A detection method and system for the sealing performance of a protective airtight door

Abstract

The present application discloses a method and system for detecting the sealing performance of a blast-proof airtight door, and the present application belongs to the field of performance detection of blast-proof airtight doors. The method includes: calculating the current air flow rate of the enclosed space; calculating the current air change rate of the enclosed space; 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 air change 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 blast-proof airtight door fails the sealing performance test. This solution can accurately quantify key parameters such as the leakage area, the current pressure difference, the air flow rate, the air change rate and the sealing performance value of the enclosed space, improve the accuracy of evaluation, help to discover and solve the problem of poor sealing performance, and thus improve the reliability of the blast-proof airtight door. The automated detection process can improve the detection efficiency and save labor costs.

Description

Technical Field

[0001] This application relates to the technical field of performance testing of airtight blast doors, and particularly to a method and system for testing the sealing performance of airtight blast doors. Background Art

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

[0003] Currently, manual testing of the sealing performance of airtight blast doors is required. First, the airtight blast door needs to be closed to ensure that the door leaf fits tightly with the door frame. Subsequently, a smoke generator or tracer gas is released on one side of the door, and at the same time, it is observed whether there is any gas leakage on the other side of the door. In addition, tools such as feeler gauges can be used to detect the gap between the door leaf and the door frame mating surface to evaluate the sealing effect.

[0004] However, manual testing relies on experience and subjective judgment, resulting in low accuracy. And the testing takes a long time and the testing efficiency is low. At the same time, manual testing is generally carried out regularly and cannot monitor the status of the airtight door in real time. Summary of the Invention

[0005] The embodiments of this application provide a method for testing the sealing performance of an airtight blast door, which solves the problems in the prior art that manual testing of the performance of an airtight blast door relies on experience and subjective judgment, resulting in low accuracy. And the testing takes a long time and the testing efficiency is low. At the same time, manual testing is generally carried out regularly and cannot monitor the status of the airtight door in real time.

[0006] In a first aspect, the embodiments of this application provide a method for testing the sealing performance of an airtight blast door, the method comprising:

[0007] 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; wherein, the enclosed space includes an airtight blast door; the preset leakage area calculation formula is:

[0008] ;

[0009] Wherein, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference;

[0010] Obtain the volume of the enclosed space and the preset calculation formula for the air change rate. Calculate the current air change rate of the enclosed space according to the volume of the enclosed space, the current air flow rate, and the preset calculation formula for the air change rate. The preset calculation formula for the air change rate is as follows:

[0011] ;

[0012] Wherein, is the current air change rate; is the current air flow rate; V is the volume of the enclosed space;

[0013] Obtain the current temperature of the enclosed space and the preset calculation formula for the sealing performance value. Calculate the current sealing performance value of the enclosed space according to the current temperature, the current pressure difference, the current air change rate, and the preset calculation formula for the sealing performance value. The preset calculation formula for the sealing performance value is as follows:

[0014] ;

[0015] Wherein, SP( ) is the current sealing performance value; is the air change rate weight coefficient; is the current air change rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature;

[0016] If the current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test.

[0017] Further, after calculating the current sealing performance value of the enclosed space, the method further includes:

[0018] If the current sealing performance value is higher than the preset sealing performance threshold, input the current air change rate, the current pressure difference, the current temperature, and the preset prediction interval time into the preset sealing performance prediction model to obtain the predicted sealing performance value after the preset prediction interval time, and record the number of predictions;

[0019] If the predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test.

[0020] Further, after obtaining the sealing performance value after the preset prediction time interval, the method further includes:

[0021] If the predicted sealing performance value is higher than the preset sealing performance threshold, then after reaching the preset acquisition interval time, the current pressure difference is re-acquired, and according to the leakage area, the current pressure difference, and the preset air flow calculation formula, the current air flow of the enclosed space is updated;

[0022] According to the updated current air flow, the volume of the enclosed space, and the preset air change rate calculation formula, the current air change rate of the enclosed space is updated;

[0023] The current temperature of the enclosed space is re-acquired and updated. According to the updated current temperature, current pressure difference, current air change rate, and the preset sealing performance value calculation formula, the current sealing performance value of the enclosed space is updated;

[0024] If the updated current sealing performance value is higher than the preset sealing performance threshold, the updated current temperature, current pressure difference, current air change rate, and the 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;

[0025] If all the predicted sealing performance values and all the current sealing performance values are higher than the preset sealing performance threshold, it is determined that the protective airtight door passes the sealing performance test;

[0026] Correspondingly, after updating the current sealing performance value of the enclosed space, the method further includes:

[0027] If the updated current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test;

[0028] Correspondingly, after updating the predicted sealing performance value after the preset prediction interval time, the method further includes:

[0029] If the updated predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test.

[0030] Further, after determining that the protective airtight door fails the sealing performance test, the method further includes:

[0031] The current temperature, current pressure difference, and current air change rate are input into the preset abnormal cause detection model to determine the abnormal cause of the protective airtight door failing the sealing performance test, and the abnormal cause is sent to the control center for the control center to improve the protective airtight door according to the abnormal cause.

[0032] Further, after determining that the protective airtight door passes the sealing performance test, the method further includes:

[0033] Obtain the historical usage data, first historical failure data, historical environmental data, and first historical maintenance records of each protective airtight door throughout its life cycle, and create a first data set based on the historical usage data, first historical failure data, historical environmental data, and first historical maintenance records;

[0034] Label the failure time tag, failure type tag, and maintenance plan tag of the first data set;

[0035] Construct a failure prediction model for the protective airtight door, and train the failure prediction model based on the first data set, the failure time tag, failure type tag, and maintenance plan tag until the failure prediction model reaches a preset failure model training standard.

[0036] Further, after training the failure prediction model based on the first data set, the failure time tag, failure type tag, and maintenance plan tag until the failure prediction model reaches a preset failure model training standard, the method further includes:

[0037] Obtain the real-time usage data, real-time environmental data, second historical failure data, and second historical maintenance records of the protective airtight door, input the real-time usage data, real-time environmental data, second historical failure data, and second historical maintenance records into the failure prediction model, and determine the predicted failure time, predicted failure type, and predicted maintenance plan;

[0038] Send the predicted failure time, predicted failure type, and predicted maintenance plan to the control center for the staff to carry out the maintenance work of the protective airtight door.

