Method and system for detecting sealing performance of protective air-tight door

Abstract

The invention discloses a method and system for detecting the sealing performance of a protective air-tight door, and belongs to the field of performance detection of protective air-tight doors. The method comprises the steps that the current air flow of the closed space is calculated; calculating the current air exchange rate of the closed space; the current temperature of the closed space and a preset sealing performance value calculation formula are obtained, and the current sealing performance value of the closed space is calculated according to the current temperature, the current pressure difference, the current air exchange rate and the preset sealing performance value calculation formula; and if the current sealing performance value is lower than the preset sealing performance threshold value, determining that the protective air-tight door does not pass the sealing performance detection. According to the scheme, key parameters such as the leakage area, the current pressure difference, the air flow, the air exchange rate and the sealing performance value of the closed space can be accurately quantified, the evaluation accuracy is improved, the problem of poor sealing performance can be found and solved easily, and therefore the reliability of the protective air-tight door is improved. The automatic detection process can improve the detection efficiency and save the labor cost.

Description

Technical Field

[0001] The present application relates to the technical field of performance detection of protective sealed doors, and in particular to a method and system for detecting the sealing performance of protective sealed doors. Background Art

[0002] Protective closed doors are widely used in laboratories, clean rooms, food processing areas, pharmaceutical factories and other places that require strict environmental control. These places have strict requirements on air cleanliness, temperature and humidity, etc. The sealing performance of protective closed doors is directly related to the maintenance of these conditions, effectively preventing pollutants from spreading through gaps and ensuring environmental safety.

[0003] Nowadays, the sealing performance of protective airtight doors needs to be manually tested. First, the protective airtight door needs to be closed to ensure that the door leaf fits tightly against the door frame. Then, a smoke generator or tracer gas is released on one side of the door, while observing whether there is gas leakage on the other side of the door. In addition, tools such as feeler gauges can be used to test the gap between the door leaf and the door frame to evaluate the sealing effect.

[0004] However, manual inspection relies on experience and subjective judgment, resulting in low accuracy. In addition, the inspection takes a long time and has low inspection efficiency. At the same time, manual inspection is generally carried out periodically and cannot monitor the status of the closed door in real time. Summary of the invention

[0005] The embodiment of the present application provides a method for detecting the sealing performance of a protective sealed door, which solves the problem that the manual detection of the performance of a protective sealed door in the prior art relies on experience and subjective judgment, resulting in low accuracy. In addition, the detection takes a long time and has low detection efficiency. At the same time, manual detection is generally performed regularly, and the status of the sealed door cannot be monitored in real time.

[0006] In a first aspect, an embodiment of the present application provides a method for detecting the sealing performance of a protective closed door, the method comprising: Obtain the leakage area, current pressure difference and preset air flow calculation formula of the confined space, and calculate the current air flow of the confined space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the confined space includes a protective closed door; the preset leakage area calculation formula is: ; in, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference; The volume of the enclosed space and a preset ventilation rate calculation formula are obtained, and the current ventilation rate of the enclosed space is calculated according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; wherein the preset ventilation rate calculation formula is: ; in, is the current ventilation rate; is the current air flow; V is the volume of the enclosed space; The current temperature of the enclosed space and a preset sealing performance value calculation formula are obtained, and the current sealing performance value of the enclosed space is calculated according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; wherein the preset sealing performance value calculation formula is: ; Among them, SP ( ) is the current sealing performance value; is the ventilation rate weight coefficient; is the current ventilation rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature; If the current sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0007] Furthermore, after calculating the current sealing performance value of the confined space, the method further includes: If the current sealing performance value is higher than the preset sealing performance threshold, the current ventilation rate, the current pressure difference, the current temperature and the preset prediction interval time are input into the preset sealing performance prediction model to obtain the predicted sealing performance value after the preset prediction interval time, and the prediction times are recorded; If the predicted sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0008] Furthermore, after obtaining the sealing performance value after the preset prediction time interval, the method further includes: If the predicted sealing performance value is higher than the preset sealing performance threshold, the current pressure difference is collected again after the preset collection interval is reached, and the current air flow rate of the enclosed space is updated according to the leakage area, the current pressure difference and the preset air flow rate calculation formula; Update the current ventilation rate of the enclosed space according to the updated current air flow, the volume of the enclosed space and a preset ventilation rate calculation formula; Re-acquire and update the current temperature of the enclosed space, and update the current sealing performance value of the enclosed space according to the updated current temperature, current pressure difference, current ventilation rate and a preset sealing performance value calculation formula; If the updated current sealing performance value is higher than the preset sealing performance threshold, the updated current temperature, current pressure difference, current ventilation rate and preset prediction interval time are input into the preset sealing performance prediction model, the predicted sealing performance value after the preset prediction interval time is updated, and the prediction times are updated until the prediction times reach the preset prediction times threshold; If all predicted sealing performance values ​​and all current sealing performance values ​​are higher than a preset sealing performance threshold, it is determined that the protective airtight door passes the sealing performance test; Accordingly, after updating the current sealing performance value of the confined space, the method further includes: If the updated current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test; Accordingly, after updating the predicted sealing performance value after the preset prediction interval time, the method further includes: If the updated predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0009] Further, after determining that the protective airtight door fails the sealing performance test, the method further includes: The current temperature, the current pressure difference and the current ventilation rate are input into a preset abnormal cause detection model to determine the abnormal cause of the protective sealed door failing the sealing performance test, and the abnormal cause is sent to the control center for the control center to improve the protective sealed door according to the abnormal cause.

[0010] Furthermore, after determining that the protective airtight door passes the sealing performance test, the method further includes: Obtain historical usage data, first historical fault data, historical environmental data, and first historical maintenance records of each protective sealed door throughout its life cycle, and create a first data set based on the historical usage data, first historical fault data, historical environmental data, and first historical maintenance records; Annotating the first data set with a failure time label, a failure type label, and a maintenance plan label; A fault prediction model for the protective sealed door is constructed, and the fault prediction model is trained according to the first data set, the fault time label, the fault type label, and the maintenance plan label until the fault prediction model reaches a preset fault model training standard.

[0011] Further, after training the fault prediction model according to the first data set, the fault time label, the fault type label, and the maintenance solution label until the fault prediction model reaches a preset fault model training standard, the method further includes: Acquire real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records of the protective sealed door, input the real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records into a fault prediction model, and determine a predicted fault time, a predicted fault type, and a predicted maintenance plan; The predicted failure time, predicted failure type and predicted maintenance plan are sent to the control center for the staff to perform maintenance work on the protective closed door.

