Real-time monitoring and data analysis system based on vacuum filling and sealing equipment

Abstract

The invention provides a real-time monitoring and data analysis system based on vacuum filling and sealing equipment, and relates to the technical field of data processing.The method comprises the steps that an equipment working condition data set is obtained, the change rate of temperature data and pressure data at adjacent time points is calculated, the water evaporation rate is calculated according to the change rate, and a change trend data set is obtained; comparing the temperature change rate and the pressure change rate of different position points, calculating a drying uniformity parameter, carrying out accumulative analysis on a moisture evaporation rate, calculating a moisture removal degree parameter, calculating a local temperature gradient and a local pressure gradient, and carrying out regional division on the vacuum filling and sealing equipment according to the results; temperature, pressure, drying uniformity parameters and moisture removal degree parameters in different areas are extracted, and heating time, vacuum holding time and temperature set values of corresponding areas in the vacuum filling and sealing equipment are adjusted. According to the invention, real-time monitoring and data analysis can be carried out on the vacuum filling and sealing equipment, and the drying process is regulated and controlled.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a real-time monitoring and data analysis system based on vacuum potting equipment. Background Art

[0002] Vacuum potting equipment is widely used to remove bubbles inside materials and improve the sealing performance and long-term stability of products. The existing vacuum potting process usually includes multiple stages such as pretreatment, heating, vacuuming, potting, and curing. The drying process is a key step to ensure the final quality of the product. In traditional processes, the drying process is mainly controlled by set temperature, vacuum degree and time parameters, and the moisture content or solvent residue inside the product is tested by regular sampling to determine whether the drying is sufficient. However, this control method based on fixed process parameters is difficult to adapt to changes in different materials and environmental conditions, resulting in unstable drying effects, and insufficient or excessive drying may occur.

[0003] A common vacuum drying method is to conduct heat through infrared heating or hot plate heating, and use a vacuum environment to accelerate the volatilization of water or solvents. However, the monitoring method of the existing technology mainly relies on temperature sensors and pressure sensors to collect environmental parameters, and cannot directly monitor the evaporation of water inside the product. Therefore, when local moisture residue or uneven heat distribution occurs during the drying process, the existing monitoring system is difficult to identify in time, and usually needs to rely on final product testing to discover quality problems, which may cause some products to be scrapped, thereby affecting production efficiency and product consistency. Summary of the invention

[0004] The purpose of the present invention is to provide a real-time monitoring and data analysis system based on vacuum potting equipment, aiming to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A real-time monitoring and data analysis system based on vacuum potting equipment, the system comprising:

[0007] A calculation module is used to calculate the change rate of temperature data and pressure data at adjacent time points based on the equipment operating condition data set, and calculate the water evaporation rate based on the data to obtain a change trend data set;

[0008] The analysis module is used to compare the temperature change rate and pressure change rate at different locations according to the change trend data set, calculate the drying uniformity parameter; perform cumulative analysis on the water evaporation rate, calculate the water removal degree parameter, and obtain the key parameter data set;

[0009] A regional module is used to calculate the local temperature gradient and the local pressure gradient according to the key parameter data set, and divide the vacuum potting equipment into regions according to the local temperature gradient and the local pressure gradient to obtain a dry region data set, which includes a normal region, a moisture residual region, and an over-dry region;

[0010] The feature module is used to extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters in different areas according to the drying area data set, and obtain the drying abnormality data set;

[0011] The control module is used to adjust the heating time, vacuum maintenance time and temperature setting value of the corresponding area in the vacuum potting equipment according to the drying abnormality data to ensure that the inside of the vacuum potting equipment is fully dried.

[0012] Furthermore, the calculation module includes:

[0013] A change rate calculation unit, used to calculate the change rate of temperature data and pressure data at adjacent time points according to the equipment operating condition data set, to obtain temperature change rate data and pressure change rate data;

[0014] A trend analysis unit, used to determine the fluctuation of the temperature change rate data and the pressure change rate data according to the time parameter, and form a trend parameter data set;

[0015] The water evaporation calculation unit is used to calculate the water evaporation rate according to the trend parameter data set, and merge it with the trend parameter data set to obtain the change trend data set.

[0016] Furthermore, the water evaporation calculation unit includes:

[0017] The initial rate calculation unit is used to calculate the initial water evaporation rate according to the temperature and pressure changes in the initial stage of drying. The calculation formula for the initial water evaporation rate is: ,

[0018] in, is the initial water evaporation rate, is the mass transfer coefficient of the vacuum potting equipment material surface, is the initial pressure, is the initial temperature, is the gas constant in the ideal gas law, is the latent heat of vaporization of water at room temperature and pressure, is the temperature of the surface of the vacuum potting equipment material, is the initial saturated steam pressure;

[0019] The water evaporation rate calculation unit is used to calculate the water evaporation rate at any time according to the initial water evaporation rate. The calculation formula of the water evaporation rate is: ,

[0020] in, For the The evaporation rate of water at a given moment, is the index of the time, For the The temperature of the moment, For the The pressure of the moment, For the The pressure change rate at a given moment, For the The temperature change rate at time, For the The saturated steam pressure at time is the coefficient.

[0021] Furthermore, the analysis module includes:

[0022] The uniformity comparison unit is used to extract the temperature change rate and pressure change rate of different positions in the vacuum potting equipment according to the change trend data set, and compare them according to the position points to obtain temperature change comparison data and pressure change comparison data;

[0023] A uniformity parameter calculation unit is used to calculate the mean and variance of the temperature change rate and the pressure change rate according to the temperature change comparison data and the pressure change comparison data, and perform standardization processing on them to obtain the temperature uniformity parameter and the pressure uniformity parameter;

[0024] A uniformity determination unit is used to screen the temperature uniformity parameter and the pressure uniformity parameter according to a preset uniformity threshold group. When the temperature uniformity parameter and the pressure uniformity parameter are both less than the preset uniformity threshold group, the position point is marked as a dry uniform point. When any one of the temperature uniformity parameter and the pressure uniformity parameter is not less than the preset uniformity threshold group, the position point is marked as a dry non-uniform point to obtain a dry uniformity parameter.

[0025] The water evaporation calculation unit is used to calculate the water evaporation at different locations in different time periods according to the water evaporation rate in the change trend data set, and accumulate the water evaporation at each location to obtain the water removal degree parameter.

[0026] Furthermore, the calculation formula of the moisture removal degree parameter is: ;

[0027] in, For the Moisture removal parameters of vacuum potting equipment at all times, is the time index, is the initial moment, is the total dry area of ​​the vacuum potting equipment, is the total moisture content in the entire drying area at the initial moment, is the cumulative amount of moisture removed at a certain point, is the total amount of water removed at all locations.

