Multi-element anti-oxidation coating and intelligent manufacturing process thereof

Abstract

According to the multi-element anti-oxidation coating and the intelligent manufacturing process thereof, component materials are selected, and the multi-element anti-oxidation coating is obtained through an intelligent self-propagating processing method. The preparation method has the advantages that through plasma activation and gradient coating design, the activity limitation of traditional powder mixing is broken through, and a gradient coating structure achieves synergistic improvement of oxidation resistance and mechanical properties; realizing process parameter closed-loop control by a quality evaluation system fusing a heat conduction equation and acoustic emission characteristics; the dynamic temperature field correction coefficient alpha is updated in real time through machine learning; a quantitative evaluation standard established by the quality index QI is combined with the coating, so that the strength is high; the product percent of pass is improved by a PID temperature compensation algorithm; a physical field-information flow fused intelligent monitoring system is utilized to realize adaptive optimization of process parameters.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of materials and Internet of Things operating system, and particularly relates to a multi-element antioxidant coating and an intelligent manufacturing process thereof. BACKGROUND

[0002] In the prior art, an antioxidant layer is usually added to the outer surface of a material to block the oxidation medium, prevent corrosive media such as oxygen and water vapor from directly contacting the base material by forming a dense barrier (such as a glass phase, an oxide film or a polymer coating), and also has the effects of enhancing high-temperature protection and thermal stability, self-repairing performance, prolonging the service life and reliability of the material, and realizing multifunctional expansion.

[0003] At present, a relatively advanced method for adding an antioxidant layer usually adopts a spraying method. For example, a method for spraying an antioxidant layer on the outer surface disclosed in patent document CN102864317A includes the following steps: (1) removing stains on the outer surface of a spraying object; (2) the outer surface of the spraying object needs to be activated; (3) spraying the spraying object; and (4) post-spraying treatment. As can be seen, the prior art uses a spraying method to add an antioxidant layer, and the operation method is relatively complex, and it is difficult to control the quality of spraying. For example, the pretreatment of removing stains on the outer surface of the spraying object is not thorough enough, which directly pollutes the coating interface, thereby causing the coating to be prone to breaking and cracking under high-temperature conditions. The spraying equipment used in the spraying method has a high initial investment and requires high operation skills, and therefore is not suitable for industrial-scale rapid production.

[0004] In summary, the prior art has high cost when adding an antioxidant layer to the outer surface of a material, and cannot achieve rapid processing, which is very unfavorable for the requirements of industrial-scale production. SUMMARY

[0005] The purpose of the present application is to solve the problems in the background art.

[0006] To achieve the above purpose, the present application provides a multi-element antioxidant coating, which includes the following components:

[0007] Component materials and a binder; the component materials include, in terms of molar parts, 1-2 parts of aluminum powder, 3-6 parts of titanium powder, 2-4 parts of carbon powder and 1-2 parts of mixed powder; or 1-2 parts of silicon-iron powder, 3-6 parts of titanium powder, 2-4 parts of carbon powder and 1-2 parts of mixed powder; and the binder includes water glass or silicon sol with a mass fraction of 10%.

[0008] Further, the mass ratio of the component materials to the binder includes 50-70:10-30.

[0009] Further, the aluminum powder is a plasma-activated aluminum powder, and a preparation method thereof comprises the following steps: placing aluminum powder with a particle size of 10-50 μm in an argon plasma for 10-30 minutes, and a power density is 50-150 W / cm 3 .

[0010] Further, the mixed powder is a gradient-coated structure powder, and from inside to outside, the mixed powder comprises the following components in sequence: a core: a nickel-based alloy, and ingredients are as follows in percentage by mass: Ni 60-70%, Cr 15-20%, and Al 5-8%; a middle layer: a titanium carbide coating layer, and a thickness is 200-500 nm; and an outer layer: yttrium oxide nanoparticles, and a particle size is 20-50 nm.

[0011] The application further provides a multi-element antioxidation coating intelligent manufacturing process, which comprises the following steps: placing titanium powder in an argon plasma reactor for 10-30 minutes, and performing magnetron sputtering coating on the mixed powder; and alternately depositing the mixed powder and sodium silicate adhesive by using ultrasonic auxiliary spraying technology to form a gradient-pore structure.

[0012] The component materials, the adhesive and the product materials are used to obtain the multi-element antioxidation coating by using a self-propagating processing method.

