Furnace temperature adjusting method and system for steel rolling heating furnace

Abstract

The invention relates to the technical field of furnace temperature control, in particular to a method and system for adjusting the furnace temperature of a steel rolling heating furnace, and the method comprises the steps: firstly responding to the input of a target steel billet, calculating the remaining in-furnace time of the target steel billet, then matching the remaining in-furnace time with a preset machining section machining time table to obtain a current machining section of the target steel billet, and finally, adjusting the furnace temperature of the target steel billet. The correction coefficient of the current machining section is called through a table look-up method, then the theoretical furnace temperature set value of the current machining section is corrected through the correction coefficient, an actual furnace temperature set value is obtained, finally, whether the monitored temperature of the current machining section is lower than the actual furnace temperature set value or not is judged, and if yes, the current machining section in the heating furnace is heated. Compared with the prior art, the method has the advantages that the furnace temperature can be reliably adjusted when infrared temperature feedback is not accurate, and safe and reliable production is maintained.

Description

Technical Field

[0001] The present invention relates to the technical field of furnace temperature control, and more particularly to a method and system for regulating the temperature of a steel rolling heating furnace. Background Art

[0002] Steel rolling heating furnaces are used for hot rolling of steel. After the temperature is raised and activated, each process section within the furnace needs to maintain a relatively high temperature to maintain the structural integrity of the furnace body. Temperature control of steel rolling heating furnaces is a crucial step in the hot rolling process. Compared to traditional heating processes, the temperature of heating furnaces used for steel rolling is typically as high as thousands of degrees Celsius, and infrared pyrometers are typically used as temperature measurement devices for monitoring. While infrared pyrometers offer the advantages of contactless measurement and fast response, when monitoring the temperature of different hot rolling sections (heat recovery section, preheating section, waiting section, uniform rolling section, and rolling cooling section), infrared pyrometers are prone to significant changes in their infrared sensing reflectivity due to changes in steel roughness, the presence of steam, smoke, or rolled steel impurities within the furnace. This can lead to inaccurate actual temperature feedback, which in turn causes large deviations in the temperature regulation of the heating furnace.

[0003] In actual applications, after the steel rolling heating furnace is put into use, in order to ensure the consistency of monitoring data, the safety of heating operations and the stability of the steel supply chain, it is difficult to clean the furnace body, optimize the ventilation structure or optimize the process section by stopping the furnace, especially for some heavy industrial areas with large steel shipments and high requirements for immediate shipments.

[0004] Therefore, how to reliably adjust the furnace temperature while maintaining production has become a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In order to solve the above-mentioned technical problem of reliably regulating the furnace temperature, the present invention discloses a furnace temperature regulation method and system for a steel rolling heating furnace.

[0006] In a first aspect, the present invention discloses a method for regulating the temperature of a steel rolling heating furnace, comprising: In response to the input of the target steel billet, the remaining furnace time of the target steel billet is calculated; Match the remaining time in the furnace with the preset processing schedule of the processing section to obtain the current processing section of the target steel billet; Use the table lookup method to retrieve the correction coefficient of the current processing section; Use the correction coefficient to correct the theoretical furnace temperature setting value of the current processing section to obtain the actual furnace temperature setting value; Determine whether the monitored temperature of the current processing section is lower than the actual furnace temperature setting value. If so, increase the temperature of the current processing section in the heating furnace.

[0007] Beneficial effect: When the target steel billet is put into the furnace, the method of the present invention will first match the remaining time of the target steel billet in the furnace with the processing time table of the processing section to obtain the current processing section of the target steel billet, and then use the table lookup method to retrieve the correction coefficient of the current processing section. The correction coefficient is then used to correct the actual furnace temperature setting value, so as to adaptively adjust the actual furnace temperature setting value according to the conditions of each processing section in the heating furnace. Finally, combined with the monitored temperature, it is determined whether the heating furnace needs to be heated. Compared with the existing technology, the method of the present invention adopts a temperature adjustment strategy with table lookup compensation to achieve reasonable control of the heating furnace temperature. It can reliably adjust the furnace temperature when the infrared temperature feedback is inaccurate, and maintain safe and reliable production.