[0028] Furthermore, the regional module includes:

[0029] A gradient calculation unit is used to calculate the local temperature gradient and the local pressure gradient at different positions according to the temperature change rate and the pressure change rate to obtain a gradient data set;

[0030] A grid processing unit, used to divide the drying space in the vacuum potting equipment into a plurality of grid units according to the position points, each grid unit containing the temperature gradient and pressure gradient data of the corresponding position point;

[0031] The threshold determination unit is used to screen the local temperature gradient and local pressure gradient of each grid unit according to the preset gradient threshold group. When the temperature gradient or pressure gradient exceeds the preset threshold, the grid unit is marked as an abnormal candidate area to obtain preliminary area classification data.

[0032] Furthermore, the regional module also includes:

[0033] The adjacent region merging unit is used to check the gradient data sets of adjacent grid cells according to the preliminary region classification data, and merge the regions with similar temperature gradient and pressure gradient to obtain optimized region data;

[0034] A moisture removal analysis unit is used to determine whether the drying state of different areas is uniform according to the moisture removal degree parameter of the optimized area data. When the moisture removal degree parameter of a certain area is lower than a preset moisture removal threshold, the boundary range of the area is adjusted and the area is reclassified as a moisture residual area.

[0035] A moisture residual determination unit, for identifying, based on the result of the moisture removal analysis unit, an area where the moisture removal degree parameter is lower than a preset moisture removal threshold and the temperature change rate is lower than a preset temperature change rate, and marking it as a moisture residual area;

[0036] The over-drying determination unit is used to identify, based on the temperature gradient and the drying uniformity parameter, an area where the temperature change rate is higher than a preset temperature change rate and the drying uniformity parameter is lower than a preset drying uniformity, and mark it as an over-drying area.

[0037] Furthermore, the feature module includes:

[0038] The abnormal data screening unit is used to screen and extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters of the moisture residual area and the over-drying area according to the drying area data set, and eliminate the data of the normal area to obtain the characteristic parameter data set;

[0039] An abnormal characteristic calculation unit, used to calculate the temperature fluctuation range, pressure fluctuation range and water evaporation rate change range of each abnormal area and the abnormal characteristic data set according to the characteristic parameter data set;

[0040] The abnormal area feature unit is used to subdivide the moisture residual area and the over-dry area according to the abnormal feature data set and the preset feature threshold group to obtain a subdivided area set, and extract the abnormal area features therefrom to obtain a dry abnormal data set.

[0041] Furthermore, the control module includes:

[0042] The abnormal area parameter unit is used to extract the temperature, pressure, drying uniformity parameter and moisture removal degree parameter corresponding to the abnormal area according to the drying abnormality data set to obtain the abnormal area parameter set;

[0043] A control parameter calculation unit, used to calculate a heating time adjustment value, a vacuum maintenance time adjustment value and a temperature setting value adjustment value for each abnormal area according to the abnormal area parameter set, to obtain a control parameter data set;

[0044] A control unit is used to control the vacuum filling equipment according to the control parameter data set to ensure the overall uniformity of the drying process;

[0045] The real-time adjustment unit is used to make real-time adjustments to the control process according to the real-time monitoring data during the drying process to ensure the uniformity of drying in different areas during the drying process.

[0046] Furthermore, the control unit includes:

[0047] The moisture residual area adjustment unit is used to increase the temperature setting value of the area and extend the vacuum maintenance time according to the control parameters of the moisture residual area to ensure the moisture removal effect;

[0048] An over-drying area adjustment unit is used to reduce the heating time of the area and adjust the temperature setting value according to the control parameters of the over-drying area to avoid local over-drying;

[0049] The global optimization unit is used to adjust the drying strategy of the entire vacuum filling equipment according to the control parameter data set of each abnormal area to ensure the overall uniformity of the drying process.

[0050] The above solution of the present invention includes at least the following beneficial effects:

[0051] The present invention can extract the temperature change rate and pressure change rate at different positions, and calculate the uniformity parameters, so as to effectively identify the uniformity of different areas during the drying process. The drying uniformity parameters are mainly calculated by the standard deviation of the temperature and pressure data. The parameters can intuitively reflect the drying status of different positions in the equipment. When the temperature change rate of a certain area is much higher than that of other areas, it may mean that the area is overheated, while the temperature fluctuations in some areas are small, which may mean that the moisture has not been completely evaporated. By calculating the uniformity parameters and comparing them with the preset thresholds, the system can automatically identify the uniformly dried areas and the unevenly dried areas, and optimize the drying strategy in the subsequent regulation process, so as to improve the drying consistency of the entire equipment, reduce product quality differences, and improve production yield.

[0052] The present invention can dynamically divide the drying area by calculating the local temperature gradient and pressure gradient, and generate a drying area data set based on the data, which includes a normal area, a moisture residual area and an over-drying area. The core advantage of regional division is that it can accurately classify according to the thermodynamic characteristics of the spatial position points. When the temperature change rate of a certain area is small but the moisture evaporation rate is low, the system will identify the area as a moisture residual area. If the temperature change rate of a certain area is too high but the moisture removal amount is large, it may belong to an over-drying area. Based on the regional division technology, the system can realize accurate monitoring and refined control of different areas, avoid the problem of local uneven drying caused by global parameter settings, and further improve the stability of drying quality.

[0053] The present invention can calculate the water evaporation rate through the temperature change rate and the pressure change rate, and generate a change trend data set. The trend data set can reflect the dynamic process of water evaporation inside the material, so as to accurately evaluate the water removal situation. Compared with the prior art, the core advantage of this method is that it can dynamically adjust the drying time to ensure that the water evaporation rate is always maintained within a reasonable range. When the temperature rises rapidly, the water evaporates faster, and in the later stage of drying, the evaporation rate slows down. The system can avoid the problem of over-drying or under-drying by adjusting the temperature or vacuum degree. The method can detect abnormal conditions of water evaporation in real time. The system can instantly identify areas where there may be residual water and adjust parameters for compensation. This adaptive adjustment based on trend analysis makes the system more intelligent and precise than traditional methods, and improves the control accuracy of water removal.

[0054] The present invention dynamically adjusts the heating time, vacuum maintenance time and temperature setting value of the vacuum filling equipment through drying abnormality data to ensure optimal control of the drying process. The core advantage of the regulation module is that it adopts closed-loop control logic. It first calculates the current drying state through the data acquisition and calculation module, and then identifies the abnormal area through the analysis module and the area module. Finally, according to the feedback mechanism of the regulation module, the heating or vacuum parameters are dynamically adjusted, and the drying strategy is optimized in real time. The closed-loop control strategy can automatically adjust the drying parameters according to different batches, different materials and different environmental conditions, avoid the instability of artificially set parameters, and improve the degree of automation of the production process.