[0012] Furthermore, the training process of the preset sealing performance prediction model includes: Acquire a first historical ventilation rate, a first historical pressure difference, a first historical temperature, and a historical prediction interval time, and create a second data set according to the first historical ventilation rate, the first historical pressure difference, the first historical temperature, and the historical prediction interval time; labeling the sealing performance value of the second data set; A sealing performance prediction model is constructed, and the sealing performance prediction model is trained according to the second data set and the sealing performance value label until the sealing performance prediction model reaches a preset sealing performance prediction model training standard.

[0013] Furthermore, the training process of the preset abnormal cause detection model includes: Acquire a second historical ventilation rate, a second historical pressure difference, and a second historical temperature when the protective airtight door fails, and create a third data set according to the second historical ventilation rate, the second historical pressure difference, and the second historical temperature; Label the abnormal reasons of the third data set; An abnormality cause detection model is constructed, and the abnormality cause detection model is trained according to the third data set and the abnormality cause label until the abnormality cause detection model reaches a preset abnormality cause detection model training standard.

[0014] Further, after determining that the protective airtight door fails the sealing performance test, the method further includes: The device information of the protective sealed door is obtained, and the device information is sent to the control center, so that the control center can lock the target protective sealed door according to the device information and perform subsequent processing.

[0015] According to a second aspect of the present application, a system for detecting the sealing performance of a protective closed door is provided, the system comprising: The air flow calculation module is used to obtain the leakage area, current pressure difference and preset air flow calculation formula of the confined space, and calculate the current air flow of the confined space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the confined space includes a protective closed door; the preset leakage area calculation formula is: ; in, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference; The ventilation rate calculation module is used to obtain the volume of the enclosed space and a preset ventilation rate calculation formula, and calculate the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; wherein the preset ventilation rate calculation formula is: ; in, is the current ventilation rate; is the current air flow; V is the volume of the enclosed space; The sealing performance value calculation module is used to obtain the current temperature of the enclosed space and the preset sealing performance value calculation formula, and calculate the current sealing performance value of the enclosed space according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; wherein the preset sealing performance value calculation formula is: ; Among them, SP ( ) is the current sealing performance value; is the ventilation rate weight coefficient; is the current ventilation rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature; The detection module is used to determine that the protective airtight door fails the sealing performance test if the current sealing performance value is lower than a preset sealing performance threshold.

[0016] In an embodiment of the present application, the leakage area, current pressure difference and preset air flow calculation formula of the enclosed space are obtained, and the current air flow of the enclosed space is calculated according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the enclosed space includes a protective enclosed door; the volume of the enclosed space and the preset ventilation rate calculation formula are obtained, and the current ventilation rate of the enclosed space is calculated according to the volume of the enclosed space, the current air flow and the preset ventilation rate calculation formula; the current temperature of the enclosed space and the preset sealing performance value calculation formula are obtained, and the current sealing performance value of the enclosed space is calculated according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; if the current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective enclosed door has not passed the sealing performance test. Through the above-mentioned protective enclosed door sealing performance detection method, key parameters such as the leakage area, current pressure difference, air flow, ventilation rate and sealing performance value of the enclosed space can be accurately quantified, errors caused by subjective judgment can be avoided, the accuracy of the evaluation can be improved, and it is helpful to discover and solve the problem of poor sealing performance, thereby improving the reliability of the protective enclosed door. Automated testing processes can improve testing efficiency and save labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a method for detecting the sealing performance of a protective sealed door provided in the first embodiment of the present application; Figure 2 It is a flow chart of a method for detecting the sealing performance of a protective sealed door provided in the second embodiment of the present application; Figure 3 It is a flow chart of a method for detecting the sealing performance of a protective sealed door provided in Embodiment 3 of the present application; Figure 4 It is a structural schematic diagram of a system for detecting the sealing performance of a protective closed door provided in the fourth embodiment of the present application; DETAILED DESCRIPTION

[0018] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only part of the present application is shown in the accompanying drawings, but not all of the content. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0019] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0020] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0021] The following is a detailed description of the method for detecting the sealing performance of a protective sealed door provided in the embodiment of the present application through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0022] Embodiment 1: Figure 1 1 is a flow chart of a method for detecting the sealing performance of a protective sealed door provided in the first embodiment of the present application. Figure 1 As shown, the specific steps include: S101, obtaining the leakage area, current pressure difference and preset air flow calculation formula of the enclosed space, and calculating the current air flow of the enclosed space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the enclosed space includes a protective enclosed door; the preset leakage area calculation formula is: ; in, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference.

[0023] First of all, the usage scenario of this solution can be to obtain relevant data of a confined space including a protective sealed door, calculate the sealing performance value of the confined space through the above relevant data, and determine whether the sealing performance of the protective sealed door has passed the test based on the sealing performance value.

[0024] Based on the above usage scenarios, it can be understood that the executor of the present application can be a detection system for the sealing performance of a protective closed door, and no excessive limitations are made here.

[0025] A confined space can be a sealed environmental area where the protective airtight door is the only potential source of gas leakage and there are no other potential leakage points. The size and shape of the confined space should be clearly defined and kept constant during the experiment.

[0026] Containment sealing doors can refer to doors used for sealing in confined spaces and are designed to prevent air or gas leakage.

[0027] Leakage area refers to the total area of ​​gas or air leakage caused by poor sealing in a confined space. It is an important indicator to measure the sealing performance.

[0028] The current pressure difference may refer to the difference in air pressure between the inside and outside of the enclosed space.

[0029] The current air flow rate may refer to the volume of air passing through the leakage point of the confined space per unit time.

