Heating furnace state monitoring method and system

Abstract

The invention provides a heating furnace state monitoring method and system, and belongs to the technical field of heating furnaces. The method comprises the steps that a target heating furnace is monitored through multiple preset monitoring methods, and monitoring parameters corresponding to the preset monitoring methods are obtained; according to the types of the monitoring parameters, according to a preset judgment rule, the corresponding monitoring parameters are combined for multiple times of heating furnace state judgment, and multiple types of heating furnace state judgment results are obtained; mutual verification is carried out according to all heating furnace state judgment results, and the overall state of the target heating furnace is determined. Therefore, through simultaneous judgment of multiple parameters, the actual use process of the target heating furnace is considered, the false alarm risk is effectively eliminated, and accurate judgment of the state of the target heating furnace is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of heating furnaces, and in particular to a method and system for monitoring the state of a heating furnace. Background Art

[0002] Driven by the rapid development of science and technology, in recent years, automation technology has been widely used in the use of heating furnaces, realizing real-time monitoring, management and intelligent control of the use of heating furnaces, thereby effectively reducing the labor intensity of manual operations to a certain extent and improving the safety index of the entire heating furnace use process.

[0003] In the process of automatic control of the heating furnace, it is particularly important to accurately determine the state of the heating furnace. At present, the working state of the heating furnace is mainly adjusted by observing the flame combustion state of the heating furnace, combining parameters such as the oxygen content and CO content in the flue gas, and taking manual experience as a reference. However, it is inaccurate to judge the state of the heating furnace solely based on the current flame combustion state of the heating furnace and parameters such as the oxygen content and CO content in the generated flue gas, and false alarms are very likely to occur. And because the problems that arise during the use of the heating furnace are usually complex and diverse, how to take into account the actual use process of the heating furnace and realize accurate judgment of the state of the heating furnace is a problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a method and system for monitoring the state of a heating furnace, so as to at least solve the above-mentioned problem that the actual use process of the heating furnace cannot be taken into account to accurately determine the state of the heating furnace.

[0005] In order to achieve the above object, the present invention provides a heating furnace state monitoring method in a first aspect, comprising:

[0006] Use multiple preset monitoring methods to monitor the target heating furnace and obtain monitoring parameters corresponding to each preset monitoring method;

[0007] According to the type of monitoring parameters and the preset judgment rules, multiple heating furnace status judgments are performed in combination with the corresponding monitoring parameters to obtain multiple types of heating furnace status judgment results;

[0008] The overall status of the target heating furnace is determined by mutual verification based on the status determination results of all heating furnaces.

[0009] Optionally, the monitoring parameters include the furnace tube temperature of the target heating furnace, the furnace tube thermocouple temperature, the flame temperature, the monitoring video, the sound data during the use of the target heating furnace, the concentration data of various flue gas components generated by the target heating furnace, and the temperature data corresponding to multiple preset combustion indicators;

[0010] The target heating furnace is monitored using a plurality of preset monitoring methods to obtain monitoring parameters corresponding to each preset monitoring method, including:

[0011] The furnace tube temperature, furnace tube thermocouple temperature and flame temperature of the target heating furnace are collected by a preset camera, and the target heating furnace is monitored to obtain a monitoring video;

[0012] Collecting sound data of the target heating furnace during use by using a sound sensor;

[0013] The concentration data of various flue gas components generated by the target heating furnace are collected through various gas sensors;

[0014] The temperature data corresponding to multiple preset combustion indicators of the target heating furnace are collected from the DCS.

[0015] Optionally, the above heating furnace state determination result includes furnace tube state;

[0016] According to the type of monitoring parameters and the preset judgment rules, the heating furnace status judgment is performed multiple times in combination with the corresponding monitoring parameters to obtain various types of heating furnace status judgment results, including:

[0017] Based on the furnace tube temperature and the furnace tube thermocouple temperature, it is determined whether the furnace tube is coked to obtain the furnace tube status.

[0018] Optionally, the above heating furnace state determination result includes the overall flame state of the target heating furnace;

[0019] According to the type of monitoring parameters and the preset judgment rules, the heating furnace status judgment is performed multiple times in combination with the corresponding monitoring parameters to obtain various types of heating furnace status judgment results, including:

[0020] Based on the flame temperature and monitoring video, it is determined whether the target heating furnace has flame to obtain the overall flame status of the target heating furnace.

[0021] Optionally, the heating furnace status monitoring method further includes:

[0022] Configure photoelectric sensors for pre-installed cameras;

[0023] Detecting the photoelectric signal of the target heating furnace through a photoelectric sensor;

[0024] Based on the photoelectric signal, the overall flame state of the target heating furnace is determined.

