Method, device and equipment for controlling temperature of graphitization furnace and storage medium

Abstract

The invention discloses a graphitization furnace temperature control method, device and equipment and a storage medium. The method comprises the steps that in the heating production process of the graphitization furnace, whether an abnormal temperature sensor exists or not is judged based on temperature data collected by all temperature sensors; if the judgment result is that one abnormal temperature sensor exists, averaging current temperature data obtained based on other temperature sensors in real time to obtain temperature data in the furnace; the temperature data in the furnace are compared with preset temperature data at the corresponding moments of the corresponding preset heating temperature curves, the number of the preset heating temperature curves is multiple, and the corresponding preset heating temperature curves are set according to the situation that any temperature sensor is abnormal and other temperature sensors are normal; and adjusting the output power of the heating device of the graphitization furnace according to the comparison result. According to the method, when the temperature sensor is found to be abnormal in the production process and production is continued, the influence on the temperature control effect of the graphitization furnace can be reduced, and unnecessary material waste is avoided.

Description

Technical Field

[0001] This application relates to the field of graphitization furnace heating, and more particularly to graphitization furnace temperature control methods, devices, equipment, and storage media. Background Technology

[0002] In the heating process of continuous graphitization furnaces, a common temperature control method is based on a stored preset heating temperature curve. Specifically, during production, multiple temperature sensors collect real-time temperatures at different locations within the furnace. These real-time temperatures are then averaged (or weighted average depending on the situation) to obtain the actual real-time furnace temperature. This real-time furnace temperature is then compared to the preset temperature value at the corresponding moment on the preset heating temperature curve. If the deviation exceeds a preset deviation value, the output power of the heating device is adjusted accordingly. However, this temperature control method has the following technical problems: If a temperature sensor malfunction is discovered during production—for example, if the sensor's data is abnormal or it cannot collect data—following this temperature control method will affect the temperature control effect. Specifically: if the real-time temperature obtained from the malfunctioning sensor is included in the calculation, its inaccuracy will affect the accuracy of the calculated real-time furnace temperature, thus impacting the temperature control effect; if the sensor is excluded, the averaging calculation will lack a data point, similarly affecting the accuracy of the calculated real-time furnace temperature, thus impacting the temperature control effect; and if the machine is shut down directly, it will lead to unnecessary material waste under normal operating conditions. Therefore, it is necessary to propose a method that can reduce the impact on the temperature control effect of the graphitization furnace when an abnormality is detected in the temperature sensor during the production process but production continues, thereby avoiding unnecessary material waste. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, equipment, and storage medium for controlling the temperature of a graphitization furnace, so that when an abnormality in the temperature sensor is detected during the production process but production continues, the impact on the temperature control effect of the graphitization furnace can be reduced, and unnecessary material waste can be avoided.

[0004] To achieve the above objectives, this application provides a method for controlling the temperature of a graphitization furnace, comprising: During the heating process in the graphitization furnace, the presence of any abnormal temperature sensors is determined based on the temperature data collected by each temperature sensor. If the determination result is that there is an abnormal temperature sensor, the furnace temperature data is obtained by averaging the current temperature data obtained in real time based on the other temperature sensors. The furnace temperature data is compared with the preset temperature data at the corresponding time of the preset heating temperature curve. The preset heating temperature curve includes multiple curves. For any one of the temperature sensors is abnormal while the other temperature sensors are normal, a corresponding preset heating temperature curve is set. Adjust the output power of the heating device of the graphitization furnace according to the comparison results.

[0005] Optionally, determining whether there is an abnormal temperature sensor based on the temperature data collected by each temperature sensor includes: The current temperature curves obtained from each of the aforementioned temperature sensors are compared. If the current temperature curve corresponding to one of the temperature sensors does not show a consistent trend with the current temperature curves corresponding to the other temperature sensors, then the temperature sensor is considered to be malfunctioning.

[0006] Optionally, the current temperature curve is formed based on temperature data within the most recent set time period.

[0007] Optionally, the current temperature curve is formed based on a set number of recently collected temperature data.

