Fire-fighting early warning system based on self-adaption

Abstract

The invention relates to the technical field of fire-fighting early warning, and discloses a self-adaption-based fire-fighting early warning system, which is characterized in that a mark generation module obtains a plurality of real-time fire related parameters of a region to be subjected to fire-fighting early warning, and generates an initial analysis mark of the region to be subjected to fire-fighting early warning; the parameter classification module collects multiple groups of real-time fire correlation parameters based on information collection nodes in a preset time period, and classifies the parameters to obtain a real-time fire correlation parameter group; the first calculation module is used for partitioning the real-time fire correlation parameter group and calculating a strong correlation fire factor and a weak correlation fire factor; a second calculation module calculates a comprehensive correlation fire factor according to the strong correlation fire factor and the weak correlation fire factor, and calculates a fire fighting early warning coefficient; and the fire-fighting early warning module judges whether fire early warning reminding is generated or not based on the fire fire-fighting early warning coefficient, obtains real-time fire related parameters, realizes initial fire detection, improves the timeliness of fire-fighting early warning, avoids fire spreading, ensures quick fire-fighting response, and improves the fire response efficiency and success rate.

Description

Technical Field

[0001] The present invention relates to the technical field of fire warning, and in particular, to an adaptive fire warning system. Background Art

[0002] Fire warning is a system that monitors and analyzes various potential fire signs, discovers in advance and notifies relevant personnel to take preventive or response measures. This warning mechanism plays a crucial role in reducing fire risks, protecting personnel safety and property.

[0003] In the prior art, fire warning is generally carried out through flame recognition, and flame recognition depends on its unique color, shape and dynamic change characteristics. Specifically, the image information of the fire scene is captured in real time by a camera. After image acquisition, preprocessing is carried out, including steps such as grayscale conversion and noise suppression. Color models such as RGB or HSV, as well as morphological methods, are used to extract the flame area, and the existence of the flame is further confirmed through motion trajectory analysis. This flame recognition method can only identify and alarm when a fire has occurred, and cannot achieve fire warning in the initial stage of a fire. Summary of the Invention

[0004] An embodiment of the present invention provides an adaptive fire warning system. By obtaining relevant information in a timely manner in the initial stage of a fire, the present invention realizes the detection in the initial stage of a fire, improves the timeliness of fire warning, avoids the spread of fire, ensures rapid fire response, and improves the efficiency and success rate of fire response.

[0005] To achieve the above object, the present invention provides an adaptive fire warning system, including:

[0006] A mark generation module, configured to determine the area to be fire-warned, obtain multiple real-time fire-related parameters of the area to be fire-warned in real time, analyze the real-time fire-related parameters, and generate an initial analysis mark for the area to be fire-warned based on the analysis result, wherein the initial analysis mark includes a real-time warning mark, a continuous acquisition mark, and a suspected fire mark;

[0007] A parameter classification module, configured to, when the suspected fire mark is recognized, collect multiple groups of real-time fire-related parameters based on information acquisition nodes within a preset time period, classify each group of real-time fire-related parameters, and obtain multiple groups of real-time fire-related parameters of the same category;

[0008] A first calculation module, configured to partition the real-time fire-related parameter groups and calculate the strong correlation fire factor and the weak correlation fire factor of the area to be fire-warned according to the real-time fire-related parameters;

[0009] A second calculation module, configured to calculate a comprehensive associated fire factor based on the strongly associated fire factors and weakly associated fire factors, and calculate a fire prevention and warning coefficient for the area to be fire-prevention-warned based on the comprehensive associated fire factor;

[0010] A fire prevention and warning module, configured to determine whether to generate a fire warning reminder for the area to be fire-prevention-warned based on the relationship between the fire prevention and warning coefficient and a preset fire prevention and warning coefficient.

[0011] Further, the mark generation module is configured to:

[0012] The mark generation module is configured to determine a preset fire associated parameter corresponding to each real-time fire associated parameter, compare the real-time fire associated parameter with the preset fire associated parameter. If the real-time fire associated parameters are all less than or equal to the preset fire associated parameter, generate the continuous acquisition mark for the area to be fire-prevention-warned;

[0013] The mark generation module is configured to, if the real-time fire associated parameters are all greater than the preset fire associated parameter, generate the real-time warning mark for the area to be fire-prevention-warned;

[0014] The mark generation module is configured to, if there are real-time fire associated parameters less than or equal to the preset fire associated parameter and there are real-time fire associated parameters greater than the preset fire associated parameter, generate the suspected fire situation mark for the area to be fire-prevention-warned.