[0008] Preferably, the correction coefficient is used to correct the theoretical furnace temperature setting value of the current processing section to obtain the actual furnace temperature setting value, including: The correction coefficient and the theoretical furnace temperature setting value are placed into the weighted average model to calculate the actual furnace temperature setting value.

[0009] Preferably, the weighted average model is specifically:

[0010] Where, Indicates the The actual furnace temperature setting value of the current processing section, Indicates the total number of sections of the billet, Indicates the The billet in the The correction coefficient of the current processing section, Indicates the The billet in the The theoretical furnace temperature setting value of the current processing section.

[0011] Beneficial effects: The method of the present invention can dynamically assign a correction coefficient to the target steel billet according to the processing section in which the target steel billet is located, so that the target steel billet can be processed at a more reasonable temperature, thereby improving the product quality of the target steel billet.

[0012] Preferably, if the pyrometer is temporarily removed from the current processing section, the correction coefficient is used to correct the theoretical furnace temperature setting value of the current processing section to obtain the actual furnace temperature setting value, including: Get expert compensation parameters; The correction coefficient, expert compensation parameter and theoretical furnace temperature setting value are placed into the correction equation to calculate the actual furnace temperature setting value.

[0013] Preferably, the correction equation is specifically:

[0014] Where, Indicates the The actual furnace temperature setting value of the current processing section, Indicates the The theoretical furnace temperature setting value of the current processing section, Indicates the expert-corrected temperature, Indicates the The actual value of the furnace temperature in the last monitoring measurement of the current processing section, Indicates the Expert compensation parameters of the current processing section, Indicates the time the billet waits for rolling in the heating furnace. Indicates the correction factor.

[0015] Preferably, The current processing section is the preheating section in the heating furnace.

[0016] Preferably, a deep learning model is used to obtain the correction coefficient, and the method of the present invention further includes: Acquire three-dimensional point cloud data and thermal imaging data of the target billet surface; Extract laser features from 3D point cloud data and thermal imaging features from thermal imaging data; The laser features and thermal imaging features are spliced ​​together to obtain a feature matrix; The feature matrix is ​​input into the pre-trained spatiotemporal attention neural network and the correction coefficient is output.

[0017] Preferably, calculating the remaining furnace time of the target steel billet includes: Obtain the processed information of the target steel billet and the production rhythm of each processing section; Determine the remaining processing section of the target steel billet based on the preset total processing information and processed information; The production cycles of all remaining processing sections are accumulated to calculate the remaining time in the furnace.

[0018] Preferably, the current processing section at least includes a preheating section, a waiting-for-rolling treatment section, a temperature-averaging steel rolling section, and a heat recovery section.

[0019] In the second aspect, the present invention discloses a furnace temperature control system for a steel rolling heating furnace, comprising a processor and a memory, wherein the memory stores computer program instructions. When the computer program instructions are executed by the processor, the furnace temperature control method for the steel rolling heating furnace recorded in the first aspect is implemented.

[0020] The beneficial effects of the present invention are: (1) Compared with the existing technology, the method of the present invention adopts a temperature control strategy of table lookup compensation to achieve reasonable control of the heating furnace temperature. When the infrared temperature feedback is inaccurate, the furnace temperature can be reliably adjusted to maintain safe and reliable production.

[0021] (2) Compared with the existing technology, the method of the present invention can dynamically adjust the correction coefficient according to the actual situation of the target steel ingot in the processing section by using artificial intelligence technology, making the reliability and universality of the method of the present invention stronger.

[0022] (3) Compared with the prior art, the method of the present invention can support the replacement of the pyrometer in the preheating section during the continuous production process. During this replacement period, the target steel billet is always preheated within a reasonable temperature range without damaging its product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an illustrative and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein: Figure 1 This is a flow chart of a method for regulating the temperature of a steel rolling heating furnace in a first embodiment of the present invention; Figure 2 This is a schematic diagram of temperature regulation of the waiting rolling treatment section in Example 1 of the present invention; Figure 3 It is a structural diagram of the furnace temperature control system of the steel rolling heating furnace in the second embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0025] This embodiment discloses a furnace temperature regulation method and system for a steel rolling heating furnace, which are used to overcome the technical problem of reliably regulating the furnace temperature while maintaining production.