[0008] Optionally, determining whether there is an abnormal temperature sensor based on the temperature data collected by each temperature sensor includes: The continuous multiple temperature data acquired in real time based on the temperature sensor are compared with the continuous multiple average temperature data at the corresponding time on the historical average temperature curve acquired based on the temperature sensor. If the difference between a set number of temperature data points and the corresponding average temperature data point in a series of consecutive temperature data points is outside a preset range, then the corresponding temperature sensor is considered to be malfunctioning.

[0009] Optionally, determining whether there is an abnormal temperature sensor based on the temperature data collected by each temperature sensor includes: The current temperature curve obtained in real time based on the temperature sensor is compared with the historical average temperature curve obtained based on the temperature sensor. If the current temperature curve corresponding to the temperature sensor is inconsistent with the corresponding historical average temperature curve, then the temperature sensor is considered to be abnormal.

[0010] Optionally, if the determination result indicates that there is an abnormal temperature sensor and the number of abnormal temperature sensors is greater than two, then the system is stopped and an alarm is triggered.

[0011] Optionally, during the processing of each of the first to Mth heats, The normal average temperature data is obtained by averaging the real-time temperature data acquired by all N temperature sensors while maintaining normal operation. A normal condition curve is obtained based on the normal average temperature data sequence obtained during processing. The standard heating temperature curve is obtained by averaging the normal condition curves obtained from each of the aforementioned furnace processing cycles. The N temperature sensors are arbitrarily combined to obtain N different combinations. Each combination includes N-1 temperature sensors. The abnormal average temperature data is obtained by averaging the temperature data acquired in real time from all the temperature sensors in any combination. An abnormal situation curve is obtained based on the abnormal average temperature data sequence obtained during the processing. The corresponding preset heating temperature curve is obtained by averaging the abnormal situation curves obtained from each of the furnace processing.

[0012] Optionally, the first to the Mth heats can be processed under the same processing conditions.

[0013] Optionally, in different combinations, the weight of the temperature data acquired in real time by each temperature sensor when participating in the weighted average calculation of the abnormal average temperature data is obtained based on all temperature sensors in the combination.

[0014] To achieve the above objectives, this application also provides a temperature control device for a graphitization furnace, comprising: The judgment module is used to determine whether there is an abnormal temperature sensor during the heating production process of the graphitization furnace based on the temperature data collected by each temperature sensor. The calculation module is used to calculate the furnace temperature data by averaging the current temperature data obtained in real time from the other temperature sensors if the judgment result is that there is an abnormal temperature sensor. The comparison module is used to compare the furnace temperature data with the preset temperature data at the corresponding time of the preset heating temperature curve. The preset heating temperature curve includes multiple curves. If any one of the temperature sensors is abnormal and the other temperature sensors are normal, the corresponding preset heating temperature curve is set respectively. An adjustment module is used to adjust the output power of the heating device of the graphitization furnace according to the comparison results.

[0015] To achieve the above objectives, this application also provides a computer device, including a memory and a processor; The memory is connected to the processor. The memory is used to store computer programs, and the processor is used to call the computer programs so that the computer device executes the graphitization furnace temperature control method as described above.

[0016] To achieve the above objectives, this application also provides a computer-readable storage medium storing a computer program adapted to be loaded by a processor and executed as described above for graphitization furnace temperature control.

[0017] In this embodiment, multiple preset heating temperature curves are pre-stored. One preset heating temperature curve is set for all temperature sensors operating normally, and corresponding preset heating temperature curves are set for all scenarios where one temperature sensor is abnormal while the other temperature sensors are normal. During the heating process in the graphitization furnace, if an abnormal temperature sensor is found, that abnormal temperature sensor is excluded. The furnace temperature data is obtained by averaging the current temperature data acquired in real time from the other temperature sensors. Then, the furnace temperature data is compared with the preset temperature data at the corresponding moment of the preset heating temperature curve (the preset heating temperature curve corresponding to the abnormal temperature sensor), and the output power of the heating device of the graphitization furnace is adjusted according to the comparison result. Since the embodiments of this application pre-set corresponding preset heating temperature curves for situations where any one temperature sensor is abnormal while the other temperature sensors are normal, when performing furnace temperature control, if there is an abnormal temperature sensor, the abnormal temperature sensor can be excluded, and the output power of the heating device can be adjusted based on the comparison results of the furnace temperature data obtained from other temperature sensors and the corresponding preset heating temperature curves. This reduces the impact of inaccurate data or simply excluding abnormal data on the accuracy of real-time furnace temperature calculation, thereby reducing the impact on temperature control effect and avoiding material waste caused by shutdown. Attached Figure Description

[0018] Figure 1 This is a flowchart of a graphitization furnace temperature control method according to an embodiment of this application.

