Self-adaptive monitoring method and device for integrated flame state of gas cooker

Abstract

The invention provides a self-adaptive monitoring method and device for an integrated flame state of a gas cooker, relates to the field of gas safety monitoring, and solves the problems that in flame monitoring of the gas cooker, flame in different scenes is difficult to dynamically monitor in a self-adaptive manner, and the safety of the gas cooker is influenced. And the technical problem that the combustion effect of flame is different due to the component difference of the fuel gas is neglected is solved. The method comprises the following steps: determining the self-adaptive monitoring frequency of the current gas cooker based on the opening degree of a valve and the wind speed; acquiring flame data of the gas cooker based on the self-adaptive monitoring frequency; acquiring characteristic flame data of the gas cooker at the current valve opening degree based on the historical flame data; establishing a flame comparison model, and inputting the current valve opening degree, the corresponding flame data, the characteristic flame data and the wind speed into the flame comparison model to obtain a safety factor; setting a control mode and sending a monitoring signal based on the safety factor; through dynamic monitoring and self-adaptive adjustment, the safety and adaptability of gas stove detection are improved.

Description

Technical Field

[0001] The present application relates to the field of gas safety monitoring, and in particular to a method and device for adaptively monitoring the integrated flame state of a gas cooker. Background Art

[0002] As modern families continue to demand higher quality of life and greater safety, the safety and intelligence of gas stoves, essential kitchen appliances in daily life, have become a major concern. Traditional gas stoves present several safety hazards during use, such as abnormal flames, which can lead to serious accidents such as fires and explosions.

[0003] At present, most gas stoves integrate flame state monitoring methods. In the flame monitoring of gas stoves, it is difficult to adaptively monitor the flames in different scenarios dynamically, which reduces the timeliness and accuracy of flame monitoring; and ignores the differences in the composition of the gas that cause the combustion effects of the flame. When different regions use the same set of gas stove flame monitoring systems, the size and color of the flames are different due to the differences in the gas composition in different regions. As a result, the flame monitoring system of the gas stove can only monitor in a small area and cannot perform integrated monitoring of a large area, which reduces the practicality of the monitoring system. Or there are conflicting errors in data analysis when monitoring a large area. For example, when other conditions remain unchanged, the flames of two gases with different compositions have different sizes, resulting in different data analysis, which poses certain safety hazards.

[0004] Therefore, the present application discloses a method and device for adaptively monitoring the integrated flame state of a gas cooker, which are used to solve the above technical problems. Summary of the Invention

[0005] The present application provides a method and device for adaptively monitoring the flame state of a gas cooker's integrated flame, which solves the technical problems in the prior art of flame monitoring of gas cookers, such as the difficulty in adaptively and dynamically monitoring the flame in different scenarios, and the neglect of the differences in combustion effects caused by differences in gas composition.

[0006] To achieve the above objectives, this application adopts the following technical solutions: In a first aspect, a method for adaptively monitoring the flame state of a gas cooker is provided, comprising: Determine the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed; Obtaining flame data corresponding to the current valve opening and closing degree of the gas stove based on the adaptive monitoring frequency; wherein the flame data includes flame size and flame color; Acquire characteristic flame data of the gas stove at the current valve opening and closing degree based on historical flame data; Establish a flame comparison model, input the current valve opening and closing degree and the corresponding flame data, characteristic flame data and wind speed into the flame comparison model to obtain the safety factor; Set control mode and send monitoring signals based on safety factors.

[0007] In combination with the first aspect above, in a possible implementation, determining the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed includes: Extract the wind speed V. When the wind speed V is greater than the safety limit wind speed QV of the current gas cooker at the current valve opening / closing degree, set the adaptive monitoring frequency of the current gas cooker to the maximum value of the standard frequency range. The safety limit wind speed is the maximum wind speed that does not cause the flame to go out at the current valve opening / closing degree, as determined by laboratory experiments on gas cookers of the same type as the current gas cooker. The standard frequency range is determined based on the performance of the photoelectric sensor and is expressed in times per minute. Both the maximum and minimum values ​​of the standard frequency range are proportional to the performance of the photoelectric sensor. When the wind speed V is not greater than the safety limit wind speed QV of the current gas cooker at the current valve opening / closing degree, the opening / closing variation amplitude HB is determined based on the real-time valve opening / closing degree, and it is judged whether the opening / closing variation amplitude HB is greater than 0; if so, the initial monitoring frequency CP of the current gas cooker is determined based on calculation formula (1); if not, the initial monitoring frequency CP of the current gas cooker is determined based on calculation formula (2); The initial monitoring frequency CP is limited to a standard frequency range to obtain an adaptive monitoring frequency YP, and the adaptive monitoring frequency YP satisfies calculation formula (3); The calculation formula (1) is: ; Where ZP is the median of the standard frequency range, ⌈⌉ is the round-up symbol; ZYP is the adaptive monitoring frequency recorded most recently after the gas cooker was turned on. If the most recently recorded adaptive monitoring frequency does not exist, ZYP is taken as the median of the standard frequency range. is the amplitude adjustment coefficient set according to the performance of the photoelectric sensor, and The value range of is [0,1]; The calculation formula (2) is: ; in, is the amplitude adjustment coefficient set according to the performance of the photoelectric sensor, and The value range of is [0,1]; The calculation formula (3) is: ; in, is the minimum value of the standard frequency range, is the maximum value of the standard frequency range, To obtain the minimum function, is the maximum value function.

