A high temperature dryer equipment intelligent monitoring method and system

Abstract

The present application discloses an intelligent monitoring method and system for high-temperature drying equipment, which relates to the field of high-temperature drying technology. In the present invention, a weighing platform weighs the high-temperature drying machine and the materials therein, and a data analysis and processing module calculates the thermal efficiency η of the drying machine according to the input material temperature and material quality data, and obtains the weighted average value η of the corrected thermal efficiency through correction and weighted average calculation. avg , when η avg Lower than η original When the data analysis and processing module detects that the temperature in the early warning monitoring area is higher than the alarm threshold temperature, the high temperature early warning information is sent to the high temperature alarm for a high temperature alarm.

Description

Technical Field

[0001] The present application relates to the field of high-temperature drying technology, and in particular to an intelligent monitoring method for high-temperature drying equipment. Background Art

[0002] With the rapid development of industrial production, high temperature dryers, as an important production equipment, have been widely used in the fields of food, chemical industry, metallurgy, etc. High temperature dryers evaporate the moisture in the materials by exposing them to high temperature and using heat conduction and radiation to achieve the purpose of drying.

[0003] The high temperature dryer is mainly composed of a heater, a drying chamber, a ventilation system, a control system and other parts. When working, the heater generates high temperature heat, and the hot air is sent into the drying chamber through the ventilation system to exchange heat with the material and evaporate the moisture in the material. At the same time, the control system monitors and adjusts the temperature, humidity, wind speed and other parameters in the drying process in real time to ensure the drying effect and the safety of equipment operation.

[0004] CN202211210682.X discloses an automatic control method and system for a dryer, the method comprising: depressurizing the interior of the dryer to a first preset pressure value, charging the interior of the dryer with regeneration gas to a preset charging pressure value; performing low-temperature purge on the interior of the dryer according to a preset low-temperature purge time, and performing constant-temperature purge on the interior of the dryer according to a preset constant-temperature purge time and a preset constant-temperature purge temperature; heating the interior of the dryer to a preset heating temperature and maintaining the temperature for a set time, cooling the interior of the dryer to a preset temperature, and the system comprises a data acquisition module, a processing module, and a control module. The present invention first performs low-temperature purge before high-temperature purge and high-temperature heating, so that hydrocarbon impurities in the bed can be removed from the dryer first, so as to prevent direct high-temperature heating from generating coking in the equipment, thereby affecting the service life of the dryer.

[0005] There are two major problems that need to be solved urgently in the automatic control method and system of a dryer disclosed in CN202211210682.X and the existing high-temperature dryer control method: one is that the thermal efficiency cannot be monitored in real time, resulting in the inability to determine whether the high-temperature dryer is in a normal working state; the second is the lack of an effective fire warning system. Once a fire occurs, it will cause serious losses to the manufacturer, employees and property. Therefore, in the existing high-temperature dryer technology, thermal efficiency monitoring and fire warning systems are often ignored or not designed well.

[0006] For thermal efficiency monitoring, most dryers only make rough judgments based on simple temperature parameters, which cannot achieve real-time monitoring and accurate judgment of thermal efficiency. This results in that even if a dryer fails during the actual production process, it cannot be detected in time, resulting in problems such as low drying efficiency.

[0007] In terms of fire warning, traditional dryers usually lack an effective warning system and can only rely on manual inspections or simple temperature alarms. This method is not only inefficient, but also easy to miss fire hazards and fail to detect and deal with fire accidents in time. Once a fire occurs, it will cause huge losses to production and even threaten the lives of employees.

[0008] To this end, the present invention provides a method and system for intelligent monitoring of high-temperature dryer equipment. Summary of the invention

[0009] Technical issues solved

[0010] In view of the shortcomings of the prior art, the present invention provides an intelligent monitoring method for high-temperature dryer equipment, which captures the real-time information of material temperature and quality, combines data processing technology, analyzes and calculates the data through data processing technology, thereby obtaining the thermal efficiency of the dryer and realizing real-time monitoring of the thermal efficiency of the dryer. A far-infrared thermal imager is used to monitor the early warning area. Once the temperature is found to be too high, the system will immediately start the alarm program to remind the user to deal with it in time to reduce the losses caused by the fire.

