A combustion temperature control method and a flame gun

Abstract

The application discloses a combustion temperature control method and a flame gun, and the method comprises the following steps: collecting multi-point temperature distribution data of a mold surface at a current time; determining the average temperature and the temperature uniformity index of the mold according to the multi-point temperature distribution data; obtaining a manual control parameter representing a manual control intention inputted externally; determining an automatic control amount at the current time according to the temperature deviation between the average temperature and a preset target temperature and the change rate of the temperature deviation; determining a basic weight factor according to the temperature uniformity index, the temperature deviation and the change rate of the temperature deviation; determining a final dynamic weight factor according to the basic weight factor and a manual intervention weight coefficient; weighting and fusing the automatic control amount and the manual control amount according to the final dynamic weight factor to obtain a final control amount at the current time; and adjusting the opening degree of a proportional adjusting valve according to the final control amount. The application can effectively improve the temperature uniformity of the mold surface while ensuring the temperature precision.

Description

Technical Field

[0001] This application generally relates to the field of heat treatment technology. More specifically, this application relates to a method for controlling combustion temperature. Furthermore, this application also relates to a flamethrower. Background Technology

[0002] Combustion temperature control is a crucial step in the injection mold preheating process, and its accuracy and uniformity directly affect mold life and product quality. During mold preheating, it is typically necessary to heat the mold surface to a preset target temperature and maintain a uniform temperature distribution. Common control methods can be categorized into manual and automatic control.

[0003] In existing technologies, manual control relies on operators directly adjusting the gas valve opening based on experience, and manual intervention is made by observing the temperature feedback of the mold surface. Automatic control typically uses a single-point thermocouple to collect the temperature of a fixed point on the mold, using the deviation between that point's temperature and the target temperature as input. A PID algorithm calculates the control quantity, driving a proportional valve to adjust the gas flow rate, maintaining the mold temperature near the set value. However, single-point temperature measurement is difficult to reflect the overall temperature distribution of the mold surface, easily leading to poor temperature uniformity due to localized temperature deviations, which can cause thermal stress concentration and even cracks. Furthermore, there is a lack of effective coordination and matching mechanisms between manual and automatic control; manual intervention and automatic adjustment are independent or even conflicting, making it difficult to leverage the advantages of human-machine collaboration. Moreover, when the overall temperature is close to the target but localized temperature differences exist, traditional control strategies cannot specifically adjust the control bias, limiting further improvement in temperature uniformity.

[0004] Therefore, there is an urgent need to provide a combustion temperature control method so as to effectively improve the temperature uniformity of the mold surface while ensuring temperature accuracy. Summary of the Invention

[0005] In order to at least solve one or more of the technical problems mentioned above, this application proposes a combustion temperature control scheme for flamethrowers in several aspects.

[0006] In a first aspect, this application provides a combustion temperature control method, comprising:

[0007] Collect multi-point temperature distribution data on the mold surface at the current moment; Based on the multi-point temperature distribution data, the average temperature and temperature uniformity index of the mold are determined; Acquire manual control parameters that represent the intention to manually control from external input, the manual control parameters including manual control quantity and manual intervention weight coefficient; The automatic control quantity at the current moment is determined based on the temperature deviation between the average temperature and the preset target temperature, and the rate of change of the temperature deviation. The basic weighting factor is determined based on the temperature uniformity index, the temperature deviation, and the rate of change of the temperature deviation. The final dynamic weight factor is determined based on the basic weight factor and the manual intervention weight coefficient. Based on the final dynamic weighting factor, the automatic control quantity and the manual control quantity are weighted and fused to obtain the final control quantity at the current moment; Adjust the opening degree of the proportional control valve according to the final control value.

[0008] In some embodiments, the multi-point temperature distribution data consists of the regional average temperature of multiple preset areas, which cover key parts of the mold, including cavities, runners, and / or risers.

[0009] In some implementations, collecting multi-point temperature distribution data on the mold surface includes: Thermal images of the mold surface were acquired using an infrared thermal imager. Based on the coordinates of the multiple preset regions in the thermal image, the average temperature of each preset region is extracted. The average temperature of the multiple preset areas is used as the multi-point temperature distribution data.

[0010] In some implementations, the coordinates of the plurality of preset regions in the thermal image are pre-calibrated by the following operation: In the initialization state, the initial thermal image acquired by the infrared thermal imager is obtained; In response to an external input selection operation, the coordinates of the selected rectangular region in the initial thermal image are recorded; The coordinates in the initial thermal image are stored as the coordinates of the preset region.

[0011] In some implementations, the automatic control quantity for the current moment is determined based on the temperature deviation between the average temperature and the preset target temperature, and the rate of change of the temperature deviation, including: Based on the temperature deviation between the average temperature and the preset target temperature, and the rate of change of the temperature deviation, an incremental PID control algorithm with feedforward is used to determine the control increment. Calculate the first sum of the automatic control quantity at the previous moment and the control increment, and use the first sum as the automatic control quantity at the current moment.

[0012] In some implementations, the formula for determining the control increment using an incremental PID control algorithm with feedforward is as follows: ; in, This is the proportionality coefficient. The integral coefficient is... The differential coefficients are... Forward coefficients; , , These represent the temperature deviations at the current moment, the previous moment, and the two moments before that, respectively. The sampling period; and These are the preset target temperatures for the current moment and the previous moment, respectively.

[0013] In some implementations, a basic weighting factor is determined based on the temperature uniformity index, the temperature deviation, and the rate of change of the temperature deviation, including: Determine whether the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold; When the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature deviation, the rate of change of the temperature deviation, the first preset temperature difference threshold, and the second preset temperature difference threshold; wherein, the second preset temperature difference threshold is less than the first preset temperature difference threshold. When the absolute value of the temperature deviation is less than the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature uniformity index and the preset uniformity threshold.

[0014] In some implementations, when the temperature deviation is greater than or equal to the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature deviation, the rate of change of the temperature deviation, the first preset temperature difference threshold, and the second preset temperature difference threshold, including: When the absolute value of the temperature deviation is greater than or equal to the first preset temperature difference threshold and the rate of change of the temperature deviation is less than or equal to the first preset rate of change threshold, the basic weighting factor is determined as the first weighting value. When the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold and less than the first preset temperature difference threshold, the basic weighting factor is obtained by linear interpolation based on the ratio of the absolute value of the temperature deviation between the second preset temperature difference threshold and the first preset temperature difference threshold, and the basic weighting factor increases linearly as the absolute value of the temperature deviation decreases.

