Fire operation hazard source identification method and system based on movable device

Abstract

The invention provides a fire operation hazard source identification method and system based on a movable device, and the method comprises the steps: controlling the movable device to carry out the visual collection of a fire operation region based on the spatial features of the fire operation region, obtaining an operation region image, recognizing the object existence features of the fire operation region, and carrying out the recognition of the fire operation hazard source. Combustible materials and fire operation equipment in the area are marked; spark motion characteristics in the live working area are identified from the working area image, so that the spark motion trend in the live working area is predicted; and then based on the object existence characteristics and the spark motion trend, a hazard source which may cause a fire accident in the fire operation area is identified, and based on the associated physical characteristics of the hazard source in the fire operation area, warning and reminding operation is performed, so that automatic and global spark motion monitoring and hazard source identification are realized. And potential fire safety hazards in a fire operation area can be found in time, and the fire operation safety is improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial operation identification, and in particular to a method and system for identifying hazard sources of hot work based on a mobile device. Background Art

[0002] Hot work refers to production operations that use equipment such as blowtorches, electric drills, and grinding wheels that may generate sparks and hot surfaces. The movement of sparks generated by hot work is random and widely distributed. In order to ensure the safety of hot work, multiple operators are usually required to monitor the hot work area to promptly detect safety hazards caused by spark spattering. However, there are limitations and omissions in the monitoring of the hot work area by operators. The movement of sparks cannot be accurately and comprehensively monitored during the entire hot work process, and the safety of the hot work cannot be guaranteed. It can be seen that how to automate and globally monitor the movement of sparks and identify hazard sources in the hot work area is of great significance for promptly discovering potential fire safety hazards in the hot work area and improving the safety of hot work. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for identifying hazardous sources of hot work operations based on a movable device. Based on the spatial characteristics of the hot work operation area, the movable device is controlled to perform visual acquisition of the hot work operation area to obtain an image of the operation area, and the existence characteristics of objects in the hot work operation area are identified therefrom, and the combustible materials and hot work operation equipment inside the area are marked, providing a reliable basis for the subsequent identification of fire accidents; the spark movement characteristics inside the hot work operation area are also identified from the image of the operation area, so as to predict the spark movement trend inside the hot work operation area and accurately predict the movement dynamics of the spark inside the area; then, based on the object existence characteristics and the spark movement trend, the hazardous sources that may cause fire accidents inside the hot work area are identified, and based on the associated physical characteristics of the hazardous sources inside the hot work area, warning reminder operations are performed to realize automated global spark movement monitoring and hazard source identification, so as to timely discover potential fire safety hazards in the hot work area and improve the safety of hot work operations.

[0004] The present invention is achieved through the following technical solutions:

[0005] The method for identifying the hazard sources of hot work based on movable devices includes:

[0006] Based on the spatial characteristics of the hot work area, the mobile device is controlled to perform visual acquisition of the hot work area to obtain an image of the work area; the image of the work area is subjected to a first recognition process to determine the existence characteristics of objects in the hot work area;

[0007] Performing a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area; based on the spark movement characteristics, predicting the spark movement trend inside the hot work area;

[0008] Based on the existence characteristics of the object and the movement trend of the spark, the hazard source inside the hot work area where a fire accident may occur is identified; based on the associated physical characteristics of the hazard source inside the hot work area, a warning reminder operation is performed.

[0009] Optionally, based on the spatial characteristics of the hot work area, controlling the mobile device to perform visual acquisition of the hot work area to obtain an image of the work area; performing a first recognition process on the image of the work area to determine the existence characteristics of objects in the hot work area, including:

[0010] Controlling a movable device to perform non-contact scanning and detection of the surrounding adjacent areas of the hot work area to obtain the obstacle distribution position characteristics of the surrounding adjacent areas; based on the obstacle distribution position characteristics, determining the distribution characteristics of the allowed passage paths in the surrounding adjacent areas, and using them as the spatial characteristics of the hot work area; based on the distribution characteristics of the allowed passage paths, controlling the movable device to move along the allowed passage paths while performing visible light vision collection and thermal infrared vision collection inside the hot work area to obtain a visible light image of the work area and a thermal infrared image of the work area;

[0011] Pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the working area to obtain pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the working area, so as to determine the existence characteristics of objects inside the hot work area; wherein the object existence characteristics include the existence characteristics of combustible materials and hot work equipment inside the hot work area; the existence characteristics of the combustible materials include the position and three-dimensional shape of the combustible materials; the existence characteristics of the hot work equipment include the operation action parameter characteristics of the hot work equipment.