[0025] Optionally, the heating furnace status monitoring method further includes:

[0026] When the overall flame state of the target heating furnace is extinguished, a signal for lighting the permanent lamp is issued;

[0027] According to the pilot light ignition signal, the pilot light is ignited, and the pilot light is used to reignite each nozzle of the target heating furnace;

[0028] Acquire the nozzle re-ignition data of the target heating furnace through a variety of preset monitoring methods;

[0029] Based on the furnace nozzle re-ignition data, determine whether the target heating furnace is successfully re-ignited.

[0030] Optionally, the above heating furnace status determination result includes a heating furnace failure condition;

[0031] According to the type of monitoring parameters and the preset judgment rules, the heating furnace status judgment is performed multiple times in combination with the corresponding monitoring parameters to obtain various types of heating furnace status judgment results, including:

[0032] The heating furnace fault condition is judged based on flame temperature, monitoring video, sound data, concentration data of multiple flue gas components and temperature data corresponding to multiple preset combustion indicators. The heating furnace fault condition includes at least excess fuel, excess combustion-supporting gas and burner blockage.

[0033] Optionally, judging the heating furnace failure condition according to the flame temperature, monitoring video, sound data, concentration data of multiple flue gas components and temperature data corresponding to multiple preset combustion indicators includes:

[0034] Decompose the monitoring video into multiple continuous image frames, pre-process each image frame, determine the combustion area of ​​each image frame, and measure the area and flame height of each combustion area. According to the area and flame height of each combustion area, determine the change trend of the flame area and the change trend of the flame height;

[0035] Perform RGB image recognition on the combustion area of ​​the latest acquired image frame to obtain the flame color recognition result;

[0036] Identify the RGB value of the top of the target heating furnace in the latest acquired image frame, and determine whether there is a flame on the top of the furnace according to the RGB value;

[0037] Comparing the combustion area of ​​the latest acquired image frame with a plurality of standard combustion area images to determine whether flame tilt occurs;

[0038] According to the concentration data of multiple smoke components, the concentration change trend of each smoke component is determined, wherein the smoke components include CO2;

[0039] Determine the trend of sound decibel changes based on sound data;

[0040] Adopting the 2ooN method to judge whether the fuel excess situation occurs for multiple first fault occurrence conditions, wherein the multiple first fault occurrence conditions include the flame temperature being higher than the first preset temperature, the flame area changing trend being increasing, the flame height changing trend being getting higher, the flame appearing at the top of the furnace, the CO2 concentration changing trend being increasing, and the temperature data corresponding to any preset combustion index of the target heating furnace in the DCS increasing;

[0041] Adopting 2ooN method to judge whether there is excess combustion gas for multiple second fault conditions, wherein the multiple second fault conditions include flame temperature lower than the second preset temperature, flame tilt, flame color recognition result is red, CO2 concentration change trend is decreasing, and sound decibel change trend is increasing;

[0042] The 2ooN method is used to determine whether a burner blockage occurs for multiple third fault conditions, where the multiple third fault conditions include a decrease in the concentration change trend of each flue gas component, a decrease in the flame area change trend, and a decrease in the temperature data corresponding to any preset combustion index of the target heating furnace in the DCS.

[0043] Optionally, the above method for measuring the area and flame height of each combustion area includes at least one or more of the Otsu method, the Boolean variable method and the Yolo V5 algorithm.

[0044] Optionally, the monitoring parameters include a real-time combustion image of the target heating furnace and an actual temperature value corresponding to each pixel in the real-time combustion image;

[0045] The target heating furnace is monitored using a plurality of preset monitoring methods to obtain monitoring parameters corresponding to each preset monitoring method, including:

[0046] The real-time combustion image of the target heating furnace is collected through a preset camera. At the same time, during the use of the target heating furnace, the actual temperature value corresponding to each pixel point in the real-time combustion image is measured.

[0047] Optionally, the above heating furnace state determination result includes the abnormality of the flame temperature of the target heating furnace;

[0048] According to the type of monitoring parameters and the preset judgment rules, the heating furnace status judgment is performed multiple times in combination with the corresponding monitoring parameters to obtain various types of heating furnace status judgment results, including:

[0049] Perform RGB image recognition on the real-time combustion image to obtain the RGB value of each pixel in the real-time combustion image;

[0050] Establish a mapping relationship between the RGB value of each pixel and the corresponding actual temperature value to obtain an RGB temperature image;

[0051] The RGB temperature image is compared with a preset RGB standard temperature image to determine the pixel points where the flame temperature is abnormal, and the pixel points where the flame temperature is abnormal are displayed.

[0052] A second aspect of the present invention provides a heating furnace state monitoring system, comprising:

[0053] A monitoring module, used to monitor the target heating furnace using a variety of preset monitoring methods and obtain monitoring parameters corresponding to each preset monitoring method;

[0054] A state determination module is used to perform multiple heating furnace state determinations in combination with corresponding monitoring parameters according to the type of monitoring parameters and preset determination rules, and obtain multiple types of heating furnace state determination results;

[0055] The target heating furnace overall state determination module is used to perform mutual verification based on all heating furnace state determination results to determine the target heating furnace overall state.

