Resistance furnace temperature intelligent control system based on Internet of Things

Abstract

The invention relates to the technical field of resistance furnace temperature control, in particular to a resistance furnace temperature intelligent control system based on Internet of Things, which comprises a data acquisition module used for acquiring resistance furnace data, heating device data and environment temperature; the stage division module is used for dividing heating stages according to the collected hearth temperature of the resistance furnace and the temperature threshold value of each stage; the power control module is used for controlling the heating power of each heating stage; the temperature monitoring module is used for analyzing the temperature rise state of the resistance furnace and adjusting the control process of the heating power of each heating stage according to an analysis result; the abnormity analysis module is used for analyzing the temperature state of the resistance furnace and optimizing the adjustment process of the heating power in the next management period according to an analysis result; and the thickness analysis module is used for evaluating the insulation performance of the resistance furnace and adjusting the analysis process of the temperature state of the resistance furnace according to an evaluation result. The temperature control efficiency of the resistance furnace is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of resistance furnace temperature control, and in particular to an intelligent temperature control system for a resistance furnace based on the Internet of Things. Background Art

[0002] In the traditional resistance furnace heating process, temperature control often relies on manual monitoring and experience settings, making it difficult to achieve precise temperature control and real-time feedback. This method has problems such as time response lag, heat loss, and uneven temperature, which can easily lead to uneven heating of materials and affect the quality of the final product. At the same time, with the promotion of industrial automation and intelligent manufacturing, Internet of Things technology has become an important means of modern industrial management. Through real-time data collection and analysis, the temperature control system has become more precise and intelligent. Therefore, the resistance furnace temperature intelligent control system based on the Internet of Things realizes comprehensive monitoring and intelligent adjustment of the resistance furnace heating process, improves production efficiency and product quality, and better meets the temperature control needs of modern manufacturing equipment.

[0003] Chinese patent publication number CN105607671A discloses a method for automatic temperature control of a resistance furnace based on a queue model. It includes the following steps: (1) uniform grouping, all heating devices in a single resistance furnace are divided into N groups according to heating power, any group of heating devices are connected to the power supply through a switch device, and all switch devices are controlled by a control device; (2) define the set temperature input from the control device as Tset, and define the measured temperature collected from the control device as Tact; (3) calculate the number of groups of heating devices required to be put into or cut off, when Tact<Tset, define the number of groups of heating devices required to be put into or cut off as B, when Tact>Tset, define the number of groups of heating devices required to be cut off as E; (4) put in or cut off the heating devices; It can be seen that this scheme only analyzes the temperature inside the resistance furnace, and does not analyze other factors such as heating devices, and there is a problem of low efficiency in temperature control of the resistance furnace. Summary of the invention

[0004] The object of the present invention is to provide a resistance furnace temperature intelligent control system based on the Internet of Things to solve at least one of the problems existing in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent temperature control system for a resistance furnace based on the Internet of Things, comprising:

[0007] Data acquisition module, used to collect resistance furnace data, heating device data and ambient temperature;

[0008] The stage division module is used to divide the heating stage according to the collected furnace temperature of the resistance furnace and the temperature threshold of each stage;

[0009] The power control module is used to control the heating power of each heating stage according to the collected data of the resistance furnace surface area, the resistance furnace thermal conductivity, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material, the ambient temperature and the division result of the heating stage;

[0010] The temperature monitoring module is used to analyze the heating state of the resistance furnace according to the collected furnace temperature of the resistance furnace and the division results of the heating stages, and adjust the control process of the heating power in each heating stage according to the analysis results;

[0011] The abnormal analysis module is used to analyze the temperature state of the resistance furnace according to the analysis results of the heating state of the resistance furnace in the management cycle, and optimize the adjustment process of the heating power in the next management cycle according to the analysis results;

[0012] The thickness analysis module is used to evaluate the insulation performance of the resistance furnace using the collected thickness of the insulation layer of the resistance furnace, and to adjust the analysis process of the temperature state of the resistance furnace according to the evaluation results.