[0039] Further, the training process of the preset sealing performance prediction model includes:

[0040] Obtain the first historical air change rate, first historical pressure difference, first historical temperature, and historical prediction interval time, and create a second data set based on the first historical air change rate, first historical pressure difference, first historical temperature, and historical prediction interval time;

[0041] Label the sealing performance value tag of the second data set;

[0042] Construct a sealing performance prediction model, and train the sealing performance prediction model based on the second data set and the sealing performance value tag until the sealing performance prediction model reaches a preset sealing performance prediction model training standard.

[0043] Further, the training process of the preset abnormal cause detection model includes:

[0044] Obtain the second historical air change rate, the second historical pressure difference, and the second historical temperature when the airtight and blast door fails, and create a third data set according to the second historical air change rate, the second historical pressure difference, and the second historical temperature;

[0045] Label the abnormal cause tags of the third data set;

[0046] Construct an abnormal cause detection model, and train the abnormal cause detection model according to the third data set and the abnormal cause tags until the abnormal cause detection model reaches the preset abnormal cause detection model training standard.

[0047] Further, after determining that the airtight and blast door fails the sealing performance test, the method further includes:

[0048] Obtain the device information of the airtight and blast door, and send the device information to the control center for the control center to lock the target airtight and blast door according to the device information and perform subsequent processing.

[0049] According to the second aspect of the present application, there is provided a detection system for the sealing performance of an airtight and blast door, the system includes:

[0050] An air flow calculation module, configured 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; wherein, the enclosed space includes an airtight and blast door; the preset leakage area calculation formula is:

[0051] ;

[0052] Wherein, is the current air flow; A is the leakage area; C is a preset flow coefficient; is the current pressure difference;

[0053] An air change rate calculation module, configured to obtain the volume of the enclosed space and a preset air change rate calculation formula, and calculate the current air change rate of the enclosed space according to the volume of the enclosed space, the current air flow, and the preset air change rate calculation formula; wherein, the preset air change rate calculation formula is:

[0054] ;

[0055] Wherein, is the current air change rate; is the current air flow; V is the volume of the enclosed space;

[0056] A sealing performance value calculation module, configured 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 air change rate, and the preset sealing performance value calculation formula; wherein, the preset sealing performance value calculation formula is:

[0057] ;

[0058] wherein, SP( ) is the current sealing performance value; is the air change rate weight coefficient; is the current air change rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature;

[0059] A detection module, configured to determine that the protective airtight door fails the sealing performance detection if the current sealing performance value is lower than a preset sealing performance threshold.

[0060] In an embodiment of the present application, 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; wherein, the enclosed space includes a protective airtight door; obtain the volume of the enclosed space and a preset air change rate calculation formula, and calculate the current air change rate of the enclosed space according to the volume of the enclosed space, the current air flow, and the preset air change rate calculation formula; 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 air change rate, and the preset sealing performance value calculation formula; if the current sealing performance value is lower than a preset sealing performance threshold, determine that the protective airtight door fails the sealing performance detection. Through the above detection method for the sealing performance of the protective airtight door, key parameters such as the leakage area, the current pressure difference, the air flow, the air change rate, and the sealing performance value of the enclosed space can be accurately quantified, avoiding errors caused by subjective judgment, improving the accuracy of evaluation, helping to discover and solve problems with poor sealing performance, thereby improving the reliability of the protective airtight door. The automated detection process can improve the detection efficiency and save labor costs. Description of the Drawings

[0061] Figure 1 is a schematic flowchart of a detection method for the sealing performance of a protective airtight door provided in Embodiment 1 of the present application;

[0062] Figure 2 is a schematic flowchart of a detection method for the sealing performance of a protective airtight door provided in Embodiment 2 of the present application;

[0063] Figure 3 It is a schematic flowchart of the detection method for the sealing performance of the airtight blast door provided in Embodiment 3 of the present application;

[0064] Figure 4 It is a schematic structural diagram of the detection system for the sealing performance of the airtight blast door provided in Embodiment 4 of the present application; Detailed implementation manners

[0065] In order to make the purpose, technical solutions and advantages of the present application clearer, the following further describes the specific embodiments of the present application in detail with reference to the accompanying drawings. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than limiting the present application. Additionally, it should be noted that for the convenience of description, only parts related to the present application are shown in the drawings rather than all 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 flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. When the operations are completed, the process can be terminated, but there may also be additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0066] The following will clearly describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings 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. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0067] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and do not limit the number of objects. For example, the first object can be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0068] The following will, with reference to the accompanying drawings, explain in detail the detection method for the sealing performance of the airtight blast door provided in the embodiments of the present application through specific embodiments and their application scenarios.

[0069] Embodiment 1: Figure 1It is a schematic flow chart of a method for detecting the sealing performance of a protective airtight door provided in the first embodiment of the present application. As Figure 1 shown, it specifically includes the following steps:

[0070] S101, 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; wherein, the enclosed space includes a protective airtight door; the preset leakage area calculation formula is:

[0071] ;

[0072] wherein, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference.

[0073] First of all, the usage scenario of this solution can be a scenario of obtaining relevant data of an enclosed space including a protective airtight door, calculating the sealing performance value of the enclosed space through the above relevant data, and determining whether the airtight performance of the protective airtight door passes the test according to the sealing performance value.

[0074] Based on the above usage scenario, it can be understood that the execution subject of the present application can be a detection system for the sealing performance of a protective airtight door, and no excessive limitation is made here.

[0075] The enclosed space can be a sealed environmental area. In this space, the protective airtight door is the only potential gas leakage source, and there are no other potential leakage points. The size and shape of the enclosed space should be clear and remain unchanged during the experiment.

[0076] The protective airtight door can refer to a door used for sealing in an enclosed space, designed to prevent air or gas leakage.

[0077] The leakage area can refer to the total area of gas or air leakage in the enclosed space due to poor sealing. It is an important indicator for measuring the airtight performance.