[0055] By analyzing the drying area data set, the present invention can extract the characteristic data of the moisture residual area and the over-drying area, and generate a drying abnormality data set for accurately diagnosing drying abnormalities. The technical advantage of this function is that it can extract the temperature fluctuation range, pressure fluctuation range and moisture evaporation rate variation range of the abnormal area, and calculate the abnormal characteristic parameters based on these data. These parameters can be used to determine whether there is unevenness in the drying process. When the temperature fluctuation range of a certain area is greater than the threshold, it indicates that the area may have excessive local heating. When the moisture evaporation rate of a certain area is lower than the preset standard, it may mean insufficient moisture removal. Combining multiple abnormal characteristic parameters, different abnormal types can be further subdivided to improve the system's abnormality diagnosis capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flowchart of a real-time monitoring and data analysis system based on vacuum potting equipment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a real-time monitoring and data analysis system based on vacuum potting equipment, the system comprising:

[0059] A calculation module is used to calculate the change rate of temperature data and pressure data at adjacent time points based on the equipment operating condition data set, and calculate the water evaporation rate based on the data to obtain a change trend data set;

[0060] The analysis module is used to compare the temperature change rate and pressure change rate at different locations according to the change trend data set, calculate the drying uniformity parameter; perform cumulative analysis on the water evaporation rate, calculate the water removal degree parameter, and obtain the key parameter data set;

[0061] A regional module is used to calculate the local temperature gradient and the local pressure gradient according to the key parameter data set, and divide the vacuum potting equipment into regions according to the local temperature gradient and the local pressure gradient to obtain a dry region data set, which includes a normal region, a moisture residual region, and an over-dry region;

[0062] The feature module is used to extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters in different areas according to the drying area data set, and obtain the drying abnormality data set;

[0063] The control module is used to adjust the heating time, vacuum maintenance time and temperature setting value of the corresponding area in the vacuum potting equipment according to the drying abnormality data to ensure that the inside of the vacuum potting equipment is fully dried.

[0064] In an embodiment of the present invention, a calculation module is used to calculate the change rate of temperature data and pressure data at adjacent time points based on the equipment operating condition data set, and calculate the water evaporation rate based on the data to obtain a change trend data set. By calculating the water evaporation rate, the module can determine the water removal situation inside the material to avoid insufficient drying or excessive drying problems; the analysis module is used to compare the temperature change rate and pressure change rate at different positions based on the change trend data set to calculate the drying uniformity parameter; the water evaporation rate is cumulatively analyzed to calculate the water removal degree parameter to obtain the key parameter data set, which can identify whether the temperature and pressure distribution in different areas are uniform; the regional module is used to calculate the local temperature gradient and the local pressure gradient based on the key parameter data set, and Based on the regional division of the vacuum filling equipment, a drying area data set is obtained, which includes a normal area, a moisture residual area and an over-drying area, so as to realize zone monitoring and accurately locate the abnormal drying area; a feature module is used to extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters in different areas according to the drying area data set, to obtain the abnormal drying data set, automatically eliminate the normal area data, focus on analyzing the abnormal drying area, and improve the accuracy of abnormality detection; a control module is used to adjust the heating time, vacuum maintenance time and temperature setting value of the corresponding area in the vacuum filling equipment according to the abnormal drying data, to ensure that the inside of the vacuum filling equipment is fully dried, and to perform real-time control based on data feedback to improve the stability of the drying process.

[0065] Wherein, the equipment operating condition data set includes:

[0066] The temperature data, pressure data and time data of the vacuum potting equipment during the drying process are obtained to obtain the original data set, which is then preprocessed to remove redundant data, unify the unit dimensions, and obtain the equipment operating condition data set.

[0067] Specifically, temperature sensors and pressure sensors are arranged at key locations of the vacuum potting equipment, such as the heating area and inside the vacuum chamber;

[0068] Use a high-frequency sampling mechanism, such as 10 samples per second, to obtain temperature and pressure data during the drying process to ensure data continuity and integrity;

[0069] Record timestamps and store temperature and pressure data synchronously with time for subsequent analysis.

[0070] Denoising: Eliminate signal noise through mean filtering or median filtering to improve data stability;

[0071] Unit standardization: Unify the data from different sensors to the same dimension, such as converting temperature to Kelvin and pressure to Pascal to ensure data consistency;

[0072] Abnormal data elimination: Use sliding window algorithm to identify and eliminate mutation data, such as abnormally high or low temperature or pressure values ​​at a certain point in time, to avoid misleading subsequent analysis.

[0073] The preprocessed data is stored in a local database or sent to a central computing system via wireless communication;

[0074] A real-time streaming processing architecture is adopted to ensure the real-time nature of data and support dynamic analysis by subsequent computing modules.

[0075] In a preferred embodiment of the present invention, the calculation module includes:

[0076] A change rate calculation unit, used to calculate the change rate of temperature data and pressure data at adjacent time points according to the equipment operating condition data set, to obtain temperature change rate data and pressure change rate data;

[0077] A trend analysis unit, used to determine the fluctuation of the temperature change rate data and the pressure change rate data according to the time parameter, and form a trend parameter data set;

[0078] The water evaporation calculation unit is used to calculate the water evaporation rate according to the trend parameter data set, and merge it with the trend parameter data set to obtain the change trend data set.

[0079] In an embodiment of the present invention, a change rate calculation unit is used to calculate the change rate of temperature data and pressure data at adjacent time points based on an equipment operating condition data set, obtain temperature change rate data and pressure change rate data, quantify the dynamic changes of temperature and pressure during the drying process, and provide basic data for subsequent analysis; a trend analysis unit is used to determine the fluctuation of temperature change rate data and pressure change rate data based on a time parameter, form a trend parameter data set, reduce random errors in the sensor sampling process, and improve data stability; a water evaporation calculation unit is used to calculate the water evaporation rate based on the trend parameter data set, and merge it with the trend parameter data set to obtain a change trend data set. By calculating the water evaporation rate, the water removal inside the material can be directly evaluated.

[0080] The trend analysis unit is used to determine the fluctuation of the temperature change rate data and the pressure change rate data according to the time parameter to form a trend parameter data set, which specifically includes:

[0081] Construct time series data based on the temperature change rate data set and the pressure change rate data set;

[0082] Calculate the fluctuation trend of temperature and pressure, and use the moving average method to calculate the trend value;

[0083] Calculate the growth rates of temperature change rate and pressure change rate to determine whether the current drying stage has entered a steady state;

[0084] Generate trend parameter data sets to record temperature trends, pressure trends and growth rate data at different time points.

