel. Based on the temperature data from different locations, several time intervals are defined where the temperature variation exceeds a specified threshold, ensuring the rationality of the time interval division and providing valuable time intervals for subsequent analysis. Based on different time intervals and pressure data, the relationship between temperature and pressure is determined for each time interval. Furthermore, based on the relationship value, temperature data, and historical normal data, the degree of influence of temperature on pressure in each time interval is determined, thus determining the sealing performance test result. Considering the influence of temperature on pressure in different time intervals helps improve the accuracy of the sealing performance test results.

Description

Technical Field

[0001] This invention relates to the field of equipment testing technology, specifically to a method, equipment, and system for testing the sealing performance of an antireflective adhesive mixing vessel. Background Technology

[0002] Antireflective adhesives are widely used in precision manufacturing processes such as semiconductors and optical components. Their mixing process is usually completed in a closed mixing vessel. A mixing vessel is a closed container that can achieve heating, evaporation, cooling and mixing functions through structural design and parameter configuration, and complete multiphase reactions such as gas-liquid, liquid-liquid and gas-liquid-solid reactions. The core structure consists of a vessel body, a stirring device, a heat transfer device and a sealing device. The reaction temperature is maintained by a jacket or a coil, and a high-pressure environment is maintained by mechanical seals or magnetic seals. Its working principle is based on the chemical reaction of materials under specific temperature, pressure and stirring conditions.

[0003] During long-term use, mixing reactors may experience a decline in sealing performance due to aging of seals, micro-cracks in welds, or flange deformation, leading to material leakage. This not only affects product quality but may also pose safety hazards. Currently, sealing inspection of mixing reactors largely relies on manual inspection or low-precision pressure maintenance tests, such as judging airtightness by the stability of the gas pressure inside the reactor, which will show a significant pressure change when a leak is present. However, antireflective adhesives contain solvents, and the gas pressure changes significantly with different temperatures. During the mixing process of antireflective adhesives, stirring, heating, or cooling all cause dynamic temperature changes. Temperature fluctuations can be superimposed on pressure data (e.g., pressure data increases), masking the true leakage signal. Therefore, judging leakage solely based on pressure data is prone to misjudgment. Summary of the Invention

[0004] To address the aforementioned technical problems, the present invention aims to provide a method, equipment, and system for testing the sealing performance of an antireflective adhesive mixing vessel. The specific technical solution adopted is as follows:

[0005] In a first aspect, embodiments of this application provide a method for testing the sealing performance of an antireflective adhesive mixing vessel, including:

[0006] Collect pressure data, temperature data at different locations, and historical normal data from the antireflective adhesive mixing reactor.

[0007] Based on the temperature data from different locations, several time intervals are divided, and the temperature change within each time interval is greater than a specified threshold.

[0008] Based on different time intervals and pressure data, determine the relationship value between temperature and pressure in each time interval, and based on the relationship value, the temperature data, and the historical normal data, determine the degree of influence of temperature on pressure corresponding to each time interval.

[0009] Based on the pressure data and the degree of each of the aforementioned effects, the sealing test results are determined.

[0010] In one implementation, dividing the time intervals based on the temperature data from different locations includes:

[0011] Based on the temperature data from different locations, calculate the average temperature at each moment to determine the average temperature sequence;

[0012] Determine the change in the average temperature at each pair of adjacent time points in the average temperature sequence;

[0013] According to the chronological order, the changes are accumulated starting from the earliest moment, and the normalized value of the accumulated result is calculated. When the normalized value is greater than a specified threshold, the corresponding end moment is determined. The earliest moment to the end moment is a time interval.

[0014] Take the end time as the new earliest time, and return to the step of accumulating the change from the earliest time according to the chronological order, until several time intervals are divided.

[0015] In one implementation, determining the relationship between temperature and pressure in each time interval based on different time intervals and the pressure data includes:

[0016] Based on the pressure data, determine the trend term of the pressure data, and determine the pressure trend curve based on the trend term;

[0017] Determine the average slope and pressure change range of the pressure trend curve in each time interval, and determine the maximum pressure change range;

[0018] In each of the time intervals, the first product of the average slope and the maximum pressure change range is determined, and the relationship between temperature and pressure in each time interval is determined based on the ratio of the first product to the corresponding cumulative result.