[0011] Technical Solution

[0012] To achieve the above objectives, the present invention is implemented through the following technical solutions: A high-temperature dryer equipment intelligent monitoring method, comprising the following steps:

[0013] a. Capture the temperature of the material inside the high-temperature dryer and weigh the mass of the material inside the high-temperature dryer at this time. The data analysis and processing module calculates the thermal efficiency η of the dryer at this time according to the input material temperature and material mass;

[0014] b. After calculating the thermal efficiency η of the dryer at this time, the data analysis and processing module corrects the thermal efficiency η according to the thermal efficiency correction coefficient α to obtain the corrected thermal efficiency η corrected , the correction formula is: η corrected =α×η; During the drying process, the temperature and mass of the material inside the high-temperature dryer at different time points are repeatedly captured, and the corrected thermal efficiency η is calculated multiple times corrected Then the data analysis and processing module calculates the η obtained by multiple calculations. corrected Perform weighted averaging to obtain the weighted average value of the corrected thermal efficiency η avg ;

[0015] c. The obtained η avg Compared with the original thermal efficiency η of the high temperature dryer when it leaves the factory original In contrast, when η avg Lower than η originalWhen the data analysis and processing module determines that the high-temperature dryer is in an abnormal working state, the device alarm information is sent to the device alarm to alarm the device for equipment failure;

[0016] d. Set the drying operation area as the early warning monitoring area, capture the infrared radiation energy distribution diagram of the early warning monitoring area in real time, form an infrared thermal image of the early warning monitoring area, and input it into the data analysis and processing module; when the data analysis and processing module detects that the temperature of the early warning monitoring area is higher than the alarm threshold temperature, the high temperature warning information is sent to the high temperature alarm for high temperature alarm.

[0017] Preferably, in the above-mentioned intelligent monitoring method for high-temperature dryer equipment, in step b, the thermal efficiency η is calculated as:

[0018] η = (Q out / Q in ) × 100%.

[0019] Where: Q out It is the heat corresponding to the water lost by the material during the drying process, Q out The calculation formula is: Q out =m water × C water × (T out -T initial ), where m water is the mass of water lost, m water The calculation formula is: water =m initial -m out , m initial is the initial mass of the material, m out is the current quality of the material; C water is the specific heat capacity of water, T out is the current material temperature, T initial is the initial temperature of the material; Q in is the input heat; Q in Converted from electrical energy, the calculation formula is: Q in = P × t, where P is the power of the electric heater in the high-temperature dryer and t is the heating time.

[0020] Preferably, in the above-mentioned intelligent monitoring method for high temperature dryer equipment,

[0021] In step b, the thermal efficiency correction factor α = ;

[0022] in is the ambient temperature correction factor; ,in It is an adjustment factor used to adjust the rate of performance degradation. The value range of α is 1-2 and is set according to the actual situation of the device. = 1 - (ΔT × β), where ΔT is the difference between the actual ambient temperature and the reference ambient temperature, ΔT = actual ambient temperature - reference ambient temperature, and β is the influence coefficient, which is 0.5%.

[0023] Preferably, in the above-mentioned intelligent monitoring method for high-temperature dryer equipment, in step b, the thermal efficiency is calculated once every 15 minutes, for a total of 5 times, and the η obtained by the 5 calculations is corrected Perform weighted averaging to obtain the weighted average value of the corrected thermal efficiency η avg , the calculation formula is:

[0024] ;

[0025] in, are the corrected thermal efficiencies calculated for the 1st to 5th times respectively; w1, w2, w3, w4, and w5 are The weight values ​​are, and w1=0.2, w2=0.15, w3=0.18, w4=0.32, w5=0.15.