[0013] Furthermore, the stage division module is used to divide the heating stage according to the collected resistance furnace furnace temperature t0 and the temperature threshold of each stage, and the heating stage includes a low temperature stage, a medium temperature stage and a high temperature stage.

[0014] Furthermore, the power control module includes a first analysis unit for controlling the heating power YP1 in the low temperature stage according to the collected resistance furnace surface area, resistance furnace thermal conductivity, heating device monomer mass, heating device quantity, heating device material specific heat capacity and the first ambient temperature hy1.

[0015] Furthermore, the power control module also includes a second analysis unit, which is used to control the heating power YP2 in the medium temperature stage based on the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device unit, the number of heating devices, the specific heat capacity of the heating device material and the second ambient temperature hy2.

[0016] Furthermore, the power control module also includes a third analysis unit, which is used to control the heating power YP3 in the high temperature stage according to the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material and the third ambient temperature hy3.

[0017] Furthermore, the temperature monitoring module includes a temperature monitoring unit, which is used to analyze the heating state of the resistance furnace according to the collected resistance furnace furnace temperature tj and the division result of the heating stage. The heating state of the resistance furnace includes normal heating in the low temperature stage, high temperature state in the low temperature stage, low temperature state in the low temperature stage, normal heating in the medium temperature stage, high temperature state in the medium temperature stage, low temperature state in the medium temperature stage, normal heating in the high temperature stage, high temperature state in the high temperature stage and low temperature state in the high temperature stage.

[0018] Furthermore, the temperature monitoring module also includes a power adjustment unit, which is used to adjust the heating power of the resistance furnace according to the analysis results of the heating state of the resistance furnace in each heating stage, wherein:

[0019] When the temperature rise state of the resistance furnace is a low temperature stage high temperature state, the power adjustment unit adjusts the heating power in the low temperature stage to YP1';

[0020] When the heating state of the resistance furnace is a low temperature state in the low temperature stage, the power adjustment unit adjusts the heating power in the low temperature stage to YP1”;

[0021] When the temperature rise state of the resistance furnace is a high temperature state in the medium temperature stage, the power adjustment unit adjusts the heating power in the medium temperature stage to YP2';

[0022] When the heating state of the resistance furnace is the low temperature state in the medium temperature stage, the power adjustment unit adjusts the heating power in the medium temperature stage to YP2”;

[0023] When the temperature rise state of the resistance furnace is a high temperature stage high temperature state, the power adjustment unit adjusts the heating power of the high temperature stage to YP3';

[0024] When the temperature rising state of the resistance furnace is a high temperature stage high temperature state, the power adjustment unit adjusts the heating power of the high temperature stage to YP3".

[0025] Furthermore, the abnormal analysis module includes an abnormal analysis unit, which is used to analyze the temperature state of the resistance furnace according to the analysis results of the heating state of the resistance furnace within the management period. The temperature state of the resistance furnace includes a normal state, a high temperature abnormal state, a low temperature abnormal state and a fault state.

[0026] Furthermore, the abnormal analysis module also includes a state adjustment unit, which optimizes the adjustment process of the heating power in the next management cycle according to the analysis results of the temperature state of the resistance furnace within the management cycle. If the temperature state of the resistance furnace is a high-temperature abnormal state, the state adjustment unit optimizes the preset adjustment ratio to β1; if the temperature state of the resistance furnace is a low-temperature abnormal state, the state adjustment unit optimizes the preset adjustment ratio to β2.

[0027] Furthermore, the thickness analysis module is used to compare the collected insulation layer thickness hd1 of the resistance furnace with the preset thickness threshold hd0 to evaluate the insulation performance of the resistance furnace. The insulation performance of the resistance furnace includes normal and abnormal. If the insulation performance of the resistance furnace is abnormal, the preset abnormal proportion is adjusted to u2.

