High-temperature infrared imaging real-time early warning system and method

Abstract

The invention relates to the technical field of real-time early warning, and particularly discloses a high-temperature infrared imaging real-time early warning system and method, and the method comprises the following steps: 1, carrying out the detection of a target region, and obtaining the abnormal data of the target region in a detection period; 2, calculating an abnormal coefficient based on the abnormal data; 3, based on the abnormal coefficient, evaluating the temperature abnormal condition of the target area, and generating a temperature abnormal evaluation signal; step 4, based on the preliminary early warning signal, analyzing historical data of the abnormal temperature condition of the target area so as to further evaluate the abnormal temperature condition of the target area, and generating an early warning degree signal; 5, sending the early warning degree signal to a worker user side; according to the invention, through real-time temperature monitoring, historical data analysis and early warning degree signal generation and transmission, an effective means is provided for deep evaluation and accurate early warning of temperature abnormity of a target area.

Description

Technical Field

[0001] The present invention relates to the field of real-time warning technology, and in particular to a high-temperature infrared imaging real-time warning system and method. Background Art

[0002] The tuyere area in front of the blast furnace, the three-way intersection of the hot blast surrounding pipe, and the tuyere straight blowing pipe are the weak links in the high-temperature area of ​​the blast furnace. If the hot blast main pipe and the tuyere blowpipe are not inspected in time and forced cooling is not taken due to high temperature, the blast furnace tuyere blowpipe will be burned through, which may cause the blast furnace to be shut down for maintenance at the very least, or even worse, it may cause surrounding equipment and facilities, cables, etc. to be burned, forcing the blast furnace to be shut down for a long time for emergency repairs and other secondary disasters.

[0003] However, in the existing technology, the real-time warning of high-temperature infrared imaging often relies on a single real-time monitoring data and lacks comprehensive analysis of historical data, resulting in low accuracy of warnings and frequent false alarms and missed alarms. Summary of the invention

[0004] The purpose of the present invention is to provide a high-temperature infrared imaging real-time warning system and method to solve the technical problems in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a high temperature infrared imaging real-time warning method, comprising the following steps:

[0007] Step 1: Detect the target area and obtain abnormal data of the target area within the detection period;

[0008] The abnormal data includes: abnormal degree characterization value and abnormal distribution characterization value;

[0009] Step 2: Calculate the abnormal coefficient based on the abnormal data;

[0010] Step 3: Based on the anomaly coefficient, evaluate the temperature anomaly of the target area and generate a temperature anomaly evaluation signal;

[0011] Among them, the temperature anomaly assessment signals include: preliminary warning signal and no warning signal;

[0012] Step 4: Based on the preliminary warning signal, analyze the historical data of temperature anomaly in the target area, so as to further evaluate the temperature anomaly in the target area and generate a warning degree signal;

[0013] Among them, the warning degree signals include: first warning signal, second warning signal and third warning signal;

[0014] Step 5: Send the warning level signal to the staff user terminal.

[0015] As a further solution of the present invention: the process of obtaining abnormal data is:

[0016] Use infrared thermal imaging technology to detect the target area in real time and obtain the real-time temperature change map of the target area;

[0017] Divide the temperature real-time change graph into several temperature zones, and obtain the average temperature of each temperature zone;

[0018] Based on the temperature mean of each temperature zone, the abnormal degree characterization value and the abnormal distribution characterization value are calculated respectively.

[0019] As a further solution of the present invention, the process of dividing the temperature real-time change graph into regions and obtaining several temperature regions is as follows:

[0020] Based on the real-time temperature change graph, the highest temperature value and the lowest temperature value are extracted to obtain the total temperature interval, and the total temperature interval is evenly divided according to the temperature value to obtain a fixed number of temperature sub-intervals;

[0021] According to each temperature sub-interval, the real-time temperature change graph is divided into regions to obtain several temperature regions;

[0022] The basis for the temperature zone division is: the parts that are continuous and in the same temperature sub-range are divided into the same temperature zone.