[0008] In combination with the first aspect above, in a possible implementation, determining the opening / closing variation range HB based on the real-time valve opening / closing degree includes: Get the valve opening and closing degrees recorded n times before the current time and mark them from the beginning to the end according to the time. , based on valve opening Determine the opening and closing variation range HB; The opening and closing variation range HB satisfies the calculation formula (4): (4); Among them, n is obtained by manual setting, usually 20; The valve opening and closing degree in n records , and The value range is [1,n].

[0009] In combination with the first aspect above, in a possible implementation, obtaining flame data corresponding to the current valve opening and closing degree of the gas cooker based on the adaptive monitoring frequency includes: The adaptive monitoring frequency YP corresponding to the current valve opening and closing degree is extracted, and the flame size and flame color corresponding to the current valve opening and closing degree are obtained on time through the photoelectric sensor based on the adaptive monitoring frequency YP.

[0010] In combination with the first aspect above, in a possible implementation, obtaining characteristic flame data of the gas cooker at the current valve opening / closing degree based on historical flame data includes: Determine whether the number of times the gas stove's historical flame data is recorded under the current valve opening and closing degree and wind speed exceeds a number threshold; if so, integrate the stove's historical flame data into a reference database; if not, determine the amount of data missing based on the number of records and the number threshold, extract a number of historical flame data from the management area where the current gas stove is located based on the amount of data missing, and integrate the stove's historical flame data and the number of historical flame data extracted from the management area into a reference database; the number threshold is set based on experience, and the management area is divided according to the gas supply company; Integrate the flame colors in the reference database into a flame color data set, and mark the flame color that appears most frequently in the flame color data set as the characteristic flame color of the gas cooker at the current valve opening degree; wherein the characteristic flame data includes characteristic flame size and characteristic flame color; Integrate the flame sizes in the reference database into a flame size data set, obtain the variance of the flame sizes in the flame size data set, and determine whether the variance is less than a variance determination value; if so, retain the data in the flame size data set; if not, remove the flame size with the largest absolute value of the difference between the flame size data set and the average value of the flame size, and re-determine the variance until the variance in the flame size data set is less than the variance determination value, and retain the remaining data in the flame size data set; The characteristic flame size is obtained by performing weight calculation on the average, maximum and minimum values ​​of the data retained in the flame size data set.

[0011] In combination with the first aspect above, in a possible implementation, extracting a number of historical flame data from the management area where the current gas cooker is located based on the amount of data missing includes: Extract the amount of missing data, obtain the difference CZ between the amount of missing data and the number threshold, and extract CZ historical flame data from the management area where the current gas stove is located from near to far in time.

[0012] In conjunction with the first aspect above, in a possible implementation, the management area is divided according to the gas supply company, including: Within the target area, gas stoves of the same type and using the same type of gas from the same company are marked as same-burning stoves, and several household areas where the same-burning stoves are located are integrated into one management area; the target area is obtained through manual setting, and generally one city is one target area.

[0013] In combination with the first aspect above, in a possible implementation, establishing the flame contrast model includes: Extracting flame data and characteristic flame data of a gas cooker of the same type as the current gas cooker at various wind speeds and various valve openings from historical reference data, as well as corresponding safety factors; wherein the historical reference data includes flame data and corresponding characteristic flame data at various wind speeds and various valve openings, as well as safety factors set by experts based on the flame data and characteristic flame data; The flame data and characteristic flame data of several valve openings and closings at different wind speeds, as well as the corresponding safety factors, are integrated into several groups of training data and test data; the artificial intelligence model is trained using the training data, and the trained artificial intelligence model is tested using the test data, and the artificial intelligence model is adjusted according to the test results; finally, a flame comparison model is obtained with the valve opening and closing degree and the flame data, characteristic flame data and wind speed corresponding to the valve opening and closing degree as input, and the safety factor as output; wherein the artificial intelligence model includes a BP neural network model and an RBF neural network model.

[0014] In conjunction with the first aspect above, in one possible implementation, setting a control mode based on a safety factor and issuing a monitoring signal include: Extract the safety factor AY. When the value of the safety factor AY exceeds the standard factor BY, the valve opening is adjusted to 0 and a flame abnormality signal is issued. The standard factor BY and the target ratio are both obtained through empirical settings. When the value of the safety factor AY is less than the standard factor BY and greater than the target ratio of the standard factor BY, the valve opening degree MK to which the gas stove needs to be adjusted is determined based on the calculation formula (5), and a flame attention signal is issued; When the value of the safety factor AY is less than the standard factor BY and greater than the target ratio of the standard factor BY, no operation is performed; The calculation formula (5) is: ; Wherein, DK is the valve opening and closing degree of the current gas stove at the current time.

[0015] In a second aspect, a gas cooker integrated flame state adaptive monitoring device is provided, comprising: a communication unit and a processing unit; The communication unit is used to obtain flame data corresponding to the current valve opening and closing degree of the gas cooker based on the adaptive monitoring frequency; wherein the flame data includes flame size and flame color; The processing unit is used to determine the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed; obtain characteristic flame data of the gas cooker at the current valve opening and closing degree based on historical flame data; establish a flame comparison model, input the current valve opening and closing degree and the corresponding flame data, characteristic flame data and wind speed into the flame comparison model to obtain a safety factor; set a control mode based on the safety factor and issue a monitoring signal.