[0056] In a third aspect of the present invention, a machine-readable storage medium is provided, on which instructions are stored. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned heating furnace state monitoring method.

[0057] In a fourth aspect of the present invention, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the heating furnace status monitoring method when executing the computer program.

[0058] Through the above technical scheme, a method and system for monitoring the state of a heating furnace uses a variety of preset monitoring methods to monitor the target heating furnace, and obtains the monitoring parameters corresponding to each preset monitoring method (including furnace tube temperature, furnace tube thermocouple temperature, flame temperature, monitoring video, sound data during the use of the target heating furnace, concentration data of multiple flue gas components generated by the target heating furnace, temperature data corresponding to multiple preset combustion indicators, real-time combustion images of the target heating furnace, and actual temperature values ​​corresponding to each pixel in the real-time combustion image). According to the type of monitoring parameters, according to the preset judgment rules, multiple heating furnace state judgments are performed in combination with the corresponding monitoring parameters to obtain multiple types of heating furnace state judgment results. Therefore, all heating furnace state judgment results are used for mutual verification to determine the overall state of the target heating furnace. The purpose of combining the monitoring parameters obtained by multiple preset monitoring methods and performing multi-parameter judgment according to the preset judgment rules is achieved. Through simultaneous judgment of multiple parameters, the actual use process of the target heating furnace is considered, the risk of false alarms is effectively eliminated, and the accurate judgment of the state of the target heating furnace is achieved.

[0059] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0061] Figure 1 is a flow chart of a heating furnace state monitoring method provided by one embodiment of the present invention;

[0062] Figure 2 is a block diagram of a heating furnace state monitoring system provided by one embodiment of the present invention;

[0063] Figure 3 It is a schematic diagram of the structure of an electronic device provided by a preferred embodiment of the present invention.

[0064] Description of Reference Numerals

[0065] 10 - electronic device, 100 - processor, 101 - memory, 102 - computer program. DETAILED DESCRIPTION

[0066] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0067] Example 1

[0068] Figure 1 FIG. 1 is a flow chart of a method for monitoring the state of a heating furnace provided by an embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a method for monitoring the state of a heating furnace, comprising:

[0069] S110: monitoring the target heating furnace using a plurality of preset monitoring methods, and obtaining monitoring parameters corresponding to each preset monitoring method;

[0070] In some implementations of this embodiment, the monitoring parameters include the furnace tube temperature, furnace tube thermocouple temperature, flame temperature, monitoring video, sound data during the use of the target heating furnace, concentration data of multiple flue gas components generated by the target heating furnace, and temperature data corresponding to multiple preset combustion indicators. The monitoring of the target heating furnace using multiple preset monitoring methods to obtain the monitoring parameters corresponding to each preset monitoring method includes:

[0071] The furnace tube temperature, furnace tube thermocouple temperature and flame temperature of the target heating furnace are collected by a preset camera, and the target heating furnace is monitored to obtain a monitoring video;

[0072] The preset camera may be a camera obtained by coupling an infrared camera and a visible light camera.

[0073] Specifically, the monitoring video is obtained by shooting for 30 to 40 minutes using a preset camera.

[0074] Collecting sound data of the target heating furnace during use by using a sound sensor;

[0075] For example, during the use of the target heating furnace, different decibels of sound may be generated due to different gas flow rates in the pipeline or different flame sizes. In this case, a sound sensor may be used to collect all sound data during the use of the target heating furnace.

[0076] The concentration data of various flue gas components generated by the target heating furnace are collected through various gas sensors;

[0077] Specifically, during the use of the target heating furnace, flue gas is generated, and various flue gas components (such as CO2) can be collected and their concentrations can be identified through a variety of gas sensors. In addition, a flue gas analyzer can be configured at the use site of the target heating furnace to directly collect and analyze various flue gas components.

[0078] The temperature data corresponding to multiple preset combustion indicators of the target heating furnace are collected from the DCS.

[0079] Among them, the temperature data corresponding to the multiple preset combustion indicators include the target heating furnace's furnace wall temperature, furnace tube temperature, flame temperature, furnace temperature, feed temperature, flue gas temperature, etc. These temperature data can be directly obtained from the DCS.

[0080] In some implementations of this embodiment, the monitoring parameters include a real-time combustion image of the target heating furnace and an actual temperature value corresponding to each pixel in the real-time combustion image. The monitoring of the target heating furnace using a plurality of preset monitoring methods to obtain monitoring parameters corresponding to each preset monitoring method includes: collecting a real-time combustion image of the target heating furnace through a preset camera, and measuring the actual temperature value corresponding to each pixel in the real-time combustion image during the use of the target heating furnace.