[0026] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0027] Example 1 like Figure 1 As shown, this embodiment discloses a method for regulating the temperature of a steel rolling heating furnace, comprising: S10: In response to the input of the target steel billet, the remaining furnace time of the target steel billet is calculated.

[0028] In this embodiment, when the target steel billet is put in, it will first enter the preheating section of the heating furnace. An in-position sensor (which can be a laser sensor) is provided on the preheating section to determine whether the target steel billet is put in. If it is put in, the in-position sensor will send an in-position signal to the main control device. At this time, the main control device calculates the remaining time of the target steel billet in the furnace based on the built-in program logic.

[0029] The above step S10 includes: S11: Obtain the processed information of the target steel billet and the production rhythm of each processing section.

[0030] It should be noted that the target billet has a production number, and each completed processing stage will have corresponding processed information uploaded. The production takt (rhythm) refers to the theoretical time required to complete each processing stage.

[0031] S12: Determine the remaining processing section of the target steel billet according to the preset total processing information and the processed information.

[0032] In this embodiment, the total processing information includes the order and total number of processing sections that the target steel billet has passed through, while the processed information refers to the information about the processing sections that the target steel billet has passed through.

[0033] Specifically, the unfinished processing sections in the total processing information can be determined through the processed information.

[0034] S13: The production cycles of all remaining processing sections are accumulated to calculate the remaining furnace time.

[0035] Through the above steps S11 to S13, the remaining furnace time of each target steel billet can be quickly calculated. This method is more suitable for a step-by-step steel rolling process.

[0036] S20: Match the remaining time in the furnace with the preset processing schedule of the processing section to obtain the current processing section of the target steel billet.

[0037] In this embodiment, the current processing section includes at least a preheating section, a waiting section, a temperature-averaging steel rolling section, and a heat recovery section. The target steel billet flows through the preheating section, the waiting section, the temperature-averaging steel rolling section, and the heat recovery section in order from front to back.

[0038] It should be explained that the preheating section mainly uses the waste heat of the furnace gas to preliminarily heat the target steel billet, so that the temperature of the target steel billet rises evenly and slowly, reducing the thermal stress when entering the high temperature section. Figure 2As shown, the waiting rolling section of this embodiment mainly performs heat preservation-cooling-heat preservation-heating regulation on the target steel billet after the preheating section. This process has a decisive influence on the mechanical properties of the target steel billet. Specifically, different temperature ranges and cooling rates will cause the target steel billet to form different structures, such as ferrite, pearlite, bainite and martensite. By accurately controlling the cooling rate and holding time in the waiting rolling section, the structural transformation process of the steel can be regulated to obtain the required mechanical properties, such as strength, toughness, hardness, etc. More specifically, in Figure 2 middle, ~ The time period represents the first holding time period in the waiting rolling treatment section. ~ The time period indicates the cooling time period in the waiting rolling treatment section. ~ The time period represents the second holding time period in the waiting rolling treatment section. ~ The time period represents the heating period within the pre-rolling treatment section. By adding the pre-rolling treatment section and adjusting its temperature, the method of this embodiment can reduce the probability of rolling defects in the target billet entering the temperature-averaging rolling section. This improves production quality while also reducing the likelihood of inaccurate pyrometer temperature monitoring due to defects (cracks or increased roughness). The temperature-averaging rolling section primarily uniformizes the internal and external temperatures of the target billet, eliminating temperature gradients and ensuring a consistent overall temperature. The target billet is then rolled. The heat recovery section primarily recovers waste heat from the exhaust gas from the heating furnace.