[0078] The current pressure difference can refer to the air pressure difference between the inside and outside of the enclosed space.

[0079] The current air flow can refer to the volume of air passing through the leakage point of the enclosed space per unit time.

[0080] The geometric modeling function of CAD software or CFD tools can be used to create a detailed 3D model of the airtight door and the space it is in. Ensure that the model accurately reflects the actual situation, including the door dimensions, the position of the sealing strip, and the shape of the airtight space. Pay special attention to the sealing area and potential leakage points, and these areas should be modeled in detail to improve the simulation accuracy. Then set the physical properties. Among them, fluid properties: define the physical characteristics of the fluid (usually air), such as density and viscosity. Airflow characteristics: set the velocity and direction of the airflow, and different flow patterns (such as laminar flow or turbulent flow) may need to be set according to the actual situation. Then set the boundary conditions. Among them, inlet boundary: define the conditions for the airflow to enter the airtight space (such as velocity, pressure). Outlet boundary: define the conditions for the airflow to leave the airtight space. Wall boundary: set the no-slip or slip conditions for the airtight door and other surfaces. Divide the geometric model into small computational units, called meshes. The finer the mesh, the higher the simulation accuracy, but the greater the computational amount. Make a finer mesh division for the key areas (such as the sealing area) to capture more details. Then select a suitable CFD solver (such as ANSYS Fluent, OpenFOAM, etc.), and set the solver parameters, such as the time step and the convergence criterion. Start the simulation calculation and monitor the convergence situation and computational stability during the calculation process. After the simulation is completed, extract data such as the flow field, pressure distribution, and airflow velocity. Calculate the air flow rate through the airtight door according to the flow velocity and pressure difference. Through the analysis of the simulation results, especially the inspection of the flow non-uniform areas, estimate the leakage area. The relationship between the fluid flow rate and the pressure difference can be used to deduce the leakage characteristics. Specifically, the flow non-uniform areas can be identified in the simulation, and the corresponding flow velocity and pressure data can be extracted. Then, using the fluid flow equation (such as Bernoulli's equation), relate the flow rate and the pressure difference to calculate the leakage area. Specifically, obtain the air flow rate by integrating the fluid velocity field, and substitute it and the pressure difference into the formula to deduce the leakage area.

[0081] Then use a pressure sensor or a differential pressure sensor to measure the air pressure difference between the inside and the outside of the airtight space, read the preset air flow rate calculation formula from the database, and after the flow coefficient preset in the formula has been set, substitute the leakage area and the current pressure difference into the formula to calculate the current air flow rate of the airtight space.

[0082] S102. Obtain the volume of the airtight space and the preset air change rate calculation formula, and calculate the current air change rate of the airtight space according to the volume of the airtight space, the current air flow rate, and the preset air change rate calculation formula; among them, the preset air change rate calculation formula is:

[0083] ;

[0084] Among them, is the current air change rate; is the current air flow rate; V is the volume of the enclosed space.

[0085] The volume of the enclosed space can refer to the total volume inside the enclosed space and can be obtained by measuring the length, width, and height of the space.

[0086] The current air change rate can refer to the ratio of the amount of air passing through the enclosed space per unit time to the total volume of the enclosed space. It represents the frequency at which the air in the space is replaced and is usually expressed as the number of air changes per hour.

[0087] A suitable tool (such as a laser rangefinder) can be used to measure the length, width, and height of the enclosed space, and then the length, width, and height are multiplied to obtain the volume of the enclosed space. Then, the preset air change rate calculation formula is read from the database, and the calculated current air flow rate and the volume of the enclosed space are substituted into the preset air change rate calculation formula to obtain the current air change rate.

[0088] S103. Obtain the current temperature of the enclosed space and the preset calculation formula for the sealing performance value. According to the current temperature, the current pressure difference, the current air change rate, and the preset calculation formula for the sealing performance value, calculate the current sealing performance value of the enclosed space; where the preset calculation formula for the sealing performance value is:

[0089] ;

[0090] where, SP ( ) is the current sealing performance value; is the air change rate weight coefficient; is the current air change rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature.

[0091] The current temperature can be the instantaneous temperature inside the enclosed space, usually measured by a temperature sensor or a temperature measuring instrument, and the unit can be Celsius or Fahrenheit.

[0092] The current sealing performance value can be an index used to measure the sealing effect of the enclosed space, usually reflecting the sealing quality of the sealed door and the overall sealing performance of the enclosed space. It can be used to evaluate the isolation effect and air leakage situation of the space, and 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. Then compare it with the current sealing performance value.

[0093] The air change rate weight coefficient, pressure difference weight coefficient, and temperature weight coefficient in the formula are all preset and extracted. A large number of experimental data can be collected, including sealing performance values, air change rates, pressure differences, and temperatures, etc. 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 change 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. When the air change rate weight coefficient, pressure difference weight coefficient, and temperature weight coefficient are determined, they can be filled into the formula and the formula is stored in the database. When needed, first read the preset sealing performance value calculation formula in the database, then use a temperature sensor or temperature measuring instrument to measure the current temperature in the enclosed space, and substitute the measured current pressure difference, current temperature, and calculated current air change rate into the preset sealing performance value calculation formula to obtain the current sealing performance value of the enclosed space.

[0094] Based on the above technical solution, optionally, after calculating the current sealing performance value of the enclosed space, the method further includes:

[0095] If the current sealing performance value is higher than the preset sealing performance threshold, input the current air change rate, the current pressure difference, the current temperature, and the preset prediction interval time into the preset sealing performance prediction model to obtain the predicted sealing performance value after the preset prediction interval time, and record the number of predictions;

[0096] If the predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test.

[0097] In this solution, the preset prediction interval time can be a time interval set by the system, indicating a future time point (such as after 30 minutes, 1 hour, 24 hours), used to predict the sealing performance. Different time intervals can be set according to the actual application requirements.

[0098] The preset sealing performance prediction model can be a machine learning or statistical model, used to predict the sealing performance at a future moment based on the current sealing performance parameters (such as air change rate, pressure difference, temperature, etc.).

[0099] The predicted sealing performance value can be the value output by the sealing performance prediction model, indicating the sealing performance state after the preset prediction interval time.