[0016] This application provides a method and device for adaptively monitoring the integrated flame state of a gas cooker, which has the following beneficial effects: 1. This application determines the current adaptive monitoring frequency of a gas cooker based on real-time valve opening and wind speed; obtains flame data corresponding to the current valve opening of the gas cooker based on the adaptive monitoring frequency; obtains characteristic flame data of the gas cooker at the current valve opening based on historical flame data; establishes a flame comparison model, inputs the current valve opening and closing, corresponding flame data, characteristic flame data, and wind speed into the flame comparison model to obtain a safety factor; sets a control mode based on the safety factor and issues a monitoring signal. This addresses the technical issues of prior art gas cooker flame monitoring, which include the difficulty in adaptively monitoring flames in different scenarios and the neglect of differences in combustion effects due to differences in gas composition. Through dynamic monitoring and adaptive adjustment, this application improves the safety and adaptability of gas cooker detection, particularly under varying environments and gas compositions.

[0017] 2. This application effectively addresses the regional limitations of flame monitoring systems caused by differences in gas composition by extracting characteristic flame data based on historical flame data for the current valve opening and closing of gas stoves. In traditional gas stove flame monitoring systems, the size and color of the burning flame vary due to regional variations in gas composition. This leads to data analysis conflicts and errors when the flame monitoring system is used across regions, reducing the practicality and safety of the monitoring system. This application analyzes historical flame data from gas stoves and extracts characteristic flame data, providing a standardized reference for the flame monitoring system, thereby enabling unified monitoring and analysis across regions.

[0018] It should be understood that the description of technical features, technical solutions, beneficial effects or similar language in this application does not imply that all features and advantages can be realized in any single embodiment. On the contrary, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution or beneficial effect is included in at least one embodiment. Therefore, the description of a technical feature, technical solution or beneficial effect in this specification does not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions and beneficial effects described in the present embodiment can also be combined in any appropriate manner. Those skilled in the art will understand that the embodiment can be implemented without one or more specific technical features, technical solutions or beneficial effects of a specific embodiment. In other embodiments, additional technical features and beneficial effects can also be identified in specific embodiments that do not embody all embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of the steps of a method for adaptively monitoring the flame state of a gas cooker integrated with an embodiment of the present application; Figure 2A schematic diagram of the steps for determining the adaptive monitoring frequency of the current gas cooker provided in an embodiment of the present application; Figure 3 This is a schematic diagram of the structure of a gas cooker integrated flame state adaptive monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In the description of this application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" means one or more, and "a plurality" means two or more. Words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not limit them to be necessarily different.

[0021] It should be noted that, in this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described in this application as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0022] The present invention provides an adaptive method for monitoring the flame state of a gas cooker's integrated flame. The method includes: adjusting the gas cooker's monitoring frequency based on real-time valve opening and closing and wind speed, and collecting flame data based on the monitoring frequency; extracting characteristic flame data at the current valve opening and closing based on historical data; inputting the current flame data, characteristic data, and wind speed into a model to calculate a safety factor; and setting a control mode and issuing a monitoring signal based on the safety factor to ensure the safe operation of the gas cooker. Consequently, the present invention improves the environmental and regional adaptability of integrated flame state monitoring for gas cookers, enhancing their practicality.

[0023] like Figure 1 As shown, an embodiment of the present application provides an adaptive monitoring method for the integrated flame state of a gas cooker, comprising: S201: Determine the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed.

[0024] In some implementations, the monitoring frequency of the gas stove can be set to multiple fixed monitoring frequencies, and the monitoring frequency can be selected according to the usage time after the gas stove is ignited; or it can be set to a dynamic monitoring frequency, and the monitoring frequency can be adjusted according to the risks generated during the use of the gas stove.

[0025] S202: Obtain flame data corresponding to the current valve opening and closing degree of the gas cooker based on the adaptive monitoring frequency.

[0026] The flame data includes flame size and flame color.

[0027] S203: Acquire characteristic flame data of the gas cooker at the current valve opening / closing degree based on the historical flame data.

[0028] S204 , establishing a flame comparison model, inputting the current valve opening / closing degree and the corresponding flame data, characteristic flame data and wind speed into the flame comparison model to obtain a safety factor.

[0029] S205: Setting a control mode based on the safety factor and issuing a monitoring signal.

[0030] In a possible implementation of the embodiment of the present application, combined with Figure 2 ,like Figure 3 As shown, the above S201 can be specifically described by the following S301 and S302: like Figure 2 As shown, S301, determining the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed, including: Extract the wind speed V. When the wind speed V is greater than the safety limit wind speed QV of the current gas cooker at the current valve opening / closing degree, set the adaptive monitoring frequency of the current gas cooker to the maximum value of the standard frequency range. The safety limit wind speed is the maximum wind speed that does not cause the flame to go out at the current valve opening / closing degree, as determined by laboratory experiments on gas cookers of the same type as the current gas cooker. The standard frequency range is determined based on the performance of the photoelectric sensor and is expressed in times per minute. Both the maximum and minimum values ​​of the standard frequency range are proportional to the performance of the photoelectric sensor. When the wind speed V is not greater than the safety limit wind speed QV of the current gas cooker at the current valve opening / closing degree, the opening / closing variation amplitude HB is determined based on the real-time valve opening / closing degree, and it is judged whether the opening / closing variation amplitude HB is greater than 0; if so, the initial monitoring frequency CP of the current gas cooker is determined based on calculation formula (1); if not, the initial monitoring frequency CP of the current gas cooker is determined based on calculation formula (2); The initial monitoring frequency CP is limited to a standard frequency range to obtain an adaptive monitoring frequency YP, and the adaptive monitoring frequency YP satisfies calculation formula (3); The calculation formula (1) is: ; Where ZP is the median of the standard frequency range, ⌈⌉ is the round-up symbol; ZYP is the adaptive monitoring frequency recorded most recently after the gas cooker was turned on. If the most recently recorded adaptive monitoring frequency does not exist, ZYP is taken as the median of the standard frequency range. is the amplitude adjustment coefficient set according to the performance of the photoelectric sensor, and The value range of is [0,1]; The calculation formula (2) is: ; in, is the amplitude adjustment coefficient set according to the performance of the photoelectric sensor, and The value range of is [0,1]; The calculation formula (3) is: ; in, is the minimum value of the standard frequency range, is the maximum value of the standard frequency range, To obtain the minimum function, is the maximum value function.