[0026] Preferably, in the above-mentioned intelligent monitoring method for high-temperature dryer equipment, in step d, data of multiple temperature points in the early warning monitoring area are captured in real time, the weighted average temperature is used as an evaluation index, and the alarm triggering condition is defined;

[0027] The calculation formula of weighted average temperature WAT is as follows:

[0028]

[0029] T i is the temperature value of the i-th temperature point in the drying operation area, w i is the weight associated with the ith temperature point, N is the total number of temperature points in the drying operation area; when WAT is higher than the alarm threshold temperature T threshold When an alarm is sounded.

[0030] Preferably, in the above-mentioned intelligent monitoring method for high-temperature dryer equipment, data of five temperature zones in the early warning monitoring area are captured, and the five temperature zones are respectively the dryer drive motor installation area , High temperature material accumulation area , Electrical equipment area 、Line area , Poor ventilation and heat dissipation areas , and their weights are ,and ; Calculated using the weighted average temperature formula: ;

[0031] The calculated weighted average temperature WAT is compared with compare, exceed Then the alarm is triggered.

[0032] Preferably, in the above-mentioned intelligent monitoring method for high-temperature dryer equipment, in step a, the temperature of the material inside the high-temperature dryer is captured by a non-contact temperature measuring instrument; the high-temperature dryer is placed on a weighing platform, the weighing platform weighs the high-temperature dryer and the material inside, and then the mass of the high-temperature dryer is subtracted to obtain the current material mass.

[0033] Preferably, in the above-mentioned intelligent monitoring method for high-temperature dryer equipment, the infrared radiation energy distribution pattern of the early warning monitoring area is captured in real time by an infrared thermal imager to form an infrared thermal image of the early warning monitoring area.

[0034] A high-temperature dryer equipment intelligent monitoring system includes a non-contact temperature measuring instrument, a weighing platform, a data analysis and processing module, an equipment alarm, and a high-temperature alarm. The non-contact temperature measuring instrument captures the temperature of the material inside the high-temperature dryer. The weighing platform weighs the high-temperature dryer and the material inside. The data analysis and processing module calculates the thermal efficiency η of the dryer at this time according to the input material temperature and material mass. The weighted average value η of the corrected thermal efficiency is obtained through correction and weighted average calculation. avg , when η avg Lower than η original When the data analysis and processing module detects that the temperature in the early warning monitoring area is higher than the alarm threshold temperature, the high temperature early warning information is sent to the high temperature alarm for a high temperature alarm.

[0035] (III) Beneficial effects

[0036] The present invention provides a high-temperature dryer equipment intelligent monitoring method and system, which has the following beneficial effects:

[0037] Thermal efficiency monitoring: By capturing real-time information on material temperature and quality, combined with data processing technology, the data is analyzed and calculated through data processing technology to obtain the thermal efficiency of the dryer, realize real-time monitoring of the thermal efficiency of the dryer, and discover equipment failures in time, thereby improving energy utilization efficiency, reducing production costs, and ensuring the stability of the drying process.

[0038] Fire warning: Use far-infrared thermal imagers to monitor the warning area. Once the temperature is found to be too high, the system will immediately start the alarm program to remind users to deal with it in time, greatly improving production safety and reducing losses caused by fire accidents.