[0019] In one implementation, determining the degree of influence of temperature on pressure for each time interval based on the relationship value, the temperature data, and the historical normal data includes:

[0020] Calculate the mean temperature for each time interval based on the time interval and the temperature data.

[0021] Based on the average temperature of each interval, determine the historical time interval corresponding to the average temperature of each interval in the historical normal data;

[0022] Based on the historical normal data, each historical time interval, the average temperature of each interval, and the relationship between temperature and pressure in each time interval, the degree of influence of temperature on pressure in each time interval is determined.

[0023] In one implementation, determining the degree of influence of temperature on pressure for each time interval based on the historical normal data, each historical time interval, the average temperature of each interval, and the relationship value between temperature and pressure in each time interval includes:

[0024] Based on the historical normal data, determine the number of historical time intervals corresponding to each of the interval temperature averages, the duration of each of the historical time intervals, and the historical relationship value of each of the historical time intervals;

[0025] Determine the relationship between temperature and pressure in each time interval and the historical relationship between the corresponding historical time intervals;

[0026] The normalized time length of each historical time interval is determined based on the normalization function and the time length of each interval.

[0027] The normalized time length of each historical time interval is determined by a second product of the difference in the relationship, and the second product and the number of corresponding historical time intervals are accumulated to obtain the degree of influence of temperature on pressure for each time interval.

[0028] In one implementation, determining the sealing test result based on the pressure data and each of the aforementioned degrees of influence includes:

[0029] Based on the pressure data, a first vibration term of the pressure data in each time interval is determined, and based on the historical normal data, a second vibration term of the corresponding historical time interval is determined.

[0030] Based on the first vibration term and the second vibration term, the pressure change in each time interval is determined respectively;

[0031] The leakage probability is determined based on the pressure changes and the degree of impact in each of the aforementioned time intervals.

[0032] The sealing test result is determined based on the leakage probability and leakage threshold.

[0033] In one embodiment, determining the pressure change in each time interval based on the first vibration term and the second vibration term includes:

[0034] Based on the first vibration term, determine the first amplitude average value and the first amplitude variance corresponding to each time interval, and based on the second vibration term, determine the second amplitude average value and the second amplitude variance corresponding to each historical time interval.

[0035] The amplitude difference corresponding to each time interval is determined based on the first amplitude average value and the second amplitude average value, and the amplitude variance difference corresponding to each time interval is determined based on the first amplitude variance and the second amplitude variance.

[0036] The pressure changes in each time interval are determined based on the amplitude difference and the amplitude variance difference, respectively.

[0037] In one implementation, determining the leakage probability based on the pressure changes and the degree of influence in each of the time intervals includes:

[0038] For each of the aforementioned time intervals, determine the third product of the corresponding pressure change and the degree of influence;

[0039] The leakage probability is determined by summing the third product and the number of time intervals.

[0040] Secondly, embodiments of this application provide a sealing performance testing system for an antireflective adhesive mixing vessel, comprising:

[0041] The data acquisition module is used to collect pressure data, temperature data at different locations, and historical normal data in real time from the antireflective adhesive mixing tank.

[0042] The segmentation module is used to divide the temperature data at different locations into several time intervals, wherein the temperature change within the time interval is greater than a specified threshold.

[0043] The determination module is used to determine the relationship value between temperature and pressure in each time interval based on different time intervals and pressure data, and to determine the degree of influence of temperature on pressure in each time interval based on the relationship value, the temperature data and the historical normal data.

[0044] The detection module is used to determine the sealing test result based on the pressure data and the degree of each of the aforementioned effects.

[0045] Thirdly, embodiments of this application provide an electronic device, including: a processor and a memory, wherein the memory stores instructions that are loaded and executed by the processor to implement the methods in any of the above-described embodiments.