[0100] The number of predictions can represent the cumulative number of times the system has performed seal performance predictions.

[0101] The preset prediction interval time can be read from the database. The obtained current ventilation rate, the current pressure difference, the current temperature, and the preset prediction interval time are input into a preset seal 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 seal performance value after a period of time in the future. Specifically, the result output by the model can be a prediction value, indicating the seal performance state of the enclosed space after the preset prediction interval time. This value can be a percentage or a specific seal performance score (such as a value between 0 and 100). For example, if it is a percentage, if the predicted value output by the model is 85%, it means that after the preset time interval (such as 1 hour), the seal 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 seal performance value is obtained, it is compared with the preset seal performance threshold. If the predicted seal performance value is lower than the preset seal performance threshold, it is determined that the protective airtight door fails the seal performance test.

[0102] In this solution, by inputting real-time data into the prediction model, the future seal performance state can be predicted quickly and accurately, thus avoiding frequent manual inspections and reducing labor costs.

[0103] On the basis of the above technical solution, optionally, after obtaining the seal performance value after the preset prediction time interval, the method further includes:

[0104] If the predicted seal performance value is higher than the preset seal performance threshold, the current pressure difference is re-collected after reaching the preset acquisition interval time. According to the leakage area, the current pressure difference, and the preset air flow calculation formula, the current air flow in the enclosed space is updated;

[0105] According to the updated current air flow, the volume of the enclosed space, and the preset ventilation rate calculation formula, the current ventilation rate of the enclosed space is updated;

[0106] The current temperature of the enclosed space is re-obtained and updated. According to the updated current temperature, current pressure difference, current ventilation rate, and the preset seal performance value calculation formula, the current seal performance value of the enclosed space is updated;

[0107] If the updated current seal performance value is higher than the preset seal performance threshold, the updated current temperature, current pressure difference, current ventilation rate, and the preset prediction interval time are input into the preset seal performance prediction model to update the predicted seal performance value after the preset prediction interval time, and the number of predictions is updated until the number of predictions reaches the preset prediction number threshold;

[0108] 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 blast door passes the sealing performance test;

[0109] Correspondingly, after updating the current sealing performance value of the enclosed space, the method further includes:

[0110] If the updated current sealing performance value is lower than the preset sealing performance threshold, it is determined that the blast door fails the sealing performance test;

[0111] Correspondingly, after updating the predicted sealing performance value after the preset prediction interval time, the method further includes:

[0112] If the updated predicted sealing performance value is lower than the preset sealing performance threshold, it is determined that the blast door fails the sealing performance test.

[0113] In this solution, the preset acquisition interval time may refer to the time interval for the system to regularly collect data, which is used to update the environmental parameters (such as pressure difference, air flow, temperature, etc.) of the enclosed space.

[0114] The preset prediction times threshold may refer to the maximum number of times limit for the system to perform sealing performance prediction during the detection. For example, it can be set to 10 predictions. If the sealing performance value is always qualified after 10 predictions, it is considered that the blast door passes the test.

[0115] The current pressure difference, temperature and other data can be collected regularly, that is, after reaching the preset collection interval time, the current pressure difference, temperature and other data are collected again. The current air flow, the current ventilation rate and the current sealing performance value are recalculated through a 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 to perform the prediction of the sealing performance after the preset prediction interval time, and the predicted sealing performance value is obtained. 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, the preset prediction interval time is one hour, the preset collection interval time is 10 minutes, and the preset prediction number threshold is 1000 times. Then the 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 according to 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, the 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, the 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 any of the currently calculated sealing performance values or predicted sealing performance values is lower than the preset sealing performance threshold, it is determined that the airtight door fails the sealing performance test. However, if after 1000 predictions, all the current sealing performance values and predicted sealing performance values are higher than the preset sealing performance threshold, it is determined that the airtight door passes the sealing performance test.

[0116] In this solution, the automated detection process can reduce the frequency of manual detection and save a large amount of manpower and resources. The prediction model is used to judge whether the sealing performance is qualified based on the trend of multiple predicted sealing performance values, ensuring that the detection of the airtight door not only reflects the current state but also can predict the change of future performance, improving the overall detection accuracy and reliability.

[0117] On the basis of the above technical solution, optionally, the training process of the preset sealing performance prediction model includes:

[0118] Obtain the first historical ventilation rate, the first historical pressure difference, the first historical temperature and the 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;

[0119] Label the sealing performance value labels of the second data set;

[0120] Construct a sealing performance prediction model, and train the sealing performance prediction model according to the second data set and the sealing performance value labels until the sealing performance prediction model reaches a preset sealing performance prediction model training standard.

[0121] In this solution, the first historical air change rate can refer to the air change rate of the airtight door in past records, that is, the air exchange volume per unit time. The air change rate can affect the air circulation and sealing performance of the enclosed space.

[0122] The first historical pressure difference can refer to the pressure difference between the inside and outside of the enclosed space in past records. This difference will affect the effectiveness of the seal.

[0123] The first historical temperature can refer to the ambient temperature in past records. Temperature can affect the expansion or contraction of materials, thereby affecting the sealing performance.

[0124] The historical prediction interval time can refer to the time interval used for sealing performance prediction in past data. For example, how often the sealing performance prediction is updated.

[0125] The second data set can be created by collecting the first historical air change rate, the first historical pressure difference, the first historical temperature, and the historical prediction interval time. This data set contains these features and the corresponding sealing performance values, which are used to train the prediction model.

[0126] The sealing performance value labels can be the sealing performance values associated with each record in the second data set. They represent the actual sealing performance of the airtight door under given conditions.

[0127] The preset sealing performance prediction model training standard can be an indicator used to evaluate whether the sealing performance prediction model is trained successfully, such as the accuracy of the model, the mean square error (MSE), the root mean square error (RMSE), etc.

[0128] Historical usage data, failure data, environmental data, and maintenance records of the airtight door can be collected from the database. Organize the data into a second data set, and each record includes the first historical air change rate, pressure difference, temperature, and historical prediction interval time. Then, each record in the second data set is labeled with a sealing performance value label, and these labels represent the sealing performance results under specific conditions. Then, select a suitable machine learning algorithm (such as linear regression, support vector machine, neural network, etc.) to construct a sealing performance prediction model. Use the features and labels in the second data set to train the model. The training process includes adjusting the model parameters until the performance indicators of the model reach the preset sealing performance prediction model training standard.