[0015] In some implementations, when the absolute value of the temperature deviation is less than the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature uniformity index and the preset uniformity threshold, including: When the absolute value of the temperature deviation is less than the second preset temperature difference threshold and the temperature uniformity index is greater than the preset uniformity threshold, the basic weighting factor is determined as the third weighting value. When the absolute value of the temperature deviation is less than the second preset temperature difference threshold and the temperature uniformity index is less than or equal to the preset uniformity threshold, the basic weighting factor is determined as the fourth weighting value.

[0016] In some implementations, the final dynamic weighting factor is determined based on the basic weighting factor and the manual intervention weighting coefficient, including: Determine the first product of the manual intervention weight coefficient and the preset coefficient, wherein the preset coefficient is determined by the basic weight factor; Calculate the second sum of the product of the basic weight factor and the first product, and determine the second sum as the final dynamic weight factor.

[0017] In some implementations, the automatic control quantity and the manual control quantity are weighted and fused according to the final dynamic weighting factor to obtain the final control quantity at the current moment, including: Calculate the difference between 1 and the final dynamic weighting factor; Calculate the second product of the difference and the automatic control quantity, and the third product of the final dynamic weighting factor and the manual control quantity; Calculate the third sum of the second product and the third product, and use this third sum as the final control quantity.

[0018] In some embodiments, the method further includes a safety interlock operation, which determines whether to cut off the gas supply and output an alarm based on multi-point temperature distribution data on the mold surface, flame signals and / or gas pressure values.

[0019] In some embodiments, determining whether to cut off the gas supply and output an alarm based on multi-point temperature distribution data on the mold surface includes: Determine whether any temperature values ​​in the multi-point temperature distribution data exceed a preset temperature threshold; When any temperature value in the multi-point temperature distribution data exceeds the preset temperature threshold, the gas supply is cut off and an over-temperature alarm is output.

[0020] In some implementations, determining whether to cut off the gas supply and output alarm based on the flame signal includes: Detect flame signals during ignition and / or operation; If no flame signal is detected within the preset ignition time after the ignition command is issued, the gas supply is cut off and an ignition failure alarm is output. When a flame signal interruption is detected during operation and continues for more than the preset interruption duration, the gas supply is cut off and a flame interruption alarm is output.

[0021] In some implementations, determining whether to cut off the gas supply and output an alarm based on the gas pressure includes: Detect the gas pressure value and determine whether the detected gas pressure value exceeds the preset pressure range; When the detected gas pressure value exceeds the preset pressure range, the gas supply is cut off and an abnormal gas pressure alarm is output.

[0022] In a second aspect, this application provides a flamethrower, comprising: The main control unit is configured to execute the combustion temperature control method described above; The human-computer interaction unit is communicatively connected to the main control unit and is used to receive manual control parameters input by the operator that represent the intention to manually control the operation. The manual control parameters include manual control quantity and manual intervention weight coefficient. A temperature sensing unit, which is communicatively connected to the main control unit, includes an infrared thermal imager for acquiring thermal images of the mold surface. The infrared thermal imager transmits the thermal images to the main control unit so that the main control unit can obtain the multi-point temperature distribution data based on the thermal images. The gas supply and regulation unit is electrically connected to the main control unit and includes a proportional regulating valve that adjusts the gas flow according to the final control quantity, a gas pressure sensor for detecting gas pressure and feeding back the gas pressure value to the main control unit, and a solenoid valve for cutting off the gas supply. The combustion execution unit, electrically connected to the main control unit, includes at least one gas gun. Each gas gun is equipped with an ignition electrode and a flame sensor. The ignition electrode generates an electric spark when it receives an ignition command, and the flame sensor is used to feed back a flame signal to the main control unit.

[0023] By using the combustion temperature control method provided above, this embodiment of the application collects multi-point temperature distribution data on the mold surface and determines the temperature uniformity index, enabling the control system to obtain the overall temperature field information of the mold and avoid ignoring local temperature deviations due to single-point temperature measurement. By calculating the automatic control quantity based on the deviation between the average temperature and the target temperature and its rate of change, it helps to ensure the temperature accuracy during the heating process. By determining the basic weighting factor based on the temperature uniformity index, temperature deviation and its rate of change, and combining it with the manual intervention weighting coefficient to determine the final dynamic weighting factor, the control strategy can be dynamically adjusted according to the temperature distribution state and the operator's intention. By weighting and fusing the automatic control quantity and the manual control quantity according to the final dynamic weighting factor, the coordination and matching of operator experience and automatic adjustment are achieved, which helps to improve temperature uniformity when the temperature is close to the target. Attached Figure Description

[0024] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of this application are illustrated by way of example and not limitation, and the same or corresponding reference numerals denote the same or corresponding parts, wherein: Figure 1 An exemplary flowchart of a combustion temperature control method 100 according to an embodiment of this application is shown; Figure 2 An exemplary flowchart illustrating the process of determining the basic weighting factor in an embodiment of this application is shown; Figure 3 An exemplary structural block diagram of a flamethrower according to an embodiment of this application is shown. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] It should be understood that the terms "comprising" and "including" used in the specification and claims of this application indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0027] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0028] As used in this specification and claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0029] The specific embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0030] Figure 1 An exemplary flowchart of a combustion temperature control method 100 according to an embodiment of this application is shown.

[0031] like Figure 1 As shown, in step S101, multi-point temperature distribution data on the surface of the mold at the current moment can be collected.

[0032] In this embodiment of the application, step S101 is used to obtain temperature information at different locations on the mold surface to comprehensively reflect the temperature field distribution of the mold and provide basic data for subsequent average temperature calculation and temperature uniformity evaluation.

[0033] Specifically, the multi-point temperature distribution data consists of the average temperature of multiple preset areas, which preferably cover key parts of the mold, including cavities, runners, and / or risers. By setting temperature measurement areas at these key parts, it is possible to specifically monitor the locations most prone to temperature differences and thermal stress during mold preheating.

