Intelligent fire extinguishing method and system based on kitchen fire

Abstract

The invention relates to an intelligent fire extinguishing method and system based on kitchen fires, and relates to the field of intelligent fire control technologies. The method comprises the steps that cooking bench firepower parameters and gas detection concentration are obtained; constructing a unit interval and determining a unit change parameter according to the unit interval; randomly delimiting a comparison interval and determining a comparison change parameter according to the comparison interval; defining a similar interval according to the analysis of the comparison interval and the unit interval, and obtaining a similar detection concentration according to the similar interval; determining the similar detection concentration with the maximum value according to a preset sorting rule, and defining the similar detection concentration with the maximum value as a reference detection concentration; calculating according to a preset permissible deviation coefficient and the reference detection concentration to determine a detection concentration threshold value; and when the current gas detection concentration is larger than the detection concentration threshold value, a preset fire extinguishing device is controlled to work. The kitchen fire monitoring system has the effect of improving the overall monitoring effect of the kitchen fire.

Description

Technical Field

[0001] The present application relates to the field of intelligent firefighting technology, and in particular to an intelligent fire extinguishing method and system based on kitchen fires. Background Art

[0002] At present, CO gas concentration detection is often used as the basis for fire judgment in intelligent monitoring technology for kitchen fires. The basic principle is: when an oil pan catches fire or fat is smoldering, incomplete combustion will produce a large amount of CO gas. Whether a fire has occurred can be determined by monitoring whether the CO concentration exceeds the preset threshold.

[0003] At present, in order to improve the sensitivity of fire detection, the CO alarm threshold is usually set lower. However, in actual use, changes in the combustion state of the gas stove (such as increasing the fire power but insufficient oxygen supply) will cause the CO concentration to rise briefly. At this time, the CO concentration may exceed the set threshold, thereby triggering a false alarm or false fire extinguishing, resulting in poor overall monitoring effect. There is still room for improvement. Summary of the Invention

[0004] In order to improve the overall monitoring effect of kitchen fires, the present application provides an intelligent fire extinguishing method and system based on kitchen fires.

[0005] In the first aspect, the present application provides an intelligent fire extinguishing method based on kitchen fires, which adopts the following technical solutions:

[0006] An intelligent fire extinguishing method based on kitchen fire, comprising:

[0007] Obtain stove fire parameters and gas detection concentration;

[0008] On a preset time axis, a unit interval with a width of a preset unit time length is constructed with the current time point as the rear end point, and a unit change parameter is determined by calculating the stove firepower parameters at the front and rear end points of the unit interval;

[0009] On the time axis, a historical interval with a preset historical duration is constructed with the current time point as the end point, and a comparison interval is randomly drawn within the historical interval according to the unit duration, and the comparison change parameter is determined based on the comparison interval;

[0010] The comparison interval in which the comparison change parameter is consistent with the unit change parameter and the stove fire parameter at the back end point is consistent with the current stove fire parameter is defined as a similar interval, and similar detection concentrations are obtained based on the similar interval;

[0011] Determine the similar detection concentration with the largest value according to a preset sorting rule, and define the similar detection concentration with the largest value as the benchmark detection concentration;

[0012] Calculate the detection concentration threshold based on the preset allowable deviation coefficient and the benchmark detection concentration;

[0013] When the current gas detection concentration is greater than the detection concentration threshold, the preset fire extinguishing device is controlled to operate.

[0014] Optionally, after the similarity detection concentration is determined, the intelligent fire extinguishing method based on the kitchen fire also includes:

[0015] Determine a similar surrounding interval based on the similar interval and the preset proximity duration, and divide the similar surrounding interval into a number of surrounding sub-intervals based on the unit duration;

[0016] Determine the corresponding similar interval in the historical interval based on the comparative change parameters of the surrounding sub-intervals and the stove firepower parameters at the back-end point, and determine the most recent interval length based on the similar interval closest to the current time point;

[0017] Determine the single trust parameter corresponding to the most recent time interval based on the preset trust matching relationship;

[0018] The overall trust parameter is determined by calculating the individual trust parameters corresponding to all surrounding sub-intervals;

[0019] The similar detection concentrations determined by the similarity interval whose overall trust parameter is smaller than the preset reliability parameter are eliminated.

[0020] Optionally, after the single trust parameter is determined, the intelligent fire extinguishing method for kitchen fires may further include:

[0021] Determine the equivalent interval based on the similar interval corresponding to the most recent time interval and the preset reliable time range;

[0022] Counting in the identical interval according to the determined similar interval to determine the identical and similar number;

[0023] The compensation parameters corresponding to the equivalent and similar quantities are determined according to the preset compensation matching relationship, and the monomer trust parameters are updated according to the compensation parameters.