[0039] For example, the processing schedule of the above processing stages may be:

[0040] It should be noted that the required production rhythm of each processing section will vary depending on the carbon content, specifications, size and thickness of the target steel billet, and the corresponding remaining time in the furnace will be adaptively adjusted according to actual conditions.

[0041] S30: Use the table lookup method to retrieve the correction coefficient of the current processing section.

[0042] In this embodiment, laser or thermal imaging inspection techniques can be used to inspect the steel billets in each processing stage, generating sampling inspection results. These sampling inspection results are then fed into a pre-trained deep learning model to dynamically update the correction coefficients for each processing stage. In other embodiments, experts can periodically perform sampling inspections on the intermediate products of each processing stage and assign correction coefficients based on the sampling inspection results, enabling dynamic updating of the correction coefficients. This dynamic updating of correction coefficients can better adapt to the complex environment of actual steel rolling.

[0043] S40: Correcting the theoretical furnace temperature setting value of the current processing section using the correction coefficient to obtain the actual furnace temperature setting value.

[0044] Specifically, the above step S40 includes: The correction coefficient and the theoretical furnace temperature setting value are placed into the weighted average model to calculate the actual furnace temperature setting value.

[0045] More specifically, the weighted average model is:

[0046] Where, Indicates the The actual furnace temperature setting value of the current processing section, Indicates the total number of sections of the billet, Indicates the The billet in the The correction coefficient of the current processing section, Indicates the The billet in the The theoretical furnace temperature setting value of the current processing section.

[0047] It should be noted that, in most cases, it is difficult to remove a pyrometer with large measurement deviations during processing in a critical process with high temperature requirements (removal would seriously disrupt the continuity of the monitoring data). However, in the preheating section, where the temperature process requirements are lower, when the pyrometer has large measurement deviations, it can be removed and replaced during processing. Specifically, if the pyrometer is removed during the preheating section, step S40 includes: Get expert compensation parameters.

[0048] The correction coefficient, expert compensation parameter and theoretical furnace temperature setting value are placed into the correction equation to calculate the actual furnace temperature setting value.

[0049] The above correction equation is specifically:

[0050] Where, Indicates the The actual furnace temperature setting value of the current processing section, Indicates the The theoretical furnace temperature setting value of the current processing section, Indicates the expert-corrected temperature, Indicates the The actual value of the furnace temperature in the last monitoring measurement of the current processing section, Indicates the Expert compensation parameters of the current processing section, Indicates the time the billet waits for rolling in the heating furnace. Indicates the correction factor.

[0051] In this embodiment, the above Take 600℃~700℃, Take 2~5, Take -1~-0.5.

[0052] Preferably, the above Take 650℃.

[0053] It should be explained that when a failure occurs in the steel rolling production and the heating time of the steel billet in the furnace is prolonged, the furnace temperature setting value should be corrected. The furnace temperature drop table of the high-speed wire heating furnace in the wire rod plant when waiting to be rolled can be referred to, and the above can be determined in combination with actual operating experience. .

[0054] Through the above technical solution, the method of this embodiment supports the temporary replacement of pyrometers during actual production, while maintaining the data continuity and integrity of the monitoring system. While maintaining the data continuity and integrity of the monitoring system, the method of this embodiment can also ensure that the target steel billet is preheated within a reasonable temperature range in the preheating section.

[0055] S50: Determine whether the monitored temperature of the current processing section is lower than the actual furnace temperature setting value. If so, heat the current processing section in the heating furnace.

[0056] It should be explained that, generally, each processing section in a high-temperature furnace is equipped with one or more pyrometers, and the above-mentioned monitoring temperature refers to the real-time monitoring temperature of the pyrometer.

[0057] Through the above steps S10 to S50, when there is a measurement deviation in the pyrometer, the method of this embodiment can perform temperature adjustment weighting based on the actual situation for different processing sections where the target steel billet is located, so that the actual temperature of the processing section is corrected, thereby maintaining safe and reliable production.

[0058] Furthermore, if a deep learning model is used to obtain the correction coefficient, the method of this embodiment further includes: S100: Acquire three-dimensional point cloud data and thermal imaging data of the target billet surface.