[0013] The application further provides a multi-element antioxidation coating intelligent manufacturing process, which comprises the following steps: placing titanium powder in an argon plasma reactor for 10-30 minutes, and performing magnetron sputtering coating on the mixed powder; and alternately depositing the mixed powder and sodium silicate adhesive by using ultrasonic auxiliary spraying technology to form a gradient-pore structure.

[0014] Further, the self-propagating processing method comprises the following steps:

[0015] (1) selecting component materials with different materials as media, and adapting to the application site environment;

[0016] (2) attaching the component materials with a uniform thickness at a position of 1 mm-5 mm below the inner surface of an evaporative pattern product frame or a product surface; adding the adhesive to the component materials; adding the antioxidation layer material, and after mixing with the product material, the mixture is put into an oven or a drying room for complete drying; and the drying process is controlled to inhibit deformation;

[0017] (3) after complete drying, the surface can be covered with 2-3 mm of the evaporative pattern for subsequent process steps, and the subsequent process steps comprise: evaporative pattern assembly-pasting-slurry-boxing-until pouring is completed.

[0018] Preferably, in the step (2), the drying temperature comprises 40-60 ℃.

[0019] Further, the middle layer titanium carbide coating layer is prepared by magnetron sputtering: a sputtering power is 300-500 W, an argon pressure is 0.3-0.8 Pa, a substrate temperature is 400-500 ℃, and a sputtering time is 20-40 minutes; and the outer layer yttrium oxide nanoparticles are prepared by pulsed laser deposition: a laser energy density is 2-5 J / cm 2Pulse frequency 10-20Hz, vacuum degree of deposition chamber ≤1×10-3Pa.

[0020] Further, the intelligent quality monitoring system is further included, comprising: an infrared thermal imaging module for real-time monitoring of a temperature field distribution of the self-propagating reaction; an acoustic emission sensor array for collecting stress wave signals in a coating curing process; and a data processing unit for performing a dynamic heat conduction model, extracting acoustic emission signal characteristic frequency band energy, calculating a coating quality index QI, and automatically adjusting a drying temperature.

[0021] Further, the automatic adjustment of the drying temperature uses an algorithm formula ΔT=K p ·(QI t -QI)+K i ·∫(QI t -QI)dt;

[0022] wherein QI t is a preset quality index threshold value, used as a target quality benchmark value, 1.0 representing a qualified product and 0.8 representing a critical defect; K p is a proportional gain coefficient, used for rapid response to current quality deviation, K p =0.5-1.2,

[0023] K i is an integral gain coefficient, used for eliminating steady-state error, K i =0.05-0.1; and ΔT is a drying temperature adjustment amount, used for dynamic compensation of process parameters to maintain quality stability.

[0024] Further, the formula used for calculating the coating quality index QI is:

[0025]

[0026] wherein ω i is a frequency band weight coefficient, used for reflecting the weight of the influence of different frequency band energy on quality; σT is a temperature field standard deviation, used for characterizing temperature distribution uniformity, and the greater the standard deviation, the more uneven the temperature; T max is a temperature field maximum temperature, used for monitoring local overheating risk, extracted in real time by the infrared thermal imaging module; T avg is a temperature field average temperature, used for reflecting the benchmark temperature of the overall reaction process, and the arithmetic mean value of the temperature field is calculated in real time; wherein k is a normalization coefficient, and k is set to 1.0; and ∑(ω i ·E i ) is a beneficial signal, and the greater the beneficial signal, the better the quality, and the denominator term represents temperature non-uniformity, and the greater the denominator term value, the worse the quality.

[0027] The beneficial effects of the present application are: 1. Through plasma activation and gradient coating design, the activity limitation of traditional powder mixing is broken through, and the gradient coating structure realizes the synergistic improvement of oxidation resistance-mechanical properties;

[0028] 2. The quality evaluation system of fusing the heat conduction equation with the acoustic emission characteristics realizes the closed-loop control of process parameters; the dynamic temperature field correction coefficient a is updated in real time by machine learning; the quality index QI establishes a quantitative evaluation standard combined with the coating, which has high strength; the PID temperature compensation algorithm improves the product qualification rate; the intelligent monitoring system of physical field-information flow fusion realizes the self-adaptive optimization of process parameters. DETAILED DESCRIPTION

[0029] The above is the preferred embodiment of the present application. It should be pointed out that for ordinary skilled persons in the technical field, without departing from the principles described in the present application, a number of improvements and refinements can be made, which should also be considered as the protection scope of the present application.