[0129] 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 prediction accuracy because the model learns from past actual situations and can capture the law of the sealing performance changing over time.

[0130] S104. If the current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test.

[0131] The preset sealing performance threshold can be a standard value for evaluating the performance of the sealing door, which represents the lowest acceptable level of the sealing performance. If the sealing performance value of the enclosed space is lower than this threshold, it is considered that the sealing performance of the sealing door does not meet the requirements.

[0132] The standard value of the sealing performance can be determined according to relevant industry standards, regulations or specifications. For example, the construction industry or the equipment manufacturing industry may have specific sealing performance requirements. After determining the preset sealing performance threshold, it can be stored in the database and directly read from the database when needed. 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 fails the sealing performance test.

[0133] For the technical solution provided in this embodiment, the leakage area, the current pressure difference, and the preset air flow calculation formula of the enclosed space are obtained. According to the leakage area, the current pressure difference, and the preset air flow calculation formula, the current air flow of the enclosed space is calculated; wherein, the enclosed space includes a protective airtight door; the volume of the enclosed space and the preset air change rate calculation formula are obtained. According to the volume of the enclosed space, the current air flow, and the preset air change rate calculation formula, the current air change rate of the enclosed space is calculated; the current temperature of the enclosed space and the preset sealing performance value calculation formula are obtained. According to the current temperature, the current pressure difference, the current air change rate, and the preset sealing performance value calculation formula, the current sealing performance value of the enclosed space is calculated; if the current sealing performance value is lower than the preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test. Through the above detection method for the sealing performance of the protective airtight door, key parameters such as the leakage area, the current pressure difference, the air flow, the air change rate, and the sealing performance value of the enclosed space can be accurately quantified, avoiding errors caused by subjective judgment, improving the accuracy of evaluation, helping to discover and solve problems with poor sealing performance, and thus improving the reliability of the protective airtight door. The automated detection process can improve the detection efficiency and save labor costs.

[0134] Based on the above technical solution, optionally, after determining that the protective airtight door fails the sealing performance test, the method further includes:

[0135] Obtain the device information of the blast-proof airtight door, and send the device information to the control center for the control center to lock the target blast-proof airtight door according to the device information and perform subsequent processing.

[0136] In this solution, the device information can be various detailed data about the blast-proof airtight door. Specifically, it can include the device ID: the number or code that uniquely identifies each blast-proof airtight door. The device model: the specific model or specification of the device. The installation location: the physical location or installation site of the device, which helps to locate the device.

[0137] If the blast-proof airtight door fails the airtightness test, the real-time device information can be automatically collected through the sensors and monitoring system on the device and sent to the control center via wireless communication technology.

[0138] In this solution, when the blast-proof airtight door fails the airtightness test, sending the device information to the control center can quickly lock the information such as the number and location of the target blast-proof airtight door that fails the test.

[0139] Embodiment 2: Figure 2 It is a schematic flowchart of the method for detecting the airtightness of the blast-proof airtight door provided in the second embodiment of the present application. As Figure 2 shown, the specific method includes the following steps:

[0140] S201, obtain the leakage area, the current pressure difference of the enclosed space, 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 the blast-proof airtight door; the preset leakage area calculation formula is:

[0141] ;

[0142] Wherein, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference.

[0143] S202, obtain the volume of the enclosed space and the preset air change rate calculation formula, and calculate the current air change rate of the enclosed space according to the volume of the enclosed space, the current air flow, and the preset air change rate calculation formula; wherein, the preset air change rate calculation formula is:

[0144] ;

[0145] Wherein, is the current air change rate; is the current air flow; V is the volume of the enclosed space.

[0146] S203. Obtain the current temperature of the enclosed space and the preset calculation formula for the sealing performance value. Calculate the current sealing performance value of the enclosed space according to the current temperature, current pressure difference, current air change rate, and the preset calculation formula for the sealing performance value. The preset calculation formula for the sealing performance value is as follows:

[0147] ;

[0148] where SP( ) is the current sealing performance value; is the air change rate weight coefficient; is the current air change rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature.

[0149] S204. If the current sealing performance value is lower than the preset sealing performance threshold, determine that the protective airtight door fails the sealing performance test.

[0150] S205. Input the current temperature, current pressure difference, and current air change rate into the preset abnormal cause detection model. Determine the abnormal cause for the protective airtight door failing the sealing performance test, and send the abnormal cause to the control center for the control center to improve the protective airtight door according to the abnormal cause.

[0151] The preset abnormal cause detection model can be a machine learning or deep learning model specifically used to identify the abnormal causes when the sealing performance of the protective airtight door does not meet the standard. The inputs of the model include data such as the current air change rate, current pressure difference, and current temperature, and the output is the abnormal cause leading to the non-compliance of the sealing performance.

[0152] The abnormal cause can refer to the specific reasons for the protective airtight door failing the sealing performance test. Specifically, it can include aging of the door frame or seal: the sealing material loses elasticity due to long-term use or environmental influence. Structural deformation: the protective airtight door is deformed under external force, resulting in a decline in sealing performance. Temperature or pressure fluctuations: the environmental temperature or pressure exceeds the design range, resulting in poor sealing effect. Installation or commissioning problems: improper installation or commissioning of the airtight door, resulting in poor airtightness.

[0153] The control center can refer to a system or platform for centralized monitoring and management of equipment status. It receives abnormal reports from the protective airtight door and takes corresponding actions according to the abnormal causes.

[0154] The current data of the airtight blast door (ventilation rate, pressure difference, temperature, etc.) can be input into the pre-trained abnormal cause detection model. Based on the input data, the model uses a preset algorithm to determine the specific abnormal cause that leads to the failure of the sealing performance detection. The model will compare each input feature (ventilation rate, pressure difference, temperature) with the abnormal patterns learned in the model to identify which abnormal cause results in the sealing performance problem. The output of the model is the abnormal cause, such as "aging of the sealing material" or "excessive temperature fluctuation", etc. Then this abnormal cause will be sent to the control center as part of the report. For example, a certain airtight blast door detects a current ventilation rate of 5 m³ / h, a pressure difference of 10 Pa, and a temperature of 35°C. These data are input into the abnormal cause detection model, and the model identifies that the abnormal cause is "aging of the sealing material". This result is sent to the control center, and the staff can formulate a maintenance plan based on this information to replace the aging seals.

