Temperature and humidity intelligent real-time monitoring alarm system

Abstract

The invention provides a temperature and humidity intelligent real-time monitoring and alarming system which comprises the steps that a main controller calculates a temperature load in a drying cabin according to a shell drying heat transfer model, calculates a humidity load according to a shell drying mass transfer model, and obtains a first working parameter of a temperature control machine and a second working parameter of a humidity control machine according to the temperature load and the humidity load; controlling a humidity controller to regulate and control the temperature and humidity in the drying cabin based on the first working parameter and the second working parameter; and the alarm carries out statistical calculation on the temperature average deviation and the humidity average deviation in a set period, and if the temperature average deviation is greater than a first threshold value and / or the humidity average deviation is greater than a second threshold value, an alarm signal is output. According to the scheme, accurate control over the temperature and humidity in the shell-making drying cabin of the single-crystal turbine blade can be achieved, and when the temperature and humidity control effect is difficult to reach the expected target, alarm processing can be conducted in time so as to reduce the probability that the shell of the single-crystal turbine blade has quality defects.

Description

Technical Field

[0001] The present invention relates to the technical field of precise temperature and humidity control, and in particular to an intelligent real-time temperature and humidity monitoring and alarm system. Background Art

[0002] Single crystal turbine blades are key components in aircraft engines, and their performance directly affects the overall performance of the engine. Shell making is a key step in the manufacturing process of single crystal turbine blades, which is directly related to the precision, quality and performance of the blades. In the shell making process, the control of temperature and humidity is also very critical. Too high or too low temperature and humidity may lead to the deterioration of the shell quality or deformation of the blade.

[0003] Since the moisture and heat generated in the shell drying chamber are unstable, in order to meet the requirements of high-precision temperature and humidity control, it is necessary to put forward higher requirements for the design of the environmental control system. The existing research is as follows: Cui Dezhen (Research on Precision Casting Constant Temperature and Humidity Drying Chamber [D], 2014) used CFD to study the relationship between ventilation frequency, moisture dissipation intensity and temperature and humidity control accuracy of the paint shell drying chamber. Wu Zhifeng (Research on Factors Affecting Temperature and Humidity in Precision Casting Drying Chamber [D], 2016) divided the entire paint shell drying chamber into three areas through simulation analysis of three different shell moisture dissipation rates of 30g / h, 60g / h and 100g / h. Each area corresponds to different ventilation times and air supply parameters to achieve energy saving.

[0004] The above existing research did not focus on the temperature, humidity and wind speed conditions near the mold shell surface, and did not make an accurate analysis of the surrounding environment of the mold shell. In addition, the production drying chamber studied was not fully enclosed, and the manual drying chamber and the automatic production line were not separated, making it difficult to provide a stable temperature and humidity environment for drying the mold shell.

[0005] Therefore, how to accurately control the temperature and humidity and provide early warning of temperature abnormalities for the closed drying chamber (the drying chamber is closed most of the time, and the automatic door is opened only 20% of the time for the robot to apply slurry and spread sand) is a technical problem that urgently needs to be solved. Summary of the invention

[0006] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a pump parts handling method, system, electronic equipment, computer storage medium and computer program product based on AGV.

[0007] The present invention provides an intelligent real-time monitoring and alarm system for temperature and humidity, which is applied to a shell drying chamber for single-crystal turbine blades; the system comprises a main controller and an alarm; wherein, The main controller is used to calculate the temperature load in the drying chamber according to the shell drying heat transfer model, and calculate the first working parameter of the temperature controller according to the temperature load; and calculate the humidity load according to the shell drying mass transfer model, and calculate the second working parameter of the humidity controller according to the humidity load; control the temperature controller to adjust the temperature in the drying chamber based on the first working parameter, and control the humidity controller to adjust the temperature in the drying chamber based on the second working parameter; The alarm is used to perform statistical calculations on the average temperature deviation and the average humidity deviation within a set period, and output an alarm signal if the average temperature deviation is greater than a first threshold and / or the average humidity deviation is greater than a second threshold.