[0030] Embodiment one: the present application provides a kind of multi-element antioxidant coating, component includes:

[0031] Component material, adhesive; Component material includes: aluminum powder 1 part, titanium powder 3 parts, carbon powder 2 parts, mixed powder 1 part; Or silicon iron powder 1 part, titanium powder 3 parts, carbon powder 2 parts, mixed powder 1 part; Adhesive includes: water glass.

[0032] The mass ratio of component material to adhesive includes 50:10.

[0033] The present application also provides a kind of multi-element antioxidant coating intelligent manufacturing process, including: titanium powder is placed in argon plasma reactor and is handled 10-30 minutes, mixed powder is implemented magnetron sputtering coating;Adopt ultrasonic assisted spraying technology to alternate deposition mixed powder and water glass adhesive, form gradient pore structure;

[0034] Component material, adhesive and product material are used to obtain multi-element antioxidant coating by self-propagating processing method.

[0035] The self-propagating processing method includes the following steps:

[0036] (1) select different material component materials as medium, adapt to application site environment;

[0037] (2) adhere to the component material with consistent thickness at 1mm-5mm below the inner surface of the lost foam product frame or the product surface; Component material adds adhesive; Add antioxidant layer material, mix with product material, enter oven or drying room for complete drying; And control the drying process to inhibit deformation;

[0038] (3) After thoroughly drying, the surface can be covered with 2-3mm lost foam, and then subsequent process steps are performed, including: lost foam assembly-paste sticking-boxing-until pouring is completed.

[0039] In the step (2), the drying temperature comprises: 40℃.

[0040] The aluminum powder is a plasma-activated aluminum powder, and a preparation method thereof comprises: placing aluminum powder with a particle size of 10μm in an argon plasma for 10 minutes, and the power density is 50W / cm 3 .

[0041] The mixed powder is a gradient-coated structure powder, and from inside to outside, the core is: a nickel-based alloy, the composition is 60% of Ni, 15% of Cr, and 5% of Al by mass percentage; the intermediate layer is a titanium carbide coating layer with a thickness of 200nm; and the outer layer is yttrium oxide nanoparticles with a particle size of 20nm.

[0042] Further comprising an intelligent quality monitoring system, comprising: an infrared thermal imaging module for real-time monitoring of the temperature field distribution of the self-propagating reaction; an acoustic emission sensor array for collecting stress wave signals during the curing process of the coating; and a data processing unit for establishing a dynamic heat conduction model, extracting acoustic emission signal characteristic frequency band energy, calculating a coating quality index QI, and automatically adjusting the drying temperature.

[0043] The algorithm formula used for automatically adjusting the drying temperature is ΔT=K p ·(QI t -QI)+K i ·∫(QI t -QI)dt;

[0044] Wherein QI t is a preset quality index threshold value, which is used as a target quality reference value, 1.0 represents a qualified product, and 0.8 represents a critical defect, and the preset threshold QI t =1.0 is a qualified reference, and the PID control is triggered when the measured QI<0.8; K p is a proportional gain coefficient, which is used for rapid response to the current quality deviation, K p =0.5-1.2, K i is an integral gain coefficient, which is used for eliminating steady-state error, K i =0.05-0.1; ΔT is a drying temperature adjustment amount, which is used for dynamic compensation of process parameters to maintain quality stability; K p =0.8 and Ki=0.08 (critical damping state) are determined through step response test.

[0045] The formula used for calculating the coating quality index QI is:

[0046]

[0047] wherein ω i is the frequency band weight coefficient, used to reflect the weight of the influence of different frequency band energy on quality; σT is the temperature field standard deviation, used to represent the temperature distribution uniformity, the larger the standard deviation, the more uneven the temperature, calculated by the statistical standard deviation of the real-time temperature field; T max is the highest temperature of the temperature field, used to monitor the risk of local overheating, extracted by the infrared thermal imaging module in real time; T avg is the average temperature of the temperature field, used to reflect the benchmark temperature of the overall reaction process, calculated by the arithmetic mean of the real-time temperature field; the frequency band weight coefficient ω i is determined according to historical data: 50-100kHz frequency band ω1=0.4 (reflecting micro-cracks), 100-200kHz frequency band ω2=0.3 (reflecting interface peeling), 200-500kHz frequency band ω3=0.3 (reflecting pores).