[0046] The present invention has the following beneficial effects:

[0047] By collecting pressure data from the antireflective adhesive mixing vessel, temperature data from different locations, and historical normal data, several time intervals with temperature variations exceeding a specified threshold are defined based on the temperature data from different locations. This ensures the rationality of the time interval division and provides valuable time intervals for subsequent analysis. Based on different time intervals and pressure data, the relationship between temperature and pressure in each time interval is determined. Furthermore, based on the relationship value, temperature data, and historical normal data, the degree of influence of temperature on pressure in each time interval is determined, thus confirming the sealing performance test results. Considering the influence of temperature on pressure in different time intervals helps improve the accuracy of the sealing performance test results. Attached Figure Description

[0048] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic flowchart of a method for testing the sealing performance of an antireflective adhesive mixing vessel according to an embodiment of the present invention;

[0050] Figure 2 This is a structural block diagram of an antireflective adhesive mixing tank sealing performance testing system provided in one embodiment of the present invention;

[0051] Figure 3 This is a structural block diagram of an electronic device provided according to an embodiment of the present invention. Detailed Implementation

[0052] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method, device, and system for testing the sealing performance of an antireflective adhesive mixing vessel according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0054] It should be noted that "exemplary" in the embodiments of this application refers to examples listed for ease of explanation, and other embodiments are not limited to the listed examples.

[0055] The following description, in conjunction with the accompanying drawings, details the specific scheme of the antireflective adhesive mixing vessel sealing test method, equipment, and system provided by the present invention.

[0056] Please see Figure 1 The diagram illustrates a flowchart of a method for testing the sealing performance of an antireflective adhesive mixing vessel according to an embodiment of the present invention. This method may include at least steps S100-S400:

[0057] S100: Collect pressure data, temperature data at different locations, and historical normal data from the antireflective adhesive mixing vessel.

[0058] S200. Based on temperature data from different locations, divide the time intervals into several time intervals, where the temperature change within each time interval exceeds a specified threshold.

[0059] S300. Based on different time intervals and pressure data, determine the relationship between temperature and pressure in each time interval, and based on the relationship value, temperature data, and historical normal data, determine the degree of influence of temperature on pressure in each time interval.

[0060] S400. Determine the sealing test results based on the pressure data and the degree of each impact.

[0061] The technical solution of this application embodiment collects pressure data, temperature data at different locations, and historical normal data from the antireflective adhesive mixing vessel. Based on the temperature data at different locations, it divides the time intervals into several time intervals where the temperature change exceeds a specified threshold, ensuring the rationality of the time interval division and providing time intervals with reference value for subsequent analysis. Based on different time intervals and pressure data, it determines the relationship value between temperature and pressure in each time interval, and determines the degree of influence of temperature on pressure corresponding to each time interval based on the relationship value, temperature data, and historical normal data, thus determining the sealing test result. Considering the influence factors of temperature on pressure corresponding to different time intervals helps to improve the accuracy of the sealing test result.

[0062] In one embodiment, in step S100, a pressure sensor is installed on the antireflective adhesive mixing vessel to collect pressure data of the vessel in real time, in kPa, at a sampling frequency of 1Hz (i.e., 1 point per second). Other embodiments use a sampling frequency set based on actual conditions. In this embodiment, when collecting pressure data, a flanged pressure tap is opened on the vessel body, and a short pipe connects the pressure tap to the pressure sensor. A diaphragm seal (filled with inert oil) is installed at the front end of the pressure sensor, or the pressure sensor itself is a flanged diaphragm sensor type. This prevents the pressure sensor from directly contacting the viscous liquid. The diaphragm is resistant to high temperatures and chemical media, providing a fast and stable response, ensuring the accuracy of the pressure data. Additionally, temperature sensors (Pt100 or thermocouples) can be installed on the walls of the antireflective adhesive mixing vessel at multiple different locations to acquire temperature data at different locations in real time, in °C, at a sampling frequency of 0.2Hz (i.e., 1 point per 5 seconds). Other embodiments use a sampling frequency set based on actual conditions.

[0063] It should be noted that the antireflective adhesive is a viscous liquid. Even with tiny solid or liquid gaps, the liquid itself will not overflow rapidly due to viscosity resistance. Early leakage is mainly manifested as vapor or gas phase escape, rather than obvious liquid leakage signals. Therefore, its airtightness is directly tested by pressure. However, when gas leakage occurs, the pressure in the mixing vessel will change. The antireflective adhesive is not a pure solvent, but a solvent plus polymers, etc. Temperature changes will significantly lead to pressure changes. At the same time, mechanical vibration and stirring during processing will change the air vapor phase (especially near the liquid surface or under high-speed conditions). Liquid surface fluctuations change the head space volume, and slight gas seepage can be amplified by mechanical action during stirring. These pressure changes will significantly interfere with airtightness analysis by pressure. Therefore, this application also introduces temperature data for assistance to reduce interference.