[0039] The use of non-contact temperature measuring instrument and weighing platform can obtain the temperature and total mass of the material inside the high-temperature dryer in real time and accurately, providing a reliable basis for subsequent data analysis and processing. Through the data analysis and processing module, the thermal efficiency of the dryer can be automatically calculated, and correction and weighted average calculation can be performed to obtain the weighted average value of the corrected thermal efficiency; this intelligent monitoring can greatly improve the efficiency and accuracy of monitoring. When the weighted average value of the thermal efficiency is lower than the original thermal efficiency, the system can automatically determine that the high-temperature dryer is in an abnormal working state and send an alarm message. This helps to timely discover and handle equipment failures, avoid production interruptions and material waste. When the temperature in the early warning monitoring area is higher than the alarm threshold temperature, the system will send a high temperature early warning message. This early warning function can remind the operator to take measures in time. Through real-time monitoring and intelligent analysis, it can ensure that the high-temperature dryer is always operating in a normal state, thereby improving production efficiency and product quality. The use of intelligent monitoring in the present invention can reduce dependence on manual operation, reduce the risk of human error, and reduce the workload of operators. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The present invention is a flowchart of an intelligent monitoring method for high-temperature dryer equipment. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 The present invention provides a high-temperature dryer equipment intelligent monitoring method, comprising the following steps:

[0043] a. Capture the temperature of the material inside the high-temperature dryer and weigh the mass of the material inside the high-temperature dryer at this time. The data analysis and processing module calculates the thermal efficiency η of the dryer at this time according to the input material temperature and material mass;

[0044] b. After calculating the thermal efficiency η of the dryer at this time, the data analysis and processing module corrects the thermal efficiency η according to the thermal efficiency correction coefficient α to obtain the corrected thermal efficiency η corrected , the correction formula is: η corrected =α×η; During the drying process, the temperature and mass of the material inside the high-temperature dryer at different time points are repeatedly captured, and the corrected thermal efficiency η is calculated multiple times corrected Then the data analysis and processing module calculates the η obtained by multiple calculations. correctedPerform weighted averaging to obtain the weighted average value of the corrected thermal efficiency η avg ;

[0045] c. The obtained η avg Compared with the original thermal efficiency η of the high temperature dryer when it leaves the factory original In contrast, when η avg Lower than η original When the data analysis and processing module determines that the high-temperature dryer is in an abnormal working state, the device alarm information is sent to the device alarm to alarm the device for equipment failure;

[0046] d. Set the drying operation area as the early warning monitoring area, capture the infrared radiation energy distribution diagram of the early warning monitoring area in real time, form an infrared thermal image of the early warning monitoring area, and input it into the data analysis and processing module; when the data analysis and processing module detects that the temperature of the early warning monitoring area is higher than the alarm threshold temperature, the high temperature warning information is sent to the high temperature alarm for high temperature alarm.

[0047] In order to further optimize the above technical solution, in step b, the thermal efficiency η is calculated as follows:

[0048] η = (Q out / Q in ) × 100%.

[0049] Where: Q out It is the heat corresponding to the water lost by the material during the drying process, Q out The calculation formula is: Q out =m water × C water × (T out -T initial ), where m water is the mass of water lost, m water The calculation formula is: water =m initial -m out , m initial is the initial mass of the material, m out is the current quality of the material; C water is the specific heat capacity of water, T out is the current material temperature, T initial is the initial temperature of the material; Q in is the input heat; Q in Converted from electrical energy, the calculation formula is: Q in = P × t, where P is the power of the electric heater in the high-temperature dryer and t is the heating time.

[0050] In order to further optimize the above technical solution, in step b, the thermal efficiency η is calculated as follows:

[0051] η = (Q out / Q in ) × 100%.

[0052] Where: Q out It is the heat corresponding to the water lost by the material during the drying process, Q out The calculation formula is: Q out =m water × C water × (T out -T initial ), where m water is the mass of water lost, m water The calculation formula is: water =m initial -m out , m initial is the initial mass of the material, m out is the current quality of the material; C water is the specific heat capacity of water, T out is the current material temperature, T initial is the initial temperature of the material; Q in is the input heat; Q in Converted from electrical energy, the calculation formula is: Q in = P × t, where P is the power of the electric heater in the high-temperature dryer and t is the heating time.