[0019] Figure 2 This is a schematic block diagram of the temperature control device for a graphitization furnace according to an embodiment of this application.

[0020] Figure 3 This is a schematic block diagram illustrating the control relationship in an embodiment of this application.

[0021] Figure 4 This is a schematic block diagram of a computer device according to an embodiment of this application. Detailed Implementation

[0022] To explain in detail the technical content, structural features, objectives and effects of this application, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0023] Example 1 Please see Figure 1 This embodiment discloses a method for controlling the temperature of a graphitization furnace, including: S1. During the heating process in the graphitization furnace, the temperature data collected by each temperature sensor 80 is used to determine whether there is an abnormal temperature sensor 80. If the determination result is that there is an abnormal temperature sensor 80, then proceed to step S2.

[0024] Understandably, if the judgment result indicates that there is no abnormal temperature sensor 80, then the subsequent operation will proceed according to the normal temperature control procedure.

[0025] In some implementations, determining whether there is an abnormal temperature sensor 80 based on the temperature data collected by each temperature sensor 80 includes: The current temperature curves obtained by each temperature sensor 80 are compared. If the current temperature curve corresponding to one of the temperature sensors 80 does not show a consistent trend with the current temperature curves corresponding to the other temperature sensors 80, then the temperature sensor 80 is considered to be abnormal.

[0026] It should be noted that "the current temperature curve corresponding to one of the temperature sensors 80 has a different trend than the current temperature curves corresponding to other temperature sensors 80" means that the current temperature curves corresponding to all other temperature sensors 80 have the same trend. If two or more trends appear in the current temperature curves, it is normal to need to stop the machine for maintenance.

[0027] It should be noted that the criteria for determining whether the current temperature curve corresponding to one temperature sensor 80 is consistent with the current temperature curve corresponding to other temperature sensors 80 can be set by those skilled in the art based on the actual situation.

[0028] For example, the data can be compared in the same coordinate system. The temperature data sequence obtained from a single temperature sensor 80 can be connected to form the current temperature curve. Then, the similarity of each current temperature curve can be compared (similarity means consistency). The similarity judgment can be based on multiple factors, such as the overall trend (including the slope of each segment of the overall trend) and the local trend (including the slope of the local trend). For example, the overall trend can be an initial increase followed by a decrease. If the overall trend of each current temperature curve is the same and the inflection points are the same or close in position (e.g., no more than two coordinate points, i.e., two sampling points), then the overall trend is considered consistent. If the overall trend of the current temperature curve of one temperature sensor 80 is inconsistent with the overall trend of the current temperature curves of other temperature sensors 80, then the temperature sensor 80 can be considered abnormal. For example, inconsistent overall trends could be: the overall trend of other current temperature curves is first rising and then falling, and the deviation of the slope of each segment is within a set range, while the overall trend inflection point deviates from the set range; while the trend of another current temperature curve is first rising and then remaining stable; or, the slope of another current temperature curve deviates significantly from the slope of other current temperature curves (the deviation can be set based on actual conditions); or, the overall trend inflection point of another current temperature curve deviates significantly from the overall trend inflection point of other current temperature curves, then the other temperature sensor 80 is considered abnormal; and so on. The overall trend ignores the local trend, but if the current temperature curve of one temperature sensor 80 has multiple local trends that are inconsistent with the local trends of the corresponding time period of the current temperature curve of other temperature sensors 80, then the temperature sensor 80 is likely to be abnormal. Therefore, in addition to considering the consistency of the overall trend, the consistency of the local trend can also be considered. Furthermore, to more promptly detect abnormal temperatures at the temperature sensor 80, the current temperature curve can be set to a shorter duration. That is, a current temperature curve is generated and compared after every n temperature data points are collected, allowing for consideration of only the overall trend. It should be noted that the above is merely an illustrative example; those skilled in the art can adjust the settings based on actual circumstances to determine the consistency of the current temperature curve's trend.