[0155] In this embodiment, the preset abnormal cause detection model can help quickly and accurately diagnose the reasons for the unqualified sealing performance of the airtight blast door, improving the efficiency and accuracy of equipment maintenance.

[0156] On the basis of the above technical solution, optionally, the training process of the preset abnormal cause detection model includes:

[0157] Obtain the second historical ventilation rate, the second historical pressure difference, and the second historical temperature when the airtight blast 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;

[0158] Label the abnormal cause tags of the third data set;

[0159] Construct an abnormal cause detection model, and train the abnormal cause detection model according to the third data set and the abnormal cause tags until the abnormal cause detection model reaches the preset abnormal cause detection model training standard.

[0160] In this solution, the second historical ventilation rate can be the ventilation rate data recorded during the period when the airtight blast door fails. These data reflect the ventilation conditions before and after the failure.

[0161] The second historical pressure difference can be the pressure difference data when the airtight blast door fails. These data provide the air pressure change information of the enclosed space.

[0162] The second historical temperature can be the temperature data when the airtight blast door fails. These data reflect the change of the ambient temperature at that time.

[0163] The third data set can be a data set created based on the historical ventilation rate, pressure difference, and temperature data when the airtight blast door fails.

[0164] The abnormal cause label can be a mark of the specific abnormal cause when the airtight door fails. It explains why the failure occurs, such as seal failure, equipment aging, etc.

[0165] The preset training standard for the abnormal cause detection model can be the goals and requirements for training the abnormal cause detection model. For example, indicators such as the accuracy rate, recall rate, and F1 score of the model reach a predetermined threshold.

[0166] It is possible to collect the historical air change rate, pressure difference, and temperature data of the airtight door during a failure, ensuring that these data have sufficient time span and representativeness. Then use the collected data to create a third data set, and assign abnormal cause labels to each piece of data in the third data set. These labels need to be marked based on the actual failure situation, for example, by analyzing historical failure records or expert judgment. Then select appropriate machine learning or deep learning algorithms (such as decision trees, random forests, support vector machines, neural networks, etc.). Use the labeled third data set and abnormal cause labels for training. Adjust the algorithm parameters to optimize the model performance until the model meets the preset training standard.

[0167] In this solution, automated anomaly detection reduces the need for manual inspections, improves detection efficiency, and reduces human errors at the same time. The trained model can detect the cause of the failure of the airtight door in real time, helping to quickly identify problems.

[0168] Embodiment 3: Figure 3 It is a schematic flow chart of the detection method for the sealing performance of the airtight door provided in Embodiment 3 of the present application, as Figure 3 shown, and the specific method includes the following steps:

[0169] S301, obtain the historical usage data, first historical failure data, historical environmental data, and first historical maintenance records of each airtight door throughout its life cycle, and create a first data set according to the historical usage data, first historical failure data, historical environmental data, and first historical maintenance records.

[0170] The historical usage data can be the operation records of the airtight door during its life cycle, including the usage frequency, the number of times of opening and closing each time, the continuous operation time, etc., which can be collected through the operation logs or monitoring systems of the equipment.

[0171] The first historical failure data can be the failure history of the airtight door, including the time of each failure, the failure type, the affected range, and the repair time, etc.

[0172] The historical environmental data can be the historical data of the environment where the airtight door is located, including environmental parameters such as temperature, humidity, air pressure, and vibration, which may all affect the performance of the airtight door.

[0173] The first historical maintenance record can be all the maintenance and repair records of the airtight door, including the maintenance time, specific operation content, replaced parts, and maintenance results, etc.

[0174] The first data set can be a comprehensive data set integrated by the above historical usage data, the first historical fault data, historical environmental data, and the first historical maintenance record. This data set is used to comprehensively analyze the operating status of the airtight door. Each data record reflects the usage status, environmental conditions, fault information, and maintenance information of the airtight door at a specific time point.

[0175] It is possible to collect the historical usage data, fault data, environmental data, and maintenance records of the entire life cycle of the airtight door, preprocess these data (such as data cleaning, duplicate removal, normalization, etc.) to ensure data quality. Arrange the data along the time axis to form a complete data set, and clearly label the faults and maintenance operations at each time point.

[0176] S302, label the fault time label, fault type label, and maintenance plan label of the first data set;

[0177] The fault time label can be a specific time label marking the occurrence of the fault, which helps the model predict the time point of the fault.

[0178] The fault type label can be a type label marking each fault, such as door frame deformation, seal failure, electronic control failure, etc., which is used for the output of the classification prediction model.

[0179] The maintenance plan label can be a label marking the maintenance or repair measures taken to solve the fault, such as replacing the sealing strip, realigning the door frame, adjusting the control system, etc. This label is used to predict the best maintenance plan in similar fault situations.

[0180] It is possible to add a fault time label (timestamp at the time of fault occurrence) to each data record in the first data set, label the fault type label to ensure that the specific type of each fault is accurately classified, and according to the historical maintenance record, label the maintenance plan label for each fault to record the specific repair plan.

[0181] S303, construct a fault prediction model for the airtight door, and train 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 the preset fault model training standard.

[0182] The fault prediction model can be a machine learning model designed to predict possible future faults, their occurrence times and types based on the historical data of the airtight door, and recommend appropriate maintenance plans. The model predicts the health status of the equipment by analyzing the usage status, environmental data, fault history and maintenance records of the equipment, and gives fault warnings.

[0183] The preset fault model training criteria can be metrics for evaluating the performance of the model. Common criteria include accuracy, recall rate, F1 score, prediction accuracy of the model within different time windows, etc. When the performance of the model on these metrics reaches the preset criteria (such as the accuracy exceeding 90% or the F1 score being greater than 0.8), it is considered that the model training is qualified and can be put into practical application.