[0031] It is worth noting that this application proposes an adaptive monitoring frequency adjustment method for gas stoves based on real-time wind speed and valve opening and closing degree. This method can optimize the monitoring strategy according to different combustion states and environmental conditions by dynamically adjusting the flame monitoring frequency, thereby improving the real-time and accuracy of monitoring while significantly reducing resource consumption and improving the operating efficiency and environmental adaptability of monitoring.

[0032] Specifically, this application demonstrates technical advantages and practical application value in the following aspects: First of all, this application can intelligently judge the changing trend of the flame combustion state by collecting wind speed and valve opening and closing data in real time, and combining it with the safety limit wind speed obtained by laboratory experiments. When the wind speed exceeds the safety limit wind speed, the system will automatically increase the monitoring frequency to the maximum value of the standard frequency range, thereby enhancing the monitoring ability of flame jitter and avoiding misjudgment caused by wind influence. This dynamic adjustment strategy not only improves the environmental adaptability of the monitoring system, but also ensures that it can still work stably in complex environments, providing a strong guarantee for the safe operation of gas stoves.

[0033] Secondly, this application can reduce resource consumption by lowering the sampling frequency when the flame is burning stably, thereby optimizing system performance. When the flame state changes, the system can automatically increase the sampling frequency to capture the dynamic changes in the flame, ensuring real-time and accurate monitoring. This intelligent adjustment mechanism not only improves monitoring efficiency but also significantly reduces unnecessary waste of computing resources, providing support for the long-term stable operation of the system.

[0034] Furthermore, by introducing a standard frequency range limitation mechanism, this application can dynamically adjust the monitoring frequency based on the performance of the photoelectric sensor, ensuring that the monitoring frequency always remains within a reasonable range. This not only improves the flexibility and adaptability of the system, but also provides a universal solution for different types of photoelectric sensors, further expanding the scope of application of this method.

[0035] Finally, through experimental verification and practical application, this application demonstrates that the proposed adaptive monitoring frequency adjustment method can effectively cope with a variety of complex environmental conditions, significantly improving the monitoring performance and safety reliability of gas cookers. This method is not only applicable to household gas cookers but can also be extended to other fields such as industrial combustion equipment, showing broad application prospects and significant socioeconomic value.

[0036] In summary, this application dynamically adjusts the flame monitoring frequency to optimize the monitoring strategy based on different combustion states and environmental conditions, significantly improving the real-time performance, accuracy, and environmental adaptability of the monitoring system while reducing resource consumption and providing a strong guarantee for the safe and stable operation of gas cookers. The innovativeness and practicality of this method make it of great application value and promotional significance in the field of gas appliances.

[0037] It should be pointed out that It is used to calculate the influence of the opening and closing change amplitude HB on the initial monitoring frequency CP in formula (1); when other conditions remain unchanged, The larger the initial monitoring frequency, the greater the impact on CP. The smaller the initial monitoring frequency, the less impact CP will have; It is used to calculate the influence of the opening and closing change amplitude HB on the initial monitoring frequency CP in formula (2); when other conditions remain unchanged, The larger the initial monitoring frequency, the greater the impact on CP. The smaller the initial monitoring frequency, the less impact CP has.

[0038] For example, in this embodiment, the current wind speed V=3m / s, the valve opening degree is 50%, and the safety limit wind speed QV=2m / s when the current gas cooker valve opening degree is 50%. The wind speed V=3m / s is greater than the safety limit wind speed QV=2m / s when the current gas cooker valve opening degree is 50%. Therefore, the adaptive monitoring frequency of the current gas cooker is set to the maximum value of the standard frequency range, 30 times / minute; wherein, in this embodiment, the standard frequency range is [10 times / minute, 30 times / minute]. In another embodiment, the current wind speed V=1 m / s, the valve opening degree is 50%, and the safety limit wind speed QV=2 m / s when the current gas cooker valve opening degree is 50%. The wind speed V=1 m / s is not greater than the safety limit wind speed QV=2 m / s when the current gas cooker valve opening degree is 50%. In this embodiment, the standard frequency range is [10 times / minute, 30 times / minute]. If the opening and closing variation range HB=5% is determined based on the real-time valve opening and closing degree, the initial monitoring frequency CP of the current gas cooker is determined based on the calculation formula (1): ; Among them, in this embodiment The value is 0.9; the adaptive monitoring frequency ZYP of the gas stove recorded most recently after the current ignition is 15 times / minute; If the opening and closing variation range HB = -2% is determined based on the real-time valve opening and closing degree, the initial monitoring frequency CP of the current gas stove is determined based on calculation formula (2): ; Among them, in this embodiment The value is 0.95; the adaptive monitoring frequency ZYP value of the gas stove recorded most recently after the current ignition is 25 times / minute.

