A measurement system, calibration method and application for online calibration of temperature sensors for warehouses

Abstract

The present invention discloses a measurement system, calibration method, and application for online calibration of warehouse temperature sensors. The system comprises a standard temperature sensor and a host computer. The standard temperature sensor is disposed in a warehouse containing a temperature sensor to be calibrated, and the standard temperature sensor is connected to the host computer. The present invention can be used to measure data for online calibration of warehouse temperature sensors. Furthermore, the temperature sensor online detection and calibration method described in the present invention can achieve online calibration of warehouse temperature sensors without disrupting industrial production order, thereby improving production efficiency and reducing labor costs. Furthermore, the present invention can display data from the temperature sensor to be calibrated and the calculation results of a temperature field distribution model, thereby enabling online monitoring of warehouse temperature data.

Description

Technical Field

[0001] The invention relates to a measurement system, a calibration method and an application for online calibration of a temperature sensor for a warehouse, and belongs to the field of detection technology. Background Art

[0002] The warehouse's storage environment significantly impacts the quality of goods. For example, the government has strict regulations on temperature and humidity in pharmaceutical warehouses, and pharmaceutical production, warehousing, and logistics must also comply with relevant national standards. Temperature sensors (digital thermometers) are typically the primary instrument for temperature detection in confined spaces and are widely used in warehouse management. To ensure the accuracy of temperature sensors, various sensors used in industrial scenarios must be regularly inspected by a legal metrology agency. Currently, sensor calibration primarily involves offline calibration, which requires disassembling the sensor and taking it to a metrology department for verification and calibration. This practice can severely impact industrial production efficiency; however, periodic offline calibration of sensors prevents real-time monitoring of sensor failures and accuracy issues. Therefore, online sensor calibration technology is an urgent need for improvement in the metrology industry and industrial production. Summary of the Invention

[0003] The present invention provides a measurement system, calibration method and application for online calibration of temperature sensors for warehouses, which are used to construct a measurement platform for online calibration of temperature sensors for warehouses. The platform is further used to obtain measurement data for calibration of the temperature sensors to be calibrated. A visual front end is further constructed to realize human-computer interaction, thereby providing online monitoring of the online calibration of temperature sensors for warehouses.

[0004] The technical solution of the present invention is:

[0005] According to one aspect of the present invention, a measurement system for online calibration of temperature sensors for warehouses is provided, comprising a standard temperature sensor and a host computer; the standard temperature sensor is arranged in the warehouse of the temperature sensor to be calibrated, and the standard temperature sensor is connected to the host computer via a network.

[0006] The arrangement rule of the standard temperature sensor adopts the first arrangement rule or the second arrangement rule;

[0007] The first arrangement rule includes:

[0008] A standard temperature sensor should be placed within 50 cm horizontally of each temperature sensor to be calibrated;

[0009] The second arrangement rule includes:

[0010] Standard temperature sensors are placed in warehouse corners, electrical heat sources, windows, ventilation openings, and work entrances and exits.

[0011] If the warehouse space occupancy rate is higher than 80%, the second layout rule is adopted; otherwise, the first layout rule is adopted.

[0012] According to another aspect of the present invention, an online calibration method for temperature sensors for warehouses is also provided, including: establishing a temperature field model of the warehouse to be calibrated: constructing a geometric model, defining the material properties of the warehouse structure, adding materials corresponding to the warehouse, setting boundary conditions, selecting multiple physical fields for physical field coupling, and meshing; calibrating standard temperature sensor data and the temperature field model to obtain a credible temperature field model; comparing the data of each temperature sensor to be calibrated with the temperature value of the corresponding point in the credible temperature field model to determine whether the corresponding temperature sensor to be calibrated meets the standard.

[0013] The boundary conditions specifically include: the ambient temperature outside the warehouse, the temperature change outside the warehouse in different time periods, the type of independent heat source, and the size and location of the ventilation device.

