A method to quickly and accurately judge the dryness of items in the oven

Abstract

The present application discloses a method for quickly and accurately judging the dryness of articles in an oven, comprising the following steps: 1) a temperature and humidity measurement module arranged at a moisture content measurement sensitive point in the oven measures temperature and humidity data in real time; 2) the temperature and humidity data are uploaded to a host computer; 3) the host computer writes a three-dimensional model of the oven interior and the wet articles, and uses the air moisture content value at the horizontal plane where the sensitive point is located to calculate the dryness of articles in an oven through a maximum allowable error e. max and the allowed mean absolute error e MAE Determine the dryness of items. Its advantages are: it can calculate the moisture content of the air in the oven in real time with high accuracy, allowing producers to accurately understand the dryness of items at the first time and improve production efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of environmental parameter measurement, and in particular to a method and device for quickly and accurately determining the dryness of items in an oven. Background Art

[0002] Drying is a crucial and indispensable step in the production process of many industries. The dryness of raw materials and production supplies directly impacts product quality, production efficiency, and production costs. For example, moisture in a ceramic crucible used for melting can reduce its efficiency and service life, and even affect the gas content of the molten metal. Engineering plastics exposed to moisture can easily cause bubbles and cracks during molding, resulting in defects such as insufficient strength and poor stability. Therefore, proper drying is an essential preparatory step to prevent these defects.

[0003] Industrial ovens are commonly used drying equipment in production processes. While they offer precise temperature control, they lack a way to monitor whether items within the oven are fully dried. Workers often rely on experience to set drying times to ensure complete drying, which reduces production efficiency. Some ovens can measure internal moisture content to determine dryness, but lack scientific guidance for sensor placement, making it difficult to accurately reflect the overall moisture content within the oven. This can easily lead to misjudgments and product quality issues.

[0004] Therefore, how to scientifically guide the layout of sensors in the oven and quickly and accurately determine the dryness of items in the oven to improve industrial production efficiency is a problem that needs to be solved. Summary of the Invention

[0005] In order to solve the problems existing in the prior art, the present application provides a method and device for quickly and accurately judging the dryness of items in an oven.

[0006] This application adopts the following technical solutions:

[0007] The present application provides a method for quickly and accurately determining the dryness of items in an oven, comprising the following steps:

[0008] 1) The temperature and humidity measurement module arranged at the moisture content measurement sensitive point in the oven measures the temperature and humidity data in real time;

[0009] 2) Temperature and humidity data are uploaded to the host computer;

[0010] 3) The host computer writes the three-dimensional model of the oven interior and the wet items, and uses the air humidity value at the level of the sensitive point to calculate the maximum allowable error e max and the allowed mean absolute error e MAE Determine the dryness of the item.

[0011] The sensitive points are obtained by simulation on a host computer and calculation using K-means clustering.

[0012] The sensitive points are obtained by the following method:

[0013] 1) Establish a three-dimensional FLUENT model of the oven interior and the wet items inside;

[0014] 2) Determine the height range of the temperature and humidity measurement module and divide the established model into grids;

[0015] 3) Simulate and measure the temperature and humidity values ​​within the height range of the temperature and humidity measurement module. The measurement interval is shortest at the beginning of the simulation. As the model gradually reaches a steady state, the measurement interval gradually increases until the model reaches a steady state. The temperature and humidity data at m moments are obtained, of which the last moment is the steady-state temperature and humidity data.

[0016] 4) Select all grids within the installation range of the temperature and humidity measurement module, and calculate the difference d between the maximum and minimum moisture content of each grid at m moments as the value of the grid;

[0017] 5) Perform K-means clustering on the grid values ​​of each horizontal plane, with the number of clusters being k. If the cluster center point is not on a grid, the grid closest to the center point is selected as the center point, and the average value of the grid value where the cluster center point is located is calculated for each horizontal plane.

[0018] 6) Select the horizontal plane with the largest average value as the temperature and humidity measurement plane, and the center point of the plane cluster is the sensitive point.

[0019] The model is reduced in order using the proper orthogonal decomposition method and the snapshot method to determine the number of temperature and humidity measurement modules and arrange them at sensitive points.

[0020] The number of temperature and humidity measurement modules is determined by the following method:

[0021] 1) Create a matrix Θ1, Θ1A = λA, where Θ1 is an m×m matrix, θ′ ti is the temperature field of the horizontal plane where the sensitive point is located at the i-th moment, A is the eigenvector of Θ1, A=[a1,a2…a m ] T , a i is the linear combination coefficient, λ is the eigenvalue of Θ1;

[0022] 2) Calculate the number of temperature measurement modules p1 so that where λ1≥λ2≥…≥λ m ;

[0023] Replace the temperature field in the above steps with the relative humidity field, and repeat the above steps to obtain the number of relative humidity measurement modules p2;

[0024] The number of required temperature and humidity measurement modules is determined to be p, where p = max{p1, p2}.