[0023] As a further solution of the present invention: the process of obtaining the abnormality degree characterization value is:

[0024] Compare and analyze the mean temperature of each temperature zone with the temperature threshold;

[0025] If the temperature mean is ≤ the temperature threshold, a normal regional temperature signal is generated;

[0026] If the temperature mean value is greater than the temperature threshold, a regional temperature anomaly signal is generated and the temperature region is marked as an abnormal region;

[0027] Based on any abnormal area, the area of ​​the temperature area is calculated by ratio with the total area of ​​the target area to obtain the area weight of the temperature area;

[0028] At the same time, the temperature mean value of the abnormal area is calculated with the temperature threshold value to obtain the temperature abnormal value;

[0029] The temperature anomaly value is multiplied by the regional weight to obtain the regional anomaly coefficient of the abnormal area;

[0030] Then the regional anomaly coefficients of all abnormal areas are summed up to obtain the abnormality degree representation value.

[0031] As a further solution of the present invention: extracting the number of temperature sub-intervals to obtain the total number of sub-intervals;

[0032] The difference between the total number of temperature zones and the total number of subintervals is calculated to obtain the zone quantity difference, and then the ratio of the zone quantity difference to the total number of subintervals is calculated to obtain the abnormal distribution characterization value.

[0033] As a further solution of the present invention: the process of obtaining the abnormal coefficient is:

[0034] By formula: Calculate the abnormality coefficient YC, where a1 and a2 are preset proportional factors and are both greater than 0, CD is the abnormality degree characterization value, and FB is the abnormality distribution characterization value.

[0035] As a further solution of the present invention: the process of generating the temperature anomaly assessment signal is:

[0036] Preset an abnormal coefficient threshold, and compare and analyze the abnormal coefficient with the abnormal coefficient threshold;

[0037] If the abnormal coefficient is ≤ the abnormal coefficient threshold, a no-warning signal is generated;

[0038] If the abnormal coefficient is greater than the abnormal coefficient threshold, a preliminary warning signal is generated.

[0039] As a further solution of the present invention: the process of generating the warning degree signal is:

[0040] Based on the preliminary warning signal, all abnormal areas in the real-time temperature change graph are extracted;

[0041] Based on any abnormal area, the abnormal area is compared with historical data to obtain the maintenance time of the abnormal area;

[0042] The maintenance time of the abnormal area is multiplied by the regional abnormality coefficient of the abnormal area to obtain the regional maintenance coefficient;

[0043] Then the regional maintenance coefficients of all abnormal regions are summed up to obtain the abnormal maintenance value;

[0044] Preset a first threshold and a second threshold, and compare and analyze the abnormal maintenance value with the first threshold and the second threshold respectively;

[0045] If the abnormal maintenance value is greater than the first threshold, a first warning signal is generated;

[0046] If the first threshold value ≥ the abnormal maintenance value > the second threshold value, a second warning signal is generated;

[0047] If the abnormal maintenance value is less than or equal to the second threshold, a third warning signal is generated.

[0048] As a further solution of the present invention: the acquisition process of the maintenance time is:

[0049] Extract basic information of abnormal area in real-time temperature change diagram;

[0050] Based on historical data, extract the time the abnormal area lasts to obtain the maintenance time;

[0051] The duration of the abnormal area is determined based on the degree of change of the basic information of the abnormal area, which is always kept within the change threshold.

[0052] In a second aspect, the present invention provides a high temperature infrared imaging real-time warning system, the system comprising:

[0053] Data acquisition module: detects the target area and obtains abnormal data of the target area within the detection period;

[0054] The abnormal data includes: abnormal degree characterization value and abnormal distribution characterization value;

[0055] Data processing module: calculate the abnormal coefficient based on abnormal data;

[0056] Primary evaluation module: Based on the anomaly coefficient, the temperature anomaly of the target area is evaluated and a temperature anomaly evaluation signal is generated;

[0057] Among them, the temperature anomaly assessment signals include: preliminary warning signal and no warning signal;

[0058] Secondary assessment module: Based on the preliminary warning signal, the historical data of temperature anomaly in the target area is analyzed to further evaluate the temperature anomaly in the target area and generate a warning degree signal;

[0059] Among them, the warning degree signals include: first warning signal, second warning signal and third warning signal;

[0060] Early warning module: sends early warning level signals to the staff user end.