[0014] The selection of multiple physical fields for physical field coupling includes: adding a "surface-to-surface radiation" heat transfer boundary and a non-isothermal flow domain, and selecting the "turbulent k-ε" and "solid and fluid heat transfer" options in the non-isothermal flow domain to achieve physical field coupling.

[0015] The “solid and fluid heat transfer” simulates the temperature of the warehouse wall through the formula:

[0016]

[0017] Where ρ is the density; C p is the constant pressure heat capacity; u is the heat convection velocity field; is the temperature gradient; q is the heat convection flux; is the divergence of heat convection flux; Q is the heat of heat convection; Q ted is the thermoelastic damping; Q p is the pressure work; Q vd is viscous dissipation; k is thermal conductivity; p A is the absolute pressure; R S is the specific gas constant; calculate the heat transfer between the wall and the air; by the formula q0=h×(T ext -T) to calculate the wall heat flux q0, where q0 is the wall convection heat flux, h is the heat transfer coefficient, and T ext is the external temperature boundary condition of the warehouse, and T is the internal temperature boundary condition.

[0018] The "surface-to-surface radiation" is added to simulate solar radiation, which includes: direct solar radiation energy and diffuse reflection of the sun on the warehouse;

[0019] 1) Through the formula Calculate the direct solar radiation energy I m ; Among them, h s is the solar altitude angle, p is the atmospheric transparency coefficient, and I0 is the solar constant;

[0020] 2) For the diffuse reflection of the sun on the warehouse, the formula is:

[0021]

[0022] Among them: J i is the effective radiation; ε i is the surface emissivity; e b (T) is the total emission power of the blackbody hemisphere at the reference temperature; T is the temperature input to the model, i.e., the reference temperature; ρ d,i is the diffuse reflectivity; G i is the total radiation energy projected onto a unit area per unit time; G m,i For mutual radiation; G amb,i is environmental radiation; G ext,i Radiation from external radiation sources; F amb,i is the environmental horizon factor; ε amb is the ambient emissivity; T amb is the ambient temperature; e b (T amb ) is the total emission power of the blackbody hemisphere at ambient temperature; FEP i (T amb ) is the partial radiation force at ambient temperature; FEP i (T) is the partial radiation force at reference temperature; n is the refractive index of the medium; σ is the blackbody radiation constant; C2 is the second radiation constant in international units; λ i is the wavelength (the subscript i indicates multiple spectral bands).

[0023] The "turbulence k-ε" is used to simulate the flow of air in the warehouse, using the formula:

[0024]

[0025] Where: ρ is density; u is velocity field; is the Hamiltonian operator; p is the pressure; l is the mixing length; K is the viscous stress tensor; F is the volume force: is the velocity field divergence; μ is the dynamic viscosity; μ T is the turbulent viscosity coefficient; is the velocity field gradient; is the transpose of the velocity field gradient; k is the turbulent kinetic energy; is the gradient of turbulent kinetic energy; ∈ is the turbulent dissipation rate; P k is the generated term; σ k , σ ∈ , C∈1, C∈2, Cμ is the model coefficient.

[0026] According to another aspect of the present invention, an application of an online calibration method for a temperature sensor for a warehouse is provided, which is used to construct a visual front-end for online calibration of the temperature sensor, including:

[0027] Use Blender to perform 3D modeling of the warehouse's internal components in the data visualization front-end interface; use the Unity engine to implement the virtual reality system; use MySQL as the database management system; use MATLAB to communicate with the COMSOL server through the LiveLink for MATLAB interface, write the warehouse properties to the COMSOL server model object to complete the model construction and solution, and after the solution is completed, import the results into Unity's particle system to complete the temperature field visualization; import the temperature field distribution into the data visualization system in the 3D scene.