[0025] The arrangement of the temperature and humidity measurement module is as follows:

[0026] I) if k < p, re-cluster the horizontal plane grid values, adjust the number of clusters to p, and place the temperature and humidity measurement modules at the grids where the p cluster centers are located;

[0027] II) If k≥p, the grid values ​​d of the sensitive points are arranged in descending order, i.e., d1≥d2≥…≥d p ≥…≥d k The temperature and humidity measurement modules are arranged at d1, d2, ..., d p The corresponding sensitive point.

[0028] The method for calculating the humidity of the air in the horizontal plane where the sensitive point is located is as follows:

[0029] 1) The initial state of the temperature field θ is obtained by using the temperature and humidity values ​​measured by the temperature and humidity measurement module and the Kalman estimator t The initial state of the relative humidity field θ rh ;

[0030] 2) Calculate the temperature field θ′ of the horizontal plane where the sensitive point is located t , in β(t)=[b1(t),b2(t)…b p (t)],

[0031] 3) The same method is used to calculate the relative field θ′ of the horizontal plane where the sensitive point is located rh , calculate the humidity content of the air at that horizontal plane.

[0032] The method to judge the dryness of the items in the oven is as follows:

[0033] 1) Set the maximum allowable error e max and the allowed mean absolute error e MAE ;

[0034] 2) Compare the air humidity value of the horizontal plane at the sensitive point obtained by measurement and calculation with the steady-state air humidity value of the horizontal plane obtained by simulation, and calculate the maximum error e1 and the mean square error e2;

[0035] 3) If e1>e max or e2>e MAE , it means the item is not dried, otherwise it means the item is dry.

[0036] The present application provides a device for quickly and accurately judging the dryness of items in an oven, the device comprising a temperature and humidity measurement module, a data transmission template, a power supply module, and a host computer;

[0037] The power supply module supplies power to the temperature and humidity measurement module and the host computer;

[0038] The temperature and humidity measurement module is arranged at a sensitive point for measuring moisture content in the oven;

[0039] The temperature and humidity measurement module transmits the real-time measured temperature and humidity data to the host computer through the data transmission module;

[0040] The host computer writes the three-dimensional model of the interior of the oven and the wet items, and uses the measured temperature and humidity data to obtain the air humidity value at the horizontal plane where the sensitive point is located, and calculates the maximum allowable error e max and the allowed mean absolute error e MAE Determine the dryness of the item.

[0041] The beneficial effects of this application are as follows:

[0042] The position layout of the temperature and humidity measurement module in the oven of this application is scientific and reasonable, and can quickly and accurately determine the dryness of the items in the oven. The moisture content in the oven can be calculated in real time through the sensor with high accuracy, allowing producers to accurately understand the dryness of the items at the first time and improve production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0044] Figure 1 This is a diagram of the deployment of the temperature and humidity data measurement module inside the oven. 1 is the area where the temperature and humidity measurement template can be installed, 2 is the temperature and humidity measurement template, 3 is the horizontal plane where the sensitive point is located, 4 is the oven, and 5 is the wet crucible.

[0045] Figure 2 This is the error diagram of the calculated temperature value inside the oven, where the unit is ℃.

[0046] Figure 3 This is the error diagram of the calculated relative humidity value inside the oven, where the unit is RH. DETAILED DESCRIPTION

[0047] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0048] A device for quickly and accurately judging the dryness of items in an oven, mainly comprising a temperature and humidity measurement module, a data transmission template, a power supply module, and a host computer.

[0049] The power supply module supplies power to the temperature and humidity measurement module and the host computer;

[0050] The host computer writes a three-dimensional FLUENT model of the interior of the oven and the wet items therein;

[0051] The temperature and humidity measurement module is arranged at a moisture content measurement sensitive point;

[0052] The temperature and humidity measurement module transmits the real-time measured temperature and humidity data to the host computer through the data transmission module;

[0053] The host computer uses the measured temperature and humidity data to calculate the air humidity value at the horizontal plane where the sensitive point is located.