[0015] Further, the first calculation module is configured to:

[0016] The first calculation module is configured to classify all fire associated parameters greater than the preset fire associated parameter in the real-time fire associated parameter group into a strongly associated fire interval;

[0017] The first calculation module is configured to classify all fire associated parameters greater than or equal to the preset fire associated parameter in the real-time fire associated parameter group into a weakly associated fire interval;

[0018] The first calculation module is configured to calculate a strongly associated fire factor for the area to be fire-prevention-warned based on the strongly associated fire interval;

[0019] The first calculation module is configured to calculate a weakly associated fire factor for the area to be fire-prevention-warned based on the weakly associated fire interval.

[0020] Further, the first calculation module is configured to:

[0021] The first calculation module is used to calculate the interval mean and interval variance corresponding to the strongly correlated fire interval, compare the numerical magnitudes of the interval mean and the interval variance, and use the smaller numerical value as the first interval identification signal;

[0022] The first calculation module is used to use the larger numerical value as the second interval identification signal;

[0023] The first calculation module is used to generate a first identification for the real-time fire correlation parameters within the strongly correlated fire interval that are less than the first interval identification signal;

[0024] The first calculation module is used to generate a second identification for the real-time fire correlation parameters within the strongly correlated fire interval that are greater than or equal to the first interval identification signal and less than the second interval identification signal;

[0025] The first calculation module is used to generate a third identification for the real-time fire correlation parameters within the strongly correlated fire interval that are greater than or equal to the second interval identification signal;

[0026] The first calculation module is used to calculate the strongly correlated fire factor of the area to be fire-prevention warned according to the first identification, the second identification, and the third identification.

[0027] Further, the first calculation module is used to:

[0028] The first calculation module is used to calculate the strongly correlated fire factor of the area to be fire-prevention warned according to the following formula:

[0029]

[0030] Where q is the strongly correlated fire factor of the area to be fire-prevention warned, a1 is the first calculation coefficient, a2 is the second calculation coefficient, a1 + a2 = 1, and a1 > a2, n1 is the number of real-time fire correlation parameters corresponding to the second identification, w1 is the first interval identification signal, e i is the i-th real-time fire correlation parameter corresponding to the second identification, (w1 - e i ) min is the minimum value of all (w1 - e i ), n2 is the number of real-time fire correlation parameters corresponding to the third identification, w2 is the second interval identification signal, r j is the j-th real-time fire correlation parameter corresponding to the third identification, (r j - w2) min is the minimum value of all (r j - w2), and y is the dynamic adjustment value of the strongly correlated fire factor;

[0031] The first calculation module is used to determine the dynamic adjustment value of the strongly correlated fire factor according to the following steps;

[0032] The first calculation module is used to count the number n3 of real-time fire correlation parameters corresponding to the first identifier;

[0033] The first calculation module is used to preset a first dynamic adjustment value, a second dynamic adjustment value, and a third dynamic adjustment value;

[0034] When n3 / (n1 + n2) < 1, the first calculation module is used to select the first dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor;

[0035] When 1 ≤ n3 / (n1 + n2) < 1.2, the first calculation module is used to select the second dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor;

[0036] When 1.2 ≤ n3 / (n1 + n2), the first calculation module is used to select the third dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor.

[0037] Further, the first calculation module is used for:

[0038] The first calculation module is used to extract the same real-time fire correlation parameters from the weakly correlated fire intervals and obtain multiple real-time fire correlation parameter sequences;

[0039] The first calculation module is used to count the number of the first real-time fire correlation parameter sequences of the real-time fire correlation parameter sequences;

[0040] The first calculation module is used to extract one real-time fire correlation parameter from all the real-time fire correlation parameter sequences respectively and calculate the sum value of the first real-time fire correlation parameters;

[0041] The first calculation module is used to calculate a preset fire correlation parameter, eliminate all the real-time fire correlation parameter sequences smaller than the preset fire correlation parameter, and count the number of the second real-time fire correlation parameter sequences of the remaining real-time fire correlation parameter sequences;

[0042] The first calculation module is used to extract one real-time fire correlation parameter from the remaining real-time fire correlation parameter sequences respectively and calculate the sum value of the second real-time fire correlation parameters;

[0043] The first calculation module is used to calculate the weakly correlated fire factor of the area to be fire-pre-alarmed according to the number of the first real-time fire correlation parameter sequences, the number of the second real-time fire correlation parameter sequences, the sum value of the first real-time fire correlation parameters, and the sum value of the second real-time fire correlation parameters.

[0044] Further, the first calculation module is used for:

[0045] The first calculation module is used to calculate the weakly associated fire factors of the area to be fire-precautioned according to the following formula:

[0046]

[0047] Where p is the weakly associated fire factor of the area to be fire-precautioned, s1 is the number of the first real-time fire association parameter sequences, s2 is the number of the second real-time fire association parameter sequences, d1 is the sum value of the first real-time fire association parameters, and d2 is the sum value of the second real-time fire association parameters.