[0028] The beneficial effects of the present invention are as follows: through real-time data collection and analysis, the system can accurately monitor the furnace temperature and environmental changes, and make timely adjustments to the heating process to ensure that the temperature is always maintained within the set value range, thereby reducing product quality problems caused by temperature fluctuations. At the same time, the intelligent power control and dynamic adjustment mechanism can effectively reduce unnecessary heat loss and energy consumption for different heating stages and material properties, so that the energy efficiency of the resistance furnace is significantly improved compared with the traditional control method. Combined with the Internet of Things technology, comprehensive data interaction between equipment and the environment is realized, and intelligent decisions can be made based on real-time data to adapt to different process requirements, thereby improving the flexibility and adaptability of the manufacturing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 This is a schematic diagram of the structure of the intelligent temperature control system of the resistance furnace based on the Internet of Things in this embodiment.

[0031] Figure 2 FIG. 4 is a schematic diagram of the structure of the power control module of this embodiment.

[0032] Figure 3 Schematic diagram of the structure of the temperature monitoring module of this embodiment.

[0033] Figure 4 Schematic diagram of the structure of the abnormality analysis module in this embodiment. DETAILED DESCRIPTION

[0034] In order to more clearly illustrate the present invention, the present invention is further described below in conjunction with preferred embodiments and accompanying drawings. Similar components in the accompanying drawings are represented by the same reference numerals. It should be understood by those skilled in the art that the content specifically described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0035] It should be noted that, although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0036] See also Figure 1 As shown, it is a structural schematic diagram of the intelligent control system of the temperature of the resistance furnace based on the Internet of Things in this embodiment, and the system includes:

[0037] The data acquisition module is used to collect resistance furnace data, heating device data and ambient temperature, wherein the resistance furnace data includes resistance furnace chamber temperature, resistance furnace surface area, resistance furnace thermal conductivity and resistance furnace insulation layer thickness, and the heating device data includes heating device monomer mass, heating device quantity and heating device material specific heat capacity; in this embodiment, no specific limitation is made on the collection method of resistance furnace data, heating device data and ambient temperature, and those skilled in the art can freely set it, as long as the collection requirements of resistance furnace data, heating device data and ambient temperature are met, wherein the resistance furnace chamber temperature and ambient temperature can be collected by temperature sensors, and the resistance furnace surface area, resistance furnace thermal conductivity, resistance furnace insulation layer thickness, heating device monomer mass, heating device quantity and heating device material specific heat capacity can be collected interactively.

[0038] Please continue reading Figure 1 As shown, the system includes a stage division module, which is connected to the data acquisition module, and the stage division module is used to divide the heating stage according to the collected resistance furnace furnace temperature t0 and the temperature threshold of each stage to improve the flexibility and pertinence of heating, wherein:

[0039] If t0≤T1, the stage division module determines that the heating stage is a low temperature stage;

[0040] If T1<t0<T2, the stage division module determines that the heating stage is a medium temperature stage;

[0041] If t0≥T2, the stage division module determines that the heating stage is a high temperature stage; by intelligently dividing the heating process into low temperature, medium temperature and high temperature stages, the flexibility and pertinence of heating are improved, which helps different materials obtain the best characteristics at a specific stage and optimizes the heating time and energy consumption;

[0042] Wherein, T1 is the temperature threshold of the first stage, T2 is the temperature threshold of the second stage, and T1<T2.

[0043] It is understandable that the present embodiment does not specifically limit the setting of the temperature thresholds of each stage, and those skilled in the art can freely set them as long as the value requirements of the temperature thresholds of each stage are met. Among them, the optimal value of T1 is 400°C, and the optimal value of T2 is 800°C.

[0044] Please continue reading Figure 1 As shown, the system also includes a power control module, which is used to control the heating power of each heating stage according to the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material and the ambient temperature.