[0061] Beneficial effects of the present invention:

[0062] (1) The present invention uses infrared thermal imaging technology to monitor the temperature of the target area in real time and obtain a real-time temperature change map. On this basis, the temperature map is divided into regions to obtain several temperature regions, and the temperature mean of each region is calculated. By comparing the temperature mean with a preset temperature threshold, the abnormal temperature region is identified. For each abnormal region, its regional weight (area ratio) and temperature abnormality degree (difference between the temperature mean and the threshold) are calculated, and then the regional abnormality coefficient is obtained. The regional abnormality coefficients of all abnormal regions are summed to obtain the abnormality degree characterization value. At the same time, the ratio of the total number of temperature regions to the total number of preset temperature sub-intervals is calculated to obtain the abnormality degree characterization value. Distribution characterization value, which reflects the discrete degree of temperature distribution; next, based on the abnormal degree characterization value and the abnormal distribution characterization value, the abnormal coefficient is calculated by a preset formula; finally, the calculated abnormal coefficient is compared with the preset abnormal coefficient threshold. If the abnormal coefficient is less than or equal to the threshold, it indicates that the temperature abnormality in the target area is relatively light, and no warning signal is generated; if the abnormal coefficient is greater than the threshold, it indicates that the temperature abnormality is relatively serious, and a preliminary warning signal is generated; the present invention has the characteristics of real-time, accuracy and flexibility, and can efficiently and accurately detect and evaluate the temperature abnormality in the target area, providing strong support for preventing potential safety hazards;

[0063] (2) Based on the preliminary warning signal, the present invention identifies and extracts all abnormal areas in the real-time temperature change diagram. For each abnormal area, the temperature anomaly maintenance time of the area is analyzed in combination with its basic information such as location and area, and with reference to historical data. The determination of the maintenance time depends on the duration of the change in the basic information of the abnormal area within the preset threshold. Then, the maintenance time of each abnormal area is calculated by multiplying the maintenance time of the area anomaly coefficient by the area anomaly coefficient to obtain the area maintenance coefficient. The area maintenance coefficients of all abnormal areas are summed to obtain the abnormal maintenance value, which reflects the overall persistence and severity of the temperature anomaly in the target area. Then, a first threshold and a second threshold are preset, and the abnormal maintenance value is compared with the two thresholds. If the abnormal maintenance value If the temperature exceeds the first threshold, a first warning signal is generated, indicating that the temperature anomaly is serious; if the abnormal maintenance value is between the first threshold and the second threshold, a second warning signal is generated, indicating that the temperature anomaly is moderate; if the abnormal maintenance value is lower than or equal to the second threshold, a third warning signal is generated, which means that the temperature anomaly is relatively mild; finally, the generated warning degree signal is quickly transmitted to the staff user end so that they can take appropriate measures in time to deal with the temperature anomaly according to the level of the warning signal, thereby effectively preventing potential safety hazards; the present invention provides an effective means for in-depth assessment and precise warning of temperature anomalies in the target area through real-time temperature monitoring, historical data analysis and generation and transmission of warning degree signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The present invention will be further described below in conjunction with the accompanying drawings.

[0065] Figure 1 It is a flowchart of the present invention;

[0066] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] Embodiment 1:

[0069] See also Figure 1 As shown, a high temperature infrared imaging real-time warning method according to an embodiment of the present invention comprises the following steps:

[0070] Step 1: Detect the target area and obtain abnormal data of the target area within the detection period;

[0071] The abnormal data includes: abnormal degree characterization value and abnormal distribution characterization value;

[0072] It should be explained that the duration of the detection cycle can be 10 seconds, 30 seconds, or 1 minute;

[0073] In some implementation schemes, infrared thermal imaging technology is used to detect the target area in real time to obtain a real-time temperature change map of the target area;

[0074] Divide the temperature real-time change graph into several temperature zones, and obtain the average temperature of each temperature zone;

[0075] Based on the temperature mean of each temperature zone, the abnormal degree characterization value and the abnormal distribution characterization value are calculated respectively;

[0076] First, specifically, the process of dividing the temperature real-time change graph into regions to obtain several temperature regions is as follows:

[0077] Based on the temperature real-time change graph, the maximum temperature value and the minimum temperature value are extracted to obtain the total temperature interval (the upper limit of the total temperature interval is the maximum temperature value, and the lower limit is the minimum temperature value), and the total temperature interval is evenly divided according to the temperature value to obtain a fixed number of temperature sub-intervals (the number of temperature sub-intervals can be 10 or 20);

[0078] According to each temperature sub-interval, the temperature real-time change graph is divided into regions to obtain several temperature regions (the basis for temperature region division is: the parts that are continuous and in the same temperature sub-interval are divided into the same temperature region);

[0079] Second, specifically, the process of obtaining the abnormality degree characterization value is as follows:

[0080] Compare and analyze the mean temperature of each temperature zone with the temperature threshold;

[0081] If the temperature mean is ≤ the temperature threshold, it means that the temperature of the temperature area is low, and a normal regional temperature signal is generated;

[0082] If the temperature mean value is greater than the temperature threshold, it means that the temperature in the temperature area is high, that is, a regional temperature anomaly signal is generated, and the temperature area is marked as an abnormal area;

[0083] Based on any abnormal area, the area of ​​the temperature area is calculated by ratio with the total area of ​​the target area to obtain the area weight of the temperature area;

[0084] At the same time, the temperature mean value of the abnormal area is calculated with the temperature threshold value to obtain the temperature abnormal value;

[0085] The temperature anomaly value is multiplied by the regional weight to obtain the regional anomaly coefficient of the abnormal area;

[0086] Then the regional anomaly coefficients of all abnormal areas are summed up and calculated to obtain the abnormality degree representation value;

[0087] Thirdly, specifically, the process of obtaining the abnormal distribution characterization value is as follows:

[0088] Extract the number of temperature sub-intervals to obtain the total number of sub-intervals;

[0089] The total number of temperature zones is calculated by difference with the total number of sub-intervals to obtain the zone number difference, and then the zone number difference is calculated by ratio with the total number of sub-intervals to obtain the abnormal distribution characterization value;

[0090] It should be explained that the abnormal distribution characterization value reflects: the difference between the number of temperature sub-intervals and temperature regions. If the total number of temperature regions is much larger than the total number of temperature sub-intervals, it means that the division of temperature regions is not concentrated, which indirectly reflects the degree of discreteness of the temperature distribution in the target area. The larger the value, the more dispersed the temperature distribution in the target area. The smaller the value, the relatively concentrated the temperature distribution in the target area.

[0091] Step 2: Calculate the abnormal coefficient based on the abnormal data;

[0092] In some embodiments, by the formula: Calculate the abnormality coefficient YC, where a1 and a2 are preset proportional factors and are both greater than 0, CD is the abnormality degree representation value, and FB is the abnormality distribution representation value;

[0093] Step 3: Based on the anomaly coefficient, evaluate the temperature anomaly of the target area and generate a temperature anomaly evaluation signal;

[0094] Among them, the temperature anomaly assessment signals include: preliminary warning signal and no warning signal;

[0095] In some implementation schemes, an abnormal coefficient threshold is preset, and the abnormal coefficient is compared and analyzed with the abnormal coefficient threshold;

[0096] If the anomaly coefficient is ≤ the anomaly coefficient threshold, it means that the temperature anomaly in the target area is small, and no warning signal is generated;

[0097] If the anomaly coefficient is greater than the anomaly coefficient threshold, it means that the temperature anomaly in the target area is large, and a preliminary warning signal is generated;

[0098] The technical solution of the embodiment of the present invention is mainly as follows: using infrared thermal imaging technology to monitor the temperature of the target area in real time, and obtaining a real-time temperature change map. On this basis, the temperature map is divided into regions to obtain a number of temperature regions, and the temperature mean of each region is calculated. By comparing the temperature mean with a preset temperature threshold, the abnormal temperature region is identified. For each abnormal region, its regional weight (area ratio) and temperature abnormality degree (difference between the temperature mean and the threshold) are calculated, and then the regional abnormality coefficient is obtained. The regional abnormality coefficients of all abnormal regions are summed to obtain an abnormality degree characterization value. At the same time, by calculating the ratio of the total number of temperature regions to the total number of preset temperature sub-intervals, the abnormal temperature region is obtained. to the abnormal distribution characterization value, which reflects the degree of discreteness of the temperature distribution; next, based on the abnormal degree characterization value and the abnormal distribution characterization value, the abnormal coefficient is calculated by a preset formula; finally, the calculated abnormal coefficient is compared with the preset abnormal coefficient threshold; if the abnormal coefficient is less than or equal to the threshold, it indicates that the temperature abnormality in the target area is relatively light, and no warning signal is generated; if the abnormal coefficient is greater than the threshold, it indicates that the temperature abnormality is relatively serious, and a preliminary warning signal is generated; the embodiment of the present invention has the characteristics of real-time, precision and flexibility, and can efficiently and accurately detect and evaluate the temperature abnormality in the target area, providing strong support for preventing potential safety hazards.