[0048] Furthermore, the second calculation module is used for:

[0049] The second calculation module is used to configure a first calculation weight for the strongly associated fire factors and a second calculation weight for the weakly associated fire factors;

[0050] The second calculation module is used to calculate the comprehensive associated fire factor according to the following formula:

[0051] f = h1×q + h2×p;

[0052] Where f is the comprehensive associated fire factor, h1 is the first calculation weight, h2 is the second calculation weight, q is the strongly associated fire factor, and p is the weakly associated fire factor;

[0053] The second calculation module is used to randomly pair all the comprehensive associated fire factors in pairs to obtain a plurality of comprehensive associated fire factor matching sets;

[0054] The second calculation module is used to calculate the difference in the comprehensive associated fire factors between two comprehensive associated fire factors in each comprehensive associated fire factor matching set;

[0055] If the difference in the comprehensive associated fire factors is less than the preset difference in the comprehensive associated fire factors, the second calculation module is used to disassemble and reorganize the comprehensive associated fire factor matching set to obtain a new comprehensive associated fire factor matching set;

[0056] The second calculation module is used to analyze the new comprehensive associated fire factor matching set until the difference in the comprehensive associated fire factors of the new comprehensive associated fire factor matching set is greater than or equal to the preset difference in the comprehensive associated fire factors;

[0057] The second calculation module is used to calculate the fire prevention and warning coefficient of the area to be fire-precautioned according to all the comprehensive associated fire factor matching sets.

[0058] Furthermore, the second calculation module is used for:

[0059] The second calculation module is used to calculate the fire prevention warning coefficient of the area to be fire-prevention warned according to the following formula:

[0060]

[0061] where k is the fire prevention warning coefficient of the area to be fire-prevention warned, m is the set of comprehensive associated fire factor matches, c1 b is the comprehensive associated fire factor in the b-th set of comprehensive associated fire factor matches, and c2 b is another comprehensive associated fire factor in the b-th set of comprehensive associated fire factor matches. ((c1 b - c2 b )) 2 ) min is the minimum value of all ((c1 b - c2 b )) 2 , and ((c1 b - c2 b )) 2 ) max is the maximum value of all ((c1 b - c2 b )) 2 .

[0062] Furthermore, the fire prevention warning module is used for:

[0063] The fire prevention warning module is used to not generate a fire warning reminder for the area to be fire-prevention warned when the fire prevention warning coefficient is less than the preset fire prevention warning coefficient;

[0064] The fire prevention warning module is used to generate a fire warning reminder for the area to be fire-prevention warned when the fire prevention warning coefficient is greater than or equal to the preset fire prevention warning coefficient.

[0065] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0066] The present invention discloses an adaptive fire warning system. The marking generation module obtains multiple real-time fire-related parameters of the area to be fire-warned, and generates a preliminary analysis mark for the area to be fire-warned; the parameter classification module collects multiple groups of real-time fire-related parameters based on the information collection nodes within a preset time period, and classifies them to obtain a real-time fire-related parameter group; the first calculation module partitions the real-time fire-related parameter group, and calculates strong-correlation fire factors and weak-correlation fire factors; the second calculation module calculates a comprehensive correlation fire factor according to the strong-correlation fire factors and weak-correlation fire factors, and calculates a fire-fighting warning coefficient; the fire warning module determines whether to generate a fire warning reminder based on the fire-fighting warning coefficient, obtains real-time fire-related parameters, realizes the detection in the initial stage of a fire, improves the timeliness of fire warning, avoids the spread of fire, ensures a rapid fire response, and improves the efficiency and success rate of fire response. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered as limiting the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0068] Figure 1 The structural schematic diagram of the adaptive fire warning system in the embodiment of the present invention is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0069] The following will further describe in detail the specific embodiments of the present invention in conjunction with the drawings and embodiments. The following embodiments are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0070] In the description of the present application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the present application.

[0071] The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0072] In the description of this application, it should be noted that unless otherwise clearly specified and defined, the terms "installation", "connection", and "linkage" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific situations.

[0073] The following is a description of the preferred embodiments of the present invention in conjunction with the accompanying drawings.