[0024] Optionally, after some similar detection concentrations are eliminated, the intelligent fire extinguishing method based on kitchen fires also includes:

[0025] Count the retained similar test concentrations to determine the data reference quantity;

[0026] Determine whether the data reference quantity is greater than the preset benchmark requirement quantity;

[0027] If the data reference quantity is greater than the benchmark requirement quantity, the benchmark test concentration is determined based on the retained similar test concentrations;

[0028] If the data reference quantity is not greater than the benchmark demand quantity, the comparison interval in which the comparison change parameter is consistent with the unit change parameter in the historical interval is defined as the semi-same interval, and the stove firepower parameter at the back end point of the semi-same interval is defined as the semi-same firepower parameter, and the semi-same detection concentration is determined based on the semi-same interval;

[0029] Determine the semi-identical representative concentration based on each semi-identical detection concentration in the semi-identical interval of the same semi-identical firepower parameter;

[0030] Calculation is performed based on each semi-identical firepower parameter and the semi-identical representative concentration to determine the predicted detection concentration corresponding to the current stove firepower parameter, and the predicted detection concentration is defined as the benchmark detection concentration.

[0031] Optionally, the step of determining the semi-identical representative concentration according to each semi-identical detection concentration in the semi-identical interval of the same semi-identical firepower parameter includes:

[0032] Determine the overall trust parameter of each half-identical interval according to the half-identical intervals of the same half-identical firepower parameter, and define the overall trust parameter as the half-identical trust parameter;

[0033] Determine whether there are at least two semi-identical intervals with the same and largest semi-identical trust parameters;

[0034] If there are not at least two largest semi-identical intervals with the same semi-identical confidence parameter, the semi-identical detection concentration of the semi-identical interval corresponding to the largest semi-identical confidence parameter is determined as the semi-identical representative concentration;

[0035] If there are at least two largest semi-identical intervals with the same semi-identical confidence parameter, the semi-identical detection concentration of the semi-identical interval corresponding to the largest semi-identical confidence parameter is determined as the semi-identical candidate concentration;

[0036] Calculation is performed based on semi-identical candidate concentrations and pre-set boundary concentrations to determine candidate coverage;

[0037] The number of alternative coverages is determined by counting the semi-identical intervals whose semi-identical detection concentrations are within the alternative coverage range;

[0038] The alternative coverage number with the largest value is determined according to the sorting rules, and the semi-identical alternative concentration corresponding to the alternative coverage number is determined as the semi-identical representative concentration.

[0039] Optionally, after the number of alternative coverage options is determined, the intelligent fire extinguishing method for kitchen fires may also include:

[0040] Determine whether there are at least two alternative semi-identical intervals with the same number of covers and the largest possible number;

[0041] If there are not at least two largest semi-identical intervals with the same number of alternative coverage, the semi-identical representative concentration is determined based on the semi-identical interval with the largest number of alternative coverage;

[0042] If there are at least two semi-identical intervals with the same number of alternative coverages and the largest number, the range mean parameter is determined by calculating the semi-identical confidence parameters of each semi-identical interval within the alternative coverage range;

[0043] The range mean parameter with the largest value is determined according to the sorting rules, and the semi-identical representative concentration is determined according to the semi-identical interval corresponding to the range mean parameter.

[0044] Optionally, the step of controlling a preset fire extinguishing device to operate when the current gas detection concentration is greater than a detection concentration threshold includes:

[0045] According to the preset dosage matching relationship, the effective fire extinguishing dosage and the effective cooling dosage corresponding to the current gas detection concentration are determined;

[0046] Control the preset flame removal device to perform fire extinguishing operations with an effective fire extinguishing dose, and control the preset delay time to count down;

[0047] When the delay timer returns to zero, the preset cooling device is controlled to operate with an effective cooling dose, wherein the flame removal device and the cooling device constitute a fire extinguishing device.

[0048] In a second aspect, the present application provides an intelligent fire extinguishing system based on kitchen fires, which adopts the following technical solutions:

[0049] An intelligent fire extinguishing system based on kitchen fires, comprising:

[0050] Acquisition module, used to obtain stove fire parameters and gas detection concentration;

[0051] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0052] The judgment module is connected with the acquisition module and the processing module and is used for judging the information;

[0053] The processing module constructs a unit interval with a width of a preset unit time length on a preset time axis with the current time point as the rear end point, and calculates the unit change parameter based on the stove firepower parameters at the front and rear end points of the unit interval;