[0085] In a preferred embodiment of the present invention, the water evaporation calculation unit includes:

[0086] The initial rate calculation unit is used to calculate the initial water evaporation rate according to the temperature and pressure changes in the initial stage of drying. The calculation formula for the initial water evaporation rate is: ,

[0087] in, is the initial water evaporation rate, is the mass transfer coefficient of the vacuum potting equipment material surface, is the initial pressure, is the initial temperature, is the gas constant in the ideal gas law, is the latent heat of vaporization of water at room temperature and pressure, is the temperature of the surface of the vacuum potting equipment material, is the initial saturated steam pressure;

[0088] The water evaporation rate calculation unit is used to calculate the water evaporation rate at any time according to the initial water evaporation rate. The calculation formula of the water evaporation rate is: ,

[0089] in, For the The evaporation rate of water at a given moment, is the index of the time, For the The temperature of the moment, For the The pressure of the moment, For the The pressure change rate at a given moment, For the The temperature change rate at time, For the The saturated steam pressure at time is the coefficient.

[0090] In an embodiment of the present invention, an initial rate calculation unit is used to calculate the initial water evaporation rate according to the temperature and pressure changes in the initial stage of drying. The formula can calculate the initial water evaporation rate based on the actual environmental parameters of the initial temperature and pressure, rather than relying on empirical values ​​or fixed set values, so that the system can adaptively adjust the drying strategy according to material properties and environmental conditions. By calculating the mass transfer influence on the material surface, the formula can dynamically adapt to different vacuum degrees and temperature changes, thereby improving the accuracy of water removal in the initial stage; a water evaporation rate calculation unit is used to calculate the water evaporation rate at any moment according to the initial water evaporation rate. The formula can calculate the water evaporation rate in combination with the real-time change trend of temperature and pressure, so that the system can accurately predict the dynamic process of water evaporation, rather than relying solely on single-point measurement values. By combining the temperature change rate and the pressure change rate, the formula can reflect transient changes and can be used to identify abnormal conditions.

[0091] In a preferred embodiment of the present invention, the analysis module includes:

[0092] The uniformity comparison unit is used to extract the temperature change rate and pressure change rate of different positions in the vacuum potting equipment according to the change trend data set, and compare them according to the position points to obtain temperature change comparison data and pressure change comparison data;

[0093] A uniformity parameter calculation unit is used to calculate the mean and variance of the temperature change rate and the pressure change rate according to the temperature change comparison data and the pressure change comparison data, and perform standardization processing on them to obtain the temperature uniformity parameter and the pressure uniformity parameter;

[0094] A uniformity determination unit is used to screen the temperature uniformity parameter and the pressure uniformity parameter according to a preset uniformity threshold group. When the temperature uniformity parameter and the pressure uniformity parameter are both less than the preset uniformity threshold group, the position point is marked as a dry uniform point. When any one of the temperature uniformity parameter and the pressure uniformity parameter is not less than the preset uniformity threshold group, the position point is marked as a dry non-uniform point to obtain a dry uniformity parameter.

[0095] The water evaporation calculation unit is used to calculate the water evaporation at different locations in different time periods according to the water evaporation rate in the change trend data set, and accumulate the water evaporation at each location to obtain the water removal degree parameter.

[0096] In an embodiment of the present invention, a uniformity comparison unit is used to extract the temperature change rate and pressure change rate of different position points in the vacuum filling equipment according to the change trend data set, and compare them according to the position points to obtain temperature change comparison data and pressure change comparison data. By comparing the temperature and pressure changes at different position points, local temperature gradient anomalies can be identified in advance, providing accurate data support for uniformity analysis; a uniformity parameter calculation unit is used to calculate the mean and variance of the temperature change rate and the pressure change rate according to the temperature change comparison data and the pressure change comparison data, and perform standardization processing on them to obtain temperature uniformity parameters and pressure uniformity parameters, determine the average characteristics of the overall drying state, improve data interpretability, and be able to quantify the degree of uniformity between different position points to ensure accurate adjustment of the drying process.

[0097] The uniformity determination unit is used to screen the temperature uniformity parameter and the pressure uniformity parameter according to the preset uniformity threshold group. When the temperature uniformity parameter and the pressure uniformity parameter are both less than the preset uniformity threshold group, the position point is marked as a dry uniform point. When any of the temperature uniformity parameter and the pressure uniformity parameter is not less than the preset uniformity threshold group, the position point is marked as a dry uneven point to obtain the dry uniformity parameter. By setting the threshold, the subjectivity of the dry uniformity analysis is avoided and the determination accuracy is improved. After data screening, the dry uneven area can be quickly locked to provide the target area for subsequent precise control. The water evaporation amount calculation unit is used to calculate the water evaporation amount of different positions in different time periods according to the water evaporation rate in the change trend data set, and the water evaporation amount of each position point is accumulated to obtain the water removal degree parameter. Through the single-point water evaporation calculation, the local water removal efficiency can be identified, and then the water removal status of the entire system can be evaluated through global calculation.

[0098] In a preferred embodiment of the present invention, the calculation formula of the moisture removal degree parameter is: ;

[0099] in, For the Moisture removal parameters of vacuum potting equipment at all times, is the time index, is the initial moment, is the total dry area of ​​the vacuum potting equipment, is the total moisture content in the entire drying area at the initial moment, is the cumulative amount of moisture removed at a certain point, is the total amount of water removed at all locations.

[0100] In an embodiment of the present invention, the formula is calculated through normalization so that the moisture removal degree parameter is always between 0 and 1, thereby providing an intuitive drying progress evaluation method, which can reflect the moisture removal situation at different time points in real time. Compared with the traditional method that relies on setting time and temperature, this calculation method ensures the dynamic visualization of the drying process, so that the system can adjust the drying parameters based on the actual moisture removal situation, avoiding insufficient or excessive drying problems caused by fixed process parameters. Since the calculation of this formula is based on the accumulation of local moisture removal, it can not only reflect the overall drying state, but also quantify the drying conditions in different areas, providing data support for subsequent intelligent regulation.

[0101] In a preferred embodiment of the present invention, the regional module includes:

[0102] A gradient calculation unit is used to calculate the local temperature gradient and the local pressure gradient at different positions according to the temperature change rate and the pressure change rate to obtain a gradient data set;

[0103] A grid processing unit, used to divide the drying space in the vacuum potting equipment into a plurality of grid units according to the position points, each grid unit containing the temperature gradient and pressure gradient data of the corresponding position point;

[0104] The threshold determination unit is used to screen the local temperature gradient and local pressure gradient of each grid unit according to the preset gradient threshold group. When the temperature gradient or pressure gradient exceeds the preset threshold, the grid unit is marked as an abnormal candidate area to obtain preliminary area classification data.