[0030] You can use the geometric modeling function of CAD software or CFD tools to create a detailed 3D model of the sealed door and the space it is in. Make sure the model accurately reflects the actual situation, including the size of the door, the location of the sealing strip, and the shape of the sealed space. Pay special attention to the sealing area and potential leakage points, which should be modeled in detail to improve the simulation accuracy. Then set the physical properties, among which, fluid properties: define the physical properties of the fluid (usually air), such as density and viscosity. Airflow properties: set the speed and direction of the airflow, and you may need to set different flow modes (such as laminar or turbulent) according to the actual situation. Then set the boundary conditions, among which, inlet boundary: define the conditions (such as speed, pressure) for airflow to enter the sealed space. Outlet boundary: define the conditions for airflow to leave the sealed space. Wall boundary: set no-slip or slip conditions for sealed doors and other surfaces. Divide the geometric model into small calculation units, called meshes. The finer the mesh, the higher the accuracy of the simulation, but the more calculations are required. Finer meshing is performed on key areas (such as sealing areas) to capture more details. Then select a suitable CFD solver (such as ANSYS Fluent, OpenFOAM, etc.) and set the solver parameters, such as time step and convergence criteria. Start the simulation and monitor the convergence and calculation stability during the calculation process. After the simulation is completed, extract data such as flow field, pressure distribution and airflow velocity. According to the flow velocity and pressure difference, calculate the airflow through the closed door. Estimate the leakage area by analyzing the simulation results, especially the inspection of the flow uneven area. The relationship between fluid flow and pressure difference can be used to infer the leakage characteristics. Specifically, the flow uneven area can be identified in the simulation and the corresponding flow velocity and pressure data can be extracted. Then, the fluid flow equation (such as Bernoulli's equation) is used to link the flow and pressure difference to calculate the leakage area. Specifically, the airflow is obtained by integrating the fluid velocity field, and it is substituted into the formula with the pressure difference to infer the leakage area.

[0031] Then use a pressure sensor or a differential pressure sensor to measure the pressure difference between the inside and outside of the confined space, read the preset air flow calculation formula from the database, and the preset flow coefficient in the formula has been set, substitute the leakage area and the current pressure difference into the formula to calculate the current air flow in the confined space.

[0032] S102, obtaining the volume of the enclosed space and a preset ventilation rate calculation formula, and calculating the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; wherein the preset ventilation rate calculation formula is: ; in, is the current ventilation rate; is the current air flow rate; V is the volume of the enclosed space.

[0033] The volume of a confined space may refer to the total volume inside the confined space, which may be measured by the length, width, and height of the space.

[0034] The current ventilation rate can be referred to as the ratio of the amount of air passing through the confined space per unit time to the total volume of the confined space. It indicates how often the air in the space is replaced, usually expressed in the number of air changes per hour.

[0035] The length, width and height of the confined space can be measured using a suitable tool (such as a laser rangefinder), and then the length, width and height are multiplied to obtain the volume of the confined space. Then, the preset ventilation rate calculation formula is read from the database, and the calculated current air flow and the confined space volume are substituted into the preset ventilation rate calculation formula to obtain the current ventilation rate.

[0036] S103, obtaining the current temperature of the enclosed space and a preset sealing performance value calculation formula, and calculating the current sealing performance value of the enclosed space according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; wherein the preset sealing performance value calculation formula is: ; Among them, SP ( ) is the current sealing performance value; is the ventilation rate weight coefficient; is the current ventilation rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature.

[0037] The current temperature may be the instantaneous temperature inside the enclosed space, which is usually measured by a temperature sensor or a temperature measuring instrument, and the unit may be Celsius or Fahrenheit.

[0038] The current sealing performance value can be an indicator used to measure the sealing effect of a confined space, and usually reflects the sealing quality of the closed door and the overall sealing performance of the confined space. It can be used to evaluate the isolation effect and air leakage of the space. The value given in the formula is the calculated sealing performance value. Specifically, it can be a percentage or a specific sealing performance score (such as a value between 0 and 100). For example, if it is a specific sealing performance score, if is 0.5, is 0.3, is 0.1, is 0.8, is 10, is 22. , and then compare the current sealing performance values.

[0039] The air exchange rate weight coefficient, pressure difference weight coefficient and temperature weight coefficient in the formula are all extracted and preset, and a large amount of experimental data can be collected, including sealing performance value, air exchange rate, pressure difference and temperature. Use linear regression or other statistical analysis methods to analyze the influence of each variable on the sealing performance. According to the regression analysis results, adjust the air exchange rate weight coefficient, pressure difference weight coefficient and temperature weight coefficient. Finally, verify the accuracy of the model through actual tests, and further adjust the weight coefficient to ensure that the predicted sealing performance value is consistent with the actual situation. After determining the air exchange rate weight coefficient, pressure difference weight coefficient and temperature weight coefficient, you can fill in the formula and store the formula in the database. When it is needed, first read the preset sealing performance value calculation formula in the database, and then use a temperature sensor or temperature measuring instrument to measure the current temperature in the confined space, substitute the measured current pressure difference, current temperature and calculated current air exchange rate into the preset sealing performance value calculation formula to obtain the current sealing performance value of the confined space.

[0040] Based on the above technical solution, optionally, after calculating the current sealing performance value of the confined space, the method further includes: If the current sealing performance value is higher than the preset sealing performance threshold, the current ventilation rate, the current pressure difference, the current temperature and the preset prediction interval time are input into the preset sealing performance prediction model to obtain the predicted sealing performance value after the preset prediction interval time, and the prediction times are recorded; If the predicted sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0041] In this solution, the preset prediction interval time can be a time interval set by the system, which means a certain time point in the future (such as 30 minutes later, 1 hour later, 24 hours later) is used to predict the sealing performance. Different time intervals can be set according to the needs of actual applications.

[0042] The preset sealing performance prediction model can be a machine learning or statistical model, which is used to predict the sealing performance at a certain point in the future based on current sealing performance parameters (such as air change rate, pressure difference, temperature, etc.).

[0043] The predicted sealing performance value may be a value output by a sealing performance prediction model, which indicates the sealing performance status after a preset prediction interval.

[0044] The number of predictions may indicate the cumulative number of times the system has performed sealing performance predictions.

[0045] The preset prediction interval time can be read from the database, and the obtained current ventilation rate, the current pressure difference, the current temperature and the preset prediction interval time are input into the preset sealing performance prediction model. The model will make inferences based on the input features and use the parameters learned during the training process to calculate the sealing performance value after a period of time in the future. Specifically, the result output by the model can be a prediction value, which indicates the sealing performance status of the enclosed space after the preset prediction interval time. The value can be a percentage or a specific sealing performance score (such as a value between 0 and 100). For example, if it is a percentage, if the prediction value output by the model is 85%, it means that after the preset time interval (such as 1 hour), the sealing performance of the enclosed space is expected to drop to 85%. And each time a prediction is made, the system will record the number of predictions. When the predicted sealing performance value is obtained, it is compared with the preset sealing performance threshold. If the predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective sealed door has not passed the sealing performance test.