[0045] See also Figure 2 As shown, the power control module includes:

[0046] The first analysis unit is used to control the heating power YP1 in the low temperature stage according to the collected resistance furnace surface area, resistance furnace thermal conductivity, heating device monomer mass, heating device quantity, heating device material specific heat capacity and the first ambient temperature hy1, so as to accurately control the temperature rise in the low temperature stage, setting:

[0047] YP1={[m×n×cp×(T1-tcx)] / η+h×A×(T1-hy1)} / tx1; The required heating power is obtained by calculation to ensure that the temperature rises steadily at a preset speed, avoid material loss or deformation due to excessively rapid temperature rise, and improve the flexibility and reliability of the overall heating process;

[0048] Among them, m is the mass of the heating device unit, n is the number of heating devices, cp is the specific heat capacity of the heating device material, tcx is the initial temperature of the resistance furnace chamber, h is the thermal conductivity of the resistance furnace, A is the surface area of ​​the resistance furnace, and tx1 is the first preset heating time.

[0049] Specifically, the first ambient temperature in this embodiment is the ambient temperature of the resistance furnace when the resistance furnace does not start heating.

[0050] It is understandable that the present embodiment does not specifically limit the setting of the first preset heating time, and those skilled in the art can freely set it as long as the setting requirements of the first preset heating time are met, wherein the best value of tx1 is 30 minutes.

[0051] Please continue reading Figure 2 As shown, the power control module also includes:

[0052] The second analysis unit is connected to the first analysis unit, and is used to control the heating power YP2 in the medium temperature stage according to the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material and the second ambient temperature hy2, so as to accurately control the temperature rise in the medium temperature stage, and set:

[0053] YP2={[m×n×cp×(T2-T1)] / η+h×A×(T2-hy2)} / tx2; The required heating power is obtained by calculation to ensure that the temperature rises steadily at a preset speed, avoid material loss or deformation due to excessively rapid temperature rise, and improve the flexibility and reliability of the overall heating process;

[0054] Among them, tx2 is the second preset heating time.

[0055] Specifically, the second ambient temperature in this embodiment is the ambient temperature of the resistance furnace when the resistance furnace starts in the medium temperature stage.

[0056] It can be understood that the present embodiment does not specifically limit the setting of the second preset heating time, and those skilled in the art can freely set it as long as the setting requirements of the second preset heating time are met, wherein the optimal value of tx2 is 15min.

[0057] Please continue reading Figure 2 As shown, the power control module also includes:

[0058] The third analysis unit is connected to the second analysis unit, and is used to control the heating power YP3 in the high temperature stage according to the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material and the third ambient temperature hy3, so as to accurately control the temperature rise in the high temperature stage, and set:

[0059] YP3={[m×n×cp×(TY-T2)] / η+h×A×(TY-hy3)} / tx3; The required heating power is obtained by calculation to ensure that the temperature rises steadily at a preset speed, avoid material loss or deformation due to excessively rapid temperature rise, and improve the flexibility and reliability of the overall heating process;

[0060] Among them, tx3 is the third preset heating time, TY is the preset heating temperature, and η is the preset thermal efficiency.

[0061] Specifically, the third ambient temperature described in this embodiment is the ambient temperature of the resistance furnace at the beginning of the high temperature stage.

[0062] It can be understood that, in this embodiment, there is no specific limitation on the setting of the preset thermal efficiency, the third preset heating time and the preset heating temperature. Those skilled in the art can set them freely as long as the setting requirements of the preset thermal efficiency, the third preset heating time and the preset heating temperature are met. Among them, the optimal value of tx3 is 35min, the optimal value of η is 0.8, and the optimal value of TY is 1100°C.

[0063] Please continue reading Figure 1 As shown, the system also includes a temperature monitoring module, which is connected to the power control module. The temperature monitoring module is used to analyze the heating state of the resistance furnace according to the collected furnace temperature of the resistance furnace and the division result of the heating stage, and adjust the heating power according to the analysis result.