[0028] The beneficial effects of the present invention are: on the one hand, the present invention can be used to realize data measurement for online calibration of temperature sensors used in warehouses; on the other hand, the online detection and calibration method of temperature sensors described in the present invention can realize online calibration of temperature sensors in warehouses without affecting the order of industrial production, thereby improving production efficiency and reducing labor costs; on still another hand, the present invention can display the data of the temperature sensor to be calibrated and the calculation results of the temperature field distribution model to realize online monitoring of warehouse temperature data. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a block diagram of the measurement system of the present invention;

[0030] Figure 2 is a geometric model diagram of an embodiment;

[0031] Figure 3 This is a basic attribute diagram of an exterior wall according to an embodiment of the present invention;

[0032] Figure 4 This is a basic attribute diagram of the middle layer of a wall according to an embodiment of the present invention;

[0033] Figure 5 This is a basic attribute diagram of the inner layer of the wall and the ceiling in an embodiment of the present invention;

[0034] Figure 6 This is a basic attribute diagram of a floor according to an embodiment of the present invention;

[0035] Figure 7 This is a basic attribute diagram of a window according to an embodiment of the present invention;

[0036] Figure 8 This is a basic attribute diagram of the internal space of a warehouse according to an embodiment of the present invention;

[0037] Figure 9It is a diagram of the arrangement of the added materials of the present invention;

[0038] Figure 10 This is a diagram showing the simulation setup using the Heat Transfer in Solids and Fluids interface.

[0039] Figure 11 The present invention utilizes "surface-to-surface radiation" to simulate the solar radiation setting diagram;

[0040] Figure 12 This is a diagram of the flow setting of the air in the warehouse using "turbulence, k-ε";

[0041] Figure 13 This is a diagram of the non-isothermal flow interface configuration according to the present invention;

[0042] Figure 14 This is a diagram of a grid division setting according to an embodiment of the present invention;

[0043] Figure 15 This is a steady-state study diagram of an embodiment of the present invention;

[0044] Figure 16 This is a standard temperature sensor arrangement diagram according to an embodiment of the present invention;

[0045] Figure 17 This is an isothermal surface distribution diagram of an embodiment of the present invention;

[0046] Figure 18 This is a result diagram of the simulation data of the present invention and the measured data of the standard temperature sensor;

[0047] Figure 19 This is a result diagram of the simulation data of the present invention and the measured data of the temperature sensor to be calibrated;

[0048] Figure 20 This is the block diagram of the online calibration visualization front end;

[0049] Figure 21 This is a schematic diagram of warehouse modeling in Unity;

[0050] Figure 22 This is the Unity sensor value interface diagram;

[0051] Figure 23 This is the Unity temperature field distribution interface diagram. DETAILED DESCRIPTION

[0052] The invention will be further described below with reference to the accompanying drawings and embodiments, but the content of the present invention is not limited to the scope of the drawings.

[0053] Example 1: Figure 1As shown, a measurement system for online calibration of warehouse temperature sensors includes a standard temperature sensor and a host computer. The standard temperature sensor is placed in the warehouse where the temperature sensor to be calibrated resides, and is connected to the host computer via a network (wired or wireless). It should be noted that the temperature sensor to be calibrated can be connected to the host computer, or its data can be directly compared with data in the model. Typically, a network is available in the warehouse to access the sensor to be calibrated.

[0054] Furthermore, the layout rules of the standard temperature sensors can be set, adopting the first layout rule or the second layout rule; the first layout rule includes: a standard temperature sensor should be arranged within a horizontal distance of 50 cm of each temperature sensor to be calibrated; the second layout rule includes: standard temperature sensors should be arranged in warehouse corners, electrical heat sources, windows, ventilation ports and work entrances and exits.

[0055] Furthermore, it can be set that when the warehouse cargo space occupancy rate is higher than 80%, the second layout rule is adopted, otherwise the first layout rule is adopted.