[0046] In this solution, by inputting real-time data into the prediction model, the future sealing performance status can be predicted quickly and accurately, thereby avoiding frequent manual inspections and reducing labor costs.

[0047] Based on the above technical solution, optionally, after obtaining the sealing performance value after the preset prediction time interval, the method further includes: If the predicted sealing performance value is higher than the preset sealing performance threshold, the current pressure difference is collected again after the preset collection interval is reached, and the current air flow rate of the enclosed space is updated according to the leakage area, the current pressure difference and the preset air flow rate calculation formula; Update the current ventilation rate of the enclosed space according to the updated current air flow, the volume of the enclosed space and a preset ventilation rate calculation formula; Re-acquire and update the current temperature of the enclosed space, and update the current sealing performance value of the enclosed space according to the updated current temperature, current pressure difference, current ventilation rate and a preset sealing performance value calculation formula; If the updated current sealing performance value is higher than the preset sealing performance threshold, the updated current temperature, current pressure difference, current ventilation rate and preset prediction interval time are input into the preset sealing performance prediction model, the predicted sealing performance value after the preset prediction interval time is updated, and the prediction times are updated until the prediction times reach the preset prediction times threshold; If all predicted sealing performance values ​​and all current sealing performance values ​​are higher than a preset sealing performance threshold, it is determined that the protective airtight door passes the sealing performance test; Accordingly, after updating the current sealing performance value of the confined space, the method further includes: If the updated current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test; Accordingly, after updating the predicted sealing performance value after the preset prediction interval time, the method further includes: If the updated predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0048] In this solution, the preset collection interval may refer to the time interval at which the system regularly collects data, which is used to update the environmental parameters of the enclosed space (such as pressure difference, air flow, temperature, etc.).

[0049] The preset prediction number threshold may refer to the maximum number of times the system performs sealing performance prediction during the test. For example, it may be set to 10 predictions, and if the sealing performance value is always qualified after 10 predictions, the protective airtight door is considered to have passed the test.

[0050] The current pressure difference, temperature and other data can be collected regularly, that is, the current pressure difference, temperature and other data are collected again after the preset collection interval time is reached, and the current air flow, current ventilation rate and current sealing performance value are recalculated by formula using the collected data. If the updated sealing performance value is higher than the preset threshold, the system continues to run and enters the next prediction. Then the updated data is input into the sealing performance prediction model, and the sealing performance prediction after the preset prediction interval time is performed to obtain the predicted sealing performance value. If the predicted sealing performance value is still higher than the preset sealing performance threshold, the above process is repeated until the number of predictions reaches the preset prediction number threshold. For example, if the preset prediction interval is one hour, the preset collection interval is 10 minutes, and the preset prediction threshold is 1000 times, data is collected every 10 minutes to predict the data for the next hour. If the current time is 10:00 am, the current sealing performance value is calculated based on the currently collected data. If the current sealing performance value is higher than the preset sealing performance threshold, the predicted sealing performance value at 11:00 am is predicted. If it is higher than the preset sealing performance threshold, data is collected at 10:10 am to calculate the current sealing performance value. If the current sealing performance value is higher than the preset sealing performance threshold, the predicted sealing performance value at 11:10 is predicted. If it is still higher than the preset sealing performance threshold, data is collected at 10:20 am to calculate the current sealing performance value. If the current sealing performance value is higher than the preset sealing performance threshold, the predicted sealing performance value at 11:20 is predicted. If the current sealing performance value or the predicted sealing performance value calculated at any time is lower than the preset sealing performance threshold, it is determined that the protective airtight door has not passed the sealing performance test. However, if after 1000 predictions, all current sealing performance values ​​and predicted sealing performance values ​​are higher than the preset sealing performance threshold, it is determined that the protective airtight door has passed the sealing performance test.

[0051] In this solution, the automated inspection process can reduce the frequency of manual inspections and save a lot of manpower and resources. The prediction model is used to determine whether the sealing performance is qualified based on the trend of multiple predicted sealing performance values, ensuring that the inspection of the sealed door is not only a reflection of the current status, but also a prediction of future performance changes, which improves the accuracy and reliability of the overall inspection.

[0052] Based on the above technical solution, the optional, preset sealing performance prediction model training process includes: Acquire a first historical ventilation rate, a first historical pressure difference, a first historical temperature, and a historical prediction interval time, and create a second data set according to the first historical ventilation rate, the first historical pressure difference, the first historical temperature, and the historical prediction interval time; labeling the sealing performance value of the second data set; A sealing performance prediction model is constructed, and the sealing performance prediction model is trained according to the second data set and the sealing performance value label until the sealing performance prediction model reaches a preset sealing performance prediction model training standard.

[0053] In this solution, the first historical ventilation rate may refer to the ventilation rate of the protective closed door in the past records, that is, the amount of air exchanged per unit time. The ventilation rate may affect the air circulation and sealing performance of the closed space.

[0054] The first historical pressure difference may refer to the pressure difference between the inside and outside of the closed space in the past records. This difference may affect the effectiveness of the seal.

[0055] The first historical temperature may refer to an ambient temperature in past records. Temperature may affect the expansion or contraction of a material, thereby affecting sealing performance.

[0056] The historical prediction interval may refer to the time interval used in the past data for sealing performance prediction, for example, the time interval for updating the sealing performance prediction.

[0057] The second data set may be created by collecting the first historical ventilation rate, the first historical pressure difference, the first historical temperature, and the historical prediction interval time. This data set includes these features and corresponding sealing performance values, and is used to train the prediction model.

[0058] The sealing performance value labels may be sealing performance values ​​associated with each record in the second data set, which represent the actual sealing performance of the sealed door under given conditions.

[0059] The preset sealing performance prediction model training standard may be an indicator for evaluating whether the sealing performance prediction model is successfully trained, such as the accuracy, mean square error (MSE), root mean square error (RMSE), etc. of the model.

[0060] The historical usage data, fault data, environmental data and maintenance records of the protective sealed door can be collected from the database. The data is organized into a second data set, each record of which includes the first historical ventilation rate, pressure difference, temperature and historical prediction interval time, and then each record in the second data set is labeled with a sealing performance value label, which represents the sealing performance results under specific conditions. Then, a suitable machine learning algorithm (such as linear regression, support vector machine, neural network, etc.) is selected to build a sealing performance prediction model. The model is trained using the features and labels in the second data set. The training process includes adjusting the model parameters until the performance indicators of the model reach the preset sealing performance prediction model training standards.