[0029] Specifically, the current temperature curve can be formed based on temperature data within the most recent set time period, such as 1 to 3 minutes.

[0030] Specifically, the current temperature profile can be formed based on a set number of the latest collected temperature data.

[0031] In some implementations, determining whether there is an abnormal temperature sensor 80 based on the temperature data collected by each temperature sensor 80 includes: The continuous multiple temperature data acquired in real time based on temperature sensor 80 are compared with the continuous multiple average temperature data at corresponding times on the historical average temperature curve acquired based on temperature sensor 80. If the difference between a set number of temperature data points and the corresponding average temperature data point in a series of consecutive temperature data points is outside the preset range, then the corresponding temperature sensor 80 is considered abnormal.

[0032] For example, assuming the number of consecutive temperature data points is 20, the set number can be set to 5.

[0033] It should be noted that the historical average temperature curve can be continuously iterated. The historical average temperature curve can always be obtained by averaging the most recent n historical temperature curves of temperature sensor 80. In addition, the curves collected when temperature sensor 80 is abnormal need to be excluded.

[0034] In some implementations, determining whether there is an abnormal temperature sensor 80 based on the temperature data collected by each temperature sensor 80 includes: The current temperature curve obtained in real time based on temperature sensor 80 is compared with the historical average temperature curve obtained based on temperature sensor 80. If the current temperature curve corresponding to temperature sensor 80 is inconsistent with the corresponding segment of the historical average temperature curve, then temperature sensor 80 is considered to be abnormal.

[0035] As for how to determine whether the current temperature curve corresponding to temperature sensor 80 is consistent with the corresponding segment of the historical average temperature curve, this is known to those skilled in the art, and they can set it according to the actual situation, so it will not be elaborated here. In addition, you can refer to the exemplary description above on "how to determine whether the changing trend of the current temperature curve corresponding to one temperature sensor 80 is consistent with the changing trend of the current temperature curve corresponding to other temperature sensors 80".

[0036] It should be noted that the method for determining whether the temperature sensor 80 is abnormal is not limited to the above method. The above is just an example. Other methods or other methods can be used to make the judgment. For example, if the temperature sensor 80 is completely unable to perform the acquisition function and the control system cannot obtain temperature data, then the temperature sensor 80 is considered abnormal.

[0037] S2, the furnace temperature data is obtained by averaging the current temperature data obtained in real time from other temperature sensors 80.

[0038] Specifically, the aforementioned average can be a weighted average. How to perform a weighted average is known to those skilled in the art and will not be elaborated upon here.

[0039] S3. Compare the furnace temperature data with the preset temperature data at the corresponding time of the preset heating temperature curve. There are multiple preset heating temperature curves. For any case where one temperature sensor 80 is abnormal and the other temperature sensors 80 are normal, set the corresponding preset heating temperature curves respectively.

[0040] It should be noted that a preset heating temperature curve is usually stored. During subsequent heating production, the average of the temperature data acquired in real time by each temperature sensor 80 is compared with the preset temperature data at the corresponding time point on the preset heating temperature curve. If the deviation is large, the output power of the heating device will be adjusted based on the deviation value. However, since the preset heating temperature curve is set based on each sampling point, the comparison also involves averaging the temperature data acquired in real time by each temperature sensor 80 and comparing it with the preset heating temperature curve. Therefore, if a temperature sensor 80 malfunctions, causing inaccurate data or failing to acquire data, the original method of averaging the data from all temperature sensors 80 and comparing it with the same preset heating temperature curve will affect the accuracy of the furnace temperature data calculation, thus affecting the comparison results.

[0041] Based on this, the embodiments of this application propose that, in addition to the preset heating temperature curve in the prior art (i.e., the curve when all temperature sensors 80 are normal, which can be defined as the standard heating temperature curve), multiple other preset heating temperature curves are also stored. That is, for any one temperature sensor 80 that is abnormal and the other temperature sensors 80 are normal, corresponding preset heating temperature curves are set respectively.