[0053] In order to further optimize the above technical solution,

[0054] In step b, the thermal efficiency correction factor α = ;

[0055] in is the ambient temperature correction factor; ,in It is an adjustment factor used to adjust the rate of performance degradation. The value range of α is 1-2 and is set according to the actual situation of the device. = 1 - (ΔT × β), where ΔT is the difference between the actual ambient temperature and the reference ambient temperature, ΔT = actual ambient temperature - reference ambient temperature, and β is the influence coefficient, which is 0.5%.

[0056] In order to further optimize the above technical solution, in step b, the thermal efficiency is calculated once every 15 minutes, for a total of 5 times, and the η obtained from the 5 calculations is corrected Perform weighted averaging to obtain the weighted average value of the corrected thermal efficiency ηavg , the calculation formula is:

[0057] ;

[0058] in, are the corrected thermal efficiencies calculated for the 1st to 5th times respectively; w1, w2, w3, w4, and w5 are The weight values ​​are, and w1=0.2, w2=0.15, w3=0.18, w4=0.32, w5=0.15.

[0059] In order to further optimize the above technical solution, in step d, the data of multiple temperature points in the early warning monitoring area are captured in real time, the weighted average temperature is used as the evaluation index, and the alarm triggering conditions are defined;

[0060] The calculation formula of weighted average temperature WAT is as follows:

[0061]

[0062] T i is the temperature value of the i-th temperature point in the drying operation area, w i is the weight associated with the ith temperature point, N is the total number of temperature points in the drying operation area; when WAT is higher than the alarm threshold temperature T threshold When an alarm is sounded.

[0063] In order to further optimize the above technical solution, the data of 5 temperature zones in the early warning monitoring area are captured. The 5 temperature zones are the dryer drive motor installation area , High temperature material accumulation area , Electrical equipment area 、Line area , Poor ventilation and heat dissipation areas , and their weights are ,and ; Calculated using the weighted average temperature formula: ;

[0064] The calculated weighted average temperature WAT is compared with compare, exceed Then the alarm is triggered.

[0065] In order to further optimize the above technical solution, in step a, the temperature of the material inside the high-temperature dryer is captured by a non-contact temperature measuring instrument; the high-temperature dryer is placed on a weighing platform, the weighing platform weighs the high-temperature dryer and the material inside, and then the mass of the high-temperature dryer is subtracted to obtain the current material mass.

[0066] In order to further optimize the above technical solution, the infrared radiation energy distribution diagram of the early warning monitoring area is captured in real time by an infrared thermal imager to form an infrared thermal image of the early warning monitoring area.

[0067] A high-temperature dryer equipment intelligent monitoring system includes a non-contact temperature measuring instrument, a weighing platform, a data analysis and processing module, an equipment alarm, and a high-temperature alarm. The non-contact temperature measuring instrument captures the temperature of the material inside the high-temperature dryer. The weighing platform weighs the high-temperature dryer and the material inside. The data analysis and processing module calculates the thermal efficiency η of the dryer at this time according to the input material temperature and material mass. The weighted average value η of the corrected thermal efficiency is obtained through correction and weighted average calculation. avg , when η avg Lower than η original When the data analysis and processing module detects that the temperature in the early warning monitoring area is higher than the alarm threshold temperature, the high temperature early warning information is sent to the high temperature alarm for a high temperature alarm.

[0068] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center containing one or more available media sets.

[0069] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0070] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0071] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only some logical function divisions. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0072] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0073] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0074] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U Disk, mobile hard disk, read-only memory ( read - onlymemory , ROM ), Random Access Memory ( RandomAccessMemory , RAM ), magnetic disks, optical disks, and other media that can store program codes.