[0039] S302, determining the opening and closing variation range HB based on the real-time valve opening and closing degree, including: Get the valve opening and closing degrees recorded n times before the current time and mark them from the beginning to the end according to the time. , based on valve opening Determine the opening and closing variation range HB; The opening and closing variation range HB satisfies the calculation formula (4): (4); Among them, n is obtained by manual setting, usually 20; The valve opening and closing degree in n records , and The value range is [1,n].

[0040] It should be noted that in this application, the unit of valve opening and closing degree is %, 0% can be understood as the valve is completely closed, and 100% can be understood as the valve is completely open. When recording the valve opening and closing degree, each time the valve changes by 1% or 2%, it is recorded once.

[0041] It should be noted that the n times of recording before the current time is triggered when the valve is opened most recently before the current time. If the number of valve changes after the most recent valve opening is not less than n, the valve opening and closing degrees recorded n times before the current time are marked as If the number of valve changes after the last valve opening is less than n, the valve opening and closing degrees recorded between the last valve opening and the current time are marked as ; For example, if n is 20 and the current time is 18:02; If the most recent valve opening time of valve 1 is 18:00, and a total of 30 valve changes are recorded, the valve opening and closing degrees of the most recent 20 records before 18:02 are marked in descending order of time as ; If the most recent valve opening time of valve 1 is 18:00, and there are 15 valve changes recorded, the valve opening and closing degrees recorded between 18:00 and 18:02 will be marked as .

[0042] It should be pointed out that when When There is no specific data. The value is 0.

[0043] In a possible implementation of the embodiment of the present application, the above S202 can be specifically described by the following S401: S401, obtaining flame data corresponding to the current valve opening and closing degree of the gas cooker based on the adaptive monitoring frequency, including: The adaptive monitoring frequency YP corresponding to the current valve opening and closing degree is extracted, and the flame size and flame color corresponding to the current valve opening and closing degree are obtained on time through the photoelectric sensor based on the adaptive monitoring frequency YP.

[0044] It should be pointed out that the flame size is the plane area size of the flame obtained by the photoelectric sensor; Flame colors include blue, yellow and orange; blue flame: indicates complete combustion, high flame temperature and high combustion efficiency; yellow flame: indicates incomplete combustion, low flame temperature and low combustion efficiency; orange flame: indicates impurities in the flame or unstable combustion conditions.

[0045] In a possible implementation of the embodiment of the present application, the above S203 can be specifically described by the following S501, S502 and S503: S501: Acquire characteristic flame data of the gas cooker at the current valve opening / closing degree based on historical flame data, including: Determine whether the number of times the gas stove's historical flame data is recorded under the current valve opening and closing degree and wind speed exceeds a number threshold; if so, integrate the stove's historical flame data into a reference database; if not, determine the amount of data missing based on the number of records and the number threshold, extract a number of historical flame data from the management area where the current gas stove is located based on the amount of data missing, and integrate the stove's historical flame data and the number of historical flame data extracted from the management area into a reference database; the number threshold is set based on experience, and the management area is divided according to the gas supply company; Integrate the flame colors in the reference database into a flame color data set, and mark the flame color that appears most frequently in the flame color data set as the characteristic flame color of the gas cooker at the current valve opening degree; wherein the characteristic flame data includes characteristic flame size and characteristic flame color; Integrate the flame sizes in the reference database into a flame size data set, obtain the variance of the flame sizes in the flame size data set, and determine whether the variance is less than a variance determination value; if so, retain the data in the flame size data set; if not, remove the flame size with the largest absolute value of the difference between the flame size data set and the average value of the flame size, and re-determine the variance until the variance in the flame size data set is less than the variance determination value, and retain the remaining data in the flame size data set; The characteristic flame size is obtained by performing weight calculation on the average, maximum and minimum values ​​of the data retained in the flame size data set.

[0046] It is worth noting that this application effectively addresses the regional limitations of flame monitoring systems caused by differences in gas composition by obtaining characteristic flame data of the gas stove at the current valve opening and closing based on historical flame data. In traditional gas stove flame monitoring systems, the size and color of the burning flame vary due to differences in gas composition in different regions. This leads to data analysis conflicts and errors when the flame monitoring system is used across regions, reducing the practicality and safety of the monitoring system. This application analyzes the historical flame data of gas stoves and extracts characteristic flame data, providing a standardized reference basis for the flame monitoring system, thereby meeting the requirements of unified monitoring and analysis across regions.

[0047] Specifically, this application constructs a reference database by integrating historical flame data from gas cookers and historical flame data from the management area. From this database, characteristic flame colors and flame sizes are extracted. Characteristic flame colors are extracted based on the most frequent colors in the flame color data set. Characteristic flame sizes are extracted by analyzing the variance and mean of the flame size data set, removing outliers, and calculating a weighted average, maximum, and minimum value. This method not only considers the flame characteristics of the gas cooker under the current valve opening and wind speed, but also incorporates historical data from other gas cookers within the management area, fully reflecting the impact of differences in gas composition on flame combustion.