[0074] As Figure 1 shown, an embodiment of the present invention discloses an adaptive fire warning system, including:

[0075] A marker generation module, which is used to determine the area to be fire warned, obtain multiple real-time fire-related parameters of the area to be fire warned in real time, analyze the real-time fire-related parameters, and generate a preliminary analysis marker for the area to be fire warned based on the analysis result, where the preliminary analysis marker includes a real-time warning marker, a continuous acquisition marker, and a suspected fire marker;

[0076] A parameter classification module, which is used to, when the suspected fire marker is recognized, collect multiple groups of real-time fire-related parameters based on the information collection nodes within a preset time period, classify each group of real-time fire-related parameters, and obtain multiple groups of real-time fire-related parameters of the same category;

[0077] A first calculation module, which is used to partition the real-time fire-related parameter groups and calculate the strong correlation fire factor and the weak correlation fire factor of the area to be fire warned according to the real-time fire-related parameters;

[0078] A second calculation module, which is used to calculate the comprehensive correlation fire factor according to the strong correlation fire factor and the weak correlation fire factor, and calculate the fire warning coefficient of the area to be fire warned according to the comprehensive correlation fire factor;

[0079] A fire warning module, which is used to judge whether to generate a fire warning reminder for the area to be fire warned based on the relationship between the fire warning coefficient and the preset fire warning coefficient.

[0080] In this embodiment, the real-time fire-related parameters include temperature parameters, smoke volume parameters, environmental pressure parameters, etc.

[0081] In this embodiment, the multiple information collection nodes are specifically collection time nodes, such as the 1st second, the 2nd second, and the 3rd second, etc. Therefore, multiple groups of real-time fire-related parameters can be collected.

[0082] In this embodiment, the real-time fire correlation parameters of each group are classified, that is, the real-time fire correlation parameters of the same type are divided into the same real-time fire correlation parameter group. For example, all temperature parameters are divided into a real-time fire correlation parameter group. Then, the data in this real-time fire correlation parameter group are all temperature parameters.

[0083] The beneficial effects of the above technical solution are as follows: The present invention obtains real-time fire correlation parameters, realizes the detection in the initial stage of a fire, improves the timeliness of fire prevention warnings, avoids the spread of fires, ensures a rapid fire response, and improves the efficiency and success rate of fire response.

[0084] In some embodiments of the present application, the marking generation module is used for:

[0085] The marking generation module is used to determine the preset fire correlation parameter corresponding to each real-time fire correlation parameter, compare the real-time fire correlation parameter with the preset fire correlation parameter. If the real-time fire correlation parameters are all less than or equal to the preset fire correlation parameter, then generate the continuous acquisition mark for the area to be fire prevention warned;

[0086] The marking generation module is used to, if the real-time fire correlation parameters are all greater than the preset fire correlation parameter, then generate the real-time warning mark for the area to be fire prevention warned;

[0087] The marking generation module is used to, if there are real-time fire correlation parameters less than or equal to the preset fire correlation parameter and there are real-time fire correlation parameters greater than the preset fire correlation parameter, then generate the suspected fire situation mark for the area to be fire prevention warned.

[0088] In this embodiment, the preset fire correlation parameter corresponds to the real-time fire correlation parameter one by one. For example, the preset temperature parameter corresponding to the temperature parameter is 30 °C, and the preset smoke amount parameter corresponding to the smoke amount parameter is 0.5 mg. The rest are not shown one by one.

[0089] In this embodiment, when the real-time warning mark is recognized, a fire warning reminder is directly issued.

[0090] The beneficial effects of the above technical solution are as follows: According to the real-time fire correlation parameter and the preset fire correlation parameter, the present invention can generate a real-time warning mark, a continuous acquisition mark and a suspected fire situation mark for the area to be fire prevention warned, realize the preliminary analysis of the area to be fire prevention warned, and directly issue a fire warning reminder when the real-time warning mark is recognized, avoiding the spread of fires. When the suspected fire situation mark is recognized, it is possible that some changes in the real-time fire correlation parameters are caused by other factors. Therefore, further judgment is required.

[0091] In some embodiments of the present application, the first calculation module is used for:

[0092] The first calculation module is configured to classify all the fire correlation parameters in the real-time fire correlation parameter group that are greater than the preset fire correlation parameter into a strong correlation fire interval;

[0093] The first calculation module is configured to classify all the fire correlation parameters in the real-time fire correlation parameter group that are greater than or equal to the preset fire correlation parameter into a weak correlation fire interval;

[0094] The first calculation module is configured to calculate the strong correlation fire factor of the area to be fire-prevention warned based on the strong correlation fire interval;

[0095] The first calculation module is configured to calculate the weak correlation fire factor of the area to be fire-prevention warned based on the weak correlation fire interval.

[0096] In some embodiments of the present application, the first calculation module is configured to:

[0097] The first calculation module is configured to calculate the interval mean value and the interval variance corresponding to the strong correlation fire interval, compare the numerical magnitudes of the interval mean value and the interval variance, and use the smaller numerical value as the first interval identification signal;

[0098] The first calculation module is configured to use the larger numerical value as the second interval identification signal;

[0099] The first calculation module is configured to generate a first identification for the real-time fire correlation parameters within the strong correlation fire interval that are less than the first interval identification signal;

[0100] The first calculation module is configured to generate a second identification for the real-time fire correlation parameters within the strong correlation fire interval that are greater than or equal to the first interval identification signal and less than the second interval identification signal;

[0101] The first calculation module is configured to generate a third identification for the real-time fire correlation parameters within the strong correlation fire interval that are greater than or equal to the second interval identification signal;

[0102] The first calculation module is configured to calculate the strong correlation fire factor of the area to be fire-prevention warned according to the first identification, the second identification, and the third identification.