[0054] A method for quickly and accurately judging the dryness of items in an oven comprises the following steps:

[0055] 1) Establish a 3D FLUENT model of the oven interior and various wet crucibles inside, determine the heat source location, and input boundary conditions;

[0056] 2) Determine the height range of the temperature and humidity measurement module layout, with a height range difference of 0.8-1.0m, and divide the established model into grids with a grid height of 0.02m;

[0057] 3) Simulate and measure the temperature and humidity values ​​within the height range of the temperature and humidity measurement module, and adjust the measurement time interval using an exponential function. The measurement time interval is shortest at the beginning of the simulation. As the model gradually reaches a steady state, the measurement interval gradually increases until the model reaches a steady state, obtaining temperature and humidity data at m moments, of which the last moment is the steady-state temperature and humidity data;

[0058] 4) Select all grids within the installation range of the temperature and humidity measurement module, and calculate the difference d between the maximum and minimum moisture content of each grid at m moments as the value of the grid;

[0059] 5) Perform K-means clustering on the grid values ​​of each horizontal plane, and use the elbow rule or silhouette coefficient to determine the number of clusters as k. If the cluster center point is not on the grid, select the grid closest to the center point as the center point, and calculate the average value of the grid value where the cluster center point is located on each horizontal plane;

[0060] 6) The horizontal plane with the largest average value is selected as the temperature and humidity measurement plane, and the center point of the plane cluster is the sensitive point for water content measurement.

[0061] The model is reduced using the proper orthogonal decomposition (POD) method and the snapshot method as follows:

[0062] 1) Create a matrix Θ1, Θ1A = λA, where Θ1 is an m×m matrix, θ t ' i is the temperature field of the horizontal plane where the sensitive point is located at the i-th moment, A is the eigenvector of Θ1, A=[a1,a2…a m ] T , a i is the linear combination coefficient, λ is the eigenvalue of Θ1;

[0063] Calculate the number of temperature measurement modules p1 so that where λ1≥λ2≥…≥λ m ;

[0064] Replace the temperature field in the above steps with the relative humidity field, and repeat the above steps to obtain the number of relative humidity measurement modules p2;

[0065] The number of required temperature and humidity measurement modules is determined to be p, where p = max{p1, p2}.

[0066] The layout of the temperature and humidity measurement module is as follows:

[0067] I) if k < p, re-clustering the horizontal plane grid values ​​selected in step 6 of the method for calculating the sensitive points for measuring moisture content inside the oven, with the number of clusters being p, and the temperature and humidity measurement modules being arranged at the grids where the p cluster centers are located;

[0068] II) If k≥p, the grid values ​​d of the sensitive points are arranged in descending order, i.e., d1≥d2≥…≥d p ≥…≥d k The temperature and humidity measurement modules are arranged at d1, d2, ..., d p The corresponding sensitive point.

[0069] The temperature and humidity sensor transmits the temperature and humidity data to the host computer in real time.

[0070] Calculate the humidity of the air in the horizontal plane where the sensitive point is located as follows:

[0071] 1) The initial state θ of the temperature field is obtained by the temperature and humidity values ​​measured by the temperature and humidity measurement module and the Kalman estimator t The initial state of the relative humidity field θ rh ;

[0072] 2) Calculate the temperature field θ′ of the horizontal plane where the sensitive point is located t , in β(t)=[b1(t),b2(t)…b p (t)], Calculation error such as Figure 2 As shown;

[0073] 3) The same method is used to calculate the relative field θ′ of the horizontal plane where the sensitive point is located rh , calculate the humidity of the air at that level, and the calculation error is as follows Figure 3 shown.

[0074] The method to judge the dryness of the items in the oven is as follows:

[0075] 1) Set the maximum allowable error e max and the allowed mean absolute error e MAE ;

[0076] 2) Compare the air humidity value of the horizontal plane at the sensitive point obtained by measurement and calculation with the steady-state air humidity value of the horizontal plane obtained by simulation, and calculate the maximum error e1 and the mean square error e2;

[0077] 3) If e1>e max or e2>e MAE , it means the item is not dried, otherwise it means the item is dry.

[0078] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for quickly and accurately judging the dryness of items in an oven, characterized in that: The following steps are involved: 1) The temperature and humidity measurement module arranged at the moisture content measurement sensitive point in the oven measures the temperature and humidity data in real time; 2) Temperature and humidity data are uploaded to the host computer; 3) The host computer writes the three-dimensional model of the oven interior and the wet items, and uses the air humidity value at the level of the sensitive point to calculate the maximum allowable error e max and the allowed mean absolute error e MAE To judge the dryness of items, the method to judge the dryness of items in the drying oven is as follows: a) Set the maximum allowable error e max and the allowed mean absolute error e MAE ; b) Compare the air humidity value of the horizontal plane at the sensitive point obtained by measurement and calculation with the steady-state air humidity value of the horizontal plane obtained by simulation, and calculate the maximum error e1 and the mean square error e2; c) If e1>e max or e2>e MAE , it means the item is not dried, otherwise it means the item is dry.