[0054] The processing module constructs a historical interval with a preset historical length on the time axis with the current time point as the end point, randomly demarcates a comparison interval according to the unit time length in the historical interval, and determines the comparison change parameter based on the comparison interval;

[0055] The processing module defines the comparison interval in which the comparison change parameter is consistent with the unit change parameter and the stove fire parameter at the back end point is consistent with the current stove fire parameter as a similar interval, and obtains a similar detection concentration based on the similar interval;

[0056] The processing module determines the similar detection concentration with the largest value according to a preset sorting rule, and defines the similar detection concentration with the largest value as the benchmark detection concentration;

[0057] The processing module calculates and determines the detection concentration threshold according to a preset allowable deviation coefficient and a reference detection concentration;

[0058] When the judging module determines that the current gas detection concentration is greater than the detection concentration threshold, the processing module controls the preset fire extinguishing device to operate.

[0059] In summary, this application includes at least one of the following beneficial technical effects:

[0060] 1. When monitoring kitchen fires, the system dynamically adjusts the CO concentration detection threshold by analyzing the fire power conversion situation to reduce false fire alarms caused by fire power changes and improve the overall monitoring effect of kitchen fires;

[0061] 2. Through a specific analysis of the stove fire situation to determine the reliability of each data, the required detection threshold can be determined more accurately, thereby improving the accuracy of fire monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a flow chart of an intelligent fire extinguishing method based on kitchen fire.

[0063] Figure 2 It is a module flow chart of the intelligent fire extinguishing method based on kitchen fire. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 2 It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0065] The embodiments of the present application are described in further detail below with reference to the accompanying drawings.

[0066] The present application embodiment discloses an intelligent fire extinguishing method based on kitchen fire, referring to Figure 1 The method flow of the intelligent fire extinguishing method based on kitchen fire includes the following steps:

[0067] Step S100: Obtain stove firepower parameters and gas detection concentration.

[0068] The stove firepower parameter is the parameter value of the firepower set on the stove. The actual firepower situation can be obtained by monitoring the rotation angle of the firepower adjustment knob; the gas detection concentration is the CO gas concentration value obtained by the sensor installed on the side of the boiler that can effectively monitor CO gas.

[0069] Step S101: construct a unit interval with a preset unit duration on a preset time axis with the current time point as the rear end point, and calculate the unit change parameter based on the stove firepower parameters at the front and rear end points of the unit interval.

[0070] The time axis is a coordinate axis formed by the combination of various time points. The coordinate axis points from the time points that have passed to the time points that have not yet arrived, where the time points that have passed are on the left side of the coordinate axis, and the left side of the coordinate axis is defined as the front side of the time axis; the unit duration is the duration value set by the staff for data analysis of the changes in the stove firepower, and the unit interval is constructed to facilitate the acquisition and analysis of data within the unit duration; the unit change parameter is the value obtained by subtracting the stove firepower parameter at the front end of the unit interval from the stove firepower parameter at the back end of the unit interval. When the value is positive, it means that the stove firepower is increased, and when the value is negative, it means that the stove firepower is decreased.

[0071] Step S102: constructing a historical interval with a preset historical duration on the time axis with the current time point as the rear end point, randomly defining a comparison interval according to the unit duration in the historical interval, and determining a comparison change parameter based on the comparison interval.

[0072] The historical duration is a duration value set by the staff that is much larger than the unit duration so that data on the historical usage of the stove can be obtained. The historical interval is constructed to facilitate the acquisition and analysis of historical data on the use of the stove. The comparison interval is an interval with a width of the unit duration at a random position in the historical interval. The comparison change parameter is the change parameter of the stove firepower in the comparison interval. The determination method is the same as the unit change parameter and is not repeated here.

[0073] Step S103: defining a comparison interval in which the comparison change parameter is consistent with the unit change parameter and the stove firepower parameter at the back-end point is consistent with the current stove firepower parameter as a similarity interval, and obtaining a similar detection concentration based on the similarity interval.

[0074] When the comparison change parameter is consistent with the unit change parameter and the stove firepower parameter at the rear end point is consistent with the current stove firepower parameter, it means that the specific usage of the stove in the corresponding comparison interval is similar to the specific usage of the current stove. Therefore, a similar interval is defined to distinguish different comparison intervals for subsequent analysis; the similar detection concentration is the CO gas concentration value obtained at the rear end point of the similar interval.

[0075] Step S104: determining the similar detection concentration with the largest value according to a preset sorting rule, and defining the similar detection concentration with the largest value as the reference detection concentration.

[0076] The sorting rule is a method set by the staff to sort the numerical values, such as the bubble method. The sorting rule can be used to determine the similar detection concentration with the largest value, which means that the similar detection concentration is the maximum CO gas concentration that will appear in the current use environment of the stove under normal circumstances. Therefore, the benchmark detection concentration is defined for identification to facilitate subsequent analysis.