[0056] Specifically, if the warehouse occupancy rate exceeds 80% and the adjacent storage locations of the sensor being tested are all occupied, preventing the first placement rule from being met, standard temperature sensors can be placed in areas with concentrated temperature influencing factors, such as corners, electrical heat sources, windows, ventilation openings, and work entrances and exits, ensuring a uniform distribution across the space. The accuracy requirement between the temperature field distribution model data obtained by finite element calculation and the standard sensor data is (for ambient temperatures between -20°C and 40°C, the error must be less than 0.5°C). Otherwise, calibrating the standard sensor within close proximity to the sensor being calibrated should be prioritized, with a distance of no more than 50 cm (with horizontally adjacent storage locations empty) to minimize the discrepancy between the standard sensor data and the sensor being calibrated, provided that normal production is not disrupted. If there are remaining standard sensors, they can be placed in areas with concentrated temperature influencing factors, such as corners, electrical heat sources, windows, ventilation openings, and work entrances and exits, ensuring a uniform distribution across the space. The accuracy requirement between the temperature field distribution model data obtained by finite element calculation and the standard sensor data is (when the ambient temperature is -20 to 40°C, the error between the two is required to be less than 0.5°C).

[0057] It should be noted that the measurement system for online calibration of warehouse temperature sensors described in this application is usually configured as a complete set when it is actually used. For example, the standard measurement system can calibrate a warehouse of 50,000 cubic meters. According to national requirements, 15-20 sensors are required. However, the standard temperature sensors can be arranged according to the volume of the actual calibration scene. If the actual detection scene is larger than the configured standard measurement system, a partition calibration method can be adopted.

[0058] In addition, the standard temperature sensor layout quantity principle is:

[0059] (a) Each independent warehouse or storage room shall be equipped with at least two measuring point terminals, which shall be evenly distributed.

[0060] (b) For warehouses with a floor area of less than 300 square meters, at least one standard temperature sensor shall be installed; for warehouses with a floor area of more than 300 square meters, at least one measuring point terminal shall be added for every additional 300 square meters. For warehouses with a floor area of less than 300 square meters, the terminal shall be calculated as 300 square meters.

[0061] (c) If the shelf height of an elevated warehouse or a fully automated high-bay warehouse is between 4.5 meters and 8 meters, at least two measuring point terminals shall be installed for every 300 square meters of area, and at least one measuring point terminal shall be added for every additional 300 square meters, and they shall be evenly distributed on the upper and lower positions of the shelves; if the shelf height is above 8 meters, at least three measuring point terminals shall be installed for every 300 square meters of area, and at least three measuring point terminals shall be added for every additional 300 square meters, and they shall be roughly distributed on the upper, middle and lower positions of the shelves; if the area is less than 300 square meters, it shall be calculated as 300 square meters.

[0062] (d) The location where the measuring point terminal is installed on the upper level of a high-bay warehouse or a fully automatic high-bay warehouse should not be lower than the highest position of the medicines stored on the top shelf.

[0063] Example 2: Figure 2-19 As shown, an online calibration method for a temperature sensor for a warehouse includes: establishing a temperature field model of the warehouse to be calibrated: constructing a geometric model, defining the material properties of the warehouse structure, adding materials corresponding to the warehouse, setting boundary conditions, selecting multiple physical fields for physical field coupling, and meshing; calibrating standard temperature sensor data and the temperature field model to obtain a credible temperature field model; comparing the data of each temperature sensor to be calibrated with the temperature value of the corresponding point in the credible temperature field model to determine whether the corresponding temperature sensor to be calibrated meets the standard.

[0064] Furthermore, an optional specific implementation of this embodiment is described as follows:

[0065] Step 1: Establish the temperature field model of the calibrated warehouse

[0066] When creating a model, the first step is usually to build a geometric model, which restores the real framework of the warehouse. Using 3D modeling in COMSOL, 3D graphics are obtained through operations such as stretching of 2D planes, and then the target graphics are obtained through some operations in Boolean operations, such as Figure 2 shown.

[0067] Step 2: Define material properties

[0068] 1. External wall: Aluminum, basic properties such as Figure 3 shown.

[0069] 2. Middle layer of the wall: thermal insulation cotton, basic properties such as Figure 4 shown.

[0070] 3. Inner wall and ceiling: SteelAISI 4340 (AISI 4340 alloy steel), basic properties such as Figure 5 shown.

[0071] 4. Floor: Concrete, basic properties such as Figure 6 shown.

[0072] 5. Window: Glass, basic properties such as Figure 7 shown.