[0061] In this solution, by using historical data and a specific prediction interval, the model can predict the sealing performance based on actual historical records, which can improve the accuracy of the prediction because the model learns the actual situation in the past and can capture the law of how the sealing performance changes over time.

[0062] S104: If the current sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0063] The preset sealing performance threshold value can be a standard value for evaluating the performance of the sealing door, which represents the minimum acceptable level of sealing performance. If the sealing performance value of the enclosed space is lower than this threshold value, it is considered that the sealing performance of the sealing door does not meet the requirements.

[0064] The standard value of sealing performance can be determined according to relevant industry standards, regulations or specifications. For example, the construction industry or equipment manufacturing industry may have specific sealing performance requirements. After the preset sealing performance threshold is determined, it can be stored in the database, and when it is needed, it can be directly read from the database, and then the calculated current sealing performance value is compared with the preset sealing performance threshold. If the calculated current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0065] The technical solution provided in this embodiment obtains the leakage area, current pressure difference and preset air flow calculation formula of the enclosed space, and calculates the current air flow of the enclosed space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the enclosed space includes a protective enclosed door; obtains the volume of the enclosed space and a preset ventilation rate calculation formula, and calculates the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow and the preset ventilation rate calculation formula; obtains the current temperature of the enclosed space and a preset sealing performance value calculation formula, and calculates the current sealing performance value of the enclosed space according to the current temperature, current pressure difference, current ventilation rate and preset sealing performance value calculation formula; if the current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective enclosed door has not passed the sealing performance test. Through the above-mentioned testing method for the sealing performance of protective sealed doors, key parameters such as the leakage area, current pressure difference, air flow, ventilation rate and sealing performance value of the confined space can be accurately quantified, avoiding errors caused by subjective judgment, improving the accuracy of the evaluation, and helping to discover and solve problems with poor sealing performance, thereby improving the reliability of protective sealed doors. Automated testing processes can improve testing efficiency and save labor costs.

[0066] Based on the above technical solution, optionally, after determining that the protective airtight door fails the sealing performance test, the method further includes: The device information of the protective sealed door is obtained, and the device information is sent to the control center, so that the control center can lock the target protective sealed door according to the device information and perform subsequent processing.

[0067] In this solution, the device information can be various detailed data about the protective sealed door, specifically, it can include device ID: a number or code that uniquely identifies each protective sealed door. Device model: the specific model or specification of the device. Installation location: the physical location or installation site of the device, which helps to locate the device.

[0068] If the protective sealed door fails the sealing performance test, the real-time equipment information can be automatically collected through the sensors and monitoring systems on the equipment and sent to the control center through wireless communication technology.

[0069] In this solution, when the protective sealed door fails the sealing performance test, the device information is sent to the control center, which can quickly lock the number and location of the target protective sealed door that failed the test.

[0070] Embodiment 2: Figure 2 is a flow chart of a method for detecting the sealing performance of a protective sealed door provided in the second embodiment of the present application, such as Figure 2 As shown, the specific method includes the following steps: S201, obtaining the leakage area, current pressure difference and preset air flow calculation formula of the enclosed space, and calculating the current air flow of the enclosed space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the enclosed space includes a protective enclosed door; the preset leakage area calculation formula is: ; in, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference.

[0071] S202, obtaining the volume of the enclosed space and a preset ventilation rate calculation formula, and calculating the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; wherein the preset ventilation rate calculation formula is: ; in, is the current ventilation rate; is the current air flow rate; V is the volume of the enclosed space.

[0072] S203, obtaining the current temperature of the enclosed space and a preset sealing performance value calculation formula, and calculating the current sealing performance value of the enclosed space according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; wherein the preset sealing performance value calculation formula is: ; Among them, SP ( ) is the current sealing performance value; is the ventilation rate weight coefficient; is the current ventilation rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature.

[0073] S204: If the current sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

[0074] S205, input the current temperature, current pressure difference and current ventilation rate into a preset abnormal cause detection model, determine the abnormal cause of the protective sealed door failing the sealing performance test, and send the abnormal cause to the control center for the control center to improve the protective sealed door according to the abnormal cause.

[0075] The preset abnormal cause detection model can be a machine learning or deep learning model, which is specifically used to identify the abnormal cause of the protective airtight door when the sealing performance does not meet the standard. The input of the model includes data such as the current ventilation rate, the current pressure difference, and the current temperature, and the output is the abnormal cause that causes the sealing performance to fail to meet the standard.

[0076] The abnormal reason may refer to the specific reason why the sealing performance of the protective sealed door fails to pass the test. Specifically, it may include aging of the door frame or seal: the sealing material loses its elasticity due to long-term use or environmental influences. Structural deformation: the protective sealed door is deformed due to external forces, and the sealing performance is reduced. Temperature or pressure fluctuations: the ambient temperature or pressure exceeds the design range, resulting in poor sealing effect. Installation or debugging problems: improper installation or debugging of the sealed door leads to poor airtightness.

[0077] The control center can refer to a system or platform for centralized monitoring and management of equipment status. It receives abnormal reports from protective closed doors and takes corresponding actions based on the abnormal causes.

[0078] The current data of the protective sealed door (air change rate, pressure difference, temperature, etc.) can be input into the trained abnormal cause detection model. Based on the input data, the model uses a preset algorithm to determine the specific abnormal cause that caused the sealing performance test to fail. The model compares each input feature (air change rate, pressure difference, temperature) with the abnormal pattern learned in the model to determine which abnormal cause caused the sealing performance problem. The output of the model is the abnormal cause, such as "aging of sealing materials" or "excessive temperature fluctuations", which will then be sent to the control center as part of the report. For example, a protective sealed door detects that the current air change rate is 5m³ / h, the pressure difference is 10Pa, and the temperature is 35℃. These data are input into the abnormal cause detection model, and the model identifies the abnormal cause as "aging of sealing materials". The result is sent to the control center, and the staff can formulate a maintenance plan based on this information to replace the aged seals.