[0008] Optionally, the shell drying heat transfer model is as follows: Ignoring the internal temperature gradient, the overall energy balance equation is as follows:

[0009] in: - temperature load; ——heat capacity of coating, kJ / (kg*K); ——weight of paint, kg; ——Difference between paint temperature and indoor temperature, K / s; ——The latent heat of evaporation of water is 2448.6 kJ / kg; ——Mass loss rate, kg / s.

[0010] Optionally, the shell drying mass transfer model is as follows: The evaporation mass flow rate of water is expressed as follows: (1) in: ——water mass, kg; ——surface area, m; ——mass transfer coefficient related to wind speed, kg / (N*s); ——Saturated vapor pressure at coating temperature T, Pa; ——Ambient vapor pressure, Pa; (2) in: ——sand loading, g; H——the thickness of the coating, mm; ——Density of coating, kg / m 3 ; Combining formulas (1) and (2) yields:

[0011] Will As the moisture dissipation rate of a single shell.

[0012] Optionally, the step of calculating the humidity load according to the shell drying mass transfer model includes: 1) Calculation of moisture dissipation of mold shell The moisture dissipation of the shell is calculated based on the number of shells in the drying chamber and the moisture dissipation rate of a single shell; 2) Outdoor intrusive moisture load Since the working shutter door of the drying chamber is opened during operation, a large amount of air outside the drying chamber will enter the drying chamber, and the amount of moisture brought in is calculated by the following formula: (5) Where: ——The humidity of the air outside the drying chamber, here is based on actual measurement =10.46 g / kg; ——humidity content of air in drying chamber, g / kg; G ——the amount of air entering when the outer door is opened, kg / h; D —— shell moisture load, kg / h; The humidity load is obtained by adding the moisture dissipated by the mold shell to the moisture brought in.

[0013] Optionally, controlling the temperature controller to adjust the temperature in the drying chamber based on the first working parameter, and controlling the humidity controller to adjust the temperature in the drying chamber based on the second working parameter, includes: The first working parameter and the second working parameter are input into a temperature and humidity control model, and the temperature and humidity control model performs multiple iterations to control the temperature and humidity in the drying chamber based on a preset temperature and a preset humidity; Wherein, the temperature and humidity control model is a PID controller or a controller based on a machine learning algorithm.

[0014] Optionally, if the temperature average deviation is greater than a first threshold value and / or the humidity average deviation is greater than a second threshold value, outputting an alarm signal comprises: Acquire historical preparation records of the mold shell, extract various historical data of quality defects from the historical preparation records, determine the mold shell preparation stage to which each historical data belongs, and count a first quantity of the historical data of each preparation stage; Determine the first quantity corresponding to the current shell preparation stage, obtain an adjustment coefficient based on the matching of the quantity and the first negative correlation relationship, use the adjustment coefficient to adjust and optimize the first threshold and the second threshold, and obtain a third threshold and a fourth threshold respectively.

[0015] Optionally, the set period is determined by: A second number of the mold shells in the drying chamber is counted, and the set period is calculated according to the second number and a second negative correlation relationship.

[0016] The present invention provides an electronic device, which is applied to a temperature and humidity intelligent real-time monitoring and alarm system as described in any of the preceding items, and comprises: a memory storing executable program codes; and a processor coupled to the memory.

[0017] The present invention also provides a computer storage medium, which is applied to a temperature and humidity intelligent real-time monitoring and alarm system as described in any of the preceding items, and a computer program is stored on the storage medium.

[0018] The present invention also provides a computer program product for use in an intelligent real-time temperature and humidity monitoring and alarm system as described in any of the preceding items, wherein the computer program product includes a computer program stored in a computer storage medium.