[0064] Meanwhile, in step S100, historical normal data is acquired. During a complete mixing process of the reflective adhesive mixing kettle under normal operating conditions (i.e., normal sealing), the collected data is recorded as historical normal data. It can be understood that historical normal data includes historical normal pressure data and historical normal temperature data at various locations.

[0065] In one implementation, step S200 includes steps S201-S204:

[0066] S201. Based on the temperature data at different locations, calculate the average temperature at each moment to determine the average temperature sequence.

[0067] Optionally, each temperature sensor can acquire temperature data at a specific location. Based on the acquisition time of the temperature data, the average temperature at each moment can be calculated. For example, assuming that at a certain moment, the temperature value measured at location A is 50℃, the temperature value measured at location B is 60℃, and the temperature value measured at location C is 70℃, then the average temperature at that moment is 60℃. Therefore, a corresponding average temperature can be obtained for each moment, and all moments and their corresponding average temperatures can form a sequence of average temperature values.

[0068] S202. Determine the change in the average temperature at any two adjacent time points in the average temperature sequence.

[0069] Optionally, determine the change in the average temperature at each pair of adjacent time points in the temperature average sequence. Or it can also be called a first-order difference.

[0070] S203. According to the chronological order, the changes are accumulated starting from the earliest time, and the normalized value of the accumulated result is calculated. When the normalized value is greater than the specified threshold, the corresponding end time is determined. The earliest time to the end time is a time interval.

[0071] Optionally, after determining the change in the average temperature at each pair of adjacent times... Then, based on the chronological order, the changes are accumulated starting from the earliest moment to obtain the accumulated result. Then calculate the cumulative result. normalized value ', the normalized value 'Characterizes the accumulated result' The temperature variation range of the candidate time interval. Among them, when the normalized value When the value is greater than a specified threshold (0.35 for example), the corresponding end time is determined, and the earliest time to the end time is a time interval.

[0072] For example, since temperature data is continuously acquired (i.e., the data in the temperature average sequence is constantly increasing), when determining the cumulative result, assuming the earliest time is 13:00:00, for example, if the current time is 13:01:00, then 13:00:00 to 13:01:00 is a candidate time interval. If the corresponding normalized value is calculated... If the value is greater than 0.35, then 13:01:00 is the end time, and the candidate time interval at this point is determined as the divided time interval. Conversely, if the corresponding normalized value... If the value is less than or equal to 0.35, continue acquiring data, for example, up to 13:01:30. At this point, a candidate time interval from 13:00:00 to 13:01:30 is determined, and the value is normalized. If the value is greater than 0.35, then the time interval is determined to be from 13:00:00 to 13:01:30 (this is the end time). Therefore, it is guaranteed that the temperature change range within the final time interval must be greater than the specified threshold of 0.35.

[0073] S204. Take the end time as the new earliest time and return to the step of accumulating the changes starting from the earliest time according to the chronological order, until several time intervals are divided.

[0074] Optionally, assuming the time interval is determined to be from 13:00:00 to 13:01:30, then the end time 13:01:30 is taken as the new earliest time. The process returns to the step of accumulating the changes starting from the earliest time, based on the chronological order. As time progresses, the next time interval can be determined based on the data in the temperature average sequence. Thus, as time continues to pass, several time intervals can be divided. It should be noted that the "until" division of several time intervals in this embodiment can mean dividing at least two time intervals, then using these two time intervals as a starting point, performing an analysis of the subsequent steps after determining the two time intervals, and then performing a subsequent calculation for each additional time interval; or setting a preset number of time intervals, performing a subsequent calculation when the number of time intervals reaches the preset number, and then setting a moving time window. As new time intervals are continuously determined, the time window for subsequent calculations is determined based on the moving time window, and then the subsequent calculations are performed. No specific limitation is made.