[0103] In this embodiment, if the interval mean value and the interval variance are equal, then generate a first identification for the real-time fire correlation parameters within the strong correlation fire interval that are less than the interval mean value (or the interval variance), generate a second identification for the real-time fire correlation parameters within the strong correlation fire interval that are equal to the interval mean value (or the interval variance), and generate a third identification for the real-time fire correlation parameters within the strong correlation fire interval that are greater than the interval mean value (or the interval variance).

[0104] The beneficial effects of the above technical solution are as follows: According to the first identifier, the second identifier, and the third identifier, the present invention calculates the strongly associated fire factors in the area to be fire-precautioned, ensuring the calculation accuracy of the strongly associated fire factors and providing a calculation premise for the calculation of the fire-prevention warning coefficient.

[0105] In some embodiments of the present application, the first calculation module is configured to:

[0106] The first calculation module is configured to calculate the strongly associated fire factors in the area to be fire-precautioned according to the following formula:

[0107]

[0108] where q is the strongly associated fire factor in the area to be fire-precautioned, a1 is the first calculation coefficient, a2 is the second calculation coefficient, a1 + a2 = 1, and a1 > a2, n1 is the number of real-time fire association parameters corresponding to the second identifier, w1 is the first interval identifier signal, e i is the real-time fire association parameter corresponding to the i-th second identifier, (w1 - e i ) min is the minimum value of all (w1 - e i ), n2 is the number of real-time fire association parameters corresponding to the third identifier, w2 is the second interval identifier signal, r j is the real-time fire association parameter corresponding to the j-th third identifier, (r j - w2) min is the minimum value of all (r j - w2), and y is the dynamic adjustment value of the strongly associated fire factor;

[0109] The first calculation module is configured to determine the dynamic adjustment value of the strongly associated fire factor according to the following steps;

[0110] The first calculation module is configured to count the number n3 of real-time fire association parameters corresponding to the first identifier;

[0111] The first calculation module is configured to preset a first dynamic adjustment value, a second dynamic adjustment value, and a third dynamic adjustment value;

[0112] The first calculation module is configured to, when n3 / (n1 + n2) < 1, select the first dynamic adjustment value as the dynamic adjustment value of the strongly associated fire factor;

[0113] The first calculation module is configured to, when 1 ≤ n3 / (n1 + n2) < 1.2, select the second dynamic adjustment value as the dynamic adjustment value of the strongly associated fire factor;

[0114] The first calculation module is used to select the third dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor when 1.2 ≤ n3 / (n1 + n2).

[0115] In this embodiment, the first dynamic adjustment value is preferably 0.85, the second dynamic adjustment value is preferably 0.95, and the third dynamic adjustment value is preferably 1.15. Specifically, it can also be adjusted according to the actual situation.

[0116] The beneficial effects of the above technical solution are as follows: According to the number n3 of real-time fire correlation parameters of the present invention, the corresponding dynamic adjustment value is selected, realizing the dynamic adjustment of the strongly correlated fire factor, and further ensuring the calculation accuracy and comprehensiveness.

[0117] In some embodiments of the present application, the first calculation module is used for:

[0118] The first calculation module is used to extract the same real-time fire correlation parameters from the weakly correlated fire intervals and obtain multiple real-time fire correlation parameter sequences;

[0119] The first calculation module is used to count the number of the first real-time fire correlation parameter sequences of the real-time fire correlation parameter sequences;

[0120] The first calculation module is used to extract one real-time fire correlation parameter from all the real-time fire correlation parameter sequences respectively and calculate the sum value of the first real-time fire correlation parameters;

[0121] The first calculation module is used to calculate the preset fire correlation parameter, eliminate all the real-time fire correlation parameter sequences smaller than the preset fire correlation parameter, and count the number of the second real-time fire correlation parameter sequences of the remaining real-time fire correlation parameter sequences;

[0122] The first calculation module is used to extract one real-time fire correlation parameter from the remaining real-time fire correlation parameter sequences respectively and calculate the sum value of the second real-time fire correlation parameters;

[0123] The first calculation module is used to calculate the weakly correlated fire factor of the area to be fire-fighting warned according to the number of the first real-time fire correlation parameter sequences, the number of the second real-time fire correlation parameter sequences, the sum value of the first real-time fire correlation parameters and the sum value of the second real-time fire correlation parameters.