[0077] Step S105: performing calculations based on a preset allowable deviation coefficient and a reference detection concentration to determine a detection concentration threshold.

[0078] The allowable deviation coefficient is the multiplier value set by the staff to allow CO gas to exceed the benchmark detection concentration. It is generally 1.2-1.3. By multiplying the allowable deviation coefficient by the benchmark detection concentration, the gas threshold that can effectively monitor the current stove situation can be obtained, that is, the detection concentration threshold.

[0079] Step S106: When the current gas detection concentration is greater than the detection concentration threshold, the preset fire extinguishing device is controlled to operate.

[0080] When the current gas detection concentration is greater than the detection concentration threshold, it means that the gas has not been completely burned and there is a high possibility that a fire has occurred. At this time, the fire extinguishing device can be controlled to extinguish the fire at the boiler location, where the fire extinguishing device can be a common fire extinguishing agent in the kitchen; in order to ensure the safety of fire extinguishing, the gas valve is closed synchronously when the fire extinguishing device is operated to cut off the gas, and at the same time, feedback can be synchronously fed back to the fire control center so that the management personnel can deal with the incident in a timely manner.

[0081] After the similar detection concentration is determined, the intelligent fire extinguishing method based on kitchen fire also includes:

[0082] Step S200: determining a similar surrounding interval according to the similar interval and the preset proximity duration, and dividing the similar surrounding interval into a plurality of surrounding sub-intervals according to the unit duration.

[0083] The nearest duration is the maximum distance between the other time points close to the similar interval set by the staff and the similar interval. Generally, the nearest duration is 3-5 times the unit duration. The similar peripheral interval is the time interval covered by the nearest duration extended from the front end point of the similar interval to the front of the time axis and the nearest duration extended from the rear end point of the similar interval to the rear of the time axis; the peripheral sub-interval is the time interval with a width of unit duration determined by equally dividing the similar peripheral interval according to the unit duration.

[0084] Step S201: Determine a corresponding similar interval in the historical interval based on the comparison change parameters of the surrounding sub-intervals and the stove firepower parameter of the back-end point, and determine the most recent interval time based on the similar interval closest to the current time point.

[0085] The currently determined similar interval is the time interval when the stove usage is consistent with the surrounding sub-intervals, and the most recent interval duration is the interval duration between the similar interval closest to the current time point and the current time point.

[0086] Step S202: Determine the monomer trust parameter corresponding to the most recent time interval according to the preset trust matching relationship.

[0087] The single trust parameter is a parameter value that reflects the reliability of the current similar interval obtained by analyzing the currently determined surrounding sub-intervals. The smaller the recent interval, the more likely the same usage environment has appeared recently, that is, the possibility of changes in the stove's own parameters (stove maintenance or changes) is low. At this time, the reliability of the similar interval corresponding to the current similar detection concentration is higher, that is, the single trust parameter is larger. Different recent intervals correspond to different single trust parameters. The trust matching relationship between the two is determined in advance by the staff. It is necessary to ensure that the smaller the recent interval, the larger the corresponding single trust parameter.

[0088] Step S203: Calculate the overall trust parameter based on the individual trust parameters corresponding to all surrounding sub-intervals.

[0089] The overall trust parameter is a parameter value that reflects the data reliability of the current similar interval obtained after analyzing all surrounding sub-intervals, and is determined by calculating the average value of all individual trust parameters.

[0090] Step S204: Eliminate similar detection concentrations determined by similar intervals whose overall confidence parameters are smaller than a preset reliability parameter.

[0091] The reliability parameter is the minimum overall trust parameter set by the staff to determine that the data reliability is high. The accuracy of data analysis is improved by eliminating similar detection concentrations determined by similar intervals where the overall trust parameter is smaller than the reliability parameter.

[0092] After the single trust parameter is determined, the intelligent fire extinguishing method for kitchen fires also includes:

[0093] Step S300: determining an equivalent interval according to the similar interval corresponding to the most recent time interval and a preset reliable time range.

[0094] The reliable duration range is a fixed range set by the staff. The equivalent interval can be obtained by constructing the width of the reliable duration range with the similar interval corresponding to the most recent interval as the center point.

[0095] Step S301: Counting the determined similarity intervals in the identical intervals to determine the identical and similarity number.

[0096] The number of identical and similar intervals is the total number of similar intervals determined in the identical interval.

[0097] Step S302: determining compensation parameters corresponding to the equivalent and similar quantities according to a preset compensation matching relationship, and updating the monomer trust parameters according to the compensation parameters.