[0048] Embodiment two: a multi-element antioxidant coating provided by the application, the composition includes:

[0049] Component materials, adhesives; component materials include: 2 parts of aluminum powder, 6 parts of titanium powder, 4 parts of carbon powder, and 2 parts of mixed powder; or 2 parts of silicon iron powder, 6 parts of titanium powder, 4 parts of carbon powder, and 2 parts of mixed powder; the adhesive includes: 10% by mass of silica sol.

[0050] The mass ratio of component materials to adhesive includes 70:30.

[0051] The application also provides a multi-element antioxidant coating intelligent manufacturing process, including:

[0052] The aluminum powder with a particle size of 10-50μm is placed in an argon plasma reactor, and is treated for 10-30 minutes at a gradient power density (50→150W / cm 3 ), to form a surface nanoscale active Al3Ti phase, and at the same time, the nickel-based alloy powder (Ni60-70%, Cr15-20%, Al5-8%) is subjected to magnetron sputtering coating: first, depositing a 200-500nm TiC intermediate layer, and then depositing 20-50nm Y2O3 nanoparticles by pulse laser deposition, with a coverage rate of ≥85%.

[0053] The activated aluminum powder 1-2 parts, titanium powder 3-6 parts, carbon powder 2-4 parts, and gradient-coated mixed powder 1-2 parts are weighed according to the proportion; a three-dimensional lattice coating structure is constructed on the inner surface of the lost foam frame: the mixed powder and water glass adhesive (mass ratio 50-70:10-30) are alternately deposited by using ultrasonic assisted spraying technology, to form a gradient pore structure.

[0054] The component materials, adhesives, and product materials are used to obtain a multi-element antioxidant coating by a self-propagating processing method. The self-propagating processing method includes the following steps:

[0055] (1) Select component materials of different materials as media to adapt to the application site environment;

[0056] (2) Attach a consistent thickness of component material 1mm-5mm below the inner surface of the lost foam product frame or the product surface; Add adhesive to the component material; Add antioxidant layer material, mix with product material, and enter the oven or drying room for complete drying; and control the drying process to inhibit deformation;

[0057] (3) After complete drying, the surface can be covered with 2-3mm of lost foam for subsequent process steps, including lost foam assembly, paste sticking, boxing, and pouring completion.

[0058] In step (2), the drying temperature includes: 60℃.

[0059] In the above embodiment, the aluminum powder of the multi-element antioxidant coating is a plasma-activated aluminum powder, and the preparation method comprises: placing aluminum powder with a particle size of 10-50μm in an argon plasma for 10-30 minutes, with a power density of 50-150W / cm 3 , the mixed powder is a gradient coated structure powder, from inside to outside: core: nickel-based alloy (Ni 60-70wt%, Cr 15-20wt%, Al 5-8wt%); intermediate layer: titanium carbide (TiC) coating layer, thickness 200-500nm; outer layer: yttrium oxide (Y2O3) nanoparticles, particle size 20-50nm, coverage ≥85%. Through plasma activation and gradient coating design, the activity limitation of traditional powder mixing is broken through, and the gradient coating structure realizes the synergistic improvement of antioxidant and mechanical properties.

[0060] The multi-element antioxidant coating intelligent manufacturing process in the above embodiment further comprises a multi-element antioxidant coating intelligent quality monitoring system, which comprises: an infrared thermal imaging module, an acoustic emission sensor array, and a data processing unit. The infrared thermal imaging module is used to monitor the temperature field distribution of the self-propagating reaction in real time; the acoustic emission sensor array is used to collect stress wave signals during the curing process of the coating; and the data processing unit is used to execute the following algorithms: (1) Establish a dynamic heat conduction model:

[0061]

[0062] Wherein α is the material thermal diffusivity correction coefficient, β is the reaction heat release intensity factor; T is the temperature field distribution of the coating surface / interior; is the Laplace operator of the temperature field; Q(x,y,z,t) is the heat source term of the self-propagating reaction;

[0063] (2) Extract the acoustic emission signal feature frequency band energy Ei ;

[0064] (3) Calculate the coating quality index QI:

[0065]

[0066] where ω i is the frequency band weight coefficient, which reflects the weight of the influence of different frequency band energy on quality; σT is the standard deviation of the temperature field, which is used to represent the uniformity of temperature distribution, and the larger the standard deviation, the more uneven the temperature. The statistical standard deviation of the real-time calculated temperature field; T max is the highest temperature of the temperature field, which is used to monitor the risk of local overheating, which is extracted in real time by the infrared thermal imaging module; T avg is the average temperature of the temperature field, which is used to reflect the reference temperature of the overall reaction process, and the arithmetic mean of the real-time calculated temperature field.