[0079] In this embodiment, the preset abnormal cause detection model can help to quickly and accurately diagnose the reasons why the sealing performance of the protective airtight door is unqualified, thereby improving the efficiency and accuracy of equipment maintenance.

[0080] Based on the above technical solution, the optional training process of the preset abnormal cause detection model includes: Acquire a second historical ventilation rate, a second historical pressure difference, and a second historical temperature when the protective airtight door fails, and create a third data set according to the second historical ventilation rate, the second historical pressure difference, and the second historical temperature; Label the abnormal reasons of the third data set; An abnormality cause detection model is constructed, and the abnormality cause detection model is trained according to the third data set and the abnormality cause label until the abnormality cause detection model reaches a preset abnormality cause detection model training standard.

[0081] In this solution, the second historical ventilation rate may be ventilation rate data recorded during the period when the protective airtight door fails, and these data reflect the ventilation conditions before and after the failure.

[0082] The second historical pressure difference may be pressure difference data when the protective airtight door fails. These data provide information on the air pressure change in the enclosed space.

[0083] The second historical temperature may be the temperature data when the protective airtight door fails, and these data reflect the change of the ambient temperature at that time.

[0084] The third data set may be a data set created based on historical air change rate, pressure difference, and temperature data when a protective airtight door fails.

[0085] The abnormal reason label can be a mark of the specific abnormal reason when the protective airtight door fails. It explains why the failure occurred, such as seal failure, equipment aging, etc.

[0086] The preset abnormal cause detection model training standard may be the goal and requirement for abnormal cause detection model training, for example, the accuracy, recall rate, F1 score and other indicators of the model reach a predetermined threshold.

[0087] You can collect historical ventilation rate, pressure difference, and temperature data of protective closed doors when they fail, ensuring that these data have sufficient time span and representativeness. Then use the collected data to create a third data set, and assign an abnormal cause label to each piece of data in the third data set. These labels need to be labeled based on the actual failure situation, such as by analyzing historical failure records or expert judgment. Then select an appropriate machine learning or deep learning algorithm (such as decision tree, random forest, support vector machine, neural network, etc.). Use the labeled third data set and abnormal cause labels for training. Adjust the algorithm parameters and optimize the model performance until the model reaches the preset training standard.

[0088] In this solution, automated anomaly detection reduces the need for manual inspection, improves detection efficiency, and reduces human errors. The training model can detect the cause of the protective airtight door failure in real time, helping to quickly identify the problem.

[0089] Embodiment 3: Figure 3 is a flow chart of a method for detecting the sealing performance of a protective sealed door provided in the third embodiment of the present application, such as Figure 3 As shown, the specific method includes the following steps: S301, obtaining historical usage data, first historical fault data, historical environmental data and first historical maintenance records of each protective sealed door throughout its life cycle, and creating a first data set based on the historical usage data, first historical fault data, historical environmental data and first historical maintenance records.

[0090] Historical usage data can be the operation record of the protective closed door during its life cycle, including frequency of use, number of openings and closings each time, continuous operation time, etc., which can be collected through the equipment's operation log or monitoring system.

[0091] The first historical fault data may be the fault history of the protective sealed door, including the time of each fault, the fault type, the impact scope and the repair time, etc.

[0092] The historical environmental data may be historical data of the environment in which the sealed door is located, including environmental parameters such as temperature, humidity, air pressure, vibration, etc., which may affect the performance of the protective sealed door.

[0093] The first historical maintenance record may be a record of all maintenance and inspections performed on the protective sealed door, including maintenance time, specific operation content, replaced parts, maintenance results, etc.

[0094] The first data set may be a comprehensive data set formed by integrating the above historical usage data, the first historical fault data, the historical environmental data and the first historical maintenance record. The data set is used to comprehensively analyze the operating status of the protective sealed door. Each data record reflects the usage status, environmental conditions, fault information and maintenance information of the protective sealed door at a specific time point.

[0095] The historical usage data, fault data, environmental data and maintenance records of the entire life cycle of the protective sealed door can be collected, and the data can be pre-processed (such as data cleaning, deduplication, normalization, etc.) to ensure data quality. The data can be arranged on a timeline to form a complete data set, and the faults and maintenance operations at each time point can be clearly marked.

[0096] S302, marking a fault time label, a fault type label, and a maintenance solution label of the first data set; The fault time label can be a label that marks the specific time when the fault occurs, helping the model predict the time point of the fault.

[0097] The fault type label can be a type label for each fault, such as door frame deformation, seal failure, electronic control failure, etc., which is used for the output of the classification prediction model.

[0098] The maintenance solution label may be a label indicating the maintenance or repair measures taken to solve the fault, such as replacing a sealing strip, recalibrating a door frame, adjusting a control system, etc. The label is used to predict the best maintenance solution under similar fault conditions.

[0099] A fault time label (timestamp when the fault occurred) and a fault type label can be added to each data record in the first data set to ensure that the specific type of each fault is accurately classified. According to historical maintenance records, a maintenance plan label is added to each fault to record the specific maintenance plan.

[0100] S303, constructing a fault prediction model for the protective sealed door, and training the fault prediction model according to the first data set, the fault time label, the fault type label, and the maintenance plan label until the fault prediction model reaches a preset fault model training standard.

[0101] The fault prediction model can be a machine learning model that aims to predict possible future faults and their occurrence time and type based on the historical data of the input protective sealed door, and recommend appropriate maintenance plans. The model predicts the health status of the equipment and gives fault warnings by analyzing the equipment's usage status, environmental data, fault history, and maintenance records.

[0102] The preset fault model training standards can be indicators for evaluating model performance. Common standards include accuracy, recall, F1 score, prediction accuracy of the model in different time windows, etc. When the performance of the model on these indicators meets the preset standards (such as accuracy exceeding 90%, or F1 score greater than 0.8), the model training is considered to meet the standards and can be put into practical application.

[0103] The data records of the first data set can be bound to the corresponding fault time labels, fault type labels, and maintenance plan labels. According to the nature of the data, select the appropriate model type. Specifically, time series models (such as LSTM or GRU) are suitable for processing data with time sequence and can predict future faults. Classification models (such as random forest, XGBoost, deep neural network) are suitable for predicting fault type and maintenance plan based on features. Multi-task learning models can simultaneously predict fault time, type, and maintenance suggestions to improve the overall performance of the model. Then input various data in the first data set as features, including historical usage data, fault data, environmental data, etc. The output is the fault time label (time series), fault type label (classification task), and maintenance plan label (classification task) that match the first data set. Use supervised learning to pair the input data with the target label and train the model to find the relationship between the input and the occurrence of the fault. Use a suitable loss function, such as the mean square error (MSE) for time prediction or the cross entropy loss in the classification task. Use optimization algorithms such as gradient descent to continuously update the model weights and gradually reduce the training error. Specifically, use the first data set as input data and the label (failure time, fault type, maintenance plan) as a supervisory signal. The fault prediction model is learned based on the correspondence between input features and labels until the preset training criteria are met.