[0019] The beneficial effects of the present invention are at least: The solution of the present invention can achieve precise control of the temperature and humidity in the shell drying chamber of the single crystal turbine blade, and when the control effect of the temperature and humidity is difficult to achieve the expected goal, timely alarm processing can be performed to reduce the probability of quality defects in the shell of the single crystal turbine blade. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 It is a structural schematic diagram of a temperature and humidity intelligent real-time monitoring and alarm system disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0023] For the above technical issues, please refer to Figure 1 The embodiment of the present invention discloses an intelligent real-time monitoring and alarm system for temperature and humidity, which is applied to a shell drying chamber for single-crystal turbine blades; the system includes a main controller and an alarm; wherein, The main controller is used to calculate the temperature load in the drying chamber according to the shell drying heat transfer model, and calculate the first working parameter of the temperature controller according to the temperature load; and calculate the humidity load according to the shell drying mass transfer model, and calculate the second working parameter of the humidity controller according to the humidity load; control the temperature controller to adjust the temperature in the drying chamber based on the first working parameter, and control the humidity controller to adjust the temperature in the drying chamber based on the second working parameter; The alarm is used to perform statistical calculations on the average temperature deviation and the average humidity deviation within a set period, and output an alarm signal if the average temperature deviation is greater than a first threshold and / or the average humidity deviation is greater than a second threshold.

[0024] The above-mentioned system of the present invention is arranged in the shell making and drying chamber of the single crystal turbine blade. The controller can calculate the temperature load and humidity load respectively according to the shell drying heat transfer model and shell drying mass transfer model corresponding to the shell of the single crystal turbine blade to be produced this time, and convert the working parameters of the temperature controller and the humidity controller according to the obtained temperature load and humidity load, that is, control the temperature controller and the humidity controller to operate according to the corresponding working parameters to accurately control the temperature and humidity inside the drying chamber. During the control process, the temperature and humidity changes in the drying chamber are monitored in real time, and then the average temperature deviation and the average humidity deviation within the set period are statistically obtained. If at least one of the average temperature deviation and the average humidity deviation exceeds the corresponding threshold value, it means that the control effect of the temperature and humidity control system of the drying chamber is not good, and an alarm signal is output at this time to prompt relevant personnel to deal with it in time.

[0025] Therefore, the scheme of the present invention can achieve precise control of the temperature and humidity in the shell making and drying chamber of the single crystal turbine blade, and when the control effect of the temperature and humidity is difficult to achieve the expected goal, timely alarm processing can be performed to reduce the probability of quality defects in the shell of the single crystal turbine blade.

[0026] Optionally, the shell drying heat transfer model is as follows: Ignoring the internal temperature gradient, the overall energy balance equation is as follows:

[0027] in: - temperature load; ——heat capacity of coating, kJ / (kg*K); ——weight of paint, kg; ——Difference between paint temperature and indoor temperature, K / s; ——The latent heat of evaporation of water is 2448.6 kJ / kg; ——Mass loss rate, kg / s.

[0028] Optionally, the shell drying mass transfer model is as follows: The evaporation mass flow rate of water is expressed as follows: (1)

[0029] in: ——water mass, kg; ——surface area, m; ——mass transfer coefficient related to wind speed, kg / (N*s); ——Saturated vapor pressure at coating temperature T, Pa; ——Ambient vapor pressure, Pa; (2)

[0030] in: ——sand loading, g; H——the thickness of the coating, mm; ——Density of coating, kg / m 3 ; Combining formulas (1) and (2) yields: .

[0031] The parameters required in the above model are obtained through actual measurement. The specific operation is as follows: during the operation of the production line, the robot grabs the mold shell, first dips the paint in the slurry bucket, and then sands the mold shell. After sanding, the robot grabs the mold shell for weighing, records the weight of the mold shell after sanding, and then sends the mold shell to the drying chamber, hangs it on the mechanical gripper of the drying chamber, and dries while moving in the drying chamber along with the conveyor belt. After drying, the robot takes out the mold shell and weighs it, and records the weight of the dried mold shell. The drying time is calculated based on the time of the two weighing records, and the moisture dissipation rate of a single mold shell is calculated based on the weight difference between the two weighings and the drying time.

[0032] After the moisture dissipation rate of a single mold shell is obtained, the humidity load can be calculated by multiplying the maximum number of mold shells carried by the surface layer and the back layer drying chamber by the moisture dissipation rate of a single mold shell.