[0099] Embodiment 2:

[0100] Based on Example 1, please refer to Figure 1 As shown, a high temperature infrared imaging real-time warning method according to an embodiment of the present invention further includes the following steps:

[0101] Step 4: Based on the preliminary warning signal, analyze the historical data of temperature anomaly in the target area, so as to further evaluate the temperature anomaly in the target area and generate a warning degree signal;

[0102] Among them, the warning degree signals include: first warning signal, second warning signal and third warning signal;

[0103] In some embodiments, based on the preliminary warning signal, all abnormal areas in the real-time temperature change graph are extracted;

[0104] Based on any abnormal area, the abnormal area is compared with historical data to obtain the maintenance time of the abnormal area;

[0105] The maintenance time of the abnormal area is multiplied by the regional abnormality coefficient of the abnormal area to obtain the regional maintenance coefficient;

[0106] Then the regional maintenance coefficients of all abnormal regions are summed up to obtain the abnormal maintenance value;

[0107] Preset a first threshold and a second threshold, and compare and analyze the abnormal maintenance value with the first threshold and the second threshold respectively;

[0108] If the abnormal maintenance value is greater than the first threshold, it means that the temperature abnormality in the target area is more serious, and a first warning signal is generated;

[0109] If the first threshold value ≥ the abnormal maintenance value > the second threshold value, it means that the temperature abnormality in the target area is moderate, and a second warning signal is generated;

[0110] If the abnormal maintenance value is less than or equal to the second threshold, it means that the temperature abnormality in the target area is relatively minor, and a third warning signal is generated;

[0111] Specifically, the process of obtaining the maintenance time is:

[0112] Extract basic information of abnormal area in real-time temperature change diagram;

[0113] The basic information includes but is not limited to: the location and area of ​​the abnormal area in the real-time temperature change diagram;

[0114] Based on historical data, extract the time the abnormal area lasts to obtain the maintenance time;

[0115] It should be explained that the duration of the abnormal area is determined based on the degree of change of the basic information of the abnormal area, which is always kept within the change threshold range;

[0116] Step 5: Send the warning level signal to the staff user terminal;

[0117] The technical solution of the embodiment of the present invention is mainly as follows: based on the preliminary warning signal, all abnormal areas in the real-time temperature change map are identified and extracted; for each abnormal area, the temperature anomaly maintenance time of the area is analyzed in combination with its basic information such as location and area, and with reference to historical data; the determination of the maintenance time depends on the duration of the change of the basic information of the abnormal area within the preset threshold; then, the maintenance time of each abnormal area is calculated by multiplying the regional anomaly coefficient by the regional maintenance coefficient, and the regional maintenance coefficient is obtained; the regional maintenance coefficients of all abnormal areas are summed up to obtain the abnormal maintenance value, which reflects the overall persistence and severity of the temperature anomaly in the target area; then, a first threshold and a second threshold are preset, and the abnormal maintenance value is compared with the two thresholds; if the abnormal If the maintenance value exceeds the first threshold, a first warning signal is generated, indicating that the temperature anomaly is serious; if the abnormal maintenance value is between the first threshold and the second threshold, a second warning signal is generated, indicating that the temperature anomaly is moderate; if the abnormal maintenance value is lower than or equal to the second threshold, a third warning signal is generated, which means that the temperature anomaly is relatively mild; finally, the generated warning degree signal is quickly transmitted to the staff user end so that they can take appropriate measures in time to deal with the temperature anomaly according to the level of the warning signal, thereby effectively preventing potential safety hazards; the embodiment of the present invention provides an effective means for in-depth assessment and precise warning of temperature anomalies in the target area through real-time temperature monitoring, historical data analysis and generation and transmission of warning degree signals.