[0081] Specifically, a real-time combustion image of the target heating furnace is obtained by capturing it with a preset camera, and based on each pixel point in the real-time combustion image, a thermometer can be used to measure the actual temperature value of each pixel point at the use site.

[0082] S120: According to the type of monitoring parameters and the preset determination rules, multiple heating furnace status determinations are performed in combination with corresponding monitoring parameters to obtain multiple types of heating furnace status determination results;

[0083] S130: Mutual verification is performed based on the status determination results of all heating furnaces to determine the overall status of the target heating furnace.

[0084] Specifically, the monitoring parameters obtained by combining multiple preset monitoring methods are judged according to preset judgment rules based on multiple parameters (including furnace tube temperature, furnace tube thermocouple temperature, flame temperature, monitoring video, sound data during the use of the target heating furnace, concentration data of various flue gas components generated by the target heating furnace, temperature data corresponding to multiple preset combustion indicators, real-time combustion image of the target heating furnace, and actual temperature values ​​corresponding to each pixel point in the real-time combustion image). By making simultaneous judgments on multiple parameters and taking into account the actual use process of the target heating furnace, the risk of false alarms is effectively eliminated, and accurate judgment of the state of the target heating furnace is achieved.

[0085] The above heating furnace state determination result includes furnace tube state. According to the type of monitoring parameters and the preset determination rules, the heating furnace state determination is performed multiple times in combination with the corresponding monitoring parameters to obtain various types of heating furnace state determination results, including: judging whether the furnace tube is coked based on the furnace tube temperature and the furnace tube thermocouple temperature to obtain the furnace tube state.

[0086] Specifically, when the temperature of the furnace tube of the target heating furnace monitored by the preset camera is higher than the corresponding temperature threshold (indicating that a hot zone appears in the furnace tube) and the temperature of the furnace tube thermocouple is higher than the corresponding temperature threshold (indicating that the temperature of the furnace tube thermocouple is too high), it is determined that the furnace tube is coked, otherwise, the furnace tube is not coked. Whether the furnace tube is coked is characterized by the above furnace tube status.

[0087] In addition, the above heating furnace state determination result includes the overall flame state of the target heating furnace. According to the type of monitoring parameters, according to the preset determination rules, multiple heating furnace state determinations are performed in combination with the corresponding monitoring parameters to obtain multiple types of heating furnace state determination results, including: judging whether the target heating furnace has flames based on the flame temperature and the monitoring video to obtain the overall flame state of the target heating furnace.

[0088] Specifically, when the flame temperature is lower than the corresponding temperature threshold (indicating that there is no flame by monitoring the flame temperature) and each image frame of the monitoring video is identified as having no flame, the target heating furnace is determined to be flameout, otherwise, the target heating furnace is determined to be not flameout. Whether the target heating furnace is flameout is characterized by the overall flame state of the target heating furnace.

[0089] In this embodiment, when it is determined that the target heating furnace is turned off, a flameout alarm signal is issued to remind the user that the target heating furnace has been turned off.

[0090] In some implementations of this embodiment, the heating furnace state monitoring method further includes:

[0091] Configure photoelectric sensors for pre-installed cameras;

[0092] Detecting the photoelectric signal of the target heating furnace through a photoelectric sensor;

[0093] Based on the photoelectric signal, the overall flame state of the target heating furnace is determined.

[0094] Specifically, a photoelectric sensor is configured for the pre-installed camera. During the process of the pre-installed camera monitoring the target heating furnace, the photoelectric signal of the target heating furnace can be detected by the photoelectric sensor, so as to determine whether the target heating furnace has flame light according to the photoelectric signal. Therefore, it can be monitored and determined whether the target heating furnace has flame, and the overall flame state of the target heating furnace can be further confirmed by the photoelectric sensor.

[0095] In some implementations of this embodiment, the heating furnace state monitoring method further includes:

[0096] When the overall flame state of the target heating furnace is extinguished, a signal for lighting the permanent lamp is issued;

[0097] According to the pilot light ignition signal, the pilot light is ignited, and the pilot light is used to reignite each nozzle of the target heating furnace;

[0098] Acquire the nozzle re-ignition data of the target heating furnace through a variety of preset monitoring methods;

[0099] Among them, the after-burning data of the furnace nozzle of the target heating furnace includes the number of after-burning furnace nozzles, the after-burning flame morphology and the flame propagation conditions.

[0100] Based on the furnace nozzle re-ignition data, determine whether the target heating furnace is successfully re-ignited.

[0101] Specifically, the target heating furnace is equipped with a permanent lamp, and when the overall flame state of the target heating furnace is determined to be extinguished, a permanent lamp ignition signal is issued to automatically ignite the permanent lamp. Thus, each nozzle of the target heating furnace is reignited through the permanent lamp, and then the nozzle reignition data of the target heating furnace is obtained through a variety of preset monitoring methods, and it is determined whether the target heating furnace is successfully reignited.