[0034] In some optional implementations, the following steps can be performed to acquire multi-point temperature distribution data on the mold surface: First, a thermal image of the mold surface is acquired using an infrared thermal imager. The infrared thermal imager acquires thermal images at a fixed sampling period. The acquired thermal image data undergoes preprocessing, which may include at least one of bad pixel correction and median filtering to improve the accuracy and stability of the temperature data. Then, based on the coordinates of multiple preset regions in the thermal image, the average temperature of each preset region is extracted. This average temperature is the arithmetic mean of the temperatures of all pixels within that region. Finally, the average temperatures of the multiple preset regions are used as multi-point temperature distribution data.

[0035] In a specific application example of this application, the infrared thermal imager can have a temperature resolution of less than 0.05°C and a field of view of 45°×35°. It is mounted on an adjustable bracket approximately 1.5 meters from the mold surface, with the lens facing the heated working surface of the mold. It communicates with the main control unit via a communication interface to transmit the acquired thermal images to the main control unit. The infrared thermal imager synchronously acquires thermal images with a resolution of 640×512 pixels at a sampling period of 50 milliseconds. The temperature value of each pixel undergoes bad pixel correction and 3×3 median filtering preprocessing to eliminate noise interference.

[0036] In some alternative implementations, the regional average temperature can be calculated using an arithmetic mean, which is the arithmetic mean of the temperatures of all pixels in the region divided by the total number of pixels in the region.

[0037] In some optional implementations, the coordinates of multiple preset regions in the thermal image can be pre-calibrated through the following operations: First, in the initialization state, acquire the initial thermal image collected by the infrared thermal imager. Then, in response to the operator's externally input selection operation, record the coordinates of the selected rectangular region in the initial thermal image. Next, store the coordinates in the initial thermal image as the coordinates of the preset regions and write them to non-volatile memory. This allows the system to directly load the stored coordinate data for temperature extraction without recalibration after power failure or mold switching. The coordinate storage employs a power-off protection mechanism to ensure that configuration data is not lost after system power failure.

[0038] In a specific application example of this application, the operator can access the area calibration function interface through the human-machine interface unit. The system enters this interface in the initialization state (e.g., during the first run or when changing molds). Six rectangular areas are sequentially selected on the displayed real-time thermal image, corresponding to key parts of the mold such as the cavity, runner, and riser. The system marks the selected areas with green borders on the image in real time, providing visual feedback to the operator. After each area is selected, the main control unit records the coordinates of the four vertices of the area in the pixel coordinate system in real time, forming a structured data block. This data block may include information such as the area identifier, the pixel coordinates of the four vertices, and the total number of pixels in the area, and is stored in non-volatile memory. The vertex coordinates are recorded with a precision of single pixel level to ensure the accuracy of area extraction.

[0039] Following step S101, in step S102, the average temperature and temperature uniformity index of the mold are determined based on the multi-point temperature distribution data.

[0040] The average temperature is the arithmetic mean of the regional average temperatures of multiple preset areas, used to characterize the overall thermal state level of the mold surface. The temperature uniformity index is used to quantitatively reflect the uniformity of the temperature distribution on the mold surface. For example, it can be the standard deviation of the regional average temperatures of multiple preset areas. The smaller the value, the more uniform the temperature distribution; the larger the value, the more uneven the temperature distribution.

[0041] In a specific application example of this application, when six preset zones are set, the average temperature It can be obtained by calculating the arithmetic mean of the average temperatures of the six regions, and the formula is expressed as: ,in Let be the average temperature of the i-th preset region.

[0042] The regional average temperature is calculated using the arithmetic mean formula: ;in For the first The total number of pixels in a preset area. For the first in the preset area Temperature value of each pixel.

[0043] Temperature uniformity index This can be obtained by calculating the standard deviation of the average temperature of the six regions. The formula is as follows: Temperature uniformity index It plays a crucial role in the control system, and its value reflects the uniformity of temperature distribution on the mold surface.

[0044] In step S103, manual control parameters representing the operator's intention to manually control are obtained from external input.

[0045] Manual control parameters can include manual control quantity and manual intervention weighting coefficient. The manual intervention weighting coefficient is used to adjust the proportion of manual control quantity in the final dynamic weighting factor, reflecting the operator's preference for manual control. The manual control quantity is mapped from the knob position value set by the operator and directly reflects the operator's desired heating intensity.

[0046] In a specific application example of this application, the manual intervention weight coefficient can be a dimensionless parameter ranging from 0 to 1 in 0.01 increments, and the knob position value can be an integer ranging from 0 to 100, mapped to a manual control quantity in percentage form. The operator inputs the above parameters through the human-machine interface unit, and the main control unit reads and stores them in its internal registers in real time for subsequent calculations.

[0047] In step S104, the automatic control quantity at the current moment is determined based on the temperature deviation between the average temperature and the preset target temperature, as well as the rate of change of the temperature deviation.

[0048] Specifically, the control increment can be determined first by using an incremental PID control algorithm with feedforward based on the temperature deviation between the average temperature and the preset target temperature, as well as the rate of change of the temperature deviation. Then, the sum of the automatic control quantity and the control increment at the previous moment (which can be called the first sum for ease of understanding) is calculated, and this first sum is used as the automatic control quantity at the current moment.

[0049] In a specific application example of this application, temperature deviation is defined as the difference between the average temperature and the preset target temperature, in degrees Celsius. The rate of change of temperature deviation is defined as the ratio of the difference between the temperature deviation at the current moment and the temperature deviation at the previous moment to the sampling period, expressed by the following formula: ,in The temperature deviation at the current moment. This represents the temperature deviation from the previous moment. The sampling period is defined as follows. It is understood that the current moment, the previous moment, and the two moments prior in this article all refer to the sampling moment of the infrared thermal imager.

[0050] In practice, the formula for determining the control increment using an incremental PID control algorithm with feedforward is as follows: ; in, This is the proportionality coefficient. The integral coefficient is... The differential coefficients are... Forward coefficients; , , These represent the temperature deviations at the current moment, the previous moment, and the two moments before that, respectively. The sampling period can be 50 milliseconds; and These are the preset target temperatures for the current and previous moments, respectively. The automatic control quantity for the current moment is obtained by summing the automatic control quantity for the previous moment and the current control increment. If the calculated result is less than 0, it is taken as 0; if it is greater than 100, it is taken as 100. That is, the value range of the automatic control quantity is limited to between 0% and 100%.