[0059] In this embodiment, the 3D point cloud data can be acquired using a Keyence LK-H052 laser displacement sensor at a 50kHz sampling frequency, with an accuracy of ±2μm. The thermal imaging data can be acquired using a FLIR A655sc thermal imager, equipped with a 160×120 pixel uncooled microbolometer capable of achieving a thermal sensitivity of 50mK in the 8-14μm band. An industrial computer (primarily a PLC) controls the laser displacement sensor and thermal imager for synchronous data acquisition, ensuring an acquisition deviation of less than 1ms, thus achieving synchronized data acquisition.

[0060] S200: Extracting laser features of the three-dimensional point cloud data and thermal imaging features of the thermal imaging data.

[0061] Furthermore, the extraction algorithm of the above laser features is:

[0062] Where, Indicates the effective detection area, Indicates time Output laser characteristics, Indicates the target billet at time 3D point cloud data, Represents the 3D coordinates of 3D point cloud data.

[0063] Furthermore, the extraction algorithm of the above thermal imaging features is:

[0064] Where, Indicates time Output thermal imaging features, represents the symbol of partial derivative, Indicates time Thermal imaging data, Represents the horizontal coordinate data of thermal imaging data, Represents the vertical coordinate data of thermal imaging data.

[0065] S300: combining the laser features and the thermal imaging features to obtain a feature matrix.

[0066] Furthermore, the generation algorithm of the above feature matrix is:

[0067] Where, Indicates time The concatenated feature matrix, Indicates the channel splicing symbol, represents the mean of the training set, represents the standard deviation of the training set.

[0068] S400: Input the feature matrix into the pre-trained spatiotemporal attention neural network (STANN) and output the correction coefficient.

[0069] Among them, the output expression of the correction coefficient is:

[0070] Where, Indicates time The correction factor, Represents spatiotemporal attention neural network for time The output result of Confidence Greater than threshold The correction factor is Otherwise, take the time Correction factor .

[0071] Through the above steps S100 to S400, the method of this embodiment first obtains the three-dimensional point cloud data and thermal imaging data of the target steel billet surface through the laser displacement sensor and the thermal imager to realize the real-time acquisition of the actual processing status of the target steel billet; then uses the above algorithm to extract the laser features and thermal imaging features to reduce the amount of data calculation; then, the extracted laser features and thermal imaging features are spliced ​​to obtain the feature matrix as the data input of the spatiotemporal attention neural network; finally, the dynamically updated correction coefficient is obtained through the spatiotemporal attention neural network and the output expression.

[0072] Compared to existing technologies, the method of this embodiment can use the spatiotemporal attention neural network to generate dynamic correction coefficients to adapt to changes in actual scenarios. Therefore, the method of this embodiment is more universal and flexible.

[0073] Preferably, in order to improve the computational efficiency (computational iteration speed) and computational accuracy of the above-mentioned spatiotemporal attention neural network, the method of this embodiment adopts the Huber loss function as the robust loss function of the spatiotemporal attention neural network, and the threshold parameter of the loss function can be taken as 0.5.

[0074] Preferably, in order to further improve the computational accuracy of the above-mentioned spatiotemporal attention neural network, an incremental learning optimization mechanism can be introduced, and a momentum optimizer can be used to update the hyperparameters of the spatiotemporal attention neural network.

[0075] Example 2 like Figure 3As shown, this embodiment discloses a furnace temperature control system for a steel rolling heating furnace, including a processor and a memory, wherein the memory stores computer program instructions. When the computer program instructions are executed by the processor, the furnace temperature control method for the steel rolling heating furnace recorded in Example 1 is implemented.

[0076] The system of this embodiment also includes other components well known to those skilled in the art, such as a communication interface. The configuration and functions of these components are known in the art and will not be described in detail here.

[0077] In the present invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, the computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc., or any other medium that can be used to store the required information and can be accessed by an application, module, or both. Any such computer storage medium can be part of, accessible to, or connectable to a device. Any application or module described in the present invention can be implemented using computer-readable / executable instructions that can be stored or otherwise maintained by such a computer-readable medium.