[0102] In the above implementation process, the nozzle re-ignition image of the target heating furnace can be obtained through a camera, and after the nozzle re-ignition image is gray-scale processed, the gray value of each pixel on the nozzle re-ignition image is identified. According to the gray value of each pixel, the overlapping part and non-overlapping part of the adjacent nozzles in the nozzle re-ignition image are determined. According to the overlapping part and non-overlapping part of any nozzle, the combustion area image of the nozzle when it is actually burning is determined. Then, the combustion area image of each nozzle is identified by using the Otsu method, Boolean variable method or yolo V5 algorithm, and the flame morphology of the re-ignition nozzle and each re-ignition nozzle is determined, and the flame propagation is determined according to the position of the long-burning lamp and the re-ignition nozzle. The nozzle re-ignition data (i.e., the number of re-ignition nozzles, the re-ignition flame morphology, and the flame propagation condition, etc.) is compared with the re-ignition judgment standard to determine whether the target heating furnace is successfully re-ignited.

[0103] In addition, the above heating furnace state determination result includes heating furnace failure. According to the type of monitoring parameters, according to the preset determination rules, multiple heating furnace state determinations are performed in combination with the corresponding monitoring parameters to obtain multiple types of heating furnace state determination results, including: judging heating furnace failure according to flame temperature, monitoring video, sound data, concentration data of multiple flue gas components and temperature data corresponding to multiple preset combustion indicators, and heating furnace failure conditions at least include excess fuel, excess combustion-supporting gas and burner blockage.

[0104] Specifically, the flame temperature, monitoring video, sound data, concentration data of multiple flue gas components and temperature data corresponding to multiple preset combustion indicators obtained by combining multiple preset monitoring methods, the actual use of the target heating furnace is taken into consideration, and multiple parameters are used to determine the specific faults that occur in the target heating furnace during use, thereby further ensuring the accurate judgment of the state of the target heating furnace.

[0105] In this embodiment, when a failure occurs in any heating furnace, a corresponding failure alarm signal is issued to remind the user of the failure of the target heating furnace.

[0106] Example 2

[0107] This embodiment provides a heating furnace state monitoring method, which is basically the same as the heating furnace state monitoring method provided in Embodiment 1, and the main difference is that: the above-mentioned method judges the heating furnace fault condition according to the flame temperature, monitoring video, sound data, concentration data of multiple flue gas components and temperature data corresponding to multiple preset combustion indicators, including:

[0108] Decompose the monitoring video into multiple continuous image frames, pre-process each image frame, determine the combustion area of ​​each image frame, and measure the area and flame height of each combustion area. According to the area and flame height of each combustion area, determine the change trend of the flame area and the change trend of the flame height;

[0109] In this embodiment, the specific steps of preprocessing each image frame and determining the burnt area of ​​each image frame are as follows: grayscale processing is performed on any image frame to obtain a grayscale processing result, and the grayscale value of each pixel on the image frame is obtained according to the grayscale processing result. Pixels with grayscale values ​​greater than a preset grayscale value are determined to belong to the burnt area, thereby determining the burnt area in the image frame.

[0110] Among them, the above-mentioned method for measuring the area and flame height of each combustion area includes at least one or more of the Otsu method, the Boolean variable method and the Yolo V5 algorithm.

[0111] Perform RGB image recognition on the combustion area of ​​the latest acquired image frame to obtain the flame color recognition result;

[0112] Exemplarily, if the R value of the burning area is greater than a preset threshold, it is determined that the flame in the image frame is red.

[0113] Identify the RGB value of the top of the target heating furnace in the latest acquired image frame, and determine whether there is a flame on the top of the furnace according to the RGB value;

[0114] Specifically, for the latest captured image frame, the RGB value of the furnace top is identified, and if the RGB value is 0, it means that no flame appears on the furnace top. Conversely, if the RGB value of the furnace top is not 0, it means that flame appears on the furnace top.

[0115] Comparing the combustion area of ​​the latest acquired image frame with a plurality of standard combustion area images to determine whether flame tilt occurs;

[0116] Specifically, if the combustion area of ​​the latest acquired image frame is consistent with one of the standard combustion area images, it is determined that the flame of the target heating furnace is not tilted. Conversely, if no standard combustion area image is consistent with the combustion area of ​​the latest acquired image frame, it is determined that the flame of the target heating furnace is tilted.

[0117] In addition, the flame inclination angle in the latest collected image frame can be calculated by one or more of the Otsu method, the Boolean variable method and the Yolo V5 algorithm, and whether flame inclination occurs can be determined according to the flame inclination angle.