[0042] To facilitate accurate understanding of the statement "For the situation where any one temperature sensor is malfunctioning at 80°C while other temperature sensors are functioning normally at 80°C, corresponding preset heating temperature curves are set respectively," an example is given below: Suppose there are 6 temperature sensors 80, namely a1, a2, a3, a4, a5, and a6.

[0043] For all temperature sensors a1, a2, a3, a4, a5, and a6 functioning normally, a corresponding standard heating temperature curve b0 is set. For the case where a1 is abnormal but the others are normal, a corresponding preset heating temperature curve b1 is set; for the case where a2 is abnormal but the others are normal, a corresponding preset heating temperature curve b2 is set; for the case where a3 is abnormal but the others are normal, a corresponding preset heating temperature curve b3 is set; for the case where a4 is abnormal but the others are normal, a corresponding preset heating temperature curve b4 is set; for the case where a5 is abnormal but the others are normal, a corresponding preset heating temperature curve b5 is set; and for the case where a6 is abnormal but the others are normal, a corresponding preset heating temperature curve b6 is set. During the heating production process, if an a1 abnormality is detected, the average of the temperature data obtained from the other temperature sensors a2, a3, a4, a5, and a6 is compared with the preset heating temperature curve b1, rather than comparing it with the preset heating temperature curve b0.

[0044] Other preset heating temperature curves based on the abnormal setting of temperature sensor 80 can be obtained synchronously in accordance with the existing method for obtaining preset heating temperature curves. Specifically, the preset heating temperature curves can be obtained by averaging the data from 3 to 5 batches (i.e., processing 3 to 5 batches of products) using the same raw materials, the same furnace load, and the same target temperature. For example, during the first batch, the average of the temperature data obtained in real time from all temperature sensors a1, a2, a3, a4, a5, and a6 is used to obtain the first average temperature data. The first curve is obtained based on the first average temperature data sequence obtained during the processing. The same method is used to obtain the four first curves for the second to fifth batches, and then the average of the first curves is used to obtain the standard heating temperature curve. During the first batch, the average of the temperature data obtained in real time from temperature sensors a2, a3, a4, a5, and a6 is used to obtain the second average temperature data. The second curve is obtained based on the second average temperature data sequence obtained during the processing. The same method is used to obtain the four second curves for the second to fifth batches. Then, the average of each second curve is taken to obtain the first preset heating temperature curve. When the temperature sensor a1 malfunctions, it can be compared based on this first preset heating temperature curve. When running the first furnace, the average of the temperature data obtained in real time by temperature sensors a1, a3, a4, a5, and a6 is taken to obtain the third average temperature data. The third curve is obtained based on the third average temperature data sequence obtained during the processing. The same method is used to obtain the four third curves for running the second to fifth furnaces. Then, the average of each third curve is taken to obtain the second preset heating temperature curve. When the temperature sensor a2 malfunctions, it can be compared based on this second preset heating temperature curve. By analogy, the third, fourth, fifth, and sixth preset heating temperature curves are obtained to be used as comparison objects when the corresponding temperature sensor 80 malfunctions.

[0045] In summary, other preset heating temperature profiles based on the existence of a temperature sensor 80 malfunction can be obtained as follows: During the processing of each batch from the 1st to the Mth batch (M can be 3 to 5, etc.), the average temperature data obtained in real time from all N temperature sensors 80 (i.e., the number of temperature sensors 80 is N, where N is multiple) is averaged to obtain the normal average temperature data. The normal condition curve (i.e., the curve when all temperature sensors 80 are normal) is obtained based on the normal average temperature data sequence obtained during the processing. The standard heating temperature curve is obtained by averaging the normal condition curves obtained from each batch. In addition, the N temperature sensors 80 are arbitrarily combined to obtain N different combinations, each combination including N-1 temperature sensors 80. The abnormal average temperature data (only referring to the data when one temperature sensor 80 is missing from the calculation, and there are no other abnormalities) is obtained by averaging the temperature data obtained in real time from all temperature sensors 80 in any combination. The abnormal condition curve (only referring to the curve when one temperature sensor 80 is missing from the calculation, and there are no other abnormalities) is obtained based on the abnormal average temperature data sequence obtained during the processing. The corresponding preset heating temperature curve is obtained by averaging the abnormal condition curves obtained from each batch. In this way, N preset heating temperature curves can be obtained.