[0067] (4) When the QI value exceeds the preset threshold, the drying temperature is automatically adjusted, and the algorithm formula used is: ΔT = K p ·(QI t -QI) + K i ·∫(QI t -QI)dt;

[0068] where QI t is the preset quality index threshold, which is used as the target quality reference value, 1.0 represents a qualified product, and 0.8 represents a critical defect; K p is the proportional gain coefficient, which is used to quickly respond to the current quality deviation, K p = 0.5-1.2,

[0069] K i is the integral gain coefficient, which is used to eliminate steady-state error, K i = 0.05-0.1; ΔT is the drying temperature adjustment amount, which is used to dynamically compensate the process parameters and maintain the quality stability.

[0070] In this embodiment, 8-channel acoustic emission sensors are installed, and the sampling frequency is 1MHz. When the QI value is monitored to decrease from the reference value 1.2 to 0.8, the system automatically increases the drying temperature by 8℃ and prolongs the drying time by 15min. According to the statistics of 200 experiments, the coating cracking defect rate is reduced from 17% to 3.2%.

[0071] In this embodiment, at least the following effects are achieved: the quality evaluation system combining the heat conduction equation with the acoustic emission characteristics realizes the closed-loop control of the process parameters; the dynamic temperature field correction coefficient α is updated in real time using machine learning; the quantitative evaluation standard established by the quality index QI has high strength with the coating; the PID temperature compensation algorithm improves the product qualification rate; the intelligent monitoring system using the fusion of physical field and information flow realizes the adaptive optimization of process parameters.

[0072] The improvement of the ceramic coating compared to 2520 heat-resistant steel (310S stainless steel) in heat resistance mainly reflects in the following aspects:

[0073] 1. Significant improvement in temperature resistance limit

[0074] The ceramic coating (such as SiC / Al2O3 nanoceramics) can withstand temperatures up to 1500°C, while 2520 heat-resistant steel will soften, oxidize and corrode above 1200°C.

[0075] In short-term temperature resistance tests, some ceramic coatings can withstand 1600°C instantaneous high temperature (such as cookware coatings), while 2520 steel will quickly fail above 1300°C.

[0076] 2. Better high-temperature stability

[0077] The ceramic coating can maintain structural stability at high temperatures without deformation or oxidation film peeling; 2520 steel will precipitate chromium carbide at the grain boundary after long-term use at 1150°C, leading to performance degradation.

[0078] The service life of 310S heat-resistant steel (2520) in a ceramic kiln is only 1 / 3-1 / 5 of that of the ceramic coating solution.

[0079] 3. Enhanced oxidation resistance and corrosion resistance

[0080] The inert oxide layer (such as Al2O3) formed on the surface of the ceramic coating can completely isolate oxygen corrosion, while the Cr2O3 protective film of 2520 steel will gradually fail above 1200°C.

[0081] In high-temperature environments containing sulfur, chlorine and other corrosive substances, the corrosion resistance of ceramic coatings is more than 2 times better than that of 2520 steel.

[0082] 4. Application scenario comparison

[0083] 2520 heat-resistant steel: suitable for heat exchangers, furnaces and other continuous working at temperatures below 1200°C.

[0084] Ceramic coating: suitable for extreme environments (such as cement preheater inner cylinder, aerospace components) at 1500°C, or cookware inner liner that requires rapid heating.

[0085] The following are specific test data, with high-temperature life test conditions being 1200°C in air atmosphere, with 100 cycles of heating and cooling:

[0086]

[0087]

[0088] (Note: The specific performance improvement is slightly different due to the difference of coating composition and process).