[0118] According to the concentration data of multiple smoke components, the concentration change trend of each smoke component is determined, wherein the smoke components include CO2;

[0119] Determine the trend of sound decibel changes based on sound data;

[0120] Adopting the 2ooN method to judge whether the fuel excess situation occurs for multiple first fault occurrence conditions, wherein the multiple first fault occurrence conditions include the flame temperature being higher than the first preset temperature, the flame area changing trend being increasing, the flame height changing trend being getting higher, the flame appearing at the top of the furnace, the CO2 concentration changing trend being increasing, and the temperature data corresponding to any preset combustion index of the target heating furnace in the DCS increasing;

[0121] Adopting 2ooN method to judge whether there is excess combustion gas for multiple second fault conditions, wherein the multiple second fault conditions include flame temperature lower than the second preset temperature, flame tilt, flame color recognition result is red, CO2 concentration change trend is decreasing, and sound decibel change trend is increasing;

[0122] The 2ooN method is used to determine whether a burner blockage occurs for multiple third fault conditions, where the multiple third fault conditions include a decrease in the concentration change trend of each flue gas component, a decrease in the flame area change trend, and a decrease in the temperature data corresponding to any preset combustion index of the target heating furnace in the DCS.

[0123] Specifically, when any two of the following conditions occur, namely, the flame temperature is too high, the flame area increases, the flame becomes higher, the flame appears on the top of the furnace, the CO2 in the flue gas increases, or the temperature corresponding to any preset combustion index of the target heating furnace in the DCS (i.e., the furnace wall temperature, the furnace tube temperature, the flame temperature, the furnace temperature, the feed temperature, the flue gas temperature, etc.) increases, it is determined that there is an excess of fuel, i.e., too much fuel. When any two of the following conditions occur, namely, the flame temperature is too low, the flame image is tilted, the flame is red, the CO2 in the flue gas decreases, or the noise increases, it is determined that there is an excess of oxidant gas, i.e., too much oxidant gas. When any two of the following conditions occur, namely, the components of the flue gas decrease, the flame area decreases, or the temperature corresponding to any preset combustion index of the target heating furnace in the DCS decreases, it is determined that there is a blockage of the burner. Thus, the purpose of using multiple parameters to judge the specific faults that occur in the use of the target heating furnace is achieved by analyzing various monitoring parameters (including flame temperature, monitoring video, sound data, concentration data of multiple flue gas components, and temperature data corresponding to multiple preset combustion indexes) .

[0124] In addition, the above heating furnace state determination result includes the flame temperature abnormality of the target heating furnace. According to the type of monitoring parameters, according to the preset determination rules, the heating furnace state determination is performed multiple times in combination with the corresponding monitoring parameters to obtain various types of heating furnace state determination results, including: performing RGB image recognition on the real-time combustion image to obtain the RGB value of each pixel in the real-time combustion image. A mapping relationship is established between the RGB value of each pixel and the corresponding actual temperature value to obtain an RGB temperature image. The RGB temperature image is compared with the preset RGB standard temperature image to determine the pixel where the flame temperature is abnormal, and the pixel where the flame temperature is abnormal is displayed. Thus, by displaying the pixel where the flame temperature is abnormal on the RGB temperature image, the effect of intuitively displaying the flame temperature abnormality of the target heating furnace is achieved. The purpose of judging the flame temperature abnormality of the target heating furnace by combining the real-time combustion image of the target heating furnace and the actual temperature values ​​corresponding to each pixel in the real-time combustion image is achieved. By obtaining the flame temperature abnormality, a basis can be further provided for the accurate determination of the state of the target heating furnace.

[0125] Example 3

[0126] Figure 2 FIG. 1 is a block diagram of a heating furnace status monitoring system provided by an embodiment of the present invention. Figure 2 As shown, an embodiment of the present invention provides a heating furnace state monitoring system, comprising:

[0127] A monitoring module, used to monitor the target heating furnace using a variety of preset monitoring methods and obtain monitoring parameters corresponding to each preset monitoring method;

[0128] A state determination module is used to perform multiple heating furnace state determinations in combination with corresponding monitoring parameters according to the type of monitoring parameters and preset determination rules, and obtain multiple types of heating furnace state determination results;

[0129] The target heating furnace overall state determination module is used to perform mutual verification based on all heating furnace state determination results to determine the target heating furnace overall state.

[0130] Specifically, the system combines the monitoring parameters obtained by multiple preset monitoring methods, and performs multi-parameter (including furnace tube temperature, furnace tube thermocouple temperature, flame temperature, monitoring video, sound data during the use of the target heating furnace, concentration data of various flue gas components generated by the target heating furnace, temperature data corresponding to multiple preset combustion indicators, real-time combustion images of the target heating furnace, and actual temperature values ​​corresponding to each pixel in the real-time combustion image) judgments according to preset judgment rules. By making simultaneous judgments on multiple parameters and taking into account the actual use process of the target heating furnace, the system effectively eliminates the risk of false alarms and achieves accurate judgment of the status of the target heating furnace.