[0184] The data records in the first dataset can be bound to the corresponding fault time labels, fault type labels and maintenance plan labels. According to the nature of the data, select a suitable model type. Specifically, time series models (such as LSTM or GRU) are suitable for processing data with time order and can predict future faults. Classification models (such as random forest, XGBoost, deep neural network) are suitable for predicting fault types and maintenance plans based on features. The multi-task learning model can predict fault time, type and maintenance suggestions simultaneously, improving the overall performance of the model. Then, input the data items in the first dataset as features, including historical usage data, fault data, environmental data, etc. The outputs are fault time labels (time series), fault type labels (classification task) and maintenance plan labels (classification task) that match the first dataset. Using supervised learning, pair the input data with the target labels, and train the model to find the relationship between the input and the occurrence of faults. Use a suitable loss function, such as the mean squared error (MSE) for time prediction or the cross-entropy loss in classification tasks. Use optimization algorithms such as gradient descent to continuously update the model weights and gradually reduce the training error. Specifically, use the first dataset as the input data and the labels (fault time, fault type, maintenance plan) as the supervision signals. The fault prediction model learns based on the corresponding relationship between the input features and labels until it reaches the preset training criteria.

[0185] In this embodiment, by constructing a fault prediction model, it is possible to predict the possible fault time and type in advance before the airtight door fails, which helps to take preventive measures. By regularly analyzing the status of the airtight door and detecting potential faults and performance degradation, adjustments and repairs can be made in a timely manner, thereby extending the service life of the airtight door and maintaining its optimal operating performance.

[0186] Based on the above technical solution, optionally, after training the fault prediction model according to the first data set, the fault time tag, the fault type tag, and the maintenance plan tag until the fault prediction model meets the preset fault model training standard, the method further includes:

[0187] Obtain the real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records of the airtight door, input the real-time usage data, real-time environmental data, second historical fault data, and second historical maintenance records into the fault prediction model, and determine the predicted fault time, predicted fault type, and predicted maintenance plan;

[0188] Send the predicted fault time, predicted fault type, and predicted maintenance plan to the control center for the staff to carry out the maintenance work of the airtight door.

[0189] In this solution, the real-time usage data can be the current operation status data of the airtight door. Specifically, it can include dynamic data related to the door operation such as the opening and closing status of the door, usage frequency, operation time, pressure change, temperature change, etc.

[0190] The real-time environmental data can be the environmental condition data around the enclosed space. This includes environmental factors such as temperature, humidity, air pressure, etc., which may affect the operation of the airtight door.

[0191] The second historical fault data refers to the fault records that have occurred during the use of the airtight door, which can include the time of the fault, the fault type, the scope of influence, and the repair time.

[0192] The second historical maintenance record can be the record of the maintenance work that has been carried out during the use of the airtight door, which can include the maintenance time, the specific operation content, the replaced parts, and the maintenance results, etc.

[0193] The predicted fault time can be the time point at which a fault may occur in the future given by the system through the prediction model.

[0194] The predicted fault type can be the specific fault type that is about to occur given by the fault prediction model, such as a decrease in sealing performance, mechanical damage, electrical fault, etc.

[0195] The predicted maintenance plan can be the maintenance solution proposed by the system based on the fault prediction result, which may include specific maintenance suggestions such as replacing parts, adjusting operation parameters, and conducting regular inspections.

[0196] Real-time usage data and real-time environmental data can be collected from the sensors and monitoring systems of the blast-proof airtight door. These data are transmitted in real time to the fault prediction system through the interface. The real-time usage data, real-time environmental data, together with the second historical fault data and the second historical maintenance records, are input into the trained fault prediction model. The model outputs the predicted fault time, fault type, and recommended maintenance plan based on these input data. Then, the predicted fault time, predicted fault type, and predicted maintenance plan are sent to the control center through wireless communication technology.

[0197] In this solution, predictive maintenance can identify potential faults in advance, reduce the costs of emergency repairs and component replacements, thereby reducing maintenance costs. Through timely maintenance and repairs, the wear and damage of the blast-proof airtight door can be reduced, the service life of the blast-proof airtight door can be extended, and the return on investment can be increased.

[0198] Embodiment 4: Figure 4 is a schematic structural diagram of a detection system for the sealing performance of a blast-proof airtight door provided in Embodiment 4 of the present application. As Figure 4 shown, this system is used to implement the method for the detection system of the sealing performance of a blast-proof airtight door provided in Embodiments 1, 2, and 3. Specifically, this system includes the following:

[0199] An air flow calculation module 401 is configured 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; wherein, the enclosed space includes a blast-proof airtight door; the preset leakage area calculation formula is:

[0200] ;

[0201] wherein, is the current air flow; A is the leakage area; C is the preset flow coefficient; is the current pressure difference;

[0202] A ventilation rate calculation module 402 is configured 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; wherein, the preset ventilation rate calculation formula is:

[0203] ;

[0204] wherein, is the current ventilation rate; is the current air flow; V is the volume of the enclosed space;

[0205] A sealing performance value calculation module 403, configured 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 air change rate, and the preset sealing performance value calculation formula; wherein, the preset sealing performance value calculation formula is:

[0206] ;

[0207] wherein, SP ( ) is the current sealing performance value; is the air change rate weight coefficient; is the current air change rate; is the current pressure difference; is the pressure difference weight coefficient; is the temperature weight coefficient; is the current temperature;

[0208] A detection module 404, configured to determine that the protective airtight door fails the sealing performance detection if the current sealing performance value is lower than a preset sealing performance threshold.

[0209] In the embodiment of the present application, an air flow calculation module is configured 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; wherein, the enclosed space includes a protective airtight door; an air change rate calculation module is configured to obtain the volume of the enclosed space and a preset air change rate calculation formula, and calculate the current air change rate of the enclosed space according to the volume of the enclosed space, the current air flow, and the preset air change rate calculation formula; a sealing performance value calculation module is configured 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 air change rate, and the preset sealing performance value calculation formula; a detection module is configured to determine that the protective airtight door fails the sealing performance detection if the current sealing performance value is lower than a preset sealing performance threshold. Through the above detection system for the sealing performance of the protective airtight door, key parameters such as the leakage area, the current pressure difference, the air flow, the air change rate, and the sealing performance value of the enclosed space can be accurately quantified, the error caused by subjective judgment can be avoided, the accuracy of the evaluation can be improved, it is helpful to discover and solve the problem of poor sealing performance, and thus the reliability of the protective airtight door can be improved. The automated detection process can improve the detection efficiency and save labor costs.