[0051] The proportional term is used to eliminate the current deviation, the integral term to eliminate steady-state error, the derivative term to suppress oscillations, and the feedforward term to improve the system's response speed to changes in the preset target temperature. In a specific application example of this application, after tuning using the Ziegler-Nichols critical proportional method and fine-tuning in the field, the PID parameters can be determined as follows: =2.5, =0.05 per second, =10 seconds, =0.3, these parameter values ​​have been verified to be effective within the preset target temperature range of 250°C to 350°C.

[0052] In step S105, the basic weighting factor is determined based on the temperature uniformity index, temperature deviation, and the rate of change of temperature deviation.

[0053] The basic weighting factor is used to adjust the weighting ratio of manual control and automatic control in the subsequent control fusion stage, so that the system can adaptively adjust the priority of manual intervention in the human-machine collaboration strategy according to the magnitude of the deviation, dynamic trend and spatial uniformity of the current thermal state.

[0054] Specifically, the following can be performed at step S105: Figure 2 Steps S1051 to S1053 shown are used to determine the basic weighting factors.

[0055] Figure 2 An exemplary flowchart illustrating the process of determining the basic weighting factors in an embodiment of this application is shown. Figure 2 As shown, in step S1051, it is determined whether the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold.

[0056] When the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold, step S1052 is executed to determine the basic weighting factor based on the temperature deviation, the rate of change of the temperature deviation, the first preset temperature difference threshold, and the second preset temperature difference threshold. The second preset temperature difference threshold is less than the first preset temperature difference threshold.

[0057] In step S1052, the following two cases can be further divided: In one case, when the absolute value of the temperature deviation... Greater than or equal to the first preset temperature difference threshold And the rate of change of temperature deviation Less than or equal to the first preset rate of change threshold At that time, the basic weighting factor Determined as the first weight value This conditional branch corresponds to a system operating condition with large deviations but tending towards stability. In this case, the system determines that the current temperature deviates significantly from the target but the change is slowing down. A lower weight value can be used to reduce human intervention and avoid excessive disturbance. This logic is expressed as a Boolean condition: If... and ,but .

[0058] In another case, when the absolute value of the temperature deviation... Greater than or equal to the second preset temperature difference threshold And less than the first preset temperature difference threshold At that time, based on the ratio of the absolute value of the temperature deviation between the second preset temperature difference threshold and the first preset temperature difference threshold, the basic weighting factor is obtained through linear interpolation, and the basic weighting factor increases linearly as the absolute value of the temperature deviation decreases. This conditional branch corresponds to the continuous adjustment condition in the medium deviation range. The basic weighting factor increases linearly as the absolute value of the temperature deviation decreases, so that the closer the temperature is to the target value, the higher the weight of manual intervention. This achieves a smooth transition between automatic adjustment efficiency and manual fine-tuning flexibility within the medium deviation range.

[0059] In a specific application example, the above linear interpolation can be calculated according to the following formula: ;in, The second weight value corresponds to The basic weighting factor at that time; The first weight value corresponds to The basic weighting factor is determined by this formula. This formula ensures that the basic weighting factor increases linearly as the absolute value of the temperature deviation decreases.

[0060] Conversely, when the absolute value of the temperature deviation is less than the second preset temperature difference threshold, step S1053 is executed to determine the basic weighting factor based on the temperature uniformity index and the preset uniformity threshold. This conditional branch corresponds to the small deviation condition, where the overall temperature is close to the target value. The control system further combines the temperature uniformity index to determine whether it is necessary to strengthen manual intervention to optimize the temperature field distribution.

[0061] In step S1053, the following two cases can be further divided: In one case, when the absolute value of the temperature deviation... Less than the second preset temperature difference threshold And temperature uniformity index Greater than the preset uniformity threshold At that time, the basic weighting factor Determined as the third weight value This logic is expressed as a Boolean condition: If and ,but This conditional branch corresponds to operating conditions with small deviations but uneven temperature distribution. The system determines that although the overall temperature is close to the target value, there are significant temperature differences in some areas. A higher weight value can be used to enhance human intervention, enabling operators to exert greater control over the heating strategy.

[0062] In another case, when the absolute value of the temperature deviation... Less than the second preset temperature difference threshold And temperature uniformity index Less than or equal to the preset uniformity threshold At that time, the basic weighting factor Determined as the fourth weight value This logic is expressed as a Boolean condition: If and ,but This conditional branch corresponds to the ideal steady-state condition. The system determines that the mold temperature is close to the target value and is evenly distributed, indicating a stable operating state. A lower weight value can be used to maintain the stable operation of automatic control and avoid unnecessary manual disturbances.

[0063] In step S106, the final dynamic weight factor is determined based on the basic weight factor and the manual intervention weight coefficient.

[0064] Specifically, first determine the product of the manual intervention weight coefficient and the preset coefficient (for ease of distinction, this can be called the first product), where the preset coefficient is determined by the basic weight factor. Then calculate the sum of the basic weight factor and the first product (for ease of distinction, this can be called the second sum), and determine this second sum as the final dynamic weight factor.

[0065] In a specific application example of this application, the final dynamic weighting factor The calculation formula is: Among them, the final dynamic weighting factor The value is a dimensionless numerical value, limited to the range of 0 to 1; basic weighting factor. The system's adaptive weight values ​​range from 0 to 1; manual intervention is required for the weight coefficients. The input parameters set for operators range from 0 to 1; the preset coefficient is... Its physical meaning is the weight margin reserved by the automatic control part of the system.

[0066] It is evident that when the base weight factor is high, the impact of the manual intervention weight coefficient on the final result is relatively compressed; when the base weight factor is low, operators can effectively increase the proportion of manual intervention by adjusting the manual intervention weight coefficient, thus balancing the role of operator experience with control safety. This design respects operator experience while preventing it from overriding the system's autonomous judgment, achieving a balance between safety and flexibility.

[0067] At step S107, the automatic control quantity and the manual control quantity are weighted and fused according to the final dynamic weight factor to obtain the final control quantity at the current moment.