[0124] In this embodiment, the preset fire correlation parameter is the variance of all the real-time fire correlation parameters in the weakly correlated fire interval.

[0125] The beneficial effects of the above technical solution are as follows: The present invention calculates the weakly associated fire factors of the area to be fire-precautioned based on the number of the first real-time fire-associated parameter sequences, the number of the second real-time fire-associated parameter sequences, the sum value of the first real-time fire-associated parameters, and the sum value of the second real-time fire-associated parameters, which ensures the calculation accuracy of the weakly associated fire factors and provides another aspect of calculation premise for the calculation of the fire-precaution warning coefficient.

[0126] In some embodiments of the present application, the first calculation module is configured to:

[0127] The first calculation module is configured to calculate the weakly associated fire factors of the area to be fire-precautioned according to the following formula:

[0128]

[0129] Wherein, p is the weakly associated fire factor of the area to be fire-precautioned, s1 is the number of the first real-time fire-associated parameter sequences, s2 is the number of the second real-time fire-associated parameter sequences, d1 is the sum value of the first real-time fire-associated parameters, and d2 is the sum value of the second real-time fire-associated parameters.

[0130] In some embodiments of the present application, the second calculation module is configured to:

[0131] The second calculation module is configured to configure a first calculation weight for the strongly associated fire factors and a second calculation weight for the weakly associated fire factors;

[0132] The second calculation module is configured to calculate the comprehensive associated fire factors according to the following formula:

[0133] f = h1×q + h2×p;

[0134] Wherein, f is the comprehensive associated fire factor, h1 is the first calculation weight, h2 is the second calculation weight, q is the strongly associated fire factor, and p is the weakly associated fire factor;

[0135] The second calculation module is configured to randomly pair all the comprehensive associated fire factors to obtain a plurality of comprehensive associated fire factor matching sets;

[0136] The second calculation module is configured to calculate the difference between the two comprehensive associated fire factors in each comprehensive associated fire factor matching set;

[0137] The second calculation module is configured to, if the difference between the comprehensive associated fire factors is less than the preset difference between the comprehensive associated fire factors, disassemble and reorganize the comprehensive associated fire factor matching set to obtain a new comprehensive associated fire factor matching set;

[0138] The second calculation module is used to analyze the new comprehensive associated fire factor matching set until the comprehensive associated fire factor difference of the new comprehensive associated fire factor matching set is greater than or equal to the preset comprehensive associated fire factor difference;

[0139] The second calculation module is used to calculate the fire prevention and warning coefficient of the area to be fire-prevention warned according to all the comprehensive associated fire factor matching sets.

[0140] In this embodiment, h1 is preferably 0.75 and h2 is preferably 0.25, and can be specifically adjusted according to actual requirements.

[0141] In this embodiment, the preset comprehensive associated fire factor difference is preferably 6.

[0142] In this embodiment, if the comprehensive associated fire factor difference is greater than or equal to the preset comprehensive associated fire factor difference, it is reserved, and all the comprehensive associated fire factor matching sets with the comprehensive associated fire factor difference less than the preset comprehensive associated fire factor difference are disassembled and randomly combined in pairs again until the comprehensive associated fire factor difference is greater than or equal to the preset comprehensive associated fire factor difference.

[0143] The beneficial effects of the above technical solution are: The present invention calculates the fire prevention and warning coefficient of the area to be fire-prevention warned according to all the comprehensive associated fire factor matching sets, and can accurately judge whether there is a fire phenomenon in the area to be fire-prevention warned by calculating the fire prevention and warning coefficient.

[0144] In some embodiments of the present application, the second calculation module is used for:

[0145] The second calculation module is used to calculate the fire prevention and warning coefficient of the area to be fire-prevention warned according to the following formula:

[0146]

[0147] Where k is the fire prevention and warning coefficient of the area to be fire-prevention warned, m is the comprehensive associated fire factor matching set, c1 b is the comprehensive associated fire factor in the bth comprehensive associated fire factor matching set, c2 b is another comprehensive associated fire factor in the bth comprehensive associated fire factor matching set, ((c1 b -c2 b ) 2 ) min is the minimum value of all (c1 b -c2 b ) 2 The minimum value of, ((c1 b -c2 b ) 2 )max For all (c1 b - c2 b ), 2 the maximum value.

[0148] In some embodiments of the present application, the fire warning module is used for:

[0149] When the fire warning coefficient is less than the preset fire warning coefficient, the fire warning module does not generate a fire warning reminder for the area to be fire-warned;

[0150] When the fire warning coefficient is greater than or equal to the preset fire warning coefficient, the fire warning module generates a fire warning reminder for the area to be fire-warned.

[0151] In this embodiment, the preset fire warning coefficient is 4, and it can be specifically adjusted according to actual needs.