[0105] In an embodiment of the present invention, a gradient calculation unit is used to calculate the local temperature gradient and local pressure gradient of different position points according to the temperature change rate and the pressure change rate to obtain a gradient data set. By calculating the gradient, the temperature and pressure distribution in the drying process can be identified, avoiding the limitation of relying solely on single-point measurement; a grid processing unit is used to divide the drying space in the vacuum filling equipment into multiple grid units according to the position points, each grid unit contains the temperature gradient and pressure gradient data of the corresponding position point. Through grid processing, complex continuous data can be structured to facilitate subsequent analysis; a threshold judgment unit is used to screen the local temperature gradient and local pressure gradient of each grid unit according to a preset gradient threshold group. When the temperature gradient or pressure gradient exceeds the preset threshold, the grid unit is marked as an abnormal candidate area to obtain preliminary area classification data. By reasonably setting the threshold, misjudgment or omission of abnormal areas can be avoided, thereby improving the accuracy of drying monitoring.

[0106] The grid processing unit is used to divide the drying space in the vacuum potting equipment into a plurality of grid units according to the position points, and specifically includes:

[0107] First of all, it is necessary to establish a reasonable mesh division model based on the structural characteristics of the vacuum potting equipment and the physical characteristics of the drying process. In order to ensure the scientificity and adaptability of the division, the dimensional data inside the vacuum potting equipment is first obtained, including the length, width, height of the cavity and the specific shape of the drying area. In some special morphological equipment (such as irregular geometric shapes), the three-dimensional modeling method can be used for spatial data mapping to ensure that the grid unit can reasonably cover the entire drying area. On this basis, the size of the grid, that is, the side length of a single grid unit, is determined according to the location distribution of the measurement points. The size of the grid unit is a key parameter affecting data accuracy and computational complexity, and can usually be adjusted according to the measurement density of the sensor, the gradient range of temperature and pressure changes, and the computational performance requirements. For example, in areas where the drying environment changes more drastically, such as near the heating element or in areas with large air flow, a finer grid division can be used to improve data resolution, while in areas where the temperature and pressure changes are more uniform, the size of the grid unit can be appropriately increased to reduce the amount of calculation and improve the system response speed.

[0108] After completing the basic parameter settings for grid division, it is necessary to map the grid cells to the actual spatial positions. The core of this step is to attribute the data of each measurement point inside the vacuum potting equipment to a specific grid cell. In practical applications, the data of the measurement points are usually discrete, so the nearest neighbor matching or interpolation algorithm can be used for data attribution processing. Specifically, the data of each measurement point determines the grid cell number to which it belongs based on its spatial coordinates. If a grid cell contains multiple measurement points, the weighted average method can be used to calculate the temperature gradient and pressure gradient of the grid so that it can represent the state of the entire grid area.

[0109] After completing the matching of the measurement data with the grid cells, it is necessary to establish a grid data storage structure for subsequent drying area analysis and anomaly detection. Usually, the grid data can be stored as a three-dimensional array, where each element represents a grid cell, containing information such as temperature gradient, pressure gradient, number of measurement points, and grid center coordinates. The storage format can use a sparse matrix to save storage space, especially in the case of irregular drying chambers or irregular data distribution. Sparse storage can significantly reduce data redundancy and improve computing efficiency. At the same time, the system can be updated in real time during the data storage stage, that is, as the drying process progresses, the temperature, pressure and other parameters of the grid cells are continuously refreshed, so that the grid data can reflect the dynamic changes of the drying state in real time.

[0110] After the grid division and data mapping are completed, it is also necessary to construct the spatial relationship of the grid cells, that is, to determine the connection relationship between the grid cells and their adjacent grids. This process is crucial for subsequent regional division and anomaly detection. For example, when judging whether a certain area belongs to a residual moisture area or an over-drying area, it is necessary to analyze the gradient changes of adjacent grids. If the temperature gradient or pressure gradient of a grid is much higher than that of the adjacent grid, it may mean that the drying process is uneven. In addition, the topological relationship between grid cells also affects the speed and computational complexity of data processing. For example, when using parallel computing for large-scale data processing, a reasonable grid topology design can reduce the computational burden and improve computational efficiency.

[0111] Overall, the implementation of the grid processing unit can convert the drying space into a structured grid data model, making the changing trends of physical parameters such as temperature and pressure more intuitive and providing a precise basis for regional division. By reasonably setting the grid size, optimizing the data interpolation method, and building an efficient storage structure and spatial relationship network, the grid processing unit can ensure that the subsequent drying state monitoring, abnormal area identification, and intelligent regulation have higher accuracy and response speed, ultimately improving the stability of the vacuum potting equipment drying process and product quality consistency.

[0112] In a preferred embodiment of the present invention, the regional module further includes:

[0113] The adjacent region merging unit is used to check the gradient data sets of adjacent grid cells according to the preliminary region classification data, and merge the regions with similar temperature gradient and pressure gradient to obtain optimized region data;

[0114] A moisture removal analysis unit is used to determine whether the drying state of different areas is uniform according to the moisture removal degree parameter of the optimized area data. When the moisture removal degree parameter of a certain area is lower than a preset moisture removal threshold, the boundary range of the area is adjusted and the area is reclassified as a moisture residual area.

[0115] A moisture residual determination unit, for identifying, based on the result of the moisture removal analysis unit, an area where the moisture removal degree parameter is lower than a preset moisture removal threshold and the temperature change rate is lower than a preset temperature change rate, and marking it as a moisture residual area;

[0116] The over-drying determination unit is used to identify, based on the temperature gradient and the drying uniformity parameter, an area where the temperature change rate is higher than a preset temperature change rate and the drying uniformity parameter is lower than a preset drying uniformity, and mark it as an over-drying area.

[0117] In an embodiment of the present invention, an adjacent region merging unit is used to check the gradient data set of adjacent grid cells according to preliminary region classification data, and merge regions with similar temperature gradients and pressure gradients to obtain optimized region data. By merging adjacent regions, excessive subdivision caused by measurement errors or local fluctuations is reduced, and the boundaries of abnormal regions are clearer and the classification is more reasonable. A moisture removal analysis unit is used to determine whether the drying state of different regions is uniform according to the moisture removal degree parameter of the optimized region data. When the moisture removal degree parameter of a certain region is lower than a preset moisture removal threshold, the boundary range of the region is adjusted and it is reclassified as a moisture residual region. By calculating the moisture removal degree, the moisture removal degree parameter of the region is calculated. , which can accurately identify areas with insufficient moisture removal; the moisture residue judgment unit is used to identify areas where the moisture removal degree parameter is lower than the preset moisture removal threshold and the temperature change rate is lower than the preset temperature change rate according to the results of the moisture removal analysis unit, and mark them as moisture residue areas, analyze the reasons for moisture residue in combination with the temperature change rate, provide data support for subsequent precise control, and improve the reliability of the drying process; the over-drying judgment unit is used to identify areas where the temperature change rate is higher than the preset temperature change rate and the drying uniformity parameter is lower than the preset drying uniformity according to the temperature gradient and drying uniformity parameters, and mark them as over-drying areas, and combine the drying uniformity parameters to make the identification of over-drying areas more accurate.