[0098] The compensation parameter is a parameter value used to update the single trust parameter. The larger the number of similarities, the more data that can meet the requirements at the same time, that is, the higher the reliability of the corresponding data. Therefore, the larger the corresponding compensation parameter, the update of the single trust parameter can be achieved by adding the compensation parameter to the single trust parameter.

[0099] After eliminating some similar detection concentrations, the intelligent fire extinguishing method based on kitchen fires also includes:

[0100] Step S400: Counting is performed based on the retained similar detection concentrations to determine the data reference quantity.

[0101] The reference data quantity is the number of currently retained data of similar detection concentrations with a certain degree of reliability.

[0102] Step S401: Determine whether the data reference quantity is greater than a preset baseline requirement quantity.

[0103] The benchmark requirement quantity is the minimum data reference quantity set by the staff to determine whether the benchmark detection concentration can be better determined. Generally, it is 0. The purpose of the judgment is to determine whether the benchmark detection concentration can be better determined.

[0104] Step S4011: If the data reference quantity is greater than the benchmark requirement quantity, the benchmark detection concentration is determined based on the retained similar detection concentrations.

[0105] When the data reference quantity is greater than the benchmark requirement quantity, it means that the benchmark detection concentration can be determined. At this time, the maximum value analysis can be performed normally to determine the benchmark detection concentration.

[0106] Step S4012: If the data reference quantity is not greater than the benchmark requirement quantity, the comparison interval in which the comparison change parameter is consistent with the unit change parameter in the historical interval is defined as a semi-same interval, and the stove firepower parameter at the back end point of the semi-same interval is defined as a semi-same firepower parameter, and the semi-same detection concentration is determined based on the semi-same interval.

[0107] When the number of data references is not greater than the benchmark requirement number, it means that the benchmark detection concentration cannot be directly determined through maximum value analysis, so further analysis is required; by defining semi-same intervals and semi-same firepower parameters to distinguish different data, the semi-same detection concentration is the CO gas concentration detected at the end point of the semi-same interval.

[0108] Step S402: determining a semi-identical representative concentration according to each semi-identical detection concentration in a semi-identical interval of the same semi-identical firepower parameter.

[0109] The semi-identical representative concentration is a concentration value that can better represent the CO concentration in the current semi-identical interval under normal conditions. The specific determination method is referred to steps S500 to S504 and will not be described in detail here.

[0110] Step S403: Calculate based on each semi-identical firepower parameter and the semi-identical representative concentration to determine the predicted detection concentration corresponding to the current stove firepower parameter, and define the predicted detection concentration as the reference detection concentration.

[0111] The predicted detection concentration is the benchmark detection concentration corresponding to the current stove fire parameters obtained by analyzing the changing trends of different semi-identical fire parameters and semi-identical representative concentrations. The specific determination method is to construct various types of linear and nonlinear functions through known semi-identical fire parameters and semi-identical representative concentrations, select the function with the smallest deviation from them, and then use the stove fire parameters according to the function to solve the corresponding predicted detection concentration.

[0112] The step of determining the semi-identical representative concentration according to each semi-identical detection concentration in the semi-identical interval of the same semi-identical firepower parameter comprises:

[0113] Step S500: determining an overall trust parameter of each semi-identical interval according to the semi-identical intervals of the semi-identical firepower parameter, and defining the overall trust parameter as a semi-identical trust parameter.

[0114] The semi-identical trust parameter is defined to distinguish the overall trust parameter determined by each semi-identical interval, which is convenient for subsequent analysis.

[0115] Step S501: Determine whether there are at least two semi-identical intervals with the same and largest semi-identical trust parameters.

[0116] The purpose of the judgment is to find out whether there are multiple semi-identical intervals that meet the requirements under the same semi-identical firepower parameters.

[0117] Step S5011: If there are not at least two largest semi-identical intervals with the same semi-identical confidence parameter, the semi-identical detection concentration of the semi-identical interval corresponding to the largest semi-identical confidence parameter is determined as the semi-identical representative concentration.

[0118] When there are not at least two semi-identical intervals with the same and largest semi-identical trust parameters, it means that there is a semi-identical interval with the highest trust level, that is, the data reliability of this semi-identical interval is the highest. Therefore, the corresponding semi-identical detection concentration can be defined as the semi-identical representative concentration.

[0119] Step S5012: If there are at least two largest semi-identical intervals with the same semi-identical confidence parameter, the semi-identical detection concentration of the semi-identical interval corresponding to the largest semi-identical confidence parameter is determined as the semi-identical candidate concentration.