[0033] Optionally, the step of calculating the humidity load according to the shell drying mass transfer model includes: 1) Calculation of moisture dissipation of mold shell The moisture dissipation of the shell is calculated based on the number of shells in the drying chamber (e.g. 30 for the surface layer and 60 for the back layer) and the moisture dissipation rate of a single shell; 2) Outdoor intrusive moisture load Since the working roller shutter door of the drying chamber is opened during operation, a large amount of air outside the drying chamber will enter the drying chamber, and the amount of moisture brought in can be calculated by the following formula: (4) Where: ——The humidity of the air outside the drying chamber, here is based on actual measurement =10.46 g / kg; ——humidity content of air in drying chamber, g / kg; G ——the amount of air entering when the outer door is opened, kg / h; D —— shell moisture load, kg / h; The humidity load is obtained by adding the moisture dissipated by the mold shell to the moisture brought in.

[0034] The amount of air entering the automatic door is calculated according to the wind speed and opening area of ​​the automatic door. For example, the air intake of the surface drying cabin is 2.07kg / s, and the air intake of the back drying cabin is 2.41kg / s. Substituting into the above formula, the wet load of the air entering the surface drying cabin is 10.43kg / h, and the wet load of the air entering the back drying cabin is 26.64kg / h.

[0035] In addition, when performing temperature control, the cooling load of the drying chamber can be further considered, and the first working parameter can be calculated by comprehensively calculating the cooling load and the temperature load. The cooling load is calculated as follows: 1) External wall cooling load The core material of the drying chamber outer wall is made of PIR material, and the inner and outer surfaces are covered with 0.5 mm thick hot-dip galvanized steel plates, with a total thickness of 55 mm. The thermal inertia is very small, and the air in the drying chamber and the air in the factory are both guaranteed by equipment to ensure their stability and will not change significantly over time. Therefore, the present invention uses the steady-state heat transfer method to calculate the heat transfer of the outer wall. The cooling load q1 (W) formed by the heat transfer of the outer wall can be calculated as follows:

[0036] Where: ——Heat transfer coefficient of enclosure structure, W / (m 2 K); ——Thermal conductivity of each layer of material, W / (m·K), PIR material: 0.021 W / (m·K), hot-dip galvanized steel plate: 45 W / (m·K); ——Thickness of each layer of material m.

[0037] Calculated K = 0.42 W / (m 2 ·K)

[0038] Where: K——Heat transfer coefficient of enclosure structure, W / (m 2 K); F——Calculated area of ​​enclosure structure, m 2 ; t w ——Dry bulb temperature of air in the plant, obtained by actual measurement w =27.56℃; t n ——Dry bulb temperature in the drying chamber, here both the surface layer and the back layer are taken as t n =22℃; q1——exterior wall heat transfer cooling load, kW.

[0039] For example, the outer wall area of ​​the surface drying cabin is 160.4m 2 The outer wall area of ​​the back drying cabin is 211.24m 2 . The calculation shows that the cooling load of the outer wall of the surface drying chamber is 0.37kW, and the cooling load of the outer wall of the back drying chamber is 0.49kW.

[0040] 2) Equipment cooling load The cooling load of the equipment in the drying chamber is mainly provided by the fans, and the cooling load generated can be calculated by their rated power and power factor. For example, there are 4 fans on the surface layer, with a maximum opening of 40%, and 16 fans on the back layer, with a maximum opening of 100%. Assuming that the equipment remains turned on, the cooling load q2 (W) generated by the heating of the equipment can be calculated as follows:

[0041] Where: n——the number of fans in the drying chamber; m——opening degree of the fan in the drying chamber; P——operating power of a single fan, W; - power factor of the fan; q2——Cooling load of fan equipment, W.

[0042] For example, if the fan operating power is 660W and the power factor is 0.74, the heat generated by the surface layer equipment is 0.27kW and the heat generated by the back layer equipment is 2.75kW.