[0068] Specifically, first, the difference between 1 and the final dynamic weighting factor is calculated. Then, the product of this difference and the automatic control quantity (for ease of distinction, it can be called the second product), and the product of the final dynamic weighting factor and the manual control quantity (for ease of distinction, it can be called the third product) are calculated. Then, the sum of the second product and the third product (for ease of distinction, it can be called the third sum) is calculated, and this third sum is used as the final control quantity.

[0069] This step defines the final control quantity. The calculation formula is: Wherein: final control quantity Dimensionless values ​​represent power adjustment commands from the heating device, with their range limited to 0% to 100%; automatic control quantities. For automatic control commands, the unit is percentage (%), representing the heating power demand calculated based on temperature feedback; for manual control commands... This is a manual control command, expressed as a percentage (%), mapped from the knob position value; the final dynamic weighting factor. The fusion weight parameter has a value range of [0,1].

[0070] The weighted fusion calculation described above constitutes a standard convex combination, ensuring that the fusion result always lies between the automatic control quantity and the manual control quantity. When the final dynamic weight factor approaches 0, the system is completely dominated by automatic control; when the final dynamic weight factor approaches 1, the system is completely dominated by manual control; when the final dynamic weight factor is between 0 and 1, the system proportionally fuses the two. This design, while ensuring the stability of automatic control, empowers operators with the ability to effectively intervene under critical operating conditions.

[0071] In practical applications, the calculated final control value can be limited to a range of 0% to 100% to ensure that the heating power command is within a safe and reasonable range.

[0072] Finally, in step S108, the opening of the proportional control valve is adjusted according to the final control value. The final control value can be converted into an analog signal or a pulse width modulation signal to drive the valve core of the proportional control valve to actuate, thereby regulating the gas flow through the proportional control valve and controlling the heating power of the mold.

[0073] In a specific application example of this application, the final control quantity can be converted into a corresponding control signal through an analog output module or a pulse width modulation signal drive circuit. When the final control quantity is 0%, the output signal closes the proportional control valve; when the final control quantity is 100%, the output signal causes the proportional control valve to reach its maximum allowable opening; intermediate values ​​correspond to the corresponding opening according to linear characteristics. This adjustment process is periodically executed by the firmware program of the control system, constituting the final execution link of the temperature closed-loop control.

[0074] In some optional embodiments, the combustion temperature control method provided in this application also includes a safety interlock operation, which can determine whether it is necessary to cut off the gas supply and output an alarm based on multi-point temperature distribution data on the mold surface, flame signal and / or gas pressure value.

[0075] In an optional implementation, determining whether to cut off the gas supply and output an alarm based on the temperature of the mold surface can specifically involve the following operations: determining whether any temperature value in the multi-point temperature distribution data exceeds a preset temperature threshold; when any temperature value in the multi-point temperature distribution data exceeds the preset temperature threshold, cutting off the gas supply and outputting an over-temperature alarm. This logic is expressed as a Boolean condition: the multi-point temperature distribution data contains several temperature measurements. ( ), preset temperature threshold The maximum permissible temperature limit is set; if it exists... Make If the gas supply is interrupted and an alarm is triggered, the gas supply will be cut off and an alarm will be triggered. This measure can quickly respond to local hot spots, making up for the shortcomings of relying solely on average temperature control and improving the thermal safety redundancy of the system.

[0076] In an optional implementation, determining whether to cut off the gas supply and issue an alarm based on the flame signal can specifically involve the following operations: detecting the flame signal during the ignition process and / or operation. The ignition command is issued by the main control unit after receiving the heating start command, triggering the coordinated action of the ignition electrode and the proportional control valve. The flame signal is acquired in real time by a flame sensor installed near the burner; its presence or absence indicates whether combustion has been successfully established.

[0077] If no flame signal is detected within the preset ignition time after the ignition command is issued, the gas supply is cut off and an ignition failure alarm is output. This logic is expressed as a Boolean condition: if a certain time has elapsed since the ignition command was issued... If the flame signal remains invalid, then the gas supply will be cut off and an alarm will be triggered. The preset ignition duration limits the maximum permissible time from the issuance of the ignition command to the establishment of a stable flame. This measure prevents unburned gas from accumulating in the furnace, avoiding the risk of explosion.

[0078] When a flame signal interruption is detected during operation and continues for more than a preset interruption duration, the gas supply is cut off and a flame interruption alarm is output. The operation period refers to the entire time after successful ignition during which the flame gun performs normal tasks such as heating or heat preservation. This logic is expressed as a Boolean condition: if the flame signal is interrupted and the duration... If this occurs, the gas supply will be cut off and an alarm will be triggered. Preset interruption duration. A pre-set time threshold is used to distinguish between momentary disturbances and actual flameout, preventing false alarms and malfunctions in the system. This measure effectively addresses accidental flameouts caused by gas pressure fluctuations, air pressure disturbances, or burner malfunctions, preventing unburned gas leaks.

[0079] In the optional implementation, determining whether to cut off the gas supply and output an alarm based on the gas pressure value can specifically involve the following operations: detecting the gas pressure value and determining whether the detected gas pressure value exceeds the preset pressure range; when the detected gas pressure value exceeds the preset pressure range, cutting off the gas supply and outputting a gas pressure abnormality alarm.

[0080] The gas pressure value is collected in real time by a gas pressure sensor installed in the gas pipeline and recorded as follows: The preset pressure range is defined by the lower pressure threshold. With upper pressure threshold Together they define and constitute a safe operation window. .like This may lead to unstable combustion or backfire; if This could lead to overpressure leaks or equipment damage. When If the pressure exceeds this range, the control immediately cuts off the gas supply and outputs a "Gas Pressure Abnormality Alarm" signal. This logic is expressed as a Boolean condition: If... or If the gas supply is cut off, an abnormal gas pressure alarm will be triggered. This interlock mechanism ensures that the gas system operates within a safe pressure range.