[0210] The above are only the preferred embodiments of the present application and the technical principles applied. The present application is not limited to the specific embodiments described herein. Various obvious changes, re-adjustments, and substitutions that can be made by those skilled in the art will not depart from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments. Without departing from the concept of the present application, it may also include more other equivalent embodiments, and the scope of the present application is determined by the scope of the claims.

Claims

1. A detection method for the sealing performance of a protective airtight door, characterized in that, The method includes: Obtaining the leakage area of the enclosed space, the current pressure difference, and a preset air flow calculation formula, and calculating 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: ； Among them, is the current air flow rate; A is the leakage area; C is a preset flow coefficient; is the current pressure difference; Obtaining the volume of the enclosed space and a preset air change rate calculation formula, and calculating the current air change rate of the enclosed space according to the volume of the enclosed space, the current air flow, and the preset air change rate calculation formula; wherein, the preset air change rate calculation formula is: ； Among them, is the current ventilation rate; is the current air flow rate; V is the volume of the enclosed space; 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 air change 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 air change rate weight coefficient; is the current air change 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 fails the sealing performance test.

2. The detection method for the sealing performance of the airtight blast 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 a preset sealing performance threshold, input the current air change rate, the current pressure difference, the current temperature, and a preset prediction interval time into a preset sealing performance prediction model to obtain a predicted sealing performance value after the preset prediction interval time, and record the prediction times; If the predicted sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test.

3. The detection method for the sealing performance of the airtight blast door according to claim 2, wherein 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 a preset sealing performance threshold, re-collect the current pressure difference after reaching the preset acquisition interval time, and update the current air flow of the enclosed space according to the leakage area, the current pressure difference, and the preset air flow calculation formula; Update the current air change rate of the enclosed space according to the updated current air flow, the volume of the enclosed space, and the preset air change rate calculation formula; Re-obtain 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, the current pressure difference, the current air change rate, and the preset sealing performance value calculation formula; If the updated current sealing performance value is higher than a preset sealing performance threshold, input the updated current temperature, the current pressure difference, the current air change rate, and the preset prediction interval time into a preset sealing performance prediction model to update the predicted sealing performance value after the preset prediction interval time, and update the prediction times until the prediction times reach a preset prediction times threshold; If all the predicted sealing performance values and all the 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; Correspondingly, after updating the current sealing performance value of the enclosed space, the method further includes: If the updated current sealing performance value is lower than a preset sealing performance threshold, it is determined that the protective airtight door fails the sealing performance test; Correspondingly, 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 fails the sealing performance test.

4. The detection method for the sealing performance of the airtight blast door according to claim 1, characterized in that, After determining that the protective airtight door fails the sealing performance test, the method further includes: Input the current temperature, current pressure difference, and current air change rate into a preset abnormal cause detection model, determine the abnormal cause of the protective airtight door failing the sealing performance test, and send the abnormal cause to the control center for the control center to improve the protective airtight door according to the abnormal cause.

5. The detection method for the sealing performance of the airtight blast 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 the historical usage data, first historical failure data, historical environmental data, and first historical maintenance records of the whole life cycle of each protective airtight door, and create a first data set according to the historical usage data, first historical failure data, historical environmental data, and first historical maintenance records; Label the failure time label, failure type label, and maintenance plan label of the first data set; Construct a failure prediction model for the protective airtight door, and train the failure prediction model according to the first data set, the failure time label, the failure type label, and the maintenance plan label until the failure prediction model reaches the preset failure model training standard.

6. The detection method for the sealing performance of the protective airtight door according to claim 5, characterized in that, After training the failure prediction model according to the first data set, the failure time label, the failure type label, and the maintenance plan label until the failure prediction model reaches the preset failure model training standard, the method further includes: Obtain the real-time usage data, real-time environmental data, second historical failure data, and second historical maintenance records of the protective airtight door, input the real-time usage data, real-time environmental data, second historical failure data, and second historical maintenance records into the failure prediction model, and determine the predicted failure time, predicted failure type, and predicted maintenance plan; Send the predicted failure time, predicted failure type, and predicted maintenance plan to the control center for the staff to carry out the maintenance work of the protective airtight door.

7. The detection method for the sealing performance of the protective airtight door according to claim 2, characterized in that, The training process of the preset sealing performance prediction model includes: Obtain the first historical air change rate, first historical pressure difference, first historical temperature, and historical prediction interval time, and create a second data set according to the first historical air change rate, first historical pressure difference, first historical temperature, and historical prediction interval time; Label the sealing performance value label of the second data set; Construct a sealing performance prediction model, and train the sealing performance prediction model according to the second data set and the sealing performance value label until the sealing performance prediction model reaches the preset sealing performance prediction model training standard.

8. The detection method for the sealing performance of the airtight blast door according to claim 4, wherein The training process of the preset abnormal cause detection model includes: Obtain the second historical air change rate, second historical pressure difference, and second historical temperature when the protective airtight door fails, and create a third data set according to the second historical air change rate, second historical pressure difference, and second historical temperature; Label the abnormal cause label of the third data set; Construct an abnormal cause detection model, and train the abnormal cause detection model according to the third data set and the abnormal cause label until the abnormal cause detection model reaches the preset abnormal cause detection model training standard.

9. The detection method for the sealing performance of the protective airtight door according to claim 1, wherein, After determining that the blast door fails the airtightness test, the method further includes: Obtaining the device information of the blast door and sending the device information to the control center for the control center to lock the target blast door according to the device information and perform subsequent processing.

10. A detection system for the sealing performance of a protective airtight door, characterized in that, The system includes: An air flow calculation module, configured 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, configured 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, configured 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; A detection module, configured to determine that the blast door fails the airtightness test if the current sealing performance value is lower than a preset airtightness threshold.

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