[0131] Example 4

[0132] The embodiment of the present invention further provides a machine-readable storage medium, on which instructions are stored. When the instructions are executed by a processor, the processor is configured to execute the above-mentioned heating furnace state monitoring method.

[0133] Machine-readable storage media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0134] An embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned heating furnace status monitoring method is implemented.

[0135] like Figure 3 FIG. 1 is a schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, the electronic device 10 of this embodiment includes: a processor 100, a memory 101, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, the steps in the above method embodiment are implemented. Alternatively, when the processor 100 executes the computer program 102, the functions of each module / unit in the above device embodiment are implemented.

[0136] Exemplarily, the computer program 102 may be divided into one or more modules / units, one or more modules / units are stored in the memory 101, and are executed by the processor 100 to complete the present invention. One or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 102 in the electronic device 10. For example, the computer program 102 may be divided into a monitoring module, a state determination module, and a target heating furnace overall state determination module.

[0137] The electronic device 10 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 10 may include, but is not limited to, a processor 100 and a memory 101. Those skilled in the art will appreciate that Figure 3 It is only an example of the electronic device 10 and does not constitute a limitation of the electronic device 10. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0138] The processor 100 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0139] The memory 101 may be an internal storage unit of the electronic device 10, such as a hard disk or memory of the electronic device 10. The memory 101 may also be an external storage device of the electronic device 10, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 10. Further, the memory 101 may also include both an internal storage unit of the electronic device 10 and an external storage device. The memory 101 is used to store computer programs and other programs and data required by the electronic device 10. The memory 101 may also be used to temporarily store data that has been output or is to be output.

[0140] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0141] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0142] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0144] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0145] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0146] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for monitoring the state of a heating furnace, characterized in that: include: Use multiple preset monitoring methods to monitor the target heating furnace and obtain monitoring parameters corresponding to each preset monitoring method; According to the type of monitoring parameters and the preset judgment rules, multiple heating furnace status judgments are performed in combination with the corresponding monitoring parameters to obtain multiple types of heating furnace status judgment results; The overall status of the target heating furnace is determined by mutual verification based on the status determination results of all heating furnaces.

2. The method for monitoring the state of a heating furnace according to claim 1, characterized in that: The monitoring parameters include the furnace tube temperature of the target heating furnace, the furnace tube thermocouple temperature, the flame temperature, the monitoring video, the sound data during the use of the target heating furnace, the concentration data of various flue gas components generated by the target heating furnace, and the temperature data corresponding to multiple preset combustion indicators; The target heating furnace is monitored by using a plurality of preset monitoring methods to obtain monitoring parameters corresponding to each preset monitoring method, including: The furnace tube temperature, the furnace tube thermocouple temperature and the flame temperature of the target heating furnace are collected by a preset camera, and the target heating furnace is monitored to obtain a monitoring video; Collecting sound data of the target heating furnace during use by using a sound sensor; The concentration data of various flue gas components generated by the target heating furnace are collected through various gas sensors; The temperature data corresponding to multiple preset combustion indicators of the target heating furnace are collected from the DCS.

3. The method for monitoring the state of a heating furnace according to claim 2, characterized in that: The heating furnace state determination result includes furnace tube state; According to the type of monitoring parameters, according to the preset judgment rules, multiple heating furnace status judgments are performed in combination with corresponding monitoring parameters to obtain multiple types of heating furnace status judgment results, including: Based on the furnace tube temperature and the furnace tube thermocouple temperature, it is determined whether the furnace tube is coked to obtain the furnace tube state.

4. The method for monitoring the state of a heating furnace according to claim 2, characterized in that: The heating furnace state determination result includes the overall flame state of the target heating furnace; According to the type of monitoring parameters, according to the preset judgment rules, multiple heating furnace status judgments are performed in combination with corresponding monitoring parameters to obtain multiple types of heating furnace status judgment results, including: Based on the flame temperature and the monitoring video, it is determined whether the target heating furnace has flame, so as to obtain the overall flame state of the target heating furnace.

5. The method for monitoring the state of a heating furnace according to claim 4, characterized in that: Also includes: Configuring a photoelectric sensor for the pre-installed camera; Detecting the photoelectric signal of the target heating furnace by the photoelectric sensor; Based on the photoelectric signal, the overall flame state of the target heating furnace is determined.

6. The method for monitoring the state of a heating furnace according to claim 4, characterized in that: Also includes: When the overall flame state of the target heating furnace is extinguished, a signal for lighting a permanent lamp is issued; According to the lighting signal of the lighting lamp, the lighting lamp is lit, and the lighting lamp is used to reignite each nozzle of the target heating furnace; Acquire the nozzle re-ignition data of the target heating furnace by using a plurality of preset monitoring methods; According to the furnace nozzle re-ignition data, it is determined whether the target heating furnace is successfully re-ignited.