[0118] Among them, the adjacent region merging unit is used to check the gradient data set of adjacent grid cells according to the preliminary regional classification data, and merge the regions with similar temperature gradients and pressure gradients to obtain optimized regional data, specifically including:

[0119] First, based on the preliminary regional classification data, the data set contains the temperature gradient, pressure gradient, moisture removal degree and category of each grid cell inside the equipment. In actual operation, each grid cell represents a finite space point inside the vacuum potting equipment. The system needs to screen the temperature and pressure data of all grid cells and build spatial adjacency relationships to identify adjacent grid cells that are related to each other. During the construction process, the system traverses all grids inside the equipment and establishes adjacency relationships in six directions for each grid cell. For grids at the boundary, if there is no adjacent cell in a certain direction, the data in that direction is ignored, thereby ensuring the integrity of the adjacency matrix and the efficiency of the calculation.

[0120] After building the adjacency relationship, the system calculates the similarity of the temperature gradient and pressure gradient of adjacent grid cells. Specifically, for two adjacent grid cells, their temperature gradient difference and pressure gradient difference are calculated respectively, and compared with the preset threshold. When the gradient change of two grid cells is within the set threshold range, it indicates that their thermal distribution and pressure distribution are basically the same and belong to the same area, so they can be merged. This process not only prevents misclassification due to local data fluctuations, but also ensures more accurate identification of abnormal areas. The system will use certain statistical methods, such as calculating the mean temperature gradient and pressure gradient of multiple grids, and standardizing them based on the standard deviation, so as to ensure that the merged area is numerically consistent and avoid mismerging due to certain abnormal data points.

[0121] After completing the judgment of merging adjacent regions, the system will perform a connected region search to determine all grid cells that can be merged and generate new optimized region data. In the specific implementation process, the depth-first search algorithm can be used to traverse the entire grid structure and merge all grid cells that meet the similarity criteria into the same region. While merging regions, the system will also recalculate the overall temperature gradient, pressure gradient, and moisture removal degree parameters of the merged region to ensure that the merged region can accurately reflect the current dry state. The merged temperature gradient and pressure gradient are usually calculated using the weighted average method, so that the new region can maintain a reasonable data mean, thereby reducing abnormal judgment errors caused by data mutations.

[0122] After the merger is completed, the system will classify the optimized regional data to form a new optimized regional data set and store it in the regional module. The optimized regional data set mainly includes three key parts: first, the updated temperature gradient, pressure gradient and moisture removal degree parameters to ensure the accuracy of the data; second, the optimized regional boundary information, that is, the spatial coordinate range of the drying area inside the equipment, so that the subsequent control module can be accurately adjusted based on the clear spatial position; third, the new regional classification, that is, marking the area as a normal area, residual moisture area or over-drying area, to facilitate subsequent intelligent control. During the data storage process, the system will also dynamically mark the optimized area to ensure that the subsequent analysis module can obtain the latest regional information in a timely manner and further optimize the drying strategy based on the data.

[0123] In a preferred embodiment of the present invention, the feature module includes:

[0124] The abnormal data screening unit is used to screen and extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters of the moisture residual area and the over-drying area according to the drying area data set, and eliminate the data of the normal area to obtain the characteristic parameter data set;

[0125] An abnormal characteristic calculation unit, used to calculate the temperature fluctuation range, pressure fluctuation range and water evaporation rate change range of each abnormal area and the abnormal characteristic data set according to the characteristic parameter data set;

[0126] The abnormal area feature unit is used to subdivide the moisture residual area and the over-dry area according to the abnormal feature data set and the preset feature threshold group to obtain a subdivided area set, and extract the abnormal area features therefrom to obtain a dry abnormal data set.

[0127] In an embodiment of the present invention, an abnormal data screening unit is used to screen and extract the temperature, pressure, drying uniformity parameter and moisture removal degree parameter of the moisture residual area and the over-drying area according to the drying area data set, eliminate the data of the normal area, and obtain a characteristic parameter data set. By accurately screening the abnormal area, data interference in the dry uniform area is avoided; the abnormal feature calculation unit is used to calculate the temperature fluctuation range, pressure fluctuation range and moisture evaporation rate change amplitude of each abnormal area according to the characteristic parameter data set. The abnormal feature data set can accurately identify the uneven thermal distribution or vacuum unevenness in the abnormal area by calculating the temperature and pressure fluctuation range, and provide key indicators for regulation; the abnormal area feature unit is used to subdivide the moisture residual area and the over-drying area according to the abnormal feature data set and the preset feature threshold group, obtain a subdivided area set, and extract the abnormal area features therefrom to obtain a drying abnormal data set. Through area subdivision, the specific cause of uneven drying can be more accurately identified.

[0128] Among them, the abnormal feature calculation unit is used to calculate the temperature fluctuation range, pressure fluctuation range and water evaporation rate change range of each abnormal area according to the characteristic parameter data set. The abnormal feature data set specifically includes:

[0129] First, the data set is sorted according to the timestamp so that all data form a continuous time series to avoid calculation deviation caused by data disorder. At the same time, in order to eliminate the noise interference that may exist in the collection process, the system uses moving average filtering or median filtering to smooth the data to reduce the impact of random fluctuations in a short period of time on the final calculation results.

[0130] The temperature data sequence of the abnormal area is extracted from the characteristic parameter data set, and the maximum and minimum temperature values ​​at all time points in the area are determined to calculate the temperature fluctuation range. At the same time, in order to further evaluate the stability of temperature fluctuations, the system calculates the standard deviation of the temperature data and combines the mean to quantitatively analyze the overall distribution of temperature. While calculating the temperature fluctuation range, the system also calculates the pressure fluctuation range, similar to the way temperature data is processed.

[0131] The system also needs to analyze the variation range of the water evaporation rate to evaluate the stability of water removal in the abnormal area. First, extract the water evaporation rate data sequence, and calculate the difference between the maximum evaporation rate and the minimum evaporation rate as the variation range of the water evaporation rate in the area. At the same time, in order to more accurately judge the stability of water evaporation, the system calculates the standard deviation of the water evaporation rate, and combines it with the average evaporation rate to quantify the uniformity of water removal during the drying process. If the variation range of the water evaporation rate is large, it may mean that there are drastic fluctuations in the water removal process in the area, resulting in uneven drying effect. If the standard deviation of the water evaporation rate is small, it means that the water removal is relatively stable and the drying process is relatively uniform. By calculating the variation characteristics of the water evaporation rate, the system can effectively identify the problem of residual water that may occur during the drying process, and optimize and adjust the relevant areas in the subsequent control module to ensure uniform water removal.