[0048] By using this characteristic flame data extraction method, the present application can provide a standardized reference for the flame monitoring system of gas stoves, thereby achieving uniformity and accuracy in flame monitoring despite differences in gas composition across different regions. This not only improves the practicality of the flame monitoring system, but also reduces data analysis errors and safety hazards caused by differences in gas composition, providing strong support for the intelligent management of gas stoves and the optimization of gas supply. In addition, the characteristic flame data extraction method of the present application can also provide a scientific basis for gas stove fault diagnosis, combustion efficiency optimization, and safety performance improvement, further promoting technological progress and intelligent development in the gas stove industry.

[0049] It should be noted that, after removing the flame size with the largest absolute difference between the flame size data set and the average value of the flame size and re-performing variance judgment, the average value of the flame size is the average value of the flame size retained in the current variance judgment step.

[0050] It should be noted that if the flame size data set has the largest absolute value of the difference from the average value of the flame size and has a maximum flame size and a minimum flame size, the largest flame size will be removed first.

[0051] It should be noted that if the variance of the remaining flame size is still greater than the variance judgment value after removing 90% of the flame size data, the average value of the original flame size of the flame size data set is used as the characteristic flame size.

[0052] It should be pointed out that the weighted calculation of the characteristic flame size by using the average, maximum and minimum values ​​of the data retained in the flame size data group is artificially set according to the importance of the data; for example, in a set of data, the average is more stable than the maximum and minimum values, so the weight of the average is greater than the maximum and minimum values, and when analyzing the characteristics of the flame, the maximum and minimum values ​​have the same effect on the flame size, so the weights of the maximum and minimum values ​​can be the same; for example, the weight of the average is 0.5, the weight of the maximum is 0.25, and the weight of the minimum is 0.25.

[0053] S502: extracting some historical flame data from the management area where the current gas stove is located based on the amount of missing data, including: Extract the amount of missing data, obtain the difference CZ between the amount of missing data and the number threshold, and extract CZ historical flame data from the management area where the current gas stove is located from near to far in time.

[0054] S503. Management areas are divided according to gas supply companies and include: Within the target area, gas stoves of the same type and using the same type of gas from the same company are marked as same-burning stoves, and several household areas where the same-burning stoves are located are integrated into one management area; the target area is obtained through manual setting, and generally one city is one target area.

[0055] It is worth noting that this application divides management areas based on the gas supply company and gas type used by gas stoves, changing the limitations of the traditional management area division method that relies on geographical proximity, and can more accurately reflect gas usage characteristics and user needs. This division method can effectively integrate household areas with the same gas usage characteristics to form management areas with gas usage as the core feature, thereby improving the efficiency of gas management and the accuracy of data analysis. Since the division of management areas is no longer limited by geographical location, it can better adapt to the diversity and complexity of urban gas use and reduce analysis errors caused by geographical location interference. In addition, the management area division method of this application can provide gas companies with more accurate user group divisions, support targeted gas services and marketing strategies, and help optimize the allocation and utilization of gas resources. Through this innovative management area division method, more scientific and systematic data support can be provided for urban gas management, the overall level of gas management can be improved, and the intelligent and refined management development of the gas industry can be promoted.

[0056] In a possible implementation of the embodiment of the present application, the above S204 can be specifically described by the following S601: S601: Establishing a flame contrast model, including: Extracting flame data and characteristic flame data of a gas cooker of the same type as the current gas cooker at various wind speeds and various valve openings from historical reference data, as well as corresponding safety factors; wherein the historical reference data includes flame data and corresponding characteristic flame data at various wind speeds and various valve openings, as well as safety factors set by experts based on the flame data and characteristic flame data; The flame data and characteristic flame data of several valve openings and closings at different wind speeds, as well as the corresponding safety factors, are integrated into several groups of training data and test data; the artificial intelligence model is trained using the training data, and the trained artificial intelligence model is tested using the test data, and the artificial intelligence model is adjusted according to the test results; finally, a flame comparison model is obtained with the valve opening and closing degree and the flame data, characteristic flame data and wind speed corresponding to the valve opening and closing degree as input, and the safety factor as output; wherein the artificial intelligence model includes a BP neural network model and an RBF neural network model.

[0057] It should be pointed out that the safety factor is a quantitative value that can represent the safety of the flame under the current valve opening and closing degree and wind speed, which is used for subsequent flame control and issuing monitoring signals; when the difference between the flame size and flame color in the flame data and the characteristic flame data is greater, the value of the safety factor is smaller, and the greater the difference in flame color, the smaller the value of the safety factor is.

[0058] Specifically, the trained artificial intelligence model is tested using test data, and the specific steps for adjusting the artificial intelligence model based on the test results are as follows: The valve opening and closing degree, wind speed and corresponding flame data and characteristic flame data in the test data are input into the trained artificial intelligence model to obtain the corresponding safety factor, and the corresponding safety factor is compared with the corresponding safety factor in the test data. When the difference between the two is within the threshold, which is obtained based on experience, there is no need to adjust the parameters, and the next set of test data is tested; if it is not within the threshold, the corresponding parameters are adjusted until the difference between the safety factor of the corresponding test data and the corresponding safety factor is within the threshold, and then the next set of test data is tested. When the number of test data with the safety factor difference within the threshold obtained from all test data accounts for 95% or more of the total test data, a flame comparison model is obtained with the valve opening and closing degree and the flame data, characteristic flame data and wind speed corresponding to the valve opening and closing degree as input, and the safety factor as output.