[0073] 6. Warehouse internal space: Air (air), basic properties such as Figure 8 shown.

[0074] Step 3: Add corresponding materials

[0075] Add corresponding materials to different areas according to the warehouse model, and the materials can replace each other. Figure 9 shown.

[0076] Step 4: Set boundary conditions

[0077] Set boundary conditions based on on-site measured data: including the ambient temperature outside the warehouse, temperature changes outside the warehouse in different time periods, type of independent heat source, size and location of ventilation device, etc.

[0078] Step 5: Use COMSOL's multiphysics coupling to perform physical field coupling:

[0079] The wall temperature (i.e., the ambient temperature of the warehouse) is simulated using the Heat Transfer in Solids and Fluids interface. Figure 10 shown.

[0080] Independent heat source: The independent heat source of the warehouse only considers solar radiation. Use "surface to surface radiation" to simulate solar radiation, such as Figure 11 shown.

[0081] Air convection: The air in the warehouse generates temperature differences due to solar radiation, which in turn generates non-isothermal flow. Use "Turbulence, k-ε" to simulate the flow of air in the warehouse, such as Figure 12 shown.

[0082] Add a surface-to-surface radiation heat transfer boundary and a non-isothermal flow domain. Select the turbulent k-ε and solid and fluid heat transfer options in the non-isothermal flow domain to implement the physical field coupling function. The non-isothermal flow interface settings are as follows: Figure 13 shown.

[0083] Step 6: Meshing

[0084] Use the physical field to control the meshing method. Figure 14 shown.

[0085] Step 7: Finite element simulation calculation

[0086] The solid and fluid heat transfer physical field simulates the wall conduction heat transfer in the warehouse, sets the wall external temperature, ceiling external temperature, ventilation device external temperature and boundary thermal insulation settings, and calculates the fluid and solid conditions respectively; through the formula:

[0087]

[0088] Where ρ is the density (in the ideal gas domain); C p is the constant pressure heat capacity; u is the heat convection velocity field; is the temperature gradient; q is the heat convection flux; is the divergence of heat convection flux; Q is the heat of heat convection; Q ted is the thermoelastic damping; Q p is the pressure work; Q vd is viscous dissipation; k is thermal conductivity; p A is the absolute pressure; R S is the specific gas constant; calculate the heat transfer between the wall and the air;

[0089] By the formula q0=h×(T ext -T) to calculate the wall heat flux q0, where q0 is the wall convection heat flux (-n·q=q0), h is the heat transfer coefficient, T ext is the external temperature boundary condition of the warehouse, and T is the internal temperature boundary condition.

[0090] The solar radiation includes: direct solar radiation energy and diffuse reflection of the sun on the warehouse;

[0091] 1) Through the formula Calculate the direct solar radiation energy I m ; Among them, h s is the solar altitude angle, p is the atmospheric transparency coefficient, and I0 is the solar constant;

[0092] 2) For the diffuse reflection of the sun on the warehouse, the formula is:

[0093]

[0094] Among them: J i is the effective radiation (the subscript i indicates multiple spectral bands); ε i is the surface emissivity; eb (T) is the total emission power (spectral radiance) of the blackbody hemisphere at the reference temperature; T is the temperature input to the model, i.e., the reference temperature, which is 293.15K by default; ρ d,i is the diffuse reflectivity; G i is the total radiation energy projected onto a unit area per unit time; G m,i For mutual radiation; G amb,i is environmental radiation; G ext,i Radiation from external radiation sources; F amb,i is the environmental horizon factor; ε amb is the ambient emissivity; T amb is the ambient temperature; e b (T amb ) is the total emission power of the blackbody hemisphere at ambient temperature; FEP i (T amb ) is the radiation force (rate) of the ambient temperature part (unit: W / m 2 ); FEP i (T) is the partial radiation force (rate) at reference temperature; n is the refractive index of the medium; σ = 5.67 × 10 -8 w / (m 2 ·K 4 ) is the Stefan-Boltzmann constant, the blackbody radiation constant; C2 is the second radiation constant (1.438X10 -2 m·K) International System of Units constant (SI unit: m·K); λ i where i represents the wavelength (i represents multiple spectral bands), and X represents the variable in the integral expression. The integral result is the radiant power of the spectral band divided by wavelength, with the upper and lower limits of the integral representing the start and end points of the band.