[0120] When there are at least two semi-identical intervals with the same and largest semi-identical confidence parameters, it means that there are multiple semi-identical intervals that meet the requirements. At this time, semi-identical alternative concentrations are defined to distinguish different semi-identical detection concentrations for subsequent analysis.

[0121] Step S502: performing calculations based on the semi-identical candidate concentrations and the preset boundary concentration to determine the candidate coverage range.

[0122] The boundary concentration is the maximum concentration difference between the remaining concentration values ​​in the area surrounding the semi-identical alternative concentration and the semi-identical alternative concentration, which is set by the staff. The alternative coverage range is constructed by adding and subtracting the bonding concentration from the semi-identical alternative concentration.

[0123] Step S503: Counting the semi-identical intervals whose semi-identical detection concentrations are within the alternative coverage range to determine the number of alternative coverages.

[0124] The number of alternative coverages is the number of semi-identical intervals included in the defined alternative coverage range.

[0125] Step S504: determining the candidate coverage number with the largest value according to the sorting rule, and determining the semi-identical candidate concentration corresponding to the candidate coverage number as the semi-identical representative concentration.

[0126] The sorting rules can be used to determine the number of alternative coverages with the largest value, that is, the data reliability of the corresponding semi-identical alternative concentration is the best, so it can be defined as the semi-identical representative concentration.

[0127] After the number of alternative coverage options is determined, the intelligent fire extinguishing method for kitchen fires also includes:

[0128] Step S600: Determine whether there are at least two candidate semi-identical intervals with the same and largest number of coverage.

[0129] The purpose of the judgment is to find out whether there are multiple semi-identical intervals that meet the requirements.

[0130] Step S6001: If there are not at least two semi-identical intervals with the same and largest candidate coverage number, the semi-identical representative concentration is determined according to the semi-identical interval with the largest candidate coverage number.

[0131] When there are not at least two alternative semi-identical intervals with the same and largest coverage number, it means that there is only one semi-identical interval that meets the requirements. At this time, the semi-identical representative concentration can be determined based on this semi-identical interval.

[0132] Step S6002: If there are at least two candidate semi-identical intervals with the same and largest number of semi-identical intervals, a range mean parameter is determined based on the semi-identical trust parameters of the semi-identical intervals within the candidate coverage range.

[0133] When there are at least two alternative semi-identical intervals with the same and largest number of coverage, it means that there are multiple semi-identical intervals that meet the requirements. At this time, the range mean parameter that can reflect the overall reliability of the data is determined by calculating the average value of the semi-identical trust parameters of each semi-identical interval within each alternative coverage range.

[0134] Step S601: determining the range mean parameter with the largest value according to the sorting rule, and determining the semi-identical representative concentration according to the semi-identical interval corresponding to the range mean parameter.

[0135] The range mean parameter with the largest value can be determined through the sorting rules, that is, the data reliability under the current corresponding semi-identical interval is higher, so the semi-identical representative concentration can be determined based on the corresponding semi-identical interval.

[0136] The steps of controlling the preset fire extinguishing device to operate when the current gas detection concentration is greater than the detection concentration threshold include:

[0137] Step S700: determining an effective fire extinguishing dose and an effective cooling dose corresponding to the current gas detection concentration according to a preset dose matching relationship.

[0138] The effective fire extinguishing dose is the dose of fire extinguishing agent required to effectively extinguish the current fire situation. The effective cooling dose is the amount of cooling water required. Different gas detection concentrations correspond to different fire severities, and the corresponding effective fire extinguishing dose and effective cooling dose are also different. The dose matching relationship between the three is determined in advance by the staff and recorded and stored.

[0139] Step S701: controlling a preset flame removal device to perform a fire extinguishing operation with an effective fire extinguishing dosage, and controlling a preset delay time to perform a countdown.

[0140] The flame removal device is a device that can release and spray fire extinguishing agents. The operation of the flame removal device can effectively extinguish the fire; the delay time is the time value set by the staff for the cooling water to delay the operation.

[0141] Step S702: When the delay timer returns to zero, the preset cooling device is controlled to operate with an effective cooling amount, wherein the flame removal device and the cooling device constitute a fire extinguishing device.

[0142] The cooling device is a device that can release cooling water flow. Through the operation of the cooling device, the fire site can be quickly cooled down, and re-ignition can be prevented. It can also effectively clean the fire extinguishing agent attached to the stove.