[0046] Processing is carried out under the same processing conditions (raw materials, furnace charge, output, target temperature, etc. are all the same) from the first furnace to the Mth furnace.

[0047] Using the above method, various preset heating temperature curves can be obtained simultaneously with the standard heating temperature curve, and multiple curves can be calculated based on the synchronously acquired temperature data.

[0048] It should be noted that the first furnace does not necessarily refer to the first furnace in the absolute sense during actual production, but should be understood as the first furnace in the M furnaces in the embodiments of this application, which is usually in the initial stage.

[0049] Typically, during furnace runs to establish preset heating temperature curves, the average of temperature data collected in real time from different acquisition locations is a weighted average, meaning each data point has its own weight. However, when establishing different preset heating temperature curves, the weight of the real-time temperature data acquired by each temperature sensor 80 in different combinations is based on the weights of all temperature sensors 80 in that combination. The weights of temperature data from the same acquisition location may differ, and technicians can set them accordingly. After acquiring each preset heating temperature curve and using it for subsequent production temperature control, the weighted average of the temperature data can be calculated based on whether all temperature sensors 80 are functioning correctly or if one temperature sensor 80 is malfunctioning, and which sensor is malfunctioning. In this case, a set of weight values ​​corresponding to the preset heating temperature curve established during the furnace run can be selected.

[0050] S4. Adjust the output power of the heating device of the graphitization furnace according to the comparison results.

[0051] In some implementations, if the determination result indicates the presence of an abnormal temperature sensor 80 and the number of abnormal temperature sensors 80 is greater than two, the system is shut down and an alarm is triggered. When two or more temperature sensors 80 are determined to be abnormal, one possibility is that they are indeed abnormal. In this case, due to the excessive number of abnormalities, the method of this embodiment is not suitable. Another possibility is that the furnace environment is abnormal. Therefore, in this case, it is best to shut down the system for inspection and trigger an alarm to alert the operators. That is, this embodiment is mainly applicable to the situation where one temperature sensor 80 is abnormal.

[0052] The above-mentioned graphitization furnace temperature control method can be implemented based on the graphitization furnace equipment's control system. The control system generally includes a host computer 40 and a PLC 50 (such as...). Figure 3 As shown in the figure, it is mainly based on the host computer 40. The PLC 50 can be responsible for receiving the collected temperature data and uploading it to the host computer 40, as well as receiving instructions from the host computer 40 to adjust the output power of the heating device 70. Of course, it is not limited to this.

[0053] In this embodiment, multiple preset heating temperature curves are pre-stored. One preset heating temperature curve is set for all temperature sensors 80 operating normally, and corresponding preset heating temperature curves are set for all scenarios where one temperature sensor 80 is abnormal while the other temperature sensors 80 are normal. During the heating production process in the graphitization furnace, if an abnormal temperature sensor 80 is found, that abnormal temperature sensor 80 will be excluded. The furnace temperature data is obtained by averaging the current temperature data acquired in real time from the other temperature sensors 80. Then, the furnace temperature data is compared with the preset temperature data at the corresponding moment of the preset heating temperature curve (the preset heating temperature curve corresponding to the abnormal temperature sensor 80), and the output power of the heating device of the graphitization furnace is adjusted according to the comparison result. Since this embodiment pre-sets corresponding preset heating temperature curves for cases where any one temperature sensor 80 is abnormal while the other temperature sensors 80 are normal, when performing furnace temperature control, if there is an abnormal temperature sensor 80, the abnormal temperature sensor 80 can be excluded, and the output power of the heating device can be adjusted based on the comparison results of the furnace temperature data obtained from the other temperature sensors 80 and the corresponding preset heating temperature curves. This reduces the impact of inaccurate data or simply excluding abnormal data on the accuracy of real-time furnace temperature calculation, thereby reducing the impact on temperature control effect and avoiding material waste caused by shutdown.