[0118] Embodiment 3:

[0119] Based on Example 1 and Example 2, please refer to Figure 2 As shown, a high temperature infrared imaging real-time warning system according to an embodiment of the present invention comprises:

[0120] Data acquisition module: detects the target area and obtains abnormal data of the target area within the detection period;

[0121] The abnormal data includes: abnormal degree characterization value and abnormal distribution characterization value;

[0122] Data processing module: calculate the abnormal coefficient based on abnormal data;

[0123] Primary evaluation module: Based on the anomaly coefficient, the temperature anomaly of the target area is evaluated and a temperature anomaly evaluation signal is generated;

[0124] Among them, the temperature anomaly assessment signals include: preliminary warning signal and no warning signal;

[0125] Secondary assessment module: Based on the preliminary warning signal, the historical data of temperature anomaly in the target area is analyzed to further evaluate the temperature anomaly in the target area and generate a warning degree signal;

[0126] Among them, the warning degree signals include: first warning signal, second warning signal and third warning signal;

[0127] Early warning module: sends early warning level signals to the staff user end.

[0128] The above thresholds are set for the convenience of comparison. The thresholds depend on the amount of sample data and the number of bases set by technicians in this field for each set of sample data.

[0129] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The factors in the formula are set by technicians in this field according to actual conditions; for example: Formula A technician in this field collects multiple groups of abnormal data and sets a corresponding abnormal coefficient for each group of abnormal data; substitutes the set abnormal coefficient and the collected abnormal data into the formula, any two formulas constitute a binary linear equation system, and the calculated factors are screened and averaged to obtain the values ​​of a1 and a2, which are 3.27 and 2.35 respectively;

[0130] The size of the factor is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the factor depends on the amount of abnormal data and the technical personnel in this field preliminarily set the corresponding abnormal coefficient for each set of abnormal data; as long as it does not affect the proportional relationship between the parameter and the quantized value, such as the abnormal coefficient is proportional to the value representing the degree of abnormality.

[0131] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A high temperature infrared imaging real-time warning method, characterized in that: The following steps are involved: Step 1: Detect the target area and obtain abnormal data of the target area within the detection period; The abnormal data includes: abnormal degree characterization value and abnormal distribution characterization value; Step 2: Calculate the abnormal coefficient based on the abnormal data; Step 3: Based on the anomaly coefficient, evaluate the temperature anomaly of the target area and generate a temperature anomaly evaluation signal; Among them, the temperature anomaly assessment signals include: preliminary warning signal and no warning signal; Step 4: Based on the preliminary warning signal, analyze the historical data of temperature anomaly in the target area, so as to further evaluate the temperature anomaly in the target area and generate a warning degree signal; Among them, the warning degree signals include: first warning signal, second warning signal and third warning signal; Step 5: Send the warning level signal to the staff user terminal.

2. A high temperature infrared imaging real-time warning method according to claim 1, characterized in that: The process of obtaining abnormal data is as follows: Use infrared thermal imaging technology to detect the target area in real time and obtain the real-time temperature change map of the target area; Divide the temperature real-time change graph into several temperature zones, and obtain the average temperature of each temperature zone; Based on the temperature mean of each temperature zone, the abnormal degree characterization value and the abnormal distribution characterization value are calculated respectively.

3. A high temperature infrared imaging real-time warning method according to claim 2, characterized in that: The process of dividing the temperature real-time change graph into regions and obtaining several temperature regions is as follows: Based on the real-time temperature change graph, the highest temperature value and the lowest temperature value are extracted to obtain the total temperature interval, and the total temperature interval is evenly divided according to the temperature value to obtain a fixed number of temperature sub-intervals; According to each temperature sub-interval, the real-time temperature change graph is divided into regions to obtain several temperature regions; The basis for the temperature zone division is: the parts that are continuous and in the same temperature sub-range are divided into the same temperature zone.