7. The method for monitoring the state of a heating furnace according to claim 2, characterized in that: The heating furnace state determination result includes a heating furnace failure condition; According to the type of monitoring parameters, according to the preset judgment rules, multiple heating furnace status judgments are performed in combination with corresponding monitoring parameters to obtain multiple types of heating furnace status judgment results, including: The heating furnace failure condition is judged based on the flame temperature, the monitoring video, the sound data, the concentration data of the multiple flue gas components and the temperature data corresponding to the multiple preset combustion indicators. The heating furnace failure condition at least includes excess fuel, excess supporting gas and burner blockage.

8. The method for monitoring the state of a heating furnace according to claim 7, characterized in that: The method of judging the heating furnace failure according to the flame temperature, the monitoring video, the sound data, the concentration data of the multiple smoke components and the temperature data corresponding to the multiple preset combustion indicators includes: Decomposing the monitoring video into a plurality of continuous image frames, preprocessing each image frame, determining the combustion area of ​​each image frame, and measuring the area and flame height of each combustion area, and judging the flame area change trend and the flame height change trend according to the area and flame height of each combustion area; Perform RGB image recognition on the combustion area of ​​the latest acquired image frame to obtain the flame color recognition result; Identify the RGB value of the top of the target heating furnace in the latest acquired image frame, and determine whether a flame appears on the top of the furnace according to the RGB value; Comparing the combustion area of ​​the latest acquired image frame with a plurality of standard combustion area images to determine whether flame tilt occurs; According to the concentration data of the multiple smoke components, determining the concentration change trend of each smoke component, wherein the smoke components include CO2; Determine the sound decibel change trend according to the sound data; Adopting the 2ooN method to judge whether the fuel excess situation occurs for multiple first fault occurrence conditions, wherein the multiple first fault occurrence conditions include the flame temperature being higher than the first preset temperature, the flame area changing trend being increasing, the flame height changing trend being getting higher, the flame appearing at the top of the furnace, the CO2 concentration changing trend being increasing, and the temperature data corresponding to any preset combustion index of the target heating furnace in the DCS increasing; Adopting the 2ooN method to judge whether there is excess combustion-supporting gas for multiple second fault occurrence conditions, wherein the multiple second fault occurrence conditions include the flame temperature being lower than the second preset temperature, the flame tilting, the flame color recognition result being red, the CO2 concentration change trend being decreasing, and the sound decibel change trend being increasing; The 2ooN method is used to determine whether a burner blockage occurs for multiple third fault conditions, wherein the multiple third fault conditions include that the concentration change trends of each flue gas component are decreasing, the flame area change trend is decreasing, and the temperature data corresponding to any preset combustion index of the target heating furnace in the DCS is reduced.

9. The method for monitoring the state of a heating furnace according to claim 8, characterized in that: The method for measuring the area and flame height of each combustion area includes at least one or more of the Otsu method, the Boolean variable method and the Yolo V5 algorithm.

10. The method for monitoring the state of a heating furnace according to claim 1, characterized in that: The monitoring parameters include a real-time combustion image of the target heating furnace and an actual temperature value corresponding to each pixel in the real-time combustion image; The target heating furnace is monitored by using a plurality of preset monitoring methods to obtain monitoring parameters corresponding to each preset monitoring method, including: The real-time combustion image of the target heating furnace is collected by a preset camera, and the actual temperature value corresponding to each pixel point in the real-time combustion image is measured during the use of the target heating furnace.

11. The method for monitoring the state of a heating furnace according to claim 10, characterized in that: The heating furnace state determination result includes the abnormality of the flame temperature of the target heating furnace; According to the type of monitoring parameters, according to the preset judgment rules, multiple heating furnace status judgments are performed in combination with corresponding monitoring parameters to obtain multiple types of heating furnace status judgment results, including: Performing RGB image recognition on the real-time combustion image to obtain the RGB value of each pixel in the real-time combustion image; Establish a mapping relationship between the RGB value of each pixel and the corresponding actual temperature value to obtain an RGB temperature image; The RGB temperature image is compared with a preset RGB standard temperature image to determine the pixel points where the flame temperature is abnormal, and the pixel points where the flame temperature is abnormal are displayed.

12. A heating furnace status monitoring system, characterized in that: include: A monitoring module, used to monitor the target heating furnace using a variety of preset monitoring methods and obtain monitoring parameters corresponding to each preset monitoring method; A state determination module is used to perform multiple heating furnace state determinations in combination with corresponding monitoring parameters according to the type of monitoring parameters and preset determination rules, and obtain multiple types of heating furnace state determination results; The target heating furnace overall state determination module is used to perform mutual verification based on all heating furnace state determination results to determine the target heating furnace overall state.

13. A machine-readable storage medium having instructions stored thereon, characterized in that: When the instruction is executed by a processor, the processor is configured to execute the heating furnace state monitoring method according to any one of claims 1 to 11.

14. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the heating furnace state monitoring method according to any one of claims 1 to 11 is implemented.

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