[0075] It should be noted that the temperature in the mixing vessel significantly affects pressure changes (because solvent vapor pressure is temperature-sensitive, and the opening of heat exchangers, heating coils, or steam valves directly alters the evaporation / condensation balance in the head space). Directly relying on pressure changes to confirm leaks leads to significant distortion. This application's embodiments consider the impact of temperature changes on pressure data. A significant change in the coupling relationship between temperature and pressure data may indicate a potential leak risk. For example, if the original pressure data also increased significantly with rising temperature, but the pressure data is lower at the current temperature, it suggests a possible leak causing the pressure drop.

[0076] In one implementation, step S300 determines the relationship between temperature and pressure in each time interval based on different time intervals and pressure data, including S301-S303:

[0077] S301. Based on the pressure data, determine the trend term of the pressure data, and determine the pressure trend curve based on the trend term.

[0078] For example, pressure data can be processed using methods such as Smoothing Prior Analysis (SPA), Empirical Mode Decomposition (EMD), Variational Mode Decomposition (VMD), and ARIMA algorithms to fit trend and periodic components. The residuals can be considered as vibration / random terms, thus obtaining the trend and vibration terms of the pressure data. In this embodiment, the ARIMA algorithm is used. Then, pressure trend curves can be plotted based on each trend term. It should be noted that when leakage exists, the pressure trend should decrease at the same temperature. Therefore, analyzing the trend over a long period can reveal the leakage situation. Furthermore, the trend changes with temperature, so the influence of temperature must be considered when performing trend analysis.

[0079] S302. Determine the average slope and pressure variation range of the pressure trend curve for each time interval, and determine the maximum pressure variation range.

[0080] Optionally, the average slope of the pressure trend curve in each time interval can be determined. and the extreme difference in pressure changes And determine the maximum pressure variation range. .

[0081] The slope and range can be determined using existing methods. For the first The average slope of the pressure trend curve over a given time interval. For the first The pressure change range corresponding to the pressure trend curve in each time interval is used to determine the largest pressure change range from all pressure change ranges. .

[0082] S303. Determine the first product of the average slope and the maximum pressure change range in each time interval, and determine the relationship between temperature and pressure in each time interval based on the ratio of the first product to the corresponding cumulative result.

[0083] Optionally, the average slope in each time interval can be determined separately. The range of the largest pressure change First product And based on the first product and the corresponding summation result respectively The ratio of these values ​​determines the relationship between temperature and pressure in each time interval.

[0084] Specifically, the formula is:

[0085]

[0086] In the formula, For the first The relationship between temperature and pressure over a given time interval. For the first The cumulative results corresponding to each time interval; The larger the value, the more significant the effect of temperature change on pressure change, indicating a stronger synergistic relationship between temperature and pressure. It should be noted that when calculating using the above formula, dimensions can be disregarded. However, to ensure consistency in the numerical range, the relevant parameters used in the formula can be normalized before calculation.

[0087] In one implementation, step S300 determines the degree of influence of temperature on pressure for each time interval based on the relationship value, temperature data, and historical normal data, including steps S304-S306:

[0088] S304. Based on the time interval and temperature data, calculate the average temperature of each time interval.

[0089] It should be noted that, The relationship value is determined by considering the impact of temperature changes on pressure. However, since the relationship between pressure and temperature is not linear, the same change in temperature will have different effects on pressure at different temperatures. Therefore, it is necessary to perform controlled variable analysis on the temperature data and calculate the mean temperature for each time interval. (i.e., the first) The average temperature of each time interval, as the corresponding first time interval. The temperature corresponding to each time interval. Among them, the mean temperature of each time interval. and relation values A two-dimensional space can be constructed, with the horizontal axis as... The vertical axis is .

[0090] S305. Obtain historical normal data, and determine the historical time interval corresponding to the average temperature of each interval in the historical normal data based on the average temperature of each interval.

[0091] Then, based on the average temperature of each interval By identifying historical normal data, the average temperature for each interval can be calculated. The historical time interval corresponding to the same historical average temperature is denoted as the th. The historical time interval, when compared with the first time intervals The first corresponding to the same historical average temperature A historical time interval.

[0092] S306. Based on historical normal data, each historical time interval, the average temperature of each interval, and the relationship between temperature and pressure in each time interval, determine the degree of influence of temperature on pressure in each time interval.

[0093] First, based on historical normal data, determine the number of historical time intervals corresponding to the average temperature of each interval, the duration of each historical time interval, and the historical relationship value of each historical time interval.