[0075] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0076] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A high temperature dryer equipment intelligent monitoring method, characterized in that: The following steps are involved: a. Capture the temperature of the material inside the high-temperature dryer and weigh the mass of the material inside the high-temperature dryer at this time. The data analysis and processing module calculates the thermal efficiency η of the dryer at this time according to the input material temperature and material mass; b. After calculating the thermal efficiency η of the dryer at this time, the data analysis and processing module corrects the thermal efficiency η according to the thermal efficiency correction coefficient α to obtain the corrected thermal efficiency η corrected , the correction formula is: η corrected =α×η; During the drying process, the temperature and mass of the material inside the high-temperature dryer at different time points are repeatedly captured, and the corrected thermal efficiency η is calculated multiple times corrected Then the data analysis and processing module calculates the η obtained by multiple calculations. corrected Perform weighted averaging to obtain the weighted average value of the corrected thermal efficiency η avg ; c. The obtained η avg Compared with the original thermal efficiency η of the high temperature dryer when it leaves the factory original In contrast, when η avg Lower than η original When the data analysis and processing module determines that the high-temperature dryer is in an abnormal working state, the device alarm information is sent to the device alarm to alarm the device for equipment failure; d. Set the drying operation area as the early warning monitoring area, capture the infrared radiation energy distribution diagram of the early warning monitoring area in real time, form an infrared thermal image of the early warning monitoring area, and input it into the data analysis and processing module; When the data analysis and processing module detects that the temperature in the early warning monitoring area is higher than the alarm threshold temperature, the high temperature warning information is sent to the high temperature alarm for high temperature alarm; In step b, the thermal efficiency η is calculated as: η = (Q out / Q in ) × 100%; Where: Q out It is the heat corresponding to the moisture lost by the material during the drying process, Q out The calculation formula is: Q out = m water × C water × (T out -T initial ), where m water is the mass of water lost, m water The calculation formula is: water =m initial -m out , m initial is the initial mass of the material, m out is the current quality of the material; C water is the specific heat capacity of water, T out is the current material temperature, T initial is the initial temperature of the material; Q in is the input heat; Q in Converted from electrical energy, the calculation formula is: Q in = P × t, where P is the power of the electric heater in the high-temperature dryer and t is the heating time; In step b, the thermal efficiency correction factor α = ; in is the ambient temperature correction factor; ,in It is an adjustment factor used to adjust the rate of performance degradation. The value range of α is 1-2 and is set according to the actual situation of the device. = 1 - (ΔT × β), where ΔT is the difference between the actual ambient temperature and the reference ambient temperature, ΔT = actual ambient temperature - reference ambient temperature, and β is the influence coefficient, which is 0.5%.

2. The intelligent monitoring method for high temperature dryer equipment according to claim 1, characterized in that: In step b, the thermal efficiency is calculated every 15 minutes for a total of 5 times. corrected Perform weighted averaging to obtain the weighted average value of the corrected thermal efficiency η avg , the calculation formula is: ； in, are the corrected thermal efficiencies calculated for the 1st to 5th times respectively; w1, w2, w3, w4, and w5 are The weight values ​​are, and w1=0.2, w2=0.15, w3=0.18, w4=0.32, w5=0.

15.

3. The intelligent monitoring method for high temperature dryer equipment according to claim 1, characterized in that: Capture data from 5 temperature zones in the early warning monitoring area, which are the dryer drive motor installation area , High temperature material accumulation area , Electrical equipment area 、Line area , Poor ventilation and heat dissipation areas , and their weights are ,and ; Calculated using the weighted average temperature formula: ; The calculated weighted average temperature WAT is compared with the alarm threshold temperature, and an alarm is triggered when the alarm threshold temperature is exceeded.

4. The intelligent monitoring method for high temperature dryer equipment according to claim 1, characterized in that: In step a, the temperature of the material inside the high-temperature dryer is captured by a non-contact temperature measuring instrument; the high-temperature dryer is placed on a weighing platform, the weighing platform weighs the high-temperature dryer and the material inside, and then the mass of the high-temperature dryer is subtracted to obtain the current mass of the material.

5. The intelligent monitoring method for high temperature dryer equipment according to claim 1, characterized in that: The infrared radiation energy distribution diagram of the early warning monitoring area is captured in real time by an infrared thermal imager to form an infrared thermal image of the early warning monitoring area.

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