[0152] The beneficial effects of the above technical solutions are as follows: The present invention issues a warning in a timely manner at the initial stage of a fire, avoids the spread of the fire, ensures rapid fire response, and improves the efficiency and success rate of fire response.

[0153] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0154] Although the present invention has been described above with reference to embodiments, various improvements can be made to it and components therein can be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention can be combined with each other in any way, and the situations of these combinations are not all described in this specification only for the sake of saving space and resources.

[0155] Those of ordinary skill in the art can understand that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A fire warning system based on self-adaptation, characterized in that: include: A mark generation module is used to determine the area to be warned of fire, obtain multiple real-time fire-related parameters of the area to be warned of fire in real time, analyze the real-time fire-related parameters, and generate a preliminary analysis mark for the area to be warned of fire based on the analysis result, wherein the preliminary analysis mark includes a real-time warning mark, a continuous acquisition mark and a suspected fire mark; A parameter classification module is used for, when the suspected fire mark is identified, collecting multiple groups of real-time fire-related parameters based on the information collection nodes within a preset time period, classifying each group of real-time fire-related parameters, and obtaining multiple groups of real-time fire-related parameters of the same category; A first calculation module, used for partitioning the real-time fire-related parameter group, and calculating the strong-correlated fire factor and the weak-correlated fire factor of the area to be warned of fire according to the real-time fire-related parameters; A second calculation module is used to calculate a comprehensive correlation fire factor according to the strong correlation fire factor and the weak correlation fire factor, and calculate a fire warning coefficient of the area to be warned according to the comprehensive correlation fire factor; The fire warning module is used to determine whether to generate a fire warning reminder for the fire warning area based on the relationship between the fire warning coefficient and the preset fire warning coefficient.

2. The adaptive fire warning system according to claim 1 is characterized in that: The tag generation module is used to: The mark generation module is used to determine a preset fire-related parameter corresponding to each real-time fire-related parameter, compare the real-time fire-related parameter with the preset fire-related parameter, and generate the continuous acquisition mark for the area to be warned of fire if the real-time fire-related parameters are all less than or equal to the preset fire-related parameters; The mark generation module is used to generate the real-time warning mark for the area to be warned of fire if the real-time fire-related parameters are all greater than the preset fire-related parameters; The mark generation module is used to generate the suspected fire mark for the area to be warned of fire if the real-time fire-related parameter is less than or equal to the preset fire-related parameter and the real-time fire-related parameter is greater than the preset fire-related parameter.

3. The adaptive fire warning system according to claim 1 is characterized in that: The first calculation module is used for: The first calculation module is used to divide all fire-related parameters in the real-time fire-related parameter group that are greater than the preset fire-related parameters into strongly correlated fire intervals; The first calculation module is used to classify all fire-related parameters in the real-time fire-related parameter group that are greater than or equal to the preset fire-related parameters into weakly correlated fire intervals; The first calculation module is used to calculate the strongly correlated fire factor of the area to be warned of fire based on the strongly correlated fire interval; The first calculation module is used to calculate the weakly correlated fire factor of the area to be warned of fire based on the weakly correlated fire interval.

4. The adaptive fire warning system according to claim 3 is characterized in that: The first calculation module is used for: The first calculation module is used to calculate the interval mean and interval variance corresponding to the strongly correlated fire interval, compare the numerical values ​​of the interval mean and the interval variance, and use the smaller value as the first interval identification signal; The first calculation module is used to use the larger value as the second interval identification signal; The first calculation module is used to generate a first identification for a real-time fire-related parameter within the strongly associated fire interval that is smaller than the first interval identification signal; The first calculation module is used to generate a second identification for a real-time fire-related parameter within the strongly associated fire interval that is greater than or equal to the first interval identification signal and less than the second interval identification signal; The first calculation module is used to generate a third identification for the real-time fire-related parameter greater than or equal to the second interval identification signal within the strongly associated fire interval; The first calculation module is used to calculate the strongly correlated fire factor of the area to be warned of fire according to the first identifier, the second identifier and the third identifier.