[0054] Example 2 Please see Figure 2 This embodiment discloses a temperature control device for a graphitization furnace, comprising: The judgment module 201 is used to determine whether there is an abnormal temperature sensor 80 based on the temperature data collected by each temperature sensor 80 during the heating production process of the graphitization furnace. The calculation module 202 is used to calculate the furnace temperature data by averaging the current temperature data obtained in real time from other temperature sensors 80 if the judgment result is that there is an abnormal temperature sensor 80. The comparison module 203 is used to compare the furnace temperature data with the preset temperature data at the corresponding time of the preset heating temperature curve. There are multiple preset heating temperature curves. For any case where one temperature sensor 80 is abnormal and the other temperature sensors 80 are normal, the corresponding preset heating temperature curves are set respectively. The adjustment module 204 is used to adjust the output power of the heating device of the graphitization furnace according to the comparison results.

[0055] Please combine Figure 3Specifically, the graphitization furnace temperature control device can be implemented based on the host computer 40 of the graphitization furnace equipment. The host computer 40 can acquire temperature data sampled from the furnace body via PLC 50, and can control the output power of the heating device 70 by sending commands to PLC 50. PLC 50 communicates with temperature sensor 80 and acquires the temperature data collected by temperature sensor 80. Of course, it is also possible that the graphitization furnace temperature control device is implemented based on PLC 50.

[0056] More specifically, the graphitization furnace equipment includes a power regulating device 60, which can be connected between the PLC 50 and the heating device 70. The power regulating device 60 adjusts the output power of the heating device 70 based on the control signal of the PLC 50. The power regulating device is known to those skilled in the art and will not be described in detail here.

[0057] Specifically, the heating device 70 includes a negative electrode and a positive electrode. The heating device 70 is known to those skilled in the art and will not be described in detail here.

[0058] In this embodiment, multiple preset heating temperature curves are pre-stored. One preset heating temperature curve is set for all temperature sensors 80 operating normally, and corresponding preset heating temperature curves are set for all scenarios where one temperature sensor 80 is abnormal while the other temperature sensors 80 are normal. During the heating production process in the graphitization furnace, if an abnormal temperature sensor 80 is found, that abnormal temperature sensor 80 will be excluded. The furnace temperature data is obtained by averaging the current temperature data acquired in real time from the other temperature sensors 80. Then, the furnace temperature data is compared with the preset temperature data at the corresponding moment of the preset heating temperature curve (the preset heating temperature curve corresponding to the abnormal temperature sensor 80), and the output power of the heating device of the graphitization furnace is adjusted according to the comparison result. Since this embodiment pre-sets corresponding preset heating temperature curves for cases where any one temperature sensor 80 is abnormal while the other temperature sensors 80 are normal, when performing furnace temperature control, if there is an abnormal temperature sensor 80, the abnormal temperature sensor 80 can be excluded, and the output power of the heating device can be adjusted based on the comparison results of the furnace temperature data obtained from the other temperature sensors 80 and the corresponding preset heating temperature curves. This reduces the impact of inaccurate data or simply excluding abnormal data on the accuracy of real-time furnace temperature calculation, thereby reducing the impact on temperature control effect and avoiding material waste caused by shutdown.

[0059] Example 3 Please see Figure 4This embodiment discloses a computer device, including a memory 302 and a processor 301. The memory 302 is connected to the processor 301. The memory 302 stores a computer program, and the processor 301 calls the computer program to cause the computer device to execute the graphitization furnace temperature control method described in Embodiment 1. Furthermore, the computer device may also include at least one communication bus 303. The communication bus 303 is used to enable communication between components. The memory 302 may be a high-speed RAM or a non-volatile memory, such as at least one disk storage device.

[0060] Example 4 This embodiment discloses a computer-readable storage medium storing a computer program adapted to be loaded by a processor and executed by the graphitization furnace temperature control method described in Embodiment 1.

[0061] Example 5 This embodiment provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the graphitization furnace temperature control method described in Embodiment 1.

[0062] It should be understood that, in the embodiments of this application, the processor may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0063] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by hardware related to computer program instructions. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0064] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0065] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the scope of this application shall still fall within the scope of this application.