[0095] The “turbulent k-ε” physical field is used to simulate the non-isothermal flow of air in the warehouse, using the formula:

[0096]

[0097] Where: ρ is density; u is velocity field; is the Hamiltonian operator; p is the pressure; l is the mixing length; K is the viscous stress tensor; F is the volume force: is the velocity field divergence; μ is the dynamic viscosity, N·s / m 2 ;μ T is the turbulent viscosity coefficient; is the velocity field gradient; is the transpose of the velocity field gradient; k is the turbulent kinetic energy; is the gradient of turbulent kinetic energy; ∈ is the turbulent dissipation rate; P k is the generated term; σ k , σ ∈, C∈1, C∈2, C μ are the model coefficients, as shown in Table 1.

[0098] Table 1

[0099] CONSTANT VALUE <![CDATA[C μ ]]> 0.09 <![CDATA[C ε1 ]]> 1.44 <![CDATA[C ε2 ]]> 1.92 <![CDATA[σ k ]]> 1.0 <![CDATA[σ ε ]]> 1.3

[0100] Step 8: Research and Results Analysis

[0101] 1. Research

[0102] After the previous steps, run a steady-state study. Figure 15 shown.

[0103] 2. Results Analysis

[0104] After completing the simulation calculation, analyze the results. Figure 16 As shown, according to the second arrangement rule of standard temperature sensors, a total of 9 standard temperature sensors are placed in the warehouse in this embodiment (the cubes in the figure are temperature sensors to be calibrated, and the circles are standard temperature sensors). Figure 17 As shown in the figure, the distribution of each isothermal surface is obtained, that is, the temperature data of the corresponding position of the standard temperature sensor in the temperature field distribution model inside the warehouse. The results of simulation data and measured data are shown in Figure 18 As shown in the figure, it can be seen that the accuracy of the finite element simulation model of the warehouse interior has reached the national standard (the data calibration requirement is that when the ambient temperature is -20 to 40°C, the error between the two is required to be less than 0.5°C), and the simulation calculation results are credible. The temperature of each corresponding position of the sensor to be calibrated in the temperature field model is further compared with the sensor data to be calibrated, and the national standard is used to determine whether the temperature sensor to be calibrated is normal. The results are shown in the figure. Figure 19 As shown in the figure, it can be seen that the data of sensors 2, 5, and 8 to be calibrated are abnormal, thus realizing the entire online calibration process of the temperature sensors inside the warehouse.

[0105] It should be noted that during the model calibration process, the standard temperature sensor data is compared with the temperature calculation results of the corresponding points in the temperature field distribution model. If the error is within the national standard specification, the temperature field model is considered credible, and the model is used to perform online calibration of the sensor to be calibrated. After obtaining the credible temperature field model, it can be directly used for subsequent calibration of the sensor to be calibrated; if the error exceeds the national standard, the temperature field model is further optimized (i.e., the first to seventh steps are repeated to optimize the warehouse model by adding or modifying boundary conditions, etc.) until the model meets the requirements of the national standard specification.

[0106] Example 3: Figure 20As shown, an application of an online calibration method for temperature sensors used in warehouses is used to build a visualization front-end for online calibration of temperature sensors, including: using Blender to perform 3D modeling of the internal components of the warehouse set in the data visualization front-end interface; using the Unity engine to implement a virtual reality system; using MySQL as a database management system; using MATLAB to communicate with the COMSOL server through the LiveLink for MATLAB interface, writing warehouse properties into the COMSOL server model object to complete model construction and solution, and after the solution is completed, importing the results into the Unity particle system to complete temperature field visualization; importing the temperature field distribution into the data visualization system in the 3D scene, and using different color attributes to intuitively display the temperature field distribution. Figure 21 Shown is a schematic diagram of warehouse modeling in Unity.