[0043] 3) Outdoor wind intrusion cooling load The cooling load of the air entering the drying chamber when the automatic door is opened is calculated by multiplying the difference between the enthalpy value of the air inside the drying chamber and the enthalpy value of the air outside the drying chamber by the air intake volume.

[0044]

[0045] Where: G——air intake volume of automatic door, kg / s; —— enthalpy of air outside the drying chamber, kJ / kg; —— enthalpy value in the drying chamber, kJ / kg; q3——Outdoor wind intrusion cooling load, W.

[0046] For example, the amount of air entering the automatic door is calculated according to the measured wind speed and opening area of ​​the automatic door, and the wind intrusion into the surface drying cabin is 2.07kg / s, and the wind intrusion into the back drying cabin is 2.41kg / s. Substituting the values ​​for calculation, the cooling load formed by the air entering the outer door of the surface drying cabin is 18.55kW, and the cooling load of the back drying cabin is 32.59kW.

[0047] 4) Shell latent heat cooling load The cooling load of the mold shell is divided into sensible cooling load and latent cooling load. The latent cooling load is formed by the moisture dissipation of the mold shell and is calculated by condensation heat and moisture dissipation.

[0048]

[0049] Where: r——condensation heat, take r=2448.6kJ / kg; ——moisture dissipation of the shell, kg / s; q4——latent heat cooling load formed by moisture dissipation, kW.

[0050] 5) Shell sensible heat and cold load The sensible cooling load is formed by the heat transfer between the temperature difference between the coating and the environment.

[0051]

[0052] Where: ——heat capacity of coating, kJ / (kg*K); ——weight of paint, kg; ——Difference between paint temperature and indoor temperature, K / s; q5——Sensible heat and cooling load of the mold shell, kW.

[0053] The relationship between the above cooling loads is shown in formula (11).

[0054]

[0055] Where: ——Sensible heat and cooling load of the shell, kJ; ——Total cooling load of air conditioning system, kJ; ——Total latent heat cooling load of shell, kJ; ——Total cooling load caused by heat transfer from the exterior wall, kJ; ——Total cooling load of the equipment, kJ; ——Total cooling load caused by outdoor wind intrusion, kJ.

[0056] From the above, it can be seen that the cooling load in the drying chamber of the present invention is mainly composed of heat transfer from the drying chamber outer wall, heat generated by the operation of the equipment in the drying chamber, cooling load of air entering the drying chamber when the automatic door is opened, cooling load of sensible heat of the mold shell, and latent cooling load formed by moisture dissipation of the mold shell. ; Assuming that the automatic door is open only 20% of the time, Multiply by a factor of 0.2, , h is the total time in the production cycle; .

[0057] Optionally, controlling the temperature controller to adjust the temperature in the drying chamber based on the first working parameter, and controlling the humidity controller to adjust the temperature in the drying chamber based on the second working parameter, includes: The first working parameter and the second working parameter are input into a temperature and humidity control model, and the temperature and humidity control model performs multiple iterations to control the temperature and humidity in the drying chamber based on a preset temperature and a preset humidity; Wherein, the temperature and humidity control model is a PID controller or a controller based on a machine learning algorithm.

[0058] In this embodiment, after the temperature load and humidity load are obtained, the first working parameter and the second working parameter can be converted according to the rated working parameters of the temperature controller (including but not limited to the working voltage and frequency, the maximum power, the maximum load current) and the rated working parameters of the humidity controller (including but not limited to the working voltage and frequency, the maximum dehumidification rate). Then, the preset temperature and humidity control model takes the preset temperature and the preset humidity as the control target, and performs coordinated processing on the first working parameter and the second working parameter, so as to realize the temperature and humidity in the drying chamber being stably maintained within the maximum deviation range of the preset temperature and the preset humidity.