[0132] In a preferred embodiment of the present invention, the control module includes:

[0133] The abnormal area parameter unit is used to extract the temperature, pressure, drying uniformity parameter and moisture removal degree parameter corresponding to the abnormal area according to the drying abnormality data set to obtain the abnormal area parameter set;

[0134] A control parameter calculation unit, used to calculate a heating time adjustment value, a vacuum maintenance time adjustment value and a temperature setting value adjustment value for each abnormal area according to the abnormal area parameter set, to obtain a control parameter data set;

[0135] A control unit is used to control the vacuum filling equipment according to the control parameter data set to ensure the overall uniformity of the drying process;

[0136] The real-time adjustment unit is used to make real-time adjustments to the control process according to the real-time monitoring data during the drying process to ensure the uniformity of drying in different areas during the drying process.

[0137] In an embodiment of the present invention, an abnormal area parameter unit is used to extract the temperature, pressure, drying uniformity parameter and moisture removal degree parameter corresponding to the abnormal area according to the drying abnormality data set, and obtain the abnormal area parameter set, which can accurately identify the areas with residual moisture or over-drying in the drying process, and provide detailed parameter information of these areas; the control parameter calculation unit is used to calculate the heating time adjustment value, vacuum maintenance time adjustment value and temperature setting value adjustment value of each abnormal area according to the abnormal area parameter set, and obtain the control parameter data set, which can accurately evaluate the adjustment needs and avoid errors caused by experience adjustment; the control unit is used to control the vacuum filling equipment according to the control parameter data set to ensure the overall uniformity of the drying process, which solves the problem that the traditional drying process cannot accurately control specific areas; the real-time adjustment unit is used to adjust the control process in real time according to the real-time monitoring data during the drying process, to ensure the uniformity of drying in different areas during the drying process, and enable the system to automatically adjust the drying process according to real-time feedback data.

[0138] The control parameter calculation unit is used to calculate the heating time adjustment value, vacuum maintenance time adjustment value and temperature setting value adjustment value of each abnormal area according to the abnormal area parameter set to obtain the control parameter data set, which specifically includes:

[0139] The system calculates the heating time adjustment value for each abnormal area. The adjustment of the heating time is mainly based on the dynamic calculation of the relationship between the temperature change rate and the water evaporation rate of the area. For areas with residual moisture, the system determines whether the heating time needs to be extended by calculating the difference between the current water evaporation rate and the target evaporation rate. If the difference is large, the system will calculate the additional heating time required for the area based on the heat conduction model, and set a reasonable heating time adjustment value based on the maximum allowable heating time of the drying equipment; for over-dried areas, the system determines whether the heating time needs to be reduced based on the deviation between the current temperature change rate and the target temperature change rate, so as to avoid local overheating leading to changes in material properties or unnecessary energy loss. During the calculation process, the system also needs to consider the thermal inertia of the drying chamber to prevent excessive adjustments from causing new uneven drying phenomena.

[0140] The system needs to further calculate the vacuum maintenance time adjustment value. The setting of the vacuum maintenance time is closely related to the moisture evaporation rate, so the system will calculate the vacuum adjustment strategy based on the changing trend of the moisture removal degree parameter. For areas with residual moisture, the system will determine whether it is necessary to extend the vacuum maintenance time to improve the moisture evaporation capacity by analyzing the current pressure level and historical pressure change data of the area; for over-dried areas, if it is detected that the pressure change rate of the area is too large and the moisture evaporation rate exceeds the normal range, the system will reduce the vacuum maintenance time to reduce the drying intensity. During the calculation process, the system will also combine the exhaust rate and sealing status of the equipment to ensure that the vacuum adjustment will not affect the normal drying of other areas.

[0141] Finally, the system calculates the temperature setting adjustment value. This step is mainly based on dynamic optimization based on temperature deviation analysis. For the area with residual moisture, if the temperature in the area is detected to be lower than the target temperature, the system will calculate the required temperature compensation value based on the heat transfer model, and set a reasonable temperature increase range based on the heating rate of the equipment; for the over-dried area, the system will calculate the temperature reduction range based on the overheating risk assessment to ensure that the normal drying rate can be maintained after the temperature adjustment. During the temperature setting value adjustment process, the system will combine historical temperature data to avoid unstable drying caused by frequent temperature fluctuations.

[0142] In a preferred embodiment of the present invention, the control unit comprises:

[0143] The moisture residual area adjustment unit is used to increase the temperature setting value of the area and extend the vacuum maintenance time according to the control parameters of the moisture residual area to ensure the moisture removal effect;

[0144] An over-drying area adjustment unit is used to reduce the heating time of the area and adjust the temperature setting value according to the control parameters of the over-drying area to avoid local over-drying;

[0145] The global optimization unit is used to adjust the drying strategy of the entire vacuum filling equipment according to the control parameter data set of each abnormal area to ensure the overall uniformity of the drying process.

[0146] In the embodiment of the present invention, the moisture residual area adjustment unit is used to increase the temperature setting value of the area and extend the vacuum maintenance time according to the control parameters of the moisture residual area to ensure the moisture removal effect, and ensure that the moisture in the area is completely removed through accurate identification of the moisture residual area and local heating optimization;

[0147] The over-drying area adjustment unit is used to reduce the heating time of the area and adjust the temperature setting value according to the control parameters of the over-drying area to avoid local over-drying. Through local temperature control, the temperature balance of the entire drying process is ensured to prevent the product quality from being reduced due to excessively high regional temperature;

[0148] The global optimization unit is used to adjust the drying strategy of the entire vacuum filling equipment according to the control parameter data set of each abnormal area to ensure the overall uniformity of the drying process. Through the global optimization strategy, it avoids the imbalance of the overall drying environment caused by the individual adjustment of local areas, thereby improving the overall product quality consistency.

[0149] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A real-time monitoring and data analysis system based on vacuum potting equipment, characterized in that: The system comprises: A calculation module is used to calculate the change rate of temperature data and pressure data at adjacent time points based on the equipment operating condition data set, and calculate the water evaporation rate based on the data to obtain a change trend data set; The analysis module is used to compare the temperature change rate and pressure change rate at different locations according to the change trend data set, calculate the drying uniformity parameter; perform cumulative analysis on the water evaporation rate, calculate the water removal degree parameter, and obtain the key parameter data set; A regional module is used to calculate the local temperature gradient and the local pressure gradient according to the key parameter data set, and divide the vacuum potting equipment into regions according to the local temperature gradient and the local pressure gradient to obtain a dry region data set, which includes a normal region, a moisture residual region, and an over-dry region; The feature module is used to extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters in different areas according to the drying area data set, and obtain the drying abnormality data set; The control module is used to adjust the heating time, vacuum maintenance time and temperature setting value of the corresponding area in the vacuum potting equipment according to the drying abnormality data to ensure that the inside of the vacuum potting equipment is fully dried.

2. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 1, characterized in that: The calculation module comprises: A change rate calculation unit, used to calculate the change rate of temperature data and pressure data at adjacent time points according to the equipment operating condition data set, to obtain temperature change rate data and pressure change rate data; A trend analysis unit, used to determine the fluctuation of the temperature change rate data and the pressure change rate data according to the time parameter, and form a trend parameter data set; The water evaporation calculation unit is used to calculate the water evaporation rate according to the trend parameter data set, and merge it with the trend parameter data set to obtain the change trend data set.

3. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 2, characterized in that: The water evaporation calculation unit comprises: The initial rate calculation unit is used to calculate the initial water evaporation rate according to the temperature and pressure changes in the initial stage of drying. The calculation formula for the initial water evaporation rate is: ， in, is the initial water evaporation rate, is the mass transfer coefficient of the vacuum potting equipment material surface, is the initial pressure, is the initial temperature, is the gas constant in the ideal gas law, is the latent heat of vaporization of water at room temperature and pressure, is the temperature of the surface of the vacuum potting equipment material, is the initial saturated steam pressure; The water evaporation rate calculation unit is used to calculate the water evaporation rate at any time according to the initial water evaporation rate. The calculation formula of the water evaporation rate is: ， in, For the The evaporation rate of water at a given moment, is the index of the time, For the The temperature of the moment, For the The pressure of the moment, For the The pressure change rate at a given moment, For the The temperature change rate at time, For the The saturated steam pressure at time is the coefficient.

4. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 3, characterized in that: The analysis module comprises: The uniformity comparison unit is used to extract the temperature change rate and pressure change rate of different positions in the vacuum potting equipment according to the change trend data set, and compare them according to the position points to obtain temperature change comparison data and pressure change comparison data; A uniformity parameter calculation unit is used to calculate the mean and variance of the temperature change rate and the pressure change rate according to the temperature change comparison data and the pressure change comparison data, and perform standardization processing on them to obtain the temperature uniformity parameter and the pressure uniformity parameter; A uniformity determination unit is used to screen the temperature uniformity parameter and the pressure uniformity parameter according to a preset uniformity threshold group. When the temperature uniformity parameter and the pressure uniformity parameter are both less than the preset uniformity threshold group, the position point is marked as a dry uniform point. When any one of the temperature uniformity parameter and the pressure uniformity parameter is not less than the preset uniformity threshold group, the position point is marked as a dry non-uniform point to obtain a dry uniformity parameter. The water evaporation calculation unit is used to calculate the water evaporation at different locations in different time periods according to the water evaporation rate in the change trend data set, and accumulate the water evaporation at each location to obtain the water removal degree parameter.

5. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 4, characterized in that: The calculation formula of the moisture removal degree parameter is: ； in, For the Moisture removal parameters of vacuum potting equipment at all times, is the time index, is the initial moment, is the total dry area of ​​the vacuum potting equipment, is the total moisture content in the entire drying area at the initial moment, is the cumulative amount of moisture removed at a certain point, is the total amount of water removed at all locations.

6. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 5, characterized in that: The regional module includes: A gradient calculation unit is used to calculate the local temperature gradient and the local pressure gradient at different positions according to the temperature change rate and the pressure change rate to obtain a gradient data set; A grid processing unit, used to divide the drying space in the vacuum potting equipment into a plurality of grid units according to the position points, each grid unit containing the temperature gradient and pressure gradient data of the corresponding position point; The threshold determination unit is used to screen the local temperature gradient and local pressure gradient of each grid unit according to the preset gradient threshold group. When the temperature gradient or pressure gradient exceeds the preset threshold, the grid unit is marked as an abnormal candidate area to obtain preliminary area classification data.

7. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 6, characterized in that: The regional module also includes: The adjacent region merging unit is used to check the gradient data sets of adjacent grid cells according to the preliminary region classification data, and merge the regions with similar temperature gradients and pressure gradients to obtain optimized region data; A moisture removal analysis unit is used to determine whether the drying state of different areas is uniform according to the moisture removal degree parameter of the optimized area data. When the moisture removal degree parameter of a certain area is lower than a preset moisture removal threshold, the boundary range of the area is adjusted and the area is reclassified as a moisture residual area. A moisture residual determination unit, for identifying an area where a moisture removal degree parameter is lower than a preset moisture removal threshold and a temperature change rate is lower than a preset temperature change rate according to a result of the moisture removal analysis unit, and marking it as a moisture residual area; The over-drying determination unit is used to identify, based on the temperature gradient and the drying uniformity parameter, an area where the temperature change rate is higher than a preset temperature change rate and the drying uniformity parameter is lower than a preset drying uniformity, and mark it as an over-drying area.

8. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 7, characterized in that: The feature module includes: The abnormal data screening unit is used to screen and extract the temperature, pressure, drying uniformity parameters and moisture removal degree parameters of the moisture residual area and the over-drying area according to the drying area data set, and eliminate the data of the normal area to obtain the characteristic parameter data set; An abnormal characteristic calculation unit, used to calculate the temperature fluctuation range, pressure fluctuation range and water evaporation rate change range of each abnormal area and the abnormal characteristic data set according to the characteristic parameter data set; The abnormal area feature unit is used to subdivide the moisture residual area and the over-dry area according to the abnormal feature data set and the preset feature threshold group to obtain a subdivided area set, and extract the abnormal area features therefrom to obtain a dry abnormal data set.

9. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 8, characterized in that: The control module includes: The abnormal area parameter unit is used to extract the temperature, pressure, drying uniformity parameter and moisture removal degree parameter corresponding to the abnormal area according to the drying abnormality data set to obtain the abnormal area parameter set; A control parameter calculation unit, used to calculate a heating time adjustment value, a vacuum maintenance time adjustment value and a temperature setting value adjustment value for each abnormal area according to the abnormal area parameter set, to obtain a control parameter data set; A control unit is used to control the vacuum filling equipment according to the control parameter data set to ensure the overall uniformity of the drying process; The real-time adjustment unit is used to make real-time adjustments to the control process according to the real-time monitoring data during the drying process to ensure the uniformity of drying in different areas during the drying process.

10. A real-time monitoring and data analysis system based on vacuum potting equipment according to claim 9, characterized in that: The control unit comprises: The moisture residual area adjustment unit is used to increase the temperature setting value of the area and extend the vacuum maintenance time according to the control parameters of the moisture residual area to ensure the moisture removal effect; An over-drying area adjustment unit is used to reduce the heating time of the area and adjust the temperature setting value according to the control parameters of the over-drying area to avoid local over-drying; The global optimization unit is used to adjust the drying strategy of the entire vacuum filling equipment according to the control parameter data set of each abnormal area to ensure the overall uniformity of the drying process.

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