[0078] In the description of this specification, “a plurality of” means at least two, for example, two, three or more, etc., unless otherwise clearly defined.

[0079] While several embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous modifications, variations, and alternatives will occur to those skilled in the art without departing from the concept and spirit of the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in practicing the present invention.

Claims

1. A method for regulating the temperature of a steel rolling heating furnace, characterized in that: include: In response to the input of the target steel billet, calculating the remaining furnace time of the target steel billet; Matching the remaining time in the furnace with a preset processing schedule of processing sections to obtain the current processing section of the target steel billet; Using a table lookup method to retrieve the correction coefficient of the current processing section; Using the correction coefficient to correct the theoretical furnace temperature setting value of the current processing section to obtain an actual furnace temperature setting value; Determine whether the monitored temperature of the current processing section is lower than the actual furnace temperature setting value. If so, heat the current processing section in the heating furnace.

2. The method for regulating the temperature of a steel rolling heating furnace according to claim 1, wherein: The correction coefficient is used to correct the theoretical furnace temperature setting value of the current processing section to obtain the actual furnace temperature setting value, including: The correction coefficient and the theoretical furnace temperature setting value are placed in a weighted average model to calculate the actual furnace temperature setting value.

3. The method for regulating the temperature of a steel rolling heating furnace according to claim 2, wherein: The weighted average model is specifically: Where, Indicates the The actual furnace temperature setting value of the current processing section, Indicates the total number of sections of the billet, Indicates the The billet in the The correction coefficient of the current processing section, Indicates the The billet in the The theoretical furnace temperature setting value of the current processing section.

4. The method for regulating the temperature of a steel rolling heating furnace according to claim 1, wherein: If the pyrometer of the current processing section is temporarily removed, the correction coefficient is used to correct the theoretical furnace temperature setting value of the current processing section to obtain the actual furnace temperature setting value, including: Get expert compensation parameters; The correction coefficient, the expert compensation parameter and the theoretical furnace temperature setting value are placed into a correction equation to calculate the actual furnace temperature setting value.

5. The method for regulating the temperature of a steel rolling heating furnace according to claim 4, characterized in that: The correction equation is specifically: Where, Indicates the The actual furnace temperature setting value of the current processing section, Indicates the The theoretical furnace temperature setting value of the current processing section, Indicates the expert-corrected temperature, Indicates the The actual value of the furnace temperature in the last monitoring measurement of the current processing section, Indicates the Expert compensation parameters of the current processing section, Indicates the time the billet waits for rolling in the heating furnace. Indicates the correction factor.

6. The method for regulating the temperature of a steel rolling heating furnace according to claim 5, characterized in that: No. The current processing section is the preheating section in the heating furnace.

7. The method for regulating the temperature of a steel rolling heating furnace according to claim 1, wherein: The correction coefficient is obtained using a deep learning model, and the method further includes: Acquire three-dimensional point cloud data and thermal imaging data of the target billet surface; extracting laser features of the three-dimensional point cloud data and thermal imaging features of the thermal imaging data; splicing the laser features and the thermal imaging features to obtain a feature matrix; The feature matrix is ​​input into a pre-trained spatiotemporal attention neural network, and the correction coefficient is output.

8. The method for regulating the temperature of a steel rolling heating furnace according to claim 1, wherein: Calculating the remaining furnace time of the target billet includes: Obtaining processed information of the target steel billet and the production rhythm of each processing section; Determining a remaining processing section of the target steel billet according to the preset total processing information and the processed information; The production cycles of all remaining processing sections are accumulated to calculate the remaining furnace time.

9. The method for regulating the temperature of a steel rolling heating furnace according to claim 1, wherein: The current processing section at least includes a preheating section, a waiting-for-rolling section, a temperature-averaging steel rolling section, and a heat recovery section.

10. A furnace temperature control system for a steel rolling heating furnace, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the method for regulating the temperature of a steel rolling heating furnace according to any one of claims 1 to 9 is implemented.

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