[0059] In a possible implementation of the embodiment of the present application, the above S205 can be specifically described by the following S701: S701. Setting a control mode based on a safety factor and issuing a monitoring signal, including: Extract the safety factor AY. When the value of the safety factor AY exceeds the standard factor BY, the valve opening is adjusted to 0 and a flame abnormality signal is issued. The standard factor BY and the target ratio are both obtained through empirical settings. When the value of the safety factor AY is less than the standard factor BY and greater than the target ratio of the standard factor BY, the valve opening degree MK to which the gas stove needs to be adjusted is determined based on the calculation formula (5), and a flame attention signal is issued; When the value of the safety factor AY is less than the standard factor BY and greater than the target ratio of the standard factor BY, no operation is performed; The calculation formula (5) is: ; Wherein, DK is the valve opening and closing degree of the current gas stove at the current time.

[0060] The above mainly introduces the scheme of the embodiment of the present application from the perspective of device implementation. It can be understood that each device, for example, an adaptive monitoring device for the integrated flame state of a gas cooker, includes at least one of the hardware structures and software modules corresponding to the execution of each function in order to realize the above functions. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0061] In the embodiment of the present application, a gas cooker integrated flame state adaptive monitoring device can be divided into functional units according to the above-mentioned method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into a processing unit. The above-mentioned integrated unit can be implemented in the form of hardware or software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical functional division. In actual implementation, other division methods may be used.

[0062] In the case of an integrated unit, Figure 3 A possible structural diagram of a gas cooker integrated flame state adaptive monitoring device (denoted as a communication device 50 ) involved in the above embodiment is shown. The communication device 50 includes a processing unit 501 and a communication unit 502 , and may further include a storage unit 503 . Figure 3 The structural diagram shown can be used to illustrate the structure of a gas cooker integrated flame state adaptive monitoring device involved in the above embodiments.

[0063] when Figure 3The structural schematic diagram shown is used to illustrate the structure of a gas cooker integrated flame state adaptive monitoring device involved in the above embodiment. The processing unit 501 is used to control and manage the operation of the gas cooker integrated flame state adaptive monitoring device, the communication unit 502 is used for the gas cooker integrated flame state adaptive monitoring device to communicate with other devices, and the storage unit 503 is used to store program code and data of the gas cooker integrated flame state adaptive monitoring device.

[0064] For example, the communication unit is used to obtain flame data corresponding to the current valve opening and closing degree of the gas stove based on the adaptive monitoring frequency; wherein the flame data includes flame size and flame color; The processing unit is used to determine the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed; obtain the characteristic flame data of the gas cooker at the current valve opening and closing degree based on the historical flame data; establish a flame comparison model, input the current valve opening and closing degree and the corresponding flame data, characteristic flame data and wind speed into the flame comparison model to obtain a safety factor; set the control mode based on the safety factor and issue a monitoring signal.

[0065] Some of the data in the above calculation formula are calculated by removing the dimensions and taking their numerical values. The calculation formula is a calculation formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the calculation formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

Claims

1. A method for adaptively monitoring the flame state of a gas cooker, characterized in that: include: Determine the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed; Obtaining flame data corresponding to the current valve opening and closing degree of the gas stove based on the adaptive monitoring frequency; wherein the flame data includes flame size and flame color; Acquire characteristic flame data of the gas stove at the current valve opening and closing degree based on historical flame data; Establish a flame comparison model, input the current valve opening and closing degree and the corresponding flame data, characteristic flame data and wind speed into the flame comparison model to obtain the safety factor; Set control mode and send monitoring signals based on safety factors.

2. The method for adaptively monitoring the flame state of a gas cooker according to claim 1, characterized in that: The method of determining the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed includes: Extracting the wind speed V, and when the wind speed V is greater than the safety limit wind speed QV of the current gas cooker at the current valve opening / closing degree, setting the adaptive monitoring frequency of the current gas cooker to the maximum value of the standard frequency range; When the wind speed V is not greater than the safety limit wind speed QV of the current gas cooker at the current valve opening / closing degree, the opening / closing variation amplitude HB is determined based on the real-time valve opening / closing degree, and it is judged whether the opening / closing variation amplitude HB is greater than 0; if so, the initial monitoring frequency CP of the current gas cooker is determined based on calculation formula (1); if not, the initial monitoring frequency CP of the current gas cooker is determined based on calculation formula (2); The initial monitoring frequency CP is limited to a standard frequency range to obtain an adaptive monitoring frequency YP, and the adaptive monitoring frequency YP satisfies calculation formula (3); The calculation formula (1) is: ； Where ZP is the median of the standard frequency range, ⌈⌉ is the round-up symbol; ZYP is the adaptive monitoring frequency recorded most recently after the gas cooker was turned on. If the most recently recorded adaptive monitoring frequency does not exist, ZYP is taken as the median of the standard frequency range. is the amplitude adjustment coefficient set according to the performance of the photoelectric sensor, and The value range of is [0,1]; The calculation formula (2) is: ； in, is the amplitude adjustment coefficient set according to the performance of the photoelectric sensor, and The value range of is [0,1]; The calculation formula (3) is: ； in, is the minimum value of the standard frequency range, is the maximum value of the standard frequency range, To obtain the minimum function, is the maximum value function.