Claims

1. A multi-element antioxidant coating, characterized in that, The ingredients include: Component materials and binders; the component materials by mass include: 1-2 parts aluminum powder, 3-6 parts titanium powder, 2-4 parts carbon powder, and 1-2 parts mixed powder; or 1-2 parts ferrosilicon powder, 3-6 parts titanium powder, 2-4 parts carbon powder, and 1-2 parts mixed powder; the binder includes water glass or 10% silica sol by mass.

2. The multi-element antioxidant coating according to claim 1, characterized in that, The mass ratio of component materials to adhesives includes 50-70:10-30.

3. The multi-element antioxidant coating according to claim 1, characterized in that, The aluminum powder is plasma-activated aluminum powder, and its preparation method includes: placing aluminum powder with a particle size of 10-50 μm in argon plasma for 10-30 minutes, with a power density of 50-150 W / cm³. 3 .

4. The multi-element antioxidant coating according to claim 1, characterized in that, The mixed powder is a gradient-coated structure powder, with the core being a nickel-based alloy from the inside out, and the composition by mass percentage being Ni 60-70%, Cr 15-20%, and Al 5-8%. Intermediate layer: Titanium carbide coating, 200-500 nm thick; Outer layer: Yttrium oxide nanoparticles, 20-50 nm in diameter.

5. A smart manufacturing process for a multi-element antioxidant coating, characterized in that, include: Titanium powder was placed in an argon plasma reactor for 10-30 minutes and then coated with magnetron sputtering. Ultrasonic-assisted spraying technology was used to alternately deposit the mixed powder and water glass binder to form a gradient pore structure. A multi-component antioxidant coating is obtained by using a self-propagating processing method to combine the component materials, adhesives, and product materials.

6. The manufacturing process according to claim 5, characterized in that, The self-propagating processing method includes the following steps: (1) Select component materials of different materials as the medium to adapt to the application site environment; (2) Attach component materials of uniform thickness to the inner surface of the lost foam product frame or 1mm-5mm below the product surface; add adhesive to the component materials; add antioxidant layer material, mix with the product material, and then put into an oven or drying room for thorough drying. And control the drying process to suppress deformation; (3) After it is completely dry, the surface can be covered with 2-3mm of lost foam before proceeding with subsequent process steps. The subsequent process steps include: lost foam assembly - slurry application - boxing - until casting is completed.

7. The manufacturing process according to claim 6, characterized in that, In step (2), the drying temperature includes 40-60℃.

8. The manufacturing process according to claim 5, characterized in that, It also includes an intelligent quality monitoring system, comprising: an infrared thermal imaging module for real-time monitoring of the temperature field distribution of the self-propagating reaction; an acoustic emission sensor array for acquiring stress wave signals during the coating curing process; and a data processing unit for performing tasks such as establishing a dynamic heat conduction model, extracting the energy of characteristic frequency bands of acoustic emission signals, calculating the coating quality index (QI), and automatically adjusting the drying temperature.

9. The manufacturing process according to claim 8, characterized in that, The automatic adjustment of drying temperature uses the algorithm formula ΔT = K. p ·(QI t -QI)+K i ·∫(QI t -QI)dt; Among them QI t This is a preset quality index threshold used as the target quality benchmark value; 1.0 represents a qualified product, and 0.8 represents a critical defect. K p K is the proportional gain coefficient used for rapid response to current quality deviation. p =0.5-1.2, K i K is the integral gain coefficient used to eliminate steady-state error. i =0.05-0.1; ΔT is the drying temperature adjustment amount, used to dynamically compensate process parameters and maintain quality stability.

10. The manufacturing process according to claim 8, characterized in that, The formula used to calculate the coating quality index (QI) is: Where ω i σT is the frequency band weighting coefficient, used to reflect the weight of the energy influence of different frequency bands on quality; σT is the standard deviation of the temperature field, used to characterize the uniformity of temperature distribution. The larger the standard deviation, the more non-uniform the temperature. It is calculated from the statistical standard deviation of the temperature field in real time; T max The highest temperature in the temperature field is used to monitor the risk of local overheating and is extracted in real time by the infrared thermal imaging module; T avg The average temperature of the temperature field is used as a reference temperature to reflect the overall reaction process. The arithmetic mean of the temperature field is calculated in real time; where k is the normalization coefficient, set to k = 1.0, ∑(ω i ·E i The positive signal is the larger the positive signal, the better the quality. The denominator represents the temperature non-uniformity, and the larger the denominator value, the worse the quality.

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