[0094] Among them, using represent The quantity, i.e. The corresponding historical time interval Quantity, The duration of each historical time interval, i.e. The corresponding time length, Representing each historical time interval Historical relationship values, calculated as follows: The difference is that the historical time interval is determined based on the currently defined time interval, which will not be elaborated further.

[0095] Secondly, determine the differences between the relationship values ​​of temperature and pressure in each time interval and the historical relationship values ​​of the corresponding historical time intervals. .

[0096] Then, based on the normalization function respectively and the length of each time Determine the normalized time length for each historical time interval. .

[0097] Finally, the normalized time length for each historical time interval is determined. Differences between each relation The second product The influence of temperature on pressure in each time interval is obtained by summing the second product and the number of corresponding historical time intervals. The specific formula is as follows:

[0098]

[0099] in, Indicates the first The degree of influence of temperature on pressure corresponding to each time interval is also called the first time interval. The deviation of each time interval from historical normal data; when The larger it is, the more it indicates the first Within a given time interval, the temperature effect is insufficient to support the possibility of an abnormal leak due to the current pressure deviation, i.e., the [missing information]. The greater the influence of temperature on pressure within a given time interval, the smaller the effect.

[0100] It should be noted that simply analyzing the relationship between temperature and pressure when performing pressure data analysis can be subject to interference. For example, bubbles or vapor-phase dissolution during processing can cause pressure changes. Furthermore, temperature changes may require a certain period of observation. For instance, in the case of a prolonged leak (i.e., a period encompassing multiple time intervals), the pressure will exhibit baseline drift (continuously decreasing to a certain level). However, at the initial stage of a leak, its impact on the overall pressure is not significant. Therefore, further analysis of the fluctuations is needed to comprehensively quantify the probability of a leak risk. Also, the above analysis is based on a prolonged and significant leak. However, in the initial stage of a leak, the pressure fluctuation trend is small and cannot be directly analyzed. When analyzing pressure data, it is necessary to consider the fluctuations within each time interval (i.e., individual time intervals, which can be understood as short periods relative to the aforementioned prolonged periods). These fluctuations can be analyzed based on vibration terms.

[0101] In one embodiment, step S400 includes steps S401-S404:

[0102] S401. Based on the pressure data, determine the first vibration term of the pressure data in each time interval, and based on the historical normal data, determine the second vibration term of each corresponding historical time interval.

[0103] Optionally, as described above, the pressure data and the historical normal pressure data in the historical normal data can be processed separately using the ARIMA algorithm to determine the first vibration term of the pressure data in each time interval and the corresponding second vibration term of each historical time interval.

[0104] S402. Determine the pressure change in each time interval based on the first vibration term and the second vibration term respectively.

[0105] First, based on the first vibration term, determine the first amplitude average (i.e., the average value calculated based on all amplitudes of the first vibration term within the time interval) and the first amplitude variance (i.e., the variance calculated based on all amplitudes of the first vibration term within the time interval). Then, based on the second vibration term, determine the second amplitude average and the second amplitude variance for each corresponding historical time interval.

[0106] Secondly, based on the first amplitude average value and the second amplitude average value, the amplitude difference corresponding to each time interval is determined, and based on the first amplitude variance and the second amplitude variance, the amplitude variance difference corresponding to each time interval is determined.

[0107] For example, the amplitude difference for each time interval can be determined based on the absolute value of the difference between the first average amplitude and the second average amplitude, respectively. That is, the first The amplitude difference corresponding to each time interval; and the amplitude variance difference corresponding to each time interval determined based on the absolute value of the difference between the first amplitude variance and the second amplitude variance, respectively. That is, the first The amplitude variance difference corresponding to each time interval.

[0108] It should be noted that, under leak-free conditions, the pressure changes in the antireflective adhesive mixing vessel mainly originate from: periodic minor disturbances caused by stirring (small amplitude, frequency related to stirring speed or blade characteristics), gas volume changes caused by temperature changes (slowly rising with heating and slowly falling with cooling, resulting in a relatively smooth curve), and step changes brought about by process operations (such as feeding, venting, and cooling) (rising / falling in a short time and then stabilizing).