4. A high temperature infrared imaging real-time warning method according to claim 3, characterized in that: The process of obtaining the abnormality degree characterization value is as follows: Compare and analyze the mean temperature of each temperature zone with the temperature threshold; If the temperature mean is ≤ the temperature threshold, a normal regional temperature signal is generated; If the temperature mean value is greater than the temperature threshold, a regional temperature anomaly signal is generated and the temperature region is marked as an abnormal region; Based on any abnormal area, the area of ​​the temperature area is calculated by ratio with the total area of ​​the target area to obtain the area weight of the temperature area; At the same time, the temperature mean value of the abnormal area is calculated with the temperature threshold value to obtain the temperature abnormal value; The temperature anomaly value is multiplied by the regional weight to obtain the regional anomaly coefficient of the abnormal area; Then the regional anomaly coefficients of all abnormal areas are summed up to obtain the abnormality degree representation value.

5. The high temperature infrared imaging real-time warning method according to claim 3, characterized in that: Extract the number of temperature sub-intervals to obtain the total number of sub-intervals; The difference between the total number of temperature zones and the total number of subintervals is calculated to obtain the zone quantity difference, and then the ratio of the zone quantity difference to the total number of subintervals is calculated to obtain the abnormal distribution characterization value.

6. The high temperature infrared imaging real-time warning method according to claim 1, characterized in that: The process of obtaining the anomaly coefficient is: By formula: Calculate the abnormality coefficient YC, where a1 and a2 are preset proportional factors and are both greater than 0, CD is the abnormality degree characterization value, and FB is the abnormality distribution characterization value.

7. The high temperature infrared imaging real-time warning method according to claim 1, characterized in that: The process of generating the temperature anomaly assessment signal is: Preset an abnormal coefficient threshold, and compare and analyze the abnormal coefficient with the abnormal coefficient threshold; If the abnormal coefficient is ≤ the abnormal coefficient threshold, a no-warning signal is generated; If the abnormal coefficient is greater than the abnormal coefficient threshold, a preliminary warning signal is generated.

8. The high temperature infrared imaging real-time warning method according to claim 1, characterized in that: The process of generating the warning level signal is: Based on the preliminary warning signal, all abnormal areas in the real-time temperature change graph are extracted; Based on any abnormal area, the abnormal area is compared with historical data to obtain the maintenance time of the abnormal area; The maintenance time of the abnormal area is multiplied by the regional abnormality coefficient of the abnormal area to obtain the regional maintenance coefficient; Then the regional maintenance coefficients of all abnormal regions are summed up to obtain the abnormal maintenance value; Preset a first threshold and a second threshold, and compare and analyze the abnormal maintenance value with the first threshold and the second threshold respectively; If the abnormal maintenance value is greater than the first threshold, a first warning signal is generated; If the first threshold value ≥ the abnormal maintenance value > the second threshold value, a second warning signal is generated; If the abnormal maintenance value is less than or equal to the second threshold, a third warning signal is generated.

9. A high temperature infrared imaging real-time warning method according to claim 8, characterized in that: The process of obtaining the maintenance time is: Extract basic information of abnormal area in real-time temperature change diagram; Based on historical data, extract the time the abnormal area lasts to obtain the maintenance time; The duration of the abnormal area is determined based on the degree of change of the basic information of the abnormal area, which is always kept within the change threshold.

10. A high temperature infrared imaging real-time warning system, characterized in that: The system is used to execute the method described in any one of claims 1 to 9, and the system comprises: Data acquisition module: detects the target area and obtains abnormal data of the target area within the detection period; The abnormal data includes: abnormal degree characterization value and abnormal distribution characterization value; Data processing module: calculate the abnormal coefficient based on abnormal data; Primary evaluation module: Based on the anomaly coefficient, the temperature anomaly of the target area is evaluated and a temperature anomaly evaluation signal is generated; Among them, the temperature anomaly assessment signals include: preliminary warning signal and no warning signal; Secondary assessment module: Based on the preliminary warning signal, the historical data of temperature anomaly in the target area is analyzed to further evaluate the temperature anomaly in the target area and generate a warning degree signal; Among them, the warning degree signals include: first warning signal, second warning signal and third warning signal; Early warning module: sends early warning level signals to the staff user end.

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