[0059] The temperature and humidity control model of the present invention can adopt both conventional PID controller and controller based on machine learning algorithm. In addition, the temperature controller and humidity controller in the prior art work separately. Since the temperature and humidity control cannot be coordinated, the temperature may not be adjusted synchronously when trying to reduce the humidity. The uncoordinated temperature and humidity control may cause the controller to over-operate in an attempt to reach the set humidity level, which will increase energy consumption and operating costs. Therefore, when adopting a controller based on a machine learning algorithm, the present invention is configured to include both temperature data and humidity data in the training data used when training the controller, so that the controller can be trained synchronously using temperature data and humidity data, so that the controller can make the best control decision based on the temperature load and humidity load, avoiding the defects caused by the above-mentioned incoordination.

[0060] Optionally, if the temperature average deviation is greater than a first threshold value and / or the humidity average deviation is greater than a second threshold value, outputting an alarm signal comprises: Acquire historical preparation records of the mold shell, extract various historical data of quality defects from the historical preparation records, determine the mold shell preparation stage to which each historical data belongs, and count a first quantity of the historical data of each preparation stage; Determine the first quantity corresponding to the current shell preparation stage, obtain an adjustment coefficient based on the matching of the quantity and the first negative correlation relationship, use the adjustment coefficient to adjust and optimize the first threshold and the second threshold, and obtain a third threshold and a fourth threshold respectively.

[0061] In this embodiment, the above-mentioned first threshold and second threshold are preset, but the preparation of the shell is divided into several stages, such as the early stage, the middle stage, the late stage, etc. The defect records belonging to each preparation stage (the historical data of quality defects) are retrieved from the historical preparation records, and the first number of these defect records is counted. The more the first number of defect records, the easier it is for quality defects to occur in this preparation stage, and vice versa. The more difficult it is for quality defects to occur. Therefore, the present invention is set to first determine the above-mentioned first number corresponding to the current shell preparation stage, and then obtain the adjustment coefficient according to the matching of the number and the first negative correlation relationship, that is, the more the first number, the smaller the corresponding adjustment coefficient (less than 1), so that the first threshold and the second threshold can be adjusted to a greater extent using the adjustment coefficient, that is, the alarm condition is set to be more stringent and more sensitive to achieve a more timely alarm. In contrast, when the first number is less, the corresponding adjustment coefficient (less than 1) is larger, so that the first threshold and the second threshold can be adjusted to a smaller extent using the adjustment coefficient, that is, the alarm condition is set to be relatively looser to reduce unnecessary false alarms.

[0062] Optionally, the set period is determined by: A second number of the mold shells in the drying chamber is counted, and the set period is calculated according to the second number and a second negative correlation relationship.

[0063] In this embodiment, when the number of mold shells in the drying chamber is large, improper temperature and humidity control will lead to greater losses, and the temperature and humidity control will be more difficult when the number of mold shells in the drying chamber is large, so the set period is set shorter to increase the alarm monitoring frequency. Otherwise, the set period is set longer.

[0064] An embodiment of the present invention further provides an electronic device, which is applied to a temperature and humidity intelligent real-time monitoring and alarm system as described in any of the preceding items, comprising: a memory storing executable program code; and a processor coupled to the memory.

[0065] An embodiment of the present invention further provides a computer storage medium, which is applied to a temperature and humidity intelligent real-time monitoring and alarm system as described in any of the preceding items, and a computer program is stored on the storage medium.