[0109] Then, based on the amplitude difference and amplitude variance differences Determine the pressure changes in each time interval. The specific formula is:

[0110]

[0111] in, For the first The pressure changes corresponding to each time interval, when The larger it is, the more it indicates the first Initial leakage may occur within a given time period; therefore, initial leakage must be considered when analyzing the seal. It should be noted that one implementation does not consider this. , The dimensions are determined directly using the formula above. In another implementation, in order to improve To determine the accuracy, we can first... , After normalization, the average of the two results is obtained. .

[0112] S403. Determine the leakage probability based on the pressure changes and their impact in each time interval.

[0113] Specifically, the pressure changes in each time interval are determined. And the degree of impact The third product According to the third product and the number of time intervals Accumulate the results to determine the leakage probability. The specific formula is as follows:

[0114]

[0115] in, Represents the normalization function, for Perform normalization to make it take the value Pressure changes or degree of impact The greater the cumulative deviation, the higher the probability of leakage. The larger the value, the more it indicates a problem with the pressure and the need for investigation.

[0116] S404. Determine the sealing test results based on the leakage probability and leakage threshold.

[0117] For example, the leakage threshold is 0.6, when the leakage probability is... A value greater than 0.6 indicates a high risk of leakage, confirming the presence of a leak in the sealing test result. In some implementations, after confirming the presence of a leak in the sealing test result, further verification can be performed through manual testing. This facilitates early warning and detection of leaks, allowing for the discovery of leaks at an early stage and preventing larger safety issues.

[0118] Reference Figure 2 The diagram illustrates a structural block diagram of an antireflective adhesive mixing tank sealing performance testing system according to an embodiment of this application. The system may include:

[0119] The data acquisition module is used to collect pressure data, temperature data at different locations, and historical normal data in real time from the antireflective adhesive mixing tank.

[0120] The segmentation module is used to divide temperature data from different locations into several time intervals, where the temperature change within each time interval exceeds a specified threshold.

[0121] The determination module is used to determine the relationship between temperature and pressure in each time interval based on different time intervals and pressure data, and to determine the degree of influence of temperature on pressure in each time interval based on the relationship value, temperature data and historical normal data.

[0122] The detection module is used to determine the sealing test results based on pressure data and the degree of each impact.

[0123] In this embodiment of the application, the functions of each module in the system can be found in the corresponding descriptions in the above methods, and will not be repeated here.

[0124] Reference Figure 3 In one embodiment, this application also provides an electronic device, including a processor 310 and a memory 320, wherein the memory 320 stores instructions which are loaded and executed by the processor 310 to implement the above-described method for detecting the sealing performance of the antireflective adhesive mixing vessel.

[0125] It should be noted that the order of the embodiments in this application is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An anti-reflective glue compounding kettle sealing detection method, characterized in that, The method comprises: Collecting pressure data of an anti-reflection glue mixing kettle, temperature data of different positions, and obtaining historical normal data; According to the temperature data of different positions, a plurality of time intervals are divided, and the temperature change amplitude in the time intervals is greater than a specified threshold value; According to different time intervals and pressure data, the relationship value between temperature and pressure in each time interval is determined, and according to the relationship value, the temperature data and the historical normal data, the influence degree of temperature on pressure corresponding to each time interval is determined; According to the pressure data and each influence degree, a sealing detection result is determined; According to the temperature data of different positions, a plurality of time intervals are divided, and the temperature change amplitude in the time intervals is greater than a specified threshold value; According to the temperature data of different positions, the average temperature at each time is calculated to determine the average temperature sequence; The change amount of the average temperature of two adjacent time points in the average temperature sequence is determined; According to the chronological order, the change amount is accumulated from the earliest time, and the normalized value of the accumulated result is calculated, and when the normalized value is greater than a specified threshold value, the corresponding end time is determined, and the earliest time to the end time is a time interval; The end time is taken as the new earliest time, and the step of accumulating the change amount from the earliest time according to the chronological order is returned until a plurality of time intervals are divided.