[0143] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention provides an intelligent fire extinguishing system based on kitchen fires, comprising:

[0144] Acquisition module, used to obtain stove fire parameters and gas detection concentration;

[0145] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0146] The judgment module is connected with the acquisition module and the processing module and is used for judging the information;

[0147] The processing module constructs a unit interval with a width of a preset unit time length on a preset time axis with the current time point as the rear end point, and calculates the unit change parameter based on the stove firepower parameters at the front and rear end points of the unit interval;

[0148] The processing module constructs a historical interval with a preset historical length on the time axis with the current time point as the end point, randomly demarcates a comparison interval according to the unit time length in the historical interval, and determines the comparison change parameter based on the comparison interval;

[0149] The processing module defines the comparison interval in which the comparison change parameter is consistent with the unit change parameter and the stove fire parameter at the back end point is consistent with the current stove fire parameter as a similar interval, and obtains a similar detection concentration based on the similar interval;

[0150] The processing module determines the similar detection concentration with the largest value according to a preset sorting rule, and defines the similar detection concentration with the largest value as the benchmark detection concentration;

[0151] The processing module calculates and determines the detection concentration threshold according to a preset allowable deviation coefficient and a reference detection concentration;

[0152] When the judgment module determines that the current gas detection concentration is greater than the detection concentration threshold, the processing module controls the preset fire extinguishing device to operate;

[0153] A similarity detection concentration analysis module is used to analyze and process the determined similarity detection concentration;

[0154] A single trust parameter updating module, configured to update the determined single trust parameter;

[0155] The module for predicting and determining the detection concentration is used to predict and determine the detection concentration when the amount of data is small;

[0156] A semi-identical representative concentration determination module, used for determining the semi-identical representative concentration;

[0157] A semi-identical interval screening module is used to screen multiple semi-identical intervals that meet the requirements;

[0158] The fire extinguishing device control module is used to control the actual use process of the fire extinguishing device.

[0159] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

Claims

1. An intelligent fire extinguishing method based on kitchen fire, characterized in that: include: Obtain stove fire parameters and gas detection concentration; On a preset time axis, a unit interval with a width of a preset unit time length is constructed with the current time point as the rear end point, and a unit change parameter is determined by calculating the stove firepower parameters at the front and rear end points of the unit interval; On the time axis, a historical interval with a preset historical duration is constructed with the current time point as the end point, and a comparison interval is randomly drawn within the historical interval according to the unit duration, and the comparison change parameter is determined based on the comparison interval; A comparison interval in which the comparison change parameter is consistent with the unit change parameter and the stove fire parameter at the back-end point is consistent with the current stove fire parameter is defined as a similar interval, and a similar detection concentration is obtained based on the similar interval; a similar detection concentration with the largest value is determined according to a preset sorting rule, and the similar detection concentration with the largest value is defined as the benchmark detection concentration; Calculate the detection concentration threshold based on the preset allowable deviation coefficient and the benchmark detection concentration; When the current gas detection concentration is greater than the detection concentration threshold, the preset fire extinguishing device is controlled to operate.

2. The intelligent fire extinguishing method based on kitchen fire according to claim 1 is characterized in that: After the similar detection concentration is determined, the intelligent fire extinguishing method based on kitchen fire also includes: Determine a similar surrounding interval based on the similar interval and the preset proximity duration, and divide the similar surrounding interval into a number of surrounding sub-intervals based on the unit duration; Based on the comparative change parameters of the surrounding sub-intervals and the stove firepower parameters at the back-end point, the corresponding similar interval is determined in the historical interval, and the most recent interval duration is determined based on the similar interval closest to the current time point. The individual trust parameter corresponding to the most recent interval duration is determined based on the preset trust matching relationship; The overall trust parameter is determined by calculating the individual trust parameters corresponding to all surrounding sub-intervals; The similar detection concentrations determined by the similarity interval whose overall trust parameter is smaller than the preset reliability parameter are eliminated.

3. The intelligent fire extinguishing method based on kitchen fire according to claim 2 is characterized in that: After the single trust parameter is determined, the intelligent fire extinguishing method for kitchen fires also includes: Determine an equivalent interval based on the similar interval corresponding to the most recent time interval and a preset reliable time range; and count the determined similar intervals in the equivalent interval to determine the number of equivalent similarities; The compensation parameters corresponding to the equivalent and similar quantities are determined according to the preset compensation matching relationship, and the monomer trust parameters are updated according to the compensation parameters.