[0066] An embodiment of the present invention further provides a computer program product, which is applied to an intelligent real-time temperature and humidity monitoring and alarm system as described in any of the preceding items, and the computer program product includes a computer program stored in a computer storage medium.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0070] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An intelligent real-time monitoring and alarm system for temperature and humidity, which is applied to the shell drying chamber of single crystal turbine blades; characterized in that: The system includes a main controller and an alarm; wherein, The main controller is used to calculate the temperature load in the drying chamber according to the shell drying heat transfer model, and calculate the first working parameter of the temperature controller according to the temperature load; and calculate the humidity load according to the shell drying mass transfer model, and calculate the second working parameter of the humidity controller according to the humidity load; control the temperature controller to adjust the temperature in the drying chamber based on the first working parameter, and control the humidity controller to adjust the temperature in the drying chamber based on the second working parameter; The alarm is used to perform statistical calculations on the average temperature deviation and the average humidity deviation within a set period, and output an alarm signal if the average temperature deviation is greater than a first threshold and / or the average humidity deviation is greater than a second threshold; The shell drying heat transfer model is as follows: Ignoring the internal temperature gradient, the overall energy balance equation is as follows: ； in: - temperature load; ——heat capacity of coating, kJ / (kg*K); ——weight of paint, kg; ——Difference between paint temperature and indoor temperature, K / s; ——The latent heat of evaporation of water is 2448.6 kJ / kg; ——mass loss rate, kg / s; The shell drying mass transfer model is as follows: The evaporation mass flow rate of water is expressed as follows: （1） in: ——water mass, kg; ——surface area, m; ——mass transfer coefficient related to wind speed, kg / (N*s); ——Saturated vapor pressure at coating temperature T, Pa; ——Ambient vapor pressure, Pa; （2） in: ——sand hanging amount, g; H——the thickness of the coating, mm; ——Density of coating, kg / m 3 ; Combining formulas (1) and (2) yields: 。 2. The intelligent real-time monitoring and alarm system for temperature and humidity according to claim 1 is characterized in that: The moisture load is calculated according to the shell drying mass transfer model, including: 1) Calculation of moisture dissipation of mold shell The moisture dissipation of the shell is calculated based on the number of shells in the drying chamber and the moisture dissipation rate of a single shell; 2) Outdoor intrusive moisture load Since the working shutter door of the drying chamber is opened during operation, a large amount of air outside the drying chamber will enter the drying chamber, and the amount of moisture brought in is calculated by the following formula: (5) Where: ——The humidity of the air outside the drying chamber, here is based on actual measurement =10.46 g / kg; ——humidity content of air in drying chamber, g / kg; G ——the amount of air entering when the outer door is opened, kg / h; D —— shell moisture load, kg / h; The humidity load is obtained by adding the moisture dissipated by the mold shell to the moisture brought in.

3. The intelligent real-time monitoring and alarm system for temperature and humidity according to claim 2 is characterized in that: The step of controlling the temperature controller to adjust the temperature in the drying chamber based on the first working parameter, and controlling the humidity controller to adjust the temperature in the drying chamber based on the second working parameter, comprises: The first working parameter and the second working parameter are input into a temperature and humidity control model, and the temperature and humidity control model performs multiple iterations to control the temperature and humidity in the drying chamber based on a preset temperature and a preset humidity; Wherein, the temperature and humidity control model is a PID controller or a controller based on a machine learning algorithm.

4. The intelligent real-time monitoring and alarm system for temperature and humidity according to claim 3 is characterized in that: If the temperature average deviation is greater than a first threshold value and / or the humidity average deviation is greater than a second threshold value, outputting an alarm signal includes: Acquire historical preparation records of the mold shell, extract various historical data of quality defects from the historical preparation records, determine the mold shell preparation stage to which each historical data belongs, and count a first quantity of the historical data of each preparation stage; Determine the first quantity corresponding to the current shell preparation stage, obtain an adjustment coefficient based on the matching of the quantity and the first negative correlation relationship, use the adjustment coefficient to adjust and optimize the first threshold and the second threshold, and obtain a third threshold and a fourth threshold respectively.

5. The intelligent real-time monitoring and alarm system for temperature and humidity according to claim 4 is characterized in that: The set period is determined by: A second number of the mold shells in the drying chamber is counted, and the set period is calculated according to the second number and a second negative correlation relationship.

6. An electronic device, characterized in that: An intelligent real-time temperature and humidity monitoring and alarm system applied to any one of claims 1-5, comprising: a memory storing executable program code; a processor coupled to the memory; and the processor calling the executable program code stored in the memory.

7. A computer storage medium, characterized in that: An intelligent real-time temperature and humidity monitoring and alarm system applied to any one of claims 1-5, wherein a computer program is stored on the storage medium.

8. A computer program product, characterized in that: An intelligent real-time temperature and humidity monitoring and alarm system applied to any one of claims 1 to 5, wherein the computer program product includes a computer program stored in a computer storage medium.

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