2. The method of claim 1, wherein the method further comprises: determining the sealability of the anti-reflective glue mixing kettle based on the detected pressure. According to the pressure data, the trend item of the pressure data is determined, and the pressure trend curve is determined according to the trend item; The average slope and the pressure change range corresponding to the pressure trend curve in each time interval are determined, and the maximum pressure change range is determined; The first product of the average slope and the maximum pressure change range in each time interval is determined, and the relationship value between temperature and pressure in each time interval is determined according to the ratio of the first product to the corresponding accumulated result. According to the time interval and the temperature data, the interval temperature mean value corresponding to each time interval is calculated; 3. The method of claim 1, wherein the method further comprises: determining the presence of the leak in the anti-reflective glue mixing kettle based on the detected pressure change. According to each interval temperature mean value, the historical time interval corresponding to each interval temperature mean value in the historical normal data is determined; According to the historical normal data, each historical time interval, each interval temperature mean value and the relationship value between temperature and pressure in each time interval, the influence degree of temperature on pressure corresponding to each time interval is determined. According to the historical normal data, each historical time interval, each interval temperature mean value and the relationship value between temperature and pressure in each time interval, the influence degree of temperature on pressure corresponding to each time interval is determined. ​ 4. The method of claim 3, wherein the method further comprises: determining the leak rate of the anti-reflective gum mixing kettle. ​ determining, according to the historical normal data, a quantity of the historical time intervals corresponding to each of the interval temperature mean values, a time length of each of the historical time intervals, and a historical relationship value of each of the historical time intervals; respectively determining a relationship difference between the relationship value between temperature and pressure in each of the time intervals and the historical relationship value of the corresponding historical time interval; respectively determining a normalized time length of each of the historical time intervals according to a normalization function and each of the time lengths; respectively determining a second product of the normalized time length of each of the historical time intervals and each of the relationship differences, and respectively accumulating the second product and the quantity of the corresponding historical time interval to obtain an influence degree of temperature on pressure corresponding to each of the time intervals.

5. The method of claim 3, wherein the method further comprises: determining the leak rate of the anti-reflective gum mixing kettle. The determining, according to the pressure data and each of the influence degrees, of the sealing detection result comprises: determining, according to the pressure data, a first vibration term of the pressure data in each of the time intervals, and determining, according to the historical normal data, a second vibration term of each of the corresponding historical time intervals; respectively determining a corresponding pressure change in each of the time intervals according to the first vibration term and the second vibration term; respectively determining a leakage probability according to the corresponding pressure change in each of the time intervals and the influence degree; determining, according to the leakage probability and a leakage threshold, a sealing detection result.

6. The method of claim 5, wherein the method further comprises: determining the presence of the leak in the anti-reflective glue mixing kettle based on the detected pressure change. The respectively determining, according to the first vibration term and the second vibration term, of a corresponding pressure change in each of the time intervals comprises: respectively determining, according to the first vibration term, a first amplitude mean value and a first amplitude variance corresponding to each of the time intervals, and respectively determining, according to the second vibration term, a second amplitude mean value and a second amplitude variance corresponding to each of the corresponding historical time intervals; respectively determining, according to the first amplitude mean value and the second amplitude mean value, an amplitude difference corresponding to each of the time intervals, and respectively determining, according to the first amplitude variance and the second amplitude variance, an amplitude variance difference corresponding to each of the time intervals; respectively determining, according to the amplitude difference and the amplitude variance difference, a corresponding pressure change in each of the time intervals.

7. The method of claim 5, wherein the method further comprises: determining the leak rate of the anti-reflective gum mixing kettle. The respectively determining, according to the corresponding pressure change in each of the time intervals and the influence degree, of a leakage probability comprises: respectively determining a third product of the corresponding pressure change and the influence degree in each of the time intervals; accumulating the third product and the quantity of the time interval to determine a leakage probability.

8. An anti-reflective glue compounding kettle sealability detection system for performing the method of claim 1, wherein, The method comprises: a collection module, configured to collect, in real time, pressure data of an anti-reflection glue mixing kettle, temperature data at different positions, and obtain historical normal data; a division module, configured to divide a plurality of time intervals according to the temperature data at different positions, a temperature change range in the time intervals being greater than a specified threshold value; determining a relationship value between temperature and pressure in each of the time intervals according to the different time intervals and the pressure data, and determining an influence degree of temperature on pressure corresponding to each of the time intervals according to the relationship value, the temperature data and the historical normal data; detecting a sealing detection result according to the pressure data and each of the influence degrees.

9. An electronic device, comprising: comprising: a processor and a memory, the memory storing instructions which are loaded and executed by the processor to implement the method of any one of claims 1-7.

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