2. The method according to claim 1, wherein The sensitive points are obtained by simulation on a host computer and calculation using K-means clustering.

3. The method according to claim 2, wherein The sensitive points are obtained by the following method: 1) Establish a three-dimensional FLUENT model of the oven interior and the wet items inside; 2) Determine the height range of the temperature and humidity measurement module and divide the established model into grids; 3) Simulate and measure the temperature and humidity values ​​within the height range of the temperature and humidity measurement module. The measurement interval is shortest at the beginning of the simulation. As the model gradually reaches a steady state, the measurement interval gradually increases until the model reaches a steady state. The temperature and humidity data at m moments are obtained, of which the last moment is the steady-state temperature and humidity data. 4) Select all grids within the installation range of the temperature and humidity measurement module, and calculate the difference d between the maximum and minimum moisture content of each grid at m moments as the value of the grid; 5) Perform K-means clustering on the grid values ​​of each horizontal plane, with the number of clusters being k. If the cluster center point is not on a grid, the grid closest to the center point is selected as the center point, and the average value of the grid value where the cluster center point is located is calculated for each horizontal plane. 6) Select the horizontal plane with the largest average value as the temperature and humidity measurement plane, and the center point of the plane cluster is the sensitive point.

4. The method according to claim 3, wherein The model is reduced in order using the proper orthogonal decomposition method and the snapshot method to determine the number of temperature and humidity measurement modules and arrange them at sensitive points.

5. The method according to claim 4, wherein The number of temperature and humidity measurement modules is determined by the following method: 1) Create a matrix Θ1, Θ1A = λA, where Θ1 is an m×m matrix, θ′ ti is the temperature field of the horizontal plane where the sensitive point is located at the i-th moment, A is the eigenvector of Θ1, A=[a1,a2…a m ] T , a i is the linear combination coefficient, λ is the eigenvalue of Θ1; 2) Calculate the number of temperature measurement modules p1 so that where λ1≥λ2≥…≥λ m ; Replace the temperature field in the above steps with the relative humidity field, and repeat the above steps to obtain the number of relative humidity measurement modules p2; The number of required temperature and humidity measurement modules is determined to be p, where p = max{p1, p2}.

6. The method according to claim 5, wherein The arrangement of the temperature and humidity measurement module is as follows: I) if k < p, re-cluster the horizontal plane grid values, adjust the number of clusters to p, and place the temperature and humidity measurement modules at the grids where the p cluster centers are located; II) If k≥p, the grid values ​​d of the sensitive points are arranged in descending order, i.e., d1≥d2≥…≥d p ≥…≥d k The temperature and humidity measurement modules are arranged at d1, d2, ..., d p The corresponding sensitive point.

7. The method according to claim 1, wherein The method for calculating the humidity of the air in the horizontal plane where the sensitive point is located is as follows: 1) The initial state of the temperature field θ is obtained by using the temperature and humidity values ​​measured by the temperature and humidity measurement module and the Kalman estimator t The initial state of the relative humidity field θ rh ; 2) Calculate the temperature field θ′ of the horizontal plane where the sensitive point is located t , Among them, θ′ ti is the temperature field of the horizontal plane where the sensitive point is located at the i-th moment, β(t)=[b1(t),b2(t)…b p (t)], 3) The same method is used to calculate the relative field θ′ of the horizontal plane where the sensitive point is located rh , calculate the humidity content of the air at that horizontal plane.

8. A device for quickly and accurately judging the dryness of items in an oven, characterized in that: The device includes a temperature and humidity measurement module, a data transmission template, a power supply module and a host computer; The power supply module supplies power to the temperature and humidity measurement module and the host computer; The temperature and humidity measurement module is arranged at a sensitive point for measuring moisture content in the oven; The temperature and humidity measurement module transmits the real-time measured temperature and humidity data to the host computer through the data transmission module; The host computer writes the three-dimensional model of the interior of the oven and the wet items, and uses the measured temperature and humidity data to obtain the horizontal air humidity value of the sensitive point, and calculates the maximum allowable error e max and the allowed mean absolute error e MAE To judge the dryness of items, the method to judge the dryness of items in the drying oven is as follows: a) Set the maximum allowable error e max and the allowed mean absolute error e MAE ; b) Compare the air humidity value of the horizontal plane at the sensitive point obtained by measurement and calculation with the steady-state air humidity value of the horizontal plane obtained by simulation, and calculate the maximum error e1 and the mean square error e2; c) If e1>e max or e2>e MAE , it means the item is not dried, otherwise it means the item is dry.

9. The device according to claim 8, wherein The device can implement the method according to any one of claims 1 to 7.

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