3. The adaptive monitoring method for integrated flame status of a gas cooker according to claim 2, characterized in that: The determining of the opening and closing variation range HB based on the real-time valve opening and closing degree includes: Get the valve opening and closing degrees recorded n times before the current time and mark them from the beginning to the end according to the time. , based on valve opening Determine the opening and closing variation range HB; The opening and closing variation range HB satisfies the calculation formula (4): (4)； in, The valve opening and closing degree in n records , and The value range is [1,n].

4. The method for adaptively monitoring the flame state of a gas cooker according to claim 1, characterized in that: The method of obtaining flame data corresponding to the current valve opening and closing degree of the gas cooker based on the adaptive monitoring frequency includes: The adaptive monitoring frequency YP corresponding to the current valve opening and closing degree is extracted, and the flame size and flame color corresponding to the current valve opening and closing degree are obtained on time through the photoelectric sensor based on the adaptive monitoring frequency YP.

5. The method for adaptively monitoring the flame state of a gas cooker according to claim 1, characterized in that: The method of obtaining characteristic flame data of the gas cooker at the current valve opening and closing degree based on historical flame data includes: Determine whether the number of times historical flame data of the current gas stove is recorded under the current valve opening and closing degree and wind speed exceeds a number threshold; if so, integrate the historical flame data of the stove into a reference database; if not, determine the amount of data missing based on the number of records and the number threshold, extract a number of historical flame data from the management area where the current gas stove is located based on the amount of data missing, and integrate the historical flame data of the stove and the historical flame data extracted from the management area into a reference database; wherein the management area is divided according to the gas supply company; Integrate the flame colors in the reference database into a flame color data set, and mark the flame color that appears most frequently in the flame color data set as the characteristic flame color of the gas cooker at the current valve opening degree; wherein the characteristic flame data includes characteristic flame size and characteristic flame color; Integrate the flame sizes in the reference database into a flame size data set, obtain the variance of the flame sizes in the flame size data set, and determine whether the variance is less than a variance determination value; if so, retain the data in the flame size data set; if not, remove the flame size with the largest absolute value of the difference between the flame size data set and the average value of the flame size, and re-determine the variance until the variance in the flame size data set is less than the variance determination value, and retain the remaining data in the flame size data set; The characteristic flame size is obtained by performing weight calculation on the average, maximum and minimum values ​​of the data retained in the flame size data set.

6. The method for adaptively monitoring the flame state of a gas cooker according to claim 5, characterized in that: The method of extracting a number of historical flame data from the management area where the current gas stove is located based on the amount of data missing includes: Extract the amount of missing data, obtain the difference CZ between the amount of missing data and the number threshold, and extract CZ historical flame data from the management area where the current gas stove is located from near to far in time.

7. The method for adaptively monitoring the flame state of a gas cooker according to claim 5, characterized in that: The management area is divided according to the gas supply company, including: Within the target area, gas stoves of the same type and using the same type of gas from the same company are marked as same-fuel stoves, and several household areas where the same-fuel stoves are located are integrated into one management area.

8. The method for adaptively monitoring the flame state of a gas cooker according to claim 1, characterized in that: The flame contrast model is established, comprising: Extracting flame data and characteristic flame data of a gas cooker of the same type as the current gas cooker at various wind speeds and various valve openings from historical reference data, as well as corresponding safety factors; wherein the historical reference data includes flame data and corresponding characteristic flame data at various wind speeds and various valve openings, as well as safety factors set by experts based on the flame data and characteristic flame data; The flame data and characteristic flame data of several valve openings and closings at different wind speeds, as well as the corresponding safety factors, are integrated into several groups of training data and test data; the artificial intelligence model is trained using the training data, and the trained artificial intelligence model is tested using the test data, and the artificial intelligence model is adjusted according to the test results; finally, a flame comparison model is obtained with the valve opening and closing degree and the flame data, characteristic flame data and wind speed corresponding to the valve opening and closing degree as input, and the safety factor as output; wherein the artificial intelligence model includes a BP neural network model and an RBF neural network model.

9. The method for adaptively monitoring the flame state of a gas cooker according to claim 1, characterized in that: The control mode is set based on the safety factor and the monitoring signal is issued, including: Extract the safety factor AY. When the value of the safety factor AY exceeds the standard factor BY, adjust the valve opening to 0 and send a signal indicating abnormal flame condition. When the value of the safety factor AY is less than the standard factor BY and greater than the target ratio of the standard factor BY, the valve opening degree MK to which the gas stove needs to be adjusted is determined based on the calculation formula (5), and a flame attention signal is issued; When the value of the safety factor AY is less than the standard factor BY and greater than the target ratio of the standard factor BY, no operation is performed; The calculation formula (5) is: ； Wherein, DK is the valve opening and closing degree of the current gas stove at the current time.

10. An adaptive monitoring device for integrated flame status of a gas cooker, used for running the adaptive monitoring method for integrated flame status of a gas cooker according to any one of claims 1 to 9, characterized in that: The device includes: a communication unit and a processing unit; The communication unit is used to obtain flame data corresponding to the current valve opening and closing degree of the gas cooker based on the adaptive monitoring frequency; wherein the flame data includes flame size and flame color; The processing unit is used to determine the adaptive monitoring frequency of the current gas cooker based on the real-time valve opening and closing degree and wind speed; obtain characteristic flame data of the gas cooker at the current valve opening and closing degree based on historical flame data; establish a flame comparison model, input the current valve opening and closing degree and the corresponding flame data, characteristic flame data and wind speed into the flame comparison model to obtain a safety factor; set a control mode based on the safety factor and issue a monitoring signal.

Images