[0012] Optionally, controlling the travel speed of the movable device includes:

[0013] Controlling the movable device to perform non-contact scanning of the hot work area at a preset initial travel speed;

[0014] Extract the number of features acquired by each scanning of the mobile device and the area of ​​the scanning area corresponding to the unit time;

[0015] Obtaining a feature evaluation coefficient according to the number of features acquired by each scanning of the mobile device and the area of ​​the scanning region corresponding to a unit time;

[0016] The characteristic evaluation coefficient is obtained by the following formula:

[0017]

[0018] Among them, J 01 represents the characteristic evaluation coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; N b V represents the standard deviation of the number of features obtained per m unit time; mbi represents the standard deviation of the running speed corresponding to the i-th unit time of the mobile operation of the mobile device; n represents the number of scans of the mobile device; S b V represents the standard deviation of the scan area corresponding to m unit time; nbi represents the standard deviation of the running speed corresponding to the i-th scanning of the mobile operation of the movable device;

[0019] Extracting the distribution density of the obstacles and combustibles;

[0020] Obtaining an object distribution density coefficient according to the distribution density of the obstacle and the combustible position;

[0021] The object distribution density coefficient is obtained by the following formula:

[0022]

[0023] Among them, J 02 represents the object distribution density coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; S b represents the standard deviation of the scanning area corresponding to the i-th unit time; M ai represents the distribution density of obstacles corresponding to the i-th unit time; M ki represents the distribution density of the combustible position corresponding to the i-th unit time; M abi represents the standard deviation of the obstacle distribution density corresponding to the i-th unit time; M kbi Represents the standard deviation of the distribution density of the combustible position corresponding to the i-th unit time;

[0024] The moving speed of the movable device is dynamically adjusted using the characteristic evaluation coefficient and the object distribution density coefficient, wherein the adjusted moving speed is obtained by the following formula:

[0025]

[0026] Among them, V t represents the travel speed after adjustment; V0 represents the travel speed before adjustment; J01 represents the characteristic evaluation coefficient; J 02 Represents the object distribution density coefficient.

[0027] Optionally, performing a second recognition process on the working area image to determine the spark movement characteristics inside the hot work area; and predicting the spark movement trend inside the hot work area based on the spark movement characteristics, including:

[0028] Performing object temperature recognition on the thermal infrared image of the operation area to determine the spark motion characteristics generated by the hot work equipment in the hot work area during the entire visual acquisition process; wherein the spark motion characteristics include the motion trajectory characteristics of the spark in the air and the distribution characteristics of the spark landing position;

[0029] Based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation relationship between the spark movement and the working action of the hot work equipment is determined; based on the correlation relationship, the spark movement trend inside the hot work area in the future time period is predicted; wherein the spark movement trend includes the changing trend of the spark's running trajectory in the air and the changing trend of the spark's landing position.

[0030] Optionally, based on the object existence characteristics and the spark movement trend, identifying a hazard source that may cause a fire accident inside the hot work area; and performing a warning reminder operation based on the associated physical characteristics of the hazard source inside the hot work area, including:

[0031] Compare the position of the combustibles inside the hot work area with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks inside the hot work area; based on the location distribution information of the contact event, identify the dangerous source of the possible fire accident inside the hot work area;

[0032] Based on the characteristics of personnel activities within the hot work area of ​​the hazardous source, determine whether the hazardous source is under effective human monitoring. If not, send a warning reminder message containing the location information of the hazardous source to the platform; if not, do not send a warning reminder message to the platform.

[0033] The hot work hazard identification system based on mobile devices includes:

[0034] A visual acquisition control module, for controlling the mobile device to perform visual acquisition of the hot work area based on the spatial characteristics of the hot work area to obtain an image of the work area;

[0035] A first image recognition module is used to perform a first recognition process on the image of the operation area to determine the existence characteristics of objects in the hot work area;

[0036] A second image recognition module is used to perform a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area;

[0037] A spark movement prediction module, used to predict the spark movement trend inside the hot work area based on the spark movement characteristics;

[0038] A hazard source identification module, used to identify the hazard source that may cause a fire accident inside the hot work area based on the existence characteristics of the object and the movement trend of the spark;

[0039] The warning operation control module is used to perform a warning operation based on the associated physical characteristics of the hazard source within the hot work area.

[0040] Optionally, the visual acquisition control module is used to control the mobile device to perform visual acquisition on the hot work area based on the spatial characteristics of the hot work area to obtain an image of the work area, including:

[0041] Controlling a movable device to perform non-contact scanning and detection of the surrounding adjacent areas of the hot work area to obtain the obstacle distribution position characteristics of the surrounding adjacent areas; based on the obstacle distribution position characteristics, determining the distribution characteristics of the allowed passage paths in the surrounding adjacent areas, and using them as the spatial characteristics of the hot work area; based on the distribution characteristics of the allowed passage paths, controlling the movable device to move along the allowed passage paths while performing visible light vision collection and thermal infrared vision collection inside the hot work area to obtain a visible light image of the work area and a thermal infrared image of the work area;

[0042] The first image recognition module is used to perform a first recognition process on the image of the operation area to determine the existence characteristics of objects in the hot work area, including:

[0043] Pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the working area to obtain pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the working area, so as to determine the existence characteristics of objects inside the hot work area; wherein the object existence characteristics include the existence characteristics of combustible materials and hot work equipment inside the hot work area; the existence characteristics of the combustible materials include the position and three-dimensional shape of the combustible materials; the existence characteristics of the hot work equipment include the operation action parameter characteristics of the hot work equipment.