[0081] The above combination Figure 1 and Figure 2 This application describes the combustion temperature control method provided, and details the optional implementation methods and specific application examples of each step. The embodiments of this application collect multi-point temperature distribution data on the mold surface and determine the temperature uniformity index, enabling the control system to acquire overall temperature field information of the mold and avoid overlooking local temperature deviations due to single-point temperature measurement. By calculating the automatic control quantity based on the deviation between the average temperature and the target temperature and its rate of change, temperature accuracy during the heating process is ensured. By determining the basic weighting factor based on the temperature uniformity index, temperature deviation, and its rate of change, and combining it with the manual intervention weighting coefficient to determine the final dynamic weighting factor, the control strategy can be dynamically adjusted according to the temperature distribution state and the operator's intentions. By weighting and fusing the automatic control quantity and the manual control quantity based on the final dynamic weighting factor, a coordinated match between operator experience and automatic adjustment is achieved, which helps to improve temperature uniformity when the temperature approaches the target.

[0082] Next, combined Figure 3 The flamethrower 300 provided in this application is described in detail. Figure 3An exemplary structural block diagram of a flamethrower according to an embodiment of this application is shown. Figure 3 As shown, the flame gun 300 includes a main control unit 301, a human-machine interaction unit 302, a temperature sensing unit 303, a gas supply and regulation unit 304, and a combustion execution unit 305.

[0083] Among them, the main control unit 301 is configured to execute the preceding text in combination. Figure 1 and Figure 2 For the sake of brevity, the combustion temperature control method described herein will not be elaborated upon here.

[0084] In a specific application example of this application, the main control unit 301 may be a programmable logic controller, whose internal firmware program executes complete combustion temperature control logic.

[0085] The human-machine interaction unit 302 is communicatively connected to the main control unit 301. It is used to receive manual control parameters input by the operator, which represent the intention of manual control, and feed them back to the main control unit 301. The manual control parameters may include manual control quantity and manual intervention weight coefficient.

[0086] In a specific application example of this application, the human-machine interaction unit 302 can be an industrial touch screen, connected to the main control unit 301 via a communication connection. The touch screen can be equipped with virtual knobs for setting manual control values, and input boxes for setting manual intervention weight coefficients.

[0087] The temperature sensing unit 303 is communicatively connected to the main control unit 301 and includes an infrared thermal imager 3031 for acquiring thermal images of the mold surface. The infrared thermal imager 3031 transmits the thermal images to the main control unit 301, so that the main control unit 301 can acquire multi-point temperature distribution data based on the thermal images.

[0088] In some optional implementations, the temperature sensing unit 303 may also include at least one thermocouple 3032. The thermocouple 3032 may be a type K armored thermocouple, used for contact measurement of the precise temperature of preset points on the mold, and installed in key parts such as the mold cavity, runner, and riser, as a supplement to the non-contact measurement of the infrared thermal imager. The two types of sensors together constitute a complete temperature field sensing system.

[0089] The gas supply and regulation unit 304 is electrically connected to the main control unit 301 and includes a proportional regulating valve 3041 that adjusts the gas flow according to the final control quantity, a gas pressure sensor 3042 for detecting gas pressure and feeding back the gas pressure value to the main control unit 301, and a solenoid valve 3043 for cutting off the gas supply.

[0090] In a specific application example of this application, the control signal of the proportional control valve 3041 can be a 0-10V analog quantity, corresponding to an opening degree of 0% to 100%. The gas pressure sensor 3042 is installed in the gas pipeline to monitor the pipeline pressure in real time and feed the signal back to the main control unit 301. The solenoid valve 3043 is a normally closed safety shut-off device used to immediately cut off the gas supply when the main control unit 301 issues a shut-off command.

[0091] The combustion execution unit 305 is electrically connected to the main control unit 301 and includes at least one gas gun 3051. Each gas gun is equipped with an ignition electrode and a flame sensor. The ignition electrode generates an electric spark when it receives an ignition command sent by the main control unit 301, and the flame sensor is used to feed back a flame signal to the main control unit 301.

[0092] In a specific application example of this application, the combustion execution unit 305 may include six independently controllable gas guns arranged around the mold to achieve uniform heating of the mold surface. The flame sensor may be an ultraviolet flame sensor, continuously outputting a binary flame status signal to the main control unit 301 for safety interlock logic judgment. The ignition electrode is a high-voltage ignition electrode, which is energized to generate an electric spark to ignite the gas when the main control unit 301 issues an ignition command.

[0093] In some optional implementations, the human-computer interaction unit 302 can also display a thermal image and detect the operator's selection operation. In response to detecting the operator's externally input selection operation, the coordinates of the selected rectangular area in the thermal image are recorded, and the coordinates in the thermal image are fed back to the main control unit 301, which stores them as the coordinates of a preset area.

[0094] In a specific operational process of the flamethrower provided in this application, after the system is powered on, the main control unit 301 first loads the preset area coordinates from the non-volatile memory. The operator sets the preset target temperature, manual intervention weight coefficient, and knob position value through the human-machine interface unit 302. The main control unit 301 sends a data acquisition command to the infrared thermal imager to receive thermal image data at a fixed sampling period. After preprocessing the thermal image, the main control unit 301 extracts the average temperature of each area based on the preset area coordinates and calculates the average temperature and temperature uniformity index of the mold. Simultaneously, the main control unit 301 calculates the automatic control quantity using an incremental PID control algorithm with feedforward based on the temperature deviation and its rate of change; determines the basic weight factor based on the temperature deviation, the rate of change of the temperature deviation, and the temperature uniformity index; calculates the final dynamic weight factor by combining the manual intervention weight coefficient; and weights and fuses the automatic control quantity and the manual control quantity to obtain the final control quantity. The final control quantity is converted into an analog signal, which drives the proportional regulating valve 3041 of the gas supply and regulation unit 304 to regulate the gas flow, and the gas gun of the combustion execution unit 305 heats the mold. Throughout the operation, the main control unit 301 continuously monitors the flame signal fed back by the flame sensor 30512, the gas pressure value fed back by the gas pressure sensor 3042, and the multi-point temperature distribution data. When any safety interlock condition is met, the solenoid valve 3043 is immediately shut off and the corresponding alarm signal is output.

[0095] In one specific embodiment of this application, the flame gun is used for the preheating process of a certain type of large aluminum alloy injection mold, with the preset target temperature set at 300°C. Actual operation verification shows that the mold surface temperature stabilizes at 300±5°C within 15 minutes, and the temperature uniformity index drops below 5°C, which is superior to the uniformity performance of traditional single-point PID control. This proves that the present technical solution can effectively achieve rapid, uniform, and safe mold preheating.