Claims

1. A method for controlling the temperature of a graphitization furnace, characterized in that, include: During the heating process in the graphitization furnace, the presence of any abnormal temperature sensors is determined based on the temperature data collected by each temperature sensor. If the determination result is that there is an abnormal temperature sensor, the furnace temperature data will be obtained by averaging the current temperature data obtained in real time from the other temperature sensors. The furnace temperature data is compared with the preset temperature data at the corresponding time of the preset heating temperature curve. The preset heating temperature curve includes multiple curves. For any one of the temperature sensors is abnormal while the other temperature sensors are normal, a corresponding preset heating temperature curve is set. Adjust the output power of the heating device of the graphitization furnace according to the comparison results.

2. The temperature control method for a graphitization furnace as described in claim 1, characterized in that, The temperature sensors used to determine whether there are any abnormalities based on the temperature data collected by each temperature sensor include: The current temperature curves obtained from each of the aforementioned temperature sensors are compared. If the current temperature curve corresponding to one of the temperature sensors does not show a consistent trend with the current temperature curves corresponding to the other temperature sensors, then the temperature sensor is considered to be malfunctioning.

3. The temperature control method for a graphitization furnace as described in claim 2, characterized in that, The current temperature curve is formed based on temperature data within the most recent set time period; or... The current temperature curve is formed based on the latest collected temperature data of a set quantity.

4. The temperature control method for a graphitization furnace as described in claim 1, characterized in that, The temperature sensors used to determine whether there are any abnormalities based on the temperature data collected by each temperature sensor include: The continuous multiple temperature data acquired in real time based on the temperature sensor are compared with the continuous multiple average temperature data at the corresponding time on the historical average temperature curve acquired based on the temperature sensor. If a set number of temperature data points in a series of consecutive temperature data points have a difference from the corresponding average temperature data point that is outside a preset range, then the corresponding temperature sensor is considered malfunctioning; or, The temperature sensors used to determine whether there are any abnormalities based on the temperature data collected by each temperature sensor include: The current temperature curve obtained in real time based on the temperature sensor is compared with the historical average temperature curve obtained based on the temperature sensor. If the current temperature curve corresponding to the temperature sensor is inconsistent with the corresponding historical average temperature curve, then the temperature sensor is considered to be abnormal.

5. The temperature control method for a graphitization furnace as described in claim 1, characterized in that, During the processing of each of the first to the Mth heats, The average temperature data is obtained by averaging the temperature data acquired in real time by all N temperature sensors that are kept normal. The normal condition curve is obtained by averaging the normal average temperature data sequence obtained during the processing. The standard heating temperature curve is obtained by averaging the normal condition curves obtained from each of the furnace processing. as well as, The N temperature sensors are arbitrarily combined to obtain N different combinations. Each combination includes N-1 temperature sensors. The abnormal average temperature data is obtained by averaging the temperature data acquired in real time from all the temperature sensors in any combination. An abnormal situation curve is obtained based on the abnormal average temperature data sequence obtained during the processing. The corresponding preset heating temperature curve is obtained by averaging the abnormal situation curves obtained from each of the furnace processing.

6. The temperature control method for a graphitization furnace as described in claim 5, characterized in that, Processing is carried out under the same processing conditions for batches 1 through M.

7. The temperature control method for a graphitization furnace as described in claim 5, characterized in that, In different combinations, the weight of the temperature data acquired in real time by each temperature sensor in the combination is obtained based on all temperature sensors in that combination.

8. A temperature control device for a graphitization furnace, characterized in that, include: The judgment module is used to determine whether there is an abnormal temperature sensor during the heating production process of the graphitization furnace based on the temperature data collected by each temperature sensor. The calculation module is used to calculate the furnace temperature data by averaging the current temperature data obtained in real time from the other temperature sensors if the judgment result is that there is an abnormal temperature sensor. The comparison module is used to compare the furnace temperature data with the preset temperature data at the corresponding time of the preset heating temperature curve. The preset heating temperature curve includes multiple curves. For any one of the temperature sensors is abnormal while the other temperature sensors are normal, the corresponding preset heating temperature curve is set respectively. An adjustment module is used to adjust the output power of the heating device of the graphitization furnace according to the comparison results.

9. A computer device, characterized in that, Including memory and processor; The memory is connected to the processor, the memory is used to store computer programs, and the processor is used to call the computer programs so that the computer device executes the graphitization furnace temperature control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted to be loaded by a processor and executed as described in any one of claims 1 to 7.

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