[0104] In this embodiment, by constructing a fault prediction model, the possible fault time and type can be predicted in advance before the protective sealed door fails, which helps to take preventive measures. By regularly analyzing the status of the protective sealed door, potential faults and performance degradation can be detected, and adjustments and repairs can be made in time, thereby extending the service life of the protective sealed door and maintaining its optimal operating performance.

[0105] On the basis of the above technical solution, optionally, after training the fault prediction model according to the first data set, the fault time label, the fault type label and the maintenance solution label until the fault prediction model reaches a preset fault model training standard, the method further includes: Acquire real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records of the protective sealed door, input the real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records into a fault prediction model, and determine a predicted fault time, a predicted fault type, and a predicted maintenance plan; The predicted failure time, predicted failure type and predicted maintenance plan are sent to the control center for the staff to perform maintenance work on the protective closed door.

[0106] In this solution, the real-time usage data may be the current operating status data of the protective sealed door. Specifically, it may include the door's switch status, usage frequency, operating time, pressure changes, temperature changes, and other dynamic data related to the door operation.

[0107] Real-time environmental data can be data on environmental conditions around the confined space. This includes environmental factors such as temperature, humidity, and air pressure that may affect the operation of the protective closed door.

[0108] The second historical fault data refers to the records of faults that have occurred during the use of the protective sealed door, which may include the time of the fault, the type of fault, the scope of impact and the repair time.

[0109] The second historical maintenance record may be a record of maintenance work that has been performed during the use of the protective sealed door, and may include maintenance time, specific operation content, replaced parts and maintenance results, etc.

[0110] The predicted failure time can be the time point in the future when the system may fail, given by a prediction model.

[0111] The predicted fault type may be a specific fault type that is about to occur given by a fault prediction model, such as sealing performance degradation, mechanical damage, electrical failure, etc.

[0112] The predictive maintenance plan can be a maintenance solution proposed by the system based on the fault prediction results, which may include specific maintenance suggestions such as replacing parts, adjusting operating parameters, and conducting regular inspections.

[0113] Real-time usage data and real-time environmental data can be collected from the sensors and monitoring systems of the protective closed doors. These data are transmitted to the fault prediction system in real time through the interface. The real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records are input into the trained fault prediction model. Based on these input data, the model outputs the predicted fault time, fault type, and recommended maintenance plan. The predicted fault time, predicted fault type, and predicted maintenance plan are then sent to the control center through wireless communication technology.

[0114] In this solution, predictive maintenance can identify potential failures in advance, reduce the cost of emergency repairs and replacement parts, and thus reduce maintenance costs. Through timely maintenance and repairs, the wear and damage of protective sealed doors can be reduced, the service life of protective sealed doors can be extended, and the return on investment can be improved.

[0115] Embodiment 4: Figure 4 : is a structural schematic diagram of a detection system for the sealing performance of a protective closed door provided in the fourth embodiment of the present application, such as Figure 4As shown, the system is used to implement a method for detecting the sealing performance of a protective closed door provided in embodiments 1, 2, and 3. The system specifically includes the following: The air flow calculation module 401 is used to obtain the leakage area of ​​the enclosed space, the current pressure difference and the preset air flow calculation formula, and calculate the current air flow of the enclosed space according to the leakage area, the current pressure difference and the preset air flow calculation formula; wherein the enclosed space includes a protective airtight door; the preset leakage area calculation formula is: ; in, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference; The ventilation rate calculation module 402 is used to obtain the volume of the enclosed space and a preset ventilation rate calculation formula, and calculate the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; wherein the preset ventilation rate calculation formula is: ; in, is the current ventilation rate; is the current air flow; V is the volume of the enclosed space; The sealing performance value calculation module 403 is used to obtain the current temperature of the enclosed space and a preset sealing performance value calculation formula, and calculate the current sealing performance value of the enclosed space according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; wherein the preset sealing performance value calculation formula is: ; Among them, SP ( ) is the current sealing performance value; is the ventilation rate weight coefficient; is the current ventilation rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature; The detection module 404 is used to determine that the protective airtight door fails the sealing performance test if the current sealing performance value is lower than a preset sealing performance threshold.

[0116] In an embodiment of the present application, an air flow calculation module is used to obtain the leakage area, current pressure difference and preset air flow calculation formula of the enclosed space, and calculate the current air flow of the enclosed space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the enclosed space includes a protective enclosed door; a ventilation rate calculation module is used to obtain the volume of the enclosed space and a preset ventilation rate calculation formula, and calculate the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow and the preset ventilation rate calculation formula; a sealing performance value calculation module is used to obtain the current temperature of the enclosed space and a preset sealing performance value calculation formula, and calculate the current sealing performance value of the enclosed space according to the current temperature, current pressure difference, current ventilation rate and preset sealing performance value calculation formula; a detection module is used to determine that the protective enclosed door has not passed the sealing performance test if the current sealing performance value is lower than a preset sealing performance threshold. Through the above-mentioned protective closed door sealing performance detection system, key parameters such as the leakage area, current pressure difference, air flow, ventilation rate and sealing performance value of the confined space can be accurately quantified, avoiding errors caused by subjective judgment, improving the accuracy of the evaluation, and helping to discover and solve problems with poor sealing performance, thereby improving the reliability of the protective closed door. The automated detection process can improve detection efficiency and save labor costs.