[0096] To facilitate a better understanding of the application effect of the technical solution of this application in actual processes, the following is an explanation using a specific application example in the preheating process of injection molds.

[0097] In this application example, the flame gun provided in this application is used to uniformly and efficiently preheat a certain type of large aluminum alloy injection mold, with a preset target temperature. Set to 300°C.

[0098] In terms of hardware configuration, the main control unit adopts a programmable logic controller (PLC), and the human-machine interface unit uses an industrial touchscreen, connected to the main control unit via a communication link. The temperature sensing unit includes six thermocouples and one infrared thermal imager. The thermocouples are installed at six key preset points, including the mold cavity, runner, and riser. The infrared thermal imager is mounted on an adjustable bracket 1.5 meters above the mold surface. The gas supply and regulation unit includes a normally closed solenoid valve, a proportional regulating valve, and a gas pressure sensor. The combustion execution unit includes six independent gas nozzles arranged around the mold, each integrating a high-voltage ignition electrode and an ultraviolet flame sensor.

[0099] During initialization, the operator selects a rectangular area corresponding to one of the six key regions in the thermal image on the touchscreen. The main control unit records the vertex coordinates of each region and stores them in non-volatile memory. During operation, the infrared thermal imager acquires 640×512 pixel thermal images at a 50-millisecond sampling period. After bad pixel correction and 3×3 median filtering, the main control unit extracts the arithmetic mean of the temperatures of all pixels in each region based on the pre-stored coordinates, thus obtaining the average temperature of the six regions. , And calculate the average temperature accordingly. and temperature uniformity index .

[0100] Temperature deviation e is the preset target temperature With average temperature The difference, that is ,in =300°C.

[0101] The rate of change of temperature deviation, de / dt, is the difference in temperature deviation between adjacent sampling times divided by the sampling period.

[0102] The automatic control quantity is calculated by an incremental PID algorithm with feedforward. The PID parameters are determined by tuning the Ziegler-Nichols critical proportional coefficient method and fine-tuning on site as follows: proportional coefficient = 2.5, integral coefficient = 0.05s⁻¹, derivative coefficient = 10s, and feedforward coefficient = 0.3.

[0103] The determination of the basic weighting factors follows the segmented logic described above, with the specific thresholds and weight values ​​set as follows: the first preset temperature difference threshold is 30°C, the second preset temperature difference threshold is 10°C, the first preset rate of change threshold is 0.5°C / s, the first weight value is 0.2, the second weight value is 0.6, the third weight value is 0.8, the fourth weight value is 0.1, and the preset uniformity threshold is 8°C.

[0104] The operator sets the manual intervention weight coefficient to 0.5 via the touchscreen and sets the virtual knob to 60, meaning the manual control amount is 60%. Assuming the base weight factor is calculated to be 0.6 under the current operating conditions, the final dynamic weight factor... =0.6 + 0.5 × (1 - 0.6) = 0.8, final control quantity =(1-0.8)× +0.8×60%. The main control unit converts the final control quantity into a 0-10V analog signal to drive the proportional regulating valve to adjust the gas flow.

[0105] The safety interlock operation operates synchronously, with the following parameters set: preset ignition duration of 5 seconds, preset interruption duration of 2 seconds, preset pressure range of 2.0-3.5 kPa, and preset over-temperature threshold of 350°C. During operation, if no flame signal is detected within 5 seconds after the ignition command is issued, the solenoid valve is shut off and an ignition failure alarm is output; if the flame signal interruption lasts for more than 2 seconds, the solenoid valve is shut off and a flame interruption alarm is output; if the gas pressure exceeds the 2.0-3.5 kPa range, the solenoid valve is shut off and a gas pressure abnormality alarm is output; if any temperature value in the multi-point temperature distribution data exceeds 350°C, the solenoid valve is shut off and an over-temperature alarm is output.

[0106] Through actual operation verification, under the conditions of this application example, the mold surface temperature stabilized at 300±5°C within 15 minutes, and the temperature uniformity index dropped to below 5°C, which is superior to the traditional single-point PID control method (whose uniformity index is usually greater than 15°C). This result shows that the technical solution of this application can effectively achieve rapid, uniform, and safe mold preheating, and significantly improve the temperature uniformity of the mold surface while ensuring temperature accuracy.

[0107] While numerous embodiments of this application 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. Many modifications, alterations, and alternatives will arise for those skilled in the art without departing from the spirit and intent of this application. It should be understood that various alternatives to the embodiments of this application described herein may be employed in the practice of this application. The appended claims are intended to define the scope of protection of this application and therefore cover equivalents or alternatives within the scope of these claims.

Claims

1. A method for controlling combustion temperature, characterized in that, include: Collect multi-point temperature distribution data on the mold surface at the current moment; Based on the multi-point temperature distribution data, the average temperature and temperature uniformity index of the mold are determined; Acquire manual control parameters that represent the intention to manually control from external input, the manual control parameters including manual control quantity and manual intervention weight coefficient; The automatic control quantity at the current moment is determined based on the temperature deviation between the average temperature and the preset target temperature, and the rate of change of the temperature deviation. The basic weighting factor is determined based on the temperature uniformity index, the temperature deviation, and the rate of change of the temperature deviation. The final dynamic weight factor is determined based on the basic weight factor and the manual intervention weight coefficient. Based on the final dynamic weighting factor, the automatic control quantity and the manual control quantity are weighted and fused to obtain the final control quantity at the current moment; Adjust the opening degree of the proportional control valve according to the final control value.

2. The method according to claim 1, characterized in that, The multi-point temperature distribution data consists of the regional average temperature of multiple preset areas, which cover the key parts of the mold, including the cavity, runner and / or riser.

3. The method according to claim 2, characterized in that, Collect multi-point temperature distribution data on the mold surface, including: Thermal images of the mold surface were acquired using an infrared thermal imager. Based on the coordinates of the multiple preset regions in the thermal image, the average temperature of each preset region is extracted. The average temperature of the multiple preset areas is used as the multi-point temperature distribution data.

4. The method according to claim 3, characterized in that, The coordinates of the multiple preset regions in the thermal image are pre-calibrated through the following operations: In the initialization state, the initial thermal image acquired by the infrared thermal imager is obtained; In response to an external input selection operation, the coordinates of the selected rectangular region in the initial thermal image are recorded; The coordinates in the initial thermal image are stored as the coordinates of the preset region.