[0064] See also Figure 3 As shown, the temperature monitoring module includes a temperature monitoring unit, which is used to analyze the temperature rise state of the resistance furnace according to the collected furnace temperature tj of the resistance furnace and the division result of the heating stage, so as to improve the safety of the operation of the resistance furnace, wherein:

[0065] If it is currently in the low temperature stage, when |tj / [tcx+(T1-tcx)×K1 / tx1]-1|≤α, the temperature monitoring unit determines that the heating state of the resistance furnace is normal heating in the low temperature stage; when tj / [tcx+(T1-tcx)×K1 / tx1]-1>α, the temperature monitoring unit determines that the heating state of the resistance furnace is a high temperature state in the low temperature stage; when 1-tj / [tcx+(T1-tcx)×K1 / tx1]>α, the temperature monitoring unit determines that the heating state of the resistance furnace is a low temperature state in the low temperature stage, K1 is the current heating time in the low temperature stage, and α is the preset error threshold;

[0066] If the current temperature is in the medium temperature stage, when |tj / [T1+(T2-T1)×K2 / tx2]-1|≤α, the temperature monitoring unit determines that the temperature rise state of the resistance furnace is normal temperature rise in the medium temperature stage; when tj / [T1+(T2-T1)×K2 / tx2]-1>α, the temperature monitoring unit determines that the temperature rise state of the resistance furnace is a high temperature state in the medium temperature stage; when 1-tj / [T1+(T2-T1)×K2 / tx2]>α, the temperature monitoring unit determines that the temperature rise state of the resistance furnace is a low temperature state in the medium temperature stage, and K2 is the current heating time in the medium temperature stage;

[0067] If the current stage is high temperature, when |tj / [T2+(TY-T2)×K3 / tx3]-1|≤α, the temperature monitoring unit determines that the heating state of the resistance furnace is normal heating in the high temperature stage; when tj / [T2+(TY-T2)×K3 / tx3]-1>α, the temperature monitoring unit determines that the heating state of the resistance furnace is high temperature state in the high temperature stage; when 1-tj / [T2+(TY-T2)×K3 / tx3]>α, the temperature monitoring unit determines that the heating state of the resistance furnace is low temperature state in the high temperature stage, and K3 is the current heating time in the high temperature stage; by real-time detection of the temperature inside and outside the furnace and the heating device, it is ensured that the system always has the latest temperature data to quickly identify temperature changes, including unexpected heating or cooling conditions, thereby achieving dynamic adjustment.

[0068] It can be understood that the present embodiment does not specifically limit the setting of the preset error threshold, and those skilled in the art can freely set it as long as the value requirement of the preset error threshold is met, wherein the best value of α is 0.05.

[0069] Please continue reading Figure 3 As shown, the temperature monitoring module also includes:

[0070] A power adjustment unit connected to the temperature monitoring unit is used to adjust the heating power of the resistance furnace according to the analysis results of the temperature rise state of the resistance furnace in each heating stage to avoid thermal shock, wherein:

[0071] When the heating state of the resistance furnace is normal heating in the low temperature stage, no adjustment is performed; when the heating state of the resistance furnace is high temperature in the low temperature stage, the power adjustment unit sets the heating power in the low temperature stage to YP1', and sets:

[0072] YP1'=YP1-β×YP1×ln{tj / [tcx+(T1-tcx)×K1 / tx1]-α} / l n2;

[0073] When the heating state of the resistance furnace is the low temperature stage, the power adjustment unit sets the heating power of the low temperature stage to YP1", and sets:

[0074] YP1”=YP1+β×YP1×ln{2-tj / [tcx+(T1-tcx)×K1 / tx1]-α} / l n2;

[0075] When the heating state of the resistance furnace is normal heating in the medium temperature stage, no adjustment is performed; when the heating state of the resistance furnace is high temperature in the medium temperature stage, the power adjustment unit sets the heating power in the medium temperature stage to YP2', and sets:

[0076] YP2'=YP2-β×YP2×ln{tj / [tj / [T1+(T2-T1)×K2 / tx2]-α} / ln2; when the heating state of the resistance furnace is the low temperature state of the medium temperature stage, the power adjustment unit sets the heating power of the medium temperature stage to YP2", and sets:

[0077] YP2”=YP2+β×YP1×ln{2-tj / [T1+(T2-T1)×K2 / tx2]-α} / l n2;

[0078] When the heating state of the resistance furnace is the normal heating state in the high temperature stage, no adjustment is performed; when the heating state of the resistance furnace is the high temperature state in the high temperature stage, the power adjustment unit sets the heating power in the high temperature stage to YP3', and sets:

[0079] YP3'=YP3-β×YP3×ln{tj / [T2+(TY-T2)×K3 / tx3]-α} / l n2;

[0080] When the heating state of the resistance furnace is a high temperature stage, the power adjustment unit sets the heating power of the high temperature stage to YP3", and sets:

[0081] YP3”=YP3+β×YP1×ln{2-tj / [T2+(TY-T2)×K3 / tx3]-α} / l n2;

[0082] By timely adjusting the heating power according to the results of the temperature rise status analysis at different heating stages, we can ensure heating at a moderate temperature, improve product quality, effectively prevent thermal shock caused by over-rapid heating, reduce possible damage to materials, and protect the integrity of the workpiece.

[0083] Among them, β is the preset adjustment ratio.

[0084] It can be understood that the present embodiment does not specifically limit the setting of the preset adjustment ratio, and those skilled in the art can freely set it as long as the setting requirements of the preset adjustment ratio are met, wherein the optimal value of β is 0.2.

[0085] Please continue reading Figure 1 As shown, the system also includes an abnormal analysis module, which is connected to the temperature monitoring module. The abnormal analysis module is used to analyze the temperature state of the resistance furnace according to the analysis results of the heating state of the resistance furnace within the management cycle, and optimize the adjustment process of the heating power of the next management cycle according to the analysis results. In this embodiment, there is no specific limitation on the setting of the management cycle, and technical personnel in this field can set it freely, as long as the setting requirements of the management cycle are met. Among them, the management cycle can be set to 5 days, 7 days, etc. In this embodiment, the management cycle is 5 days.

[0086] See also Figure 3 As shown, the abnormality analysis module includes:

[0087] The abnormality analysis unit is used to analyze the temperature state of the resistance furnace according to the analysis results of the temperature rise state of the resistance furnace within the management period, wherein:

[0088] If (i 1+i2+i3) / i0≤u1 and (i4+i5+i6) / i0≤u1, the abnormality analysis unit determines that the temperature state of the resistance furnace is normal;

[0089] If (i1+i2+i3) / i0≤u1 and (i4+i5+i6) / i0>u1, the abnormality analysis unit determines that the temperature state of the resistance furnace is a high temperature abnormal state;

[0090] If (i1+i2+i3) / i0>u1 and (i4+i5+i6) / i0≤u1, the abnormality analysis unit determines that the temperature state of the resistance furnace is a low temperature abnormal state;

[0091] If (i 1+i2+i3) / i0>u1 and (i4+i5+i6) / i0>u1, the abnormality analysis unit determines that the temperature state of the resistance furnace is a fault state and sends a fault warning to the user; by collecting data within the management cycle, analyzing and identifying abnormal states, timely responding to reduce losses and improve the temperature control efficiency of the resistance furnace;

[0092] Among them, i1 is the duration of the temperature rising state of the resistance furnace in the low temperature stage during the management period, i2 is the duration of the temperature rising state of the resistance furnace in the medium temperature stage during the management period, i3 is the duration of the temperature rising state of the resistance furnace in the high temperature stage during the management period, i4 is the duration of the temperature rising state of the resistance furnace in the low temperature stage during the management period, i5 is the duration of the temperature rising state of the resistance furnace in the medium temperature stage during the management period, i6 is the duration of the temperature rising state of the resistance furnace in the high temperature stage during the management period, i0 is the duration of the management period, and u1 is the preset abnormality proportion.

[0093] It can be understood that the present embodiment does not specifically limit the setting of the preset abnormality ratio, and those skilled in the art can freely set it as long as the setting requirements of the preset abnormality ratio are met, wherein the best value of u1 is 0.06.