[0117] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A method for detecting the sealing performance of a protective closed door, characterized in that: The method comprises: Obtain the leakage area, current pressure difference and preset air flow calculation formula of the confined space, and calculate the current air flow of the confined space according to the leakage area, current pressure difference and preset air flow calculation formula; wherein the confined space includes a protective closed door; the preset leakage area calculation formula is: ； in, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference; The volume of the enclosed space and a preset ventilation rate calculation formula are obtained, and the current ventilation rate of the enclosed space is calculated according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; wherein the preset ventilation rate calculation formula is: ； in, is the current ventilation rate; is the current air flow; V is the volume of the enclosed space; The current temperature of the enclosed space and a preset sealing performance value calculation formula are obtained, and the current sealing performance value of the enclosed space is calculated according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; wherein the preset sealing performance value calculation formula is: ； Among them, SP ( ) is the current sealing performance value; is the ventilation rate weight coefficient; is the current ventilation rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature; If the current sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

2. The method for detecting the sealing performance of a protective airtight door according to claim 1, characterized in that: After calculating the current sealing performance value of the enclosed space, the method further includes: If the current sealing performance value is higher than the preset sealing performance threshold, the current ventilation rate, the current pressure difference, the current temperature and the preset prediction interval time are input into the preset sealing performance prediction model to obtain the predicted sealing performance value after the preset prediction interval time, and the prediction times are recorded; If the predicted sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

3. The method for detecting the sealing performance of a protective closed door according to claim 2, characterized in that: After obtaining the sealing performance value after the preset prediction time interval, the method further includes: If the predicted sealing performance value is higher than the preset sealing performance threshold, the current pressure difference is collected again after the preset collection interval is reached, and the current air flow rate of the enclosed space is updated according to the leakage area, the current pressure difference and the preset air flow rate calculation formula; Update the current ventilation rate of the enclosed space according to the updated current air flow, the volume of the enclosed space and a preset ventilation rate calculation formula; Re-acquire and update the current temperature of the enclosed space, and update the current sealing performance value of the enclosed space according to the updated current temperature, current pressure difference, current ventilation rate and a preset sealing performance value calculation formula; If the updated current sealing performance value is higher than the preset sealing performance threshold, the updated current temperature, current pressure difference, current ventilation rate and preset prediction interval time are input into the preset sealing performance prediction model, the predicted sealing performance value after the preset prediction interval time is updated, and the prediction times are updated until the prediction times reach the preset prediction times threshold; If all predicted sealing performance values ​​and all current sealing performance values ​​are higher than a preset sealing performance threshold, it is determined that the protective airtight door passes the sealing performance test; Accordingly, after updating the current sealing performance value of the confined space, the method further includes: If the updated current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test; Accordingly, after updating the predicted sealing performance value after the preset prediction interval time, the method further includes: If the updated predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door has failed the sealing performance test.

4. The method for detecting the sealing performance of a protective closed door according to claim 1, characterized in that: After determining that the protective airtight door fails the sealing performance test, the method further includes: The current temperature, the current pressure difference and the current ventilation rate are input into a preset abnormal cause detection model to determine the abnormal cause of the protective sealed door failing the sealing performance test, and the abnormal cause is sent to the control center for the control center to improve the protective sealed door according to the abnormal cause.

5. The method for detecting the sealing performance of a protective airtight door according to claim 3, characterized in that: After determining that the protective airtight door passes the sealing performance test, the method further includes: Obtain historical usage data, first historical fault data, historical environmental data, and first historical maintenance records of each protective sealed door throughout its life cycle, and create a first data set based on the historical usage data, first historical fault data, historical environmental data, and first historical maintenance records; Annotating the first data set with a failure time label, a failure type label, and a maintenance plan label; A fault prediction model for the protective sealed door is constructed, and the fault prediction model is trained according to the first data set, the fault time label, the fault type label, and the maintenance plan label until the fault prediction model reaches a preset fault model training standard.

6. The method for detecting the sealing performance of a protective airtight door according to claim 5, characterized in that: After training the fault prediction model according to the first data set, the fault time label, the fault type label, and the maintenance solution label until the fault prediction model reaches a preset fault model training standard, the method further includes: Acquire real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records of the protective sealed door, input the real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records into a fault prediction model, and determine a predicted fault time, a predicted fault type, and a predicted maintenance plan; The predicted failure time, predicted failure type and predicted maintenance plan are sent to the control center for the staff to perform maintenance work on the protective closed door.

7. The method for detecting the sealing performance of a protective airtight door according to claim 2, characterized in that: The training process of the preset sealing performance prediction model includes: Acquire a first historical ventilation rate, a first historical pressure difference, a first historical temperature, and a historical prediction interval time, and create a second data set according to the first historical ventilation rate, the first historical pressure difference, the first historical temperature, and the historical prediction interval time; labeling the sealing performance value of the second data set; A sealing performance prediction model is constructed, and the sealing performance prediction model is trained according to the second data set and the sealing performance value label until the sealing performance prediction model reaches a preset sealing performance prediction model training standard.

8. The method for detecting the sealing performance of a protective airtight door according to claim 4, characterized in that: The training process of the preset abnormal cause detection model includes: Acquire a second historical ventilation rate, a second historical pressure difference, and a second historical temperature when the protective airtight door fails, and create a third data set according to the second historical ventilation rate, the second historical pressure difference, and the second historical temperature; Label the abnormal reasons of the third data set; An abnormality cause detection model is constructed, and the abnormality cause detection model is trained according to the third data set and the abnormality cause label until the abnormality cause detection model reaches a preset abnormality cause detection model training standard.

9. The method for detecting the sealing performance of a protective airtight door according to claim 1, characterized in that: After determining that the protective airtight door fails the sealing performance test, the method further includes: The device information of the protective sealed door is obtained, and the device information is sent to the control center, so that the control center can lock the target protective sealed door according to the device information and perform subsequent processing.

10. A system for detecting the sealing performance of a protective closed door, characterized in that: The system comprises: An air flow calculation module is used to obtain the leakage area of ​​the enclosed space, the current pressure difference and a preset air flow calculation formula, and calculate the current air flow of the enclosed space according to the leakage area, the current pressure difference and the preset air flow calculation formula; A ventilation rate calculation module, used to obtain the volume of the enclosed space and a preset ventilation rate calculation formula, and calculate the current ventilation rate of the enclosed space according to the volume of the enclosed space, the current air flow rate and the preset ventilation rate calculation formula; A sealing performance value calculation module, used to obtain the current temperature of the enclosed space and a preset sealing performance value calculation formula, and calculate the current sealing performance value of the enclosed space according to the current temperature, the current pressure difference, the current ventilation rate and the preset sealing performance value calculation formula; The detection module is used to determine that the protective airtight door fails the sealing performance test if the current sealing performance value is lower than a preset sealing performance threshold.

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