5. The method according to claim 1, characterized in that, Based on the temperature deviation between the average temperature and the preset target temperature, and the rate of change of the temperature deviation, the automatic control quantity for the current moment is determined, including: Based on the temperature deviation between the average temperature and the preset target temperature, and the rate of change of the temperature deviation, an incremental PID control algorithm with feedforward is used to determine the control increment. Calculate the first sum of the automatic control quantity at the previous moment and the control increment, and use the first sum as the automatic control quantity at the current moment.

6. The method according to claim 5, characterized in that, The formula for determining the control increment using an incremental PID control algorithm with feedforward is as follows: ； in, This is the proportionality coefficient. The integral coefficient is... The differential coefficients are... Forward coefficients; , , These represent the temperature deviations at the current moment, the previous moment, and the two moments before that, respectively. The sampling period; and These are the preset target temperatures for the current moment and the previous moment, respectively.

7. The method according to claim 1, characterized in that, The basic weighting factors are determined based on the temperature uniformity index, the temperature deviation, and the rate of change of the temperature deviation, including: Determine whether the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold; When the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature deviation, the rate of change of the temperature deviation, the first preset temperature difference threshold, and the second preset temperature difference threshold; wherein, the second preset temperature difference threshold is less than the first preset temperature difference threshold. When the absolute value of the temperature deviation is less than the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature uniformity index and the preset uniformity threshold.

8. The method according to claim 7, characterized in that, When the temperature deviation is greater than or equal to the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature deviation, the rate of change of the temperature deviation, the first preset temperature difference threshold, and the second preset temperature difference threshold, including: When the absolute value of the temperature deviation is greater than or equal to the first preset temperature difference threshold and the rate of change of the temperature deviation is less than or equal to the first preset rate of change threshold, the basic weighting factor is determined as the first weighting value. When the absolute value of the temperature deviation is greater than or equal to the second preset temperature difference threshold and less than the first preset temperature difference threshold, the basic weighting factor is obtained by linear interpolation based on the ratio of the absolute value of the temperature deviation between the second preset temperature difference threshold and the first preset temperature difference threshold, and the basic weighting factor increases linearly as the absolute value of the temperature deviation decreases.

9. The method according to claim 7, characterized in that, When the absolute value of the temperature deviation is less than the second preset temperature difference threshold, the basic weighting factor is determined based on the temperature uniformity index and the preset uniformity threshold, including: When the absolute value of the temperature deviation is less than the second preset temperature difference threshold and the temperature uniformity index is greater than the preset uniformity threshold, the basic weighting factor is determined as the third weighting value. When the absolute value of the temperature deviation is less than the second preset temperature difference threshold and the temperature uniformity index is less than or equal to the preset uniformity threshold, the basic weighting factor is determined as the fourth weighting value.

10. The method according to claim 1, characterized in that, Based on the basic weighting factor and the manual intervention weighting coefficient, the final dynamic weighting factor is determined, including: Determine the first product of the manual intervention weight coefficient and the preset coefficient, wherein the preset coefficient is determined by the basic weight factor; Calculate the second sum of the product of the basic weight factor and the first product, and determine the second sum as the final dynamic weight factor.

11. The method according to claim 1, characterized in that, Based on the final dynamic weighting factor, the automatic control quantity and the manual control quantity are weighted and fused to obtain the final control quantity at the current moment, including: Calculate the difference between 1 and the final dynamic weighting factor; Calculate the second product of the difference and the automatic control quantity, and the third product of the final dynamic weighting factor and the manual control quantity; Calculate the third sum of the second product and the third product, and use this third sum as the final control quantity.

12. The method according to claim 1, characterized in that, It also includes a safety interlock operation, which determines whether to cut off the gas supply and output an alarm based on the multi-point temperature distribution data on the surface of the mold, the flame signal and / or the gas pressure value.

13. The method according to claim 12, characterized in that, Determining whether to cut off the gas supply and output an alarm based on the multi-point temperature distribution data on the mold surface includes: Determine whether any temperature values ​​in the multi-point temperature distribution data exceed a preset temperature threshold; When any temperature value in the multi-point temperature distribution data exceeds the preset temperature threshold, the gas supply is cut off and an over-temperature alarm is output.

14. The method according to claim 12, characterized in that, The alarm for determining whether to cut off the gas supply and output based on the flame signal includes: Detect flame signals during ignition and / or operation; If no flame signal is detected within the preset ignition time after the ignition command is issued, the gas supply is cut off and an ignition failure alarm is output. When a flame signal interruption is detected during operation and continues for more than the preset interruption duration, the gas supply is cut off and a flame interruption alarm is output.

15. The method according to claim 12, characterized in that, Determine whether to cut off the gas supply based on gas pressure and output an alarm, including: Detect the gas pressure value and determine whether the detected gas pressure value exceeds the preset pressure range; When the detected gas pressure value exceeds the preset pressure range, the gas supply is cut off and an abnormal gas pressure alarm is output.

16. A flamethrower, characterized in that, include: The main control unit is configured to execute the combustion temperature control method as described in any one of claims 1 to 15; The human-computer interaction unit is communicatively connected to the main control unit and is used to receive manual control parameters input by the operator that represent the intention to manually control the operation. The manual control parameters include manual control quantity and manual intervention weight coefficient. A temperature sensing unit, which is communicatively connected to the main control unit, includes an infrared thermal imager for acquiring thermal images of the mold surface. The infrared thermal imager transmits the thermal images to the main control unit so that the main control unit can obtain the multi-point temperature distribution data based on the thermal images. The gas supply and regulation unit is electrically connected to the main control unit and includes a proportional regulating valve that adjusts the gas flow according to the final control quantity, a gas pressure sensor for detecting gas pressure and feeding back the gas pressure value to the main control unit, and a solenoid valve for cutting off the gas supply. The combustion execution unit, electrically connected to the main control unit, includes at least one gas gun. Each gas gun is equipped with an ignition electrode and a flame sensor. The ignition electrode generates an electric spark when it receives an ignition command, and the flame sensor is used to feed back a flame signal to the main control unit.

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