[0107] Step 1: Create a warehouse model and edit parameters in the visualization terminal based on the measured warehouse data:

[0108] (1) Warehouse size (inner diameter): 90m long, 15.14m wide, 22.4m high, volume approximately 29,700m 3 .

[0109] (2) Two doors: Dimensions: 1.6m x 2.34m, the right side of the right door is 1.95m from the right wall, the left side of the left door is 3.46m from the left wall.

[0110] (3) 7 ventilation devices;

[0111] (4) 5 skylights, size: 7.5m×0.7m;

[0112] (5) 5 windows, dimensions: width: 1.51m, height: 14m, distance from the warehouse floor: 3.3m;

[0113] Set the properties of various materials in the warehouse in the visual terminal:

[0114] (1) Outer wall layer: Aluminum;

[0115] (2) Middle layer of wall: thermal insulation cotton;

[0116] (3) Inner wall and ceiling: SteelAISI 4340 (AISI 4340 alloy steel);

[0117] (4) Floor: Concrete;

[0118] (5) Window: glass;

[0119] (6) Internal space of the warehouse: Air.

[0120] The boundary conditions for finite element calculation of temperature field distribution in the warehouse were obtained through on-site measurements.

[0121] Specifically, boundary conditions are set according to on-site measured data, including the ambient temperature outside the warehouse, temperature changes outside the warehouse in different time periods, independent heat source type, ventilation device size and location, etc.; and a suitable physical field model is established based on the measured parameters.

[0122] Step 2:

[0123] In this embodiment, a total of 9 standard temperature sensors are placed in the warehouse, such as Figure 16 shown.

[0124] In the visualization terminal, the warehouse model is meshed and finite element calculated to obtain the temperature field distribution model.

[0125] Calibrate the standard temperature sensor data and the temperature field distribution model. The data visualization front-end compares the standard temperature sensor data with the corresponding points in the temperature field distribution model. If the error is within the national standard, the temperature field distribution model is considered reliable and used for online calibration. If the error is too large, the temperature field distribution model needs to be optimized until it meets the national standard.

[0126] Step 3:

[0127] The data of each temperature sensor to be calibrated is compared with the temperature value of the corresponding point in the credible temperature field distribution model. If the difference is greater than the national standard specification, the temperature sensor to be calibrated can be considered abnormal. If the difference is less than the national standard range, the temperature sensor to be calibrated is considered normal.

[0128] Step 4:

[0129] The data visualization front end displays all data in the detailed information interface. This includes: warehouse parameter editing interface, 3D scene interface, chart interface and abnormal temperature sensor alarm interface to be calibrated. The 3D scene interface and chart interface can display both the data of the temperature sensor to be calibrated and the calculation results of the temperature field distribution model, such as Figure 22 、 23 This step enables online monitoring of warehouse temperature data.

[0130] By applying the technical solution of the present invention, online calibration of temperature sensors in the warehouse can be achieved, avoiding the problem of traditional offline calibration of temperature sensors affecting production, thereby improving production efficiency and reducing the labor cost of sensor disassembly and assembly; at the same time, the visual front-end realizes online real-time calibration of sensors, which can promptly detect sensor anomalies and avoid losses caused by unreliable sensor data; finally, the visual front-end realizes sensor data accumulation based on database management, which can evaluate the health status of sensors and predict sensor life.

[0131] The specific embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in this field without departing from the scope of the present invention.