[0094] Please continue reading Figure 4 As shown, the abnormal analysis module also includes:

[0095] A state adjustment unit is connected to the abnormality analysis unit, and the state adjustment unit optimizes the adjustment process of the heating power in the next management cycle according to the analysis result of the temperature state of the resistance furnace in the management cycle, wherein:

[0096] If the temperature state of the resistance furnace is normal or faulty, no adjustment is performed;

[0097] If the temperature state of the resistance furnace is in an abnormally high temperature state, the state adjustment unit sets the preset adjustment ratio to β1, setting:

[0098] β1=β×exp{u1-(i4+i5+i6) / i0};

[0099] If the temperature state of the resistance furnace is in a low temperature abnormal state, the state adjustment unit sets the preset adjustment ratio to β2, setting:

[0100] β2=β×{1+exp{3×[(i 1+i2+i 3) / i 0-u1]-3}}; By flexibly adjusting the power output according to the temperature state of the resistance furnace (normal state, high temperature abnormality, low temperature abnormality, etc.), unnecessary energy consumption can be effectively reduced, while keeping the heating power within the efficient use range. This energy efficiency optimization not only saves costs but also reduces environmental impact.

[0101] Please continue reading Figure 1 As shown, the system further includes a thickness analysis module, which is connected to the abnormality analysis module, and the thickness analysis module is used to compare the collected thickness hd1 of the insulation layer of the resistance furnace with the preset thickness threshold hd0 to evaluate the insulation performance of the resistance furnace, and adjust the analysis process of the temperature state of the resistance furnace according to the evaluation result to ensure the thermal efficiency and safety of the furnace body, wherein:

[0102] If hd1≤hd0, the thickness analysis module determines that the insulation performance of the resistance furnace is abnormal, and sets the preset abnormal proportion to u2, setting u2=u1×{1-exp[lg(hd0-hd1) / hd0]};

[0103] If hd1>hd0, the thickness analysis module determines that the insulation performance of the resistance furnace is normal and no adjustment is made; by real-time monitoring of the thickness of the insulation layer, it is determined whether it meets the performance requirements to ensure the thermal efficiency and safety of the furnace body. By analyzing the status of the insulation layer, maintenance and replacement decisions can be made in a timely manner to prevent energy loss due to insulation failure, improve the thermal efficiency of the overall system, and reduce energy consumption.

[0104] It can be understood that, in this embodiment, no specific limitation is imposed on the setting of the preset thickness threshold, and those skilled in the art can freely set it as long as the value requirement of the preset thickness threshold is met, wherein the best value of hd0 is 80 mm.

[0105] Specifically, the system described in this embodiment is used to heat metal materials such as steel, aluminum alloy, etc., to ensure uniform temperature distribution during the heating process and to improve the mechanical properties of the metal materials.

[0106] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. An intelligent temperature control system for a resistance furnace based on the Internet of Things, characterized in that: include: Data acquisition module, used to collect resistance furnace data, heating device data and ambient temperature; The stage division module is used to divide the heating stage according to the collected furnace temperature of the resistance furnace and the temperature threshold of each stage; The power control module is used to control the heating power of each heating stage according to the collected data of the resistance furnace surface area, the resistance furnace thermal conductivity, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material, the ambient temperature and the division result of the heating stage; The temperature monitoring module is used to analyze the heating state of the resistance furnace according to the collected furnace temperature of the resistance furnace and the division results of the heating stages, and adjust the control process of the heating power in each heating stage according to the analysis results; The abnormal analysis module is used to analyze the temperature state of the resistance furnace according to the analysis results of the heating state of the resistance furnace in the management cycle, and optimize the adjustment process of the heating power in the next management cycle according to the analysis results; The thickness analysis module is used to evaluate the insulation performance of the resistance furnace using the collected thickness of the insulation layer of the resistance furnace, and to adjust the analysis process of the temperature state of the resistance furnace according to the evaluation results.

2. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 1 is characterized in that: The stage division module is used to divide the heating stage according to the collected resistance furnace furnace temperature t0 and the temperature threshold of each stage, and the heating stage includes a low temperature stage, a medium temperature stage and a high temperature stage.

3. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 2 is characterized in that: The power control module includes a first analysis unit for controlling the heating power YP1 in the low temperature stage according to the collected resistance furnace surface area, resistance furnace thermal conductivity, heating device monomer mass, heating device quantity, heating device material specific heat capacity and the first ambient temperature hy1.

4. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 3 is characterized in that: The power control module also includes a second analysis unit, which is used to control the heating power YP2 in the medium temperature stage according to the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device unit, the number of heating devices, the specific heat capacity of the heating device material and the second ambient temperature hy2.

5. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 4 is characterized in that: The power control module also includes a third analysis unit, which is used to control the heating power YP3 in the high temperature stage according to the collected surface area of ​​the resistance furnace, the thermal conductivity of the resistance furnace, the mass of the heating device monomer, the number of heating devices, the specific heat capacity of the heating device material and the third ambient temperature hy3.

6. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 5 is characterized in that: The temperature monitoring module includes a temperature monitoring unit, which is used to analyze the heating state of the resistance furnace according to the collected resistance furnace furnace temperature tj and the division result of the heating stage. The heating state of the resistance furnace includes normal heating in the low temperature stage, high temperature state in the low temperature stage, low temperature state in the low temperature stage, normal heating in the medium temperature stage, high temperature state in the medium temperature stage, low temperature state in the medium temperature stage, normal heating in the high temperature stage, high temperature state in the high temperature stage and low temperature state in the high temperature stage.

7. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 6 is characterized in that: The temperature monitoring module also includes a power adjustment unit, which is used to adjust the heating power of the resistance furnace according to the analysis results of the heating state of the resistance furnace in each heating stage, wherein: When the temperature rise state of the resistance furnace is a low temperature stage high temperature state, the power adjustment unit adjusts the heating power in the low temperature stage to YP1'; When the heating state of the resistance furnace is a low temperature state in the low temperature stage, the power adjustment unit adjusts the heating power in the low temperature stage to YP1”; When the temperature rise state of the resistance furnace is a high temperature state in the medium temperature stage, the power adjustment unit adjusts the heating power in the medium temperature stage to YP2'; When the heating state of the resistance furnace is the low temperature state in the medium temperature stage, the power adjustment unit adjusts the heating power in the medium temperature stage to YP2”; When the temperature rise state of the resistance furnace is a high temperature stage high temperature state, the power adjustment unit adjusts the heating power of the high temperature stage to YP3'; When the temperature rising state of the resistance furnace is a high temperature stage high temperature state, the power adjustment unit adjusts the heating power of the high temperature stage to YP3".

8. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 7 is characterized in that: The abnormality analysis module includes an abnormality analysis unit, which is used to analyze the temperature state of the resistance furnace according to the analysis result of the temperature rise state of the resistance furnace within the management period. The temperature state of the resistance furnace includes a normal state, a high temperature abnormal state, a low temperature abnormal state and a fault state.

9. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 8 is characterized in that: The abnormal analysis module also includes a state adjustment unit, which optimizes the adjustment process of the heating power in the next management cycle according to the analysis result of the temperature state of the resistance furnace within the management cycle. If the temperature state of the resistance furnace is a high-temperature abnormal state, the state adjustment unit optimizes the preset adjustment ratio to β1; if the temperature state of the resistance furnace is a low-temperature abnormal state, the state adjustment unit optimizes the preset adjustment ratio to β2.

10. The intelligent temperature control system of a resistance furnace based on the Internet of Things according to claim 9 is characterized in that: The thickness analysis module is used to compare the collected insulation layer thickness hd1 of the resistance furnace with the preset thickness threshold hd0 to evaluate the insulation performance of the resistance furnace. The insulation performance of the resistance furnace includes normal and abnormal. If the insulation performance of the resistance furnace is abnormal, the preset abnormal proportion is adjusted to u2.

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