4. The intelligent fire extinguishing method based on kitchen fire according to claim 2 is characterized in that: After eliminating some similar detection concentrations, the intelligent fire extinguishing method based on kitchen fires also includes: Count the retained similar test concentrations to determine the data reference quantity; Determine whether the data reference quantity is greater than the preset benchmark requirement quantity; If the data reference quantity is greater than the benchmark requirement quantity, the benchmark test concentration is determined based on the retained similar test concentrations; If the data reference quantity is not greater than the benchmark demand quantity, the comparison interval in which the comparison change parameter is consistent with the unit change parameter in the historical interval is defined as the semi-same interval, and the stove firepower parameter at the back end point of the semi-same interval is defined as the semi-same firepower parameter, and the semi-same detection concentration is determined based on the semi-same interval; Determine the semi-identical representative concentration based on each semi-identical detection concentration in the semi-identical interval of the same semi-identical firepower parameter; Calculation is performed based on each semi-identical firepower parameter and the semi-identical representative concentration to determine the predicted detection concentration corresponding to the current stove firepower parameter, and the predicted detection concentration is defined as the benchmark detection concentration.

5. The intelligent fire extinguishing method based on kitchen fire according to claim 4 is characterized in that: The step of determining the semi-identical representative concentration according to each semi-identical detection concentration in the semi-identical interval of the same semi-identical firepower parameter comprises: Determine the overall trust parameter of each half-identical interval according to the half-identical intervals of the same half-identical firepower parameter, and define the overall trust parameter as the half-identical trust parameter; Determine whether there are at least two semi-identical intervals with the same and largest semi-identical trust parameters; If there are not at least two largest semi-identical intervals with the same semi-identical confidence parameter, the semi-identical detection concentration of the semi-identical interval corresponding to the largest semi-identical confidence parameter is determined as the semi-identical representative concentration; If there are at least two largest semi-identical intervals with the same semi-identical confidence parameter, the semi-identical detection concentration of the semi-identical interval corresponding to the largest semi-identical confidence parameter is determined as the semi-identical candidate concentration; Calculation is performed based on semi-identical candidate concentrations and pre-set boundary concentrations to determine candidate coverage; The number of alternative coverages is determined by counting the semi-identical intervals whose semi-identical detection concentrations are within the alternative coverage range; The alternative coverage number with the largest value is determined according to the sorting rules, and the semi-identical alternative concentration corresponding to the alternative coverage number is determined as the semi-identical representative concentration.

6. The intelligent fire extinguishing method based on kitchen fire according to claim 5 is characterized in that: After the number of alternative coverage options is determined, the intelligent fire extinguishing method for kitchen fires also includes: Determine whether there are at least two alternative semi-identical intervals with the same number of covers and the largest possible number; If there are not at least two largest semi-identical intervals with the same number of alternative coverage, the semi-identical representative concentration is determined based on the semi-identical interval with the largest number of alternative coverage; If there are at least two semi-identical intervals with the same number of alternative coverages and the largest number, the range mean parameter is determined by calculating the semi-identical confidence parameters of each semi-identical interval within the alternative coverage range; The range mean parameter with the largest value is determined according to the sorting rules, and the semi-identical representative concentration is determined according to the semi-identical interval corresponding to the range mean parameter.

7. The intelligent fire extinguishing method based on kitchen fire according to claim 1 is characterized in that: The steps of controlling the preset fire extinguishing device to operate when the current gas detection concentration is greater than the detection concentration threshold include: According to the preset dosage matching relationship, the effective fire extinguishing dosage and the effective cooling dosage corresponding to the current gas detection concentration are determined; Control the preset flame removal device to perform fire extinguishing operations with an effective fire extinguishing dose, and control the preset delay time to count down; When the delay timer returns to zero, the preset cooling device is controlled to operate with an effective cooling dose, wherein the flame removal device and the cooling device constitute a fire extinguishing device.

8. An intelligent fire extinguishing system based on kitchen fire, characterized in that: include: Acquisition module, used to obtain stove fire parameters and gas detection concentration; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; The judgment module is connected with the acquisition module and the processing module and is used for judging the information; The processing module constructs a unit interval with a width of a preset unit time length on a preset time axis with the current time point as the rear end point, and calculates the unit change parameter based on the stove firepower parameters at the front and rear end points of the unit interval; The processing module constructs a historical interval with a preset historical length on the time axis with the current time point as the end point, randomly demarcates a comparison interval according to the unit time length in the historical interval, and determines the comparison change parameter based on the comparison interval; The processing module defines the comparison interval in which the comparison change parameter is consistent with the unit change parameter and the stove fire parameter at the back end point is consistent with the current stove fire parameter as a similar interval, and obtains a similar detection concentration based on the similar interval; The processing module determines the similar detection concentration with the largest value according to a preset sorting rule, and defines the similar detection concentration with the largest value as the benchmark detection concentration; The processing module calculates and determines the detection concentration threshold according to a preset allowable deviation coefficient and a reference detection concentration; When the judging module determines that the current gas detection concentration is greater than the detection concentration threshold, the processing module controls the preset fire extinguishing device to operate.

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