Claims

1. A method for online calibration of a temperature sensor for a warehouse, characterized in that: include: Establish a temperature field model for the warehouse to be calibrated: construct a geometric model, define the material properties of the warehouse structure, add the corresponding materials for the warehouse, set boundary conditions, select multi-physics fields for physical field coupling, and mesh; Calibrate the standard temperature sensor data and the temperature field model to obtain a credible temperature field model; Compare the data of each temperature sensor to be calibrated with the temperature value of the corresponding point in the trusted temperature field model to determine whether the corresponding temperature sensor to be calibrated meets the standard; Selecting multiple physical fields for physical field coupling includes: adding a "Surface-to-Surface Radiation" heat transfer boundary and a non-isothermal flow domain, and selecting the "Turbulent k-ε" and "Solid and Fluid Heat Transfer" options in the non-isothermal flow domain to achieve physical field coupling; The "surface-to-surface radiation" is added to simulate solar radiation, which includes: direct solar radiation energy and diffuse reflection of the sun on the warehouse; 1) Through the formula Calculate the direct solar radiation energy I m ; Among them, h s is the solar altitude angle, p is the atmospheric transparency coefficient, and I0 is the solar constant; 2) For the diffuse reflection of the sun on the warehouse, the formula is: Among them: J i is the effective radiation; ε i is the surface emissivity; e b (T) is the total emission power of the blackbody hemisphere at the reference temperature; T is the temperature input to the model, i.e., the reference temperature; ρ d,i is the diffuse reflectivity; G i is the total radiation energy projected onto a unit area per unit time; G m,i For mutual radiation; G amb,i is environmental radiation; G ext,i Radiation from external radiation sources; F amb,i is the environmental horizon factor; ε amb is the ambient emissivity; T amb is the ambient temperature; e b (T amb ) is the total emission power of the blackbody hemisphere at ambient temperature; FEP i (T amb ) is the partial radiation force at ambient temperature; FEP i (T) is the partial radiation force at reference temperature; n is the refractive index of the medium; σ is the blackbody radiation constant; C2 is the second radiation constant in international units; λ i is the wavelength; i represents multiple spectral bands.

2. The online calibration method for a temperature sensor for a warehouse according to claim 1, characterized in that: The boundary conditions specifically include: the ambient temperature outside the warehouse, the temperature change outside the warehouse in different time periods, the type of independent heat source, and the size and location of the ventilation device.

3. The online calibration method for a temperature sensor for a warehouse according to claim 1, characterized in that: The "solid and fluid heat transfer" simulates the temperature of the warehouse wall through the formula: Where ρ is the density; C p is the constant pressure heat capacity; u is the heat convection velocity field; is the temperature gradient; q is the heat convection flux; is the divergence of heat convection flux; Q is the heat of heat convection; Q ted is the thermoelastic damping; Q p is the pressure work; Q vd is viscous dissipation; k is thermal conductivity; p A is the absolute pressure; R S is the specific gas constant; calculate the heat transfer between the wall and the air; By the formula q0=h×(T ext -T) to calculate the wall heat flux q0, where q0 is the wall convection heat flux, h is the heat transfer coefficient, and T ext is the external temperature boundary condition of the warehouse, and T is the internal temperature boundary condition.

4. The online calibration method for a temperature sensor for a warehouse according to claim 1, characterized in that: The "turbulence k-ε" is used to simulate the flow of air in the warehouse, using the formula: Where: ρ is density; u is velocity field; is the Hamiltonian operator; p is the pressure; l is the mixing length; K is the viscous stress tensor; F is the volume force: is the velocity field divergence; μ is the dynamic viscosity; μ T is the turbulent viscosity coefficient; is the velocity field gradient; is the transpose of the velocity field gradient; k is the turbulent kinetic energy; is the gradient of turbulent kinetic energy; ∈ is the turbulent dissipation rate; P k is the generated term; σ k , σ ∈ , C∈1, C∈2, C μ is the model coefficient.

5. An application of the online calibration method for a temperature sensor for a warehouse as claimed in claim 1, characterized in that: Used to build a temperature sensor online calibration visualization front end, including: Use Blender to perform 3D modeling of the warehouse's internal components in the data visualization front-end interface; use the Unity engine to implement the virtual reality system; use MySQL as the database management system; use MATLAB to communicate with the COMSOL server via the LiveLink for MATLAB interface, write warehouse properties to the COMSOL server model object to complete model construction and solution, and after the solution is completed, import the results into Unity's particle system to complete temperature field visualization; and import the temperature field distribution into the data visualization system in the 3D scene.

Images