5. The adaptive fire warning system according to claim 4 is characterized in that: The first calculation module is used for: The first calculation module is used to calculate the strong correlation fire factor of the area to be warned according to the following formula: Wherein, q is the strong correlation fire factor of the area to be warned, a1 is the first calculation coefficient, a2 is the second calculation coefficient, a1+a2=1, and a1>a2, n1 is the number of real-time fire correlation parameters corresponding to the second identification, w1 is the first interval identification signal, e i is the real-time fire-related parameter corresponding to the i-th second identifier, (w1-e i ) min For all (w1-e i ), n2 is the number of real-time fire-related parameters corresponding to the third identification, w2 is the second interval identification signal, r j is the real-time fire-related parameter corresponding to the jth third identifier, (r j -w2) min For all (r j -w2), y is the dynamic adjustment value of the strongly correlated fire factor; The first calculation module is used to determine the dynamic adjustment value of the strongly correlated fire factor according to the following steps; The first calculation module is used to count the number n3 of real-time fire-related parameters corresponding to the first identifier; The first calculation module is used to preset a first dynamic adjustment value, a second dynamic adjustment value and a third dynamic adjustment value; The first calculation module is used for selecting the first dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor when n3 / (n1+n2)<1; The first calculation module is used for selecting the second dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor when 1≤n3 / (n1+n2)<1.2; The first calculation module is used for selecting the third dynamic adjustment value as the dynamic adjustment value of the strongly correlated fire factor when 1.2≤n3 / (n1+n2).

6. The adaptive fire warning system according to claim 4 is characterized in that: The first calculation module is used for: The first calculation module is used to extract the same real-time fire-related parameters from the weakly correlated fire intervals and obtain multiple real-time fire-related parameter sequences; The first calculation module is used to count the number of first real-time fire-related parameter sequences of real-time fire-related parameter sequences; The first calculation module is used to extract a real-time fire-related parameter from all real-time fire-related parameter sequences respectively, and calculate the first real-time fire-related parameter and value; The first calculation module is used to calculate a preset fire-related parameter, eliminate all real-time fire-related parameter sequences that are smaller than the preset fire-related parameter, and count the number of second real-time fire-related parameter sequences of the remaining real-time fire-related parameter sequences; The first calculation module is used to extract a real-time fire-related parameter from the remaining real-time fire-related parameter sequence, and calculate the second real-time fire-related parameter and value; The first calculation module is used to calculate the weakly correlated fire factor of the area to be warned according to the first real-time fire-related parameter sequence number, the second real-time fire-related parameter sequence number, the first real-time fire-related parameter and value, and the second real-time fire-related parameter and value.

7. The adaptive fire warning system according to claim 6 is characterized in that: The first calculation module is used for: The first calculation module is used to calculate the weakly correlated fire factor of the area to be warned according to the following formula: Among them, p is the weakly correlated fire factor of the area to be warned, s1 is the number of the first real-time fire-related parameter sequence, s2 is the number of the second real-time fire-related parameter sequence, d1 is the first real-time fire-related parameter and value, and d2 is the second real-time fire-related parameter and value.

8. The adaptive fire warning system according to claim 1 is characterized in that: The second calculation module is used for: The second calculation module is used to configure a first calculation weight for the strongly correlated fire factor and a second calculation weight for the weakly correlated fire factor; The second calculation module is used to calculate the comprehensive correlation fire factor according to the following formula: f = h1 × q + h2 × p; Among them, f is the comprehensive correlation fire factor, h1 is the first calculation weight, h2 is the second calculation weight, q is the strong correlation fire factor, and p is the weak correlation fire factor; The second calculation module is used to randomly match all comprehensive related fire factors in pairs to obtain multiple comprehensive related fire factor matching sets; The second calculation module is used to calculate the comprehensive correlation fire factor difference between two comprehensive correlation fire factors in each comprehensive correlation fire factor matching set; The second calculation module is used for disassembling and reorganizing the comprehensive correlation fire factor matching set to obtain a new comprehensive correlation fire factor matching set if the comprehensive correlation fire factor difference is less than a preset comprehensive correlation fire factor difference; The second calculation module is used to analyze the new comprehensive correlation fire factor matching set until the comprehensive correlation fire factor difference of the new comprehensive correlation fire factor matching set is greater than or equal to the preset comprehensive correlation fire factor difference; The second calculation module is used to calculate the fire warning coefficient of the area to be warned according to all the comprehensive related fire factor matching sets.

9. The adaptive fire warning system according to claim 8, characterized in that: The second calculation module is used for: The second calculation module is used to calculate the fire warning coefficient of the fire warning area according to the following formula: Among them, k is the fire warning coefficient of the area to be warned, m is the matching set of comprehensive related fire factors, c1 b is the comprehensive associated fire factor in the bth comprehensive associated fire factor matching set, c2 b is another comprehensive associated fire factor in the matching set of the bth comprehensive associated fire factor, ((c1 b -c2 b ) 2 ) min For all (c1 b -c2 b ) 2 The minimum value of ((c1 b -c2 b ) 2 ) max For all (c1 b -c2 b ) 2 The maximum value of .

10. The adaptive fire warning system according to claim 1, characterized in that: The fire warning module is used for: The fire warning module is used for not generating a fire warning reminder for the area to be warned when the fire warning coefficient is less than the preset fire warning coefficient; The fire warning module is used to generate a fire warning reminder for the area to be warned when the fire warning coefficient is greater than or equal to the preset fire warning coefficient.

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