[0044] Optionally, controlling the travel speed of the movable device includes:

[0045] Controlling the movable device to perform non-contact scanning of the hot work area at a preset initial travel speed;

[0046] Extract the number of features acquired by each scanning of the mobile device and the area of ​​the scanning area corresponding to the unit time;

[0047] Obtaining a feature evaluation coefficient according to the number of features acquired by each scanning of the mobile device and the area of ​​the scanning region corresponding to a unit time;

[0048] The characteristic evaluation coefficient is obtained by the following formula:

[0049]

[0050] Among them, J 01 represents the characteristic evaluation coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; N b V represents the standard deviation of the number of features obtained per m unit time; mbi represents the standard deviation of the running speed corresponding to the i-th unit time of the mobile operation of the mobile device; n represents the number of scans of the mobile device; S b V represents the standard deviation of the scan area corresponding to m unit time; nbi represents the standard deviation of the running speed corresponding to the i-th scanning of the mobile operation of the movable device;

[0051] Extracting the distribution density of the obstacles and combustibles;

[0052] Obtaining an object distribution density coefficient according to the distribution density of the obstacle and the combustible position;

[0053] The object distribution density coefficient is obtained by the following formula:

[0054]

[0055] Among them, J 02 represents the object distribution density coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; S b represents the standard deviation of the scanning area corresponding to the i-th unit time; M ai represents the distribution density of obstacles corresponding to the i-th unit time; M ki represents the distribution density of the combustible position corresponding to the i-th unit time; M abi represents the standard deviation of the obstacle distribution density corresponding to the i-th unit time; M kbi Represents the standard deviation of the distribution density of the combustible position corresponding to the i-th unit time;

[0056] The moving speed of the movable device is dynamically adjusted using the characteristic evaluation coefficient and the object distribution density coefficient, wherein the adjusted moving speed is obtained by the following formula:

[0057]

[0058] Among them, V t represents the travel speed after adjustment; V0 represents the travel speed before adjustment; J 01 represents the characteristic evaluation coefficient; J 02 Represents the object distribution density coefficient.

[0059] Optionally, the second image recognition module is used to perform a second recognition process on the image of the working area to determine the spark movement characteristics inside the hot work area, including:

[0060] Performing object temperature recognition on the thermal infrared image of the operation area to determine the spark motion characteristics generated by the hot work equipment in the hot work area during the entire visual acquisition process; wherein the spark motion characteristics include the motion trajectory characteristics of the spark in the air and the distribution characteristics of the spark landing position;

[0061] The spark movement prediction module is used to predict the spark movement trend inside the hot work area based on the spark movement characteristics, including:

[0062] Based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation relationship between the spark movement and the working action of the hot work equipment is determined; based on the correlation relationship, the spark movement trend inside the hot work area in the future time period is predicted; wherein the spark movement trend includes the changing trend of the spark's running trajectory in the air and the changing trend of the spark's landing position.

[0063] Optionally, the hazard source identification module is used to identify the hazard source where a fire accident may occur inside the hot work area based on the object existence characteristics and the spark movement trend, including:

[0064] Compare the position of the combustibles inside the hot work area with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks inside the hot work area; based on the location distribution information of the contact event, identify the dangerous source of the possible fire accident inside the hot work area;

[0065] The warning operation control module is used to perform a warning operation based on the associated physical characteristics of the hazard source inside the hot work area, including:

[0066] Based on the characteristics of personnel activities within the hot work area of ​​the hazardous source, determine whether the hazardous source is under effective human monitoring. If not, send a warning reminder message containing the location information of the hazardous source to the platform; if not, do not send a warning reminder message to the platform.

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] The method and system for identifying hazardous sources of hot work based on a mobile device provided in the present application are based on the spatial characteristics of the hot work area, control the mobile device to perform visual acquisition of the hot work area, obtain an image of the work area, and identify the object existence characteristics of the hot work area, mark the combustible materials and hot work equipment inside the area, and provide a reliable basis for the subsequent identification of fire accidents; the spark movement characteristics inside the hot work area are also identified from the image of the work area, so as to predict the spark movement trend inside the hot work area and accurately predict the movement dynamics of the spark inside the area; then, based on the object existence characteristics and spark movement trend, the hazardous sources that may cause fire accidents inside the hot work area are identified, and based on the associated physical characteristics of the hazardous sources inside the hot work area, warning reminder operations are performed to realize automated global spark movement monitoring and hazard source identification, so as to timely discover potential fire safety hazards in the hot work area and improve the safety of hot work. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary combustible materials in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0070] Figure 1 A schematic flow chart of a method for identifying hot work hazards based on a mobile device provided by the present invention.

[0071] Figure 2 A schematic structural diagram of a hot work hazard identification system based on a mobile device provided by the present invention. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the sake of ease of description, only part of the structure related to the present application but not all of it is shown in the accompanying drawings. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of the present application.

[0073] The terms "including" and "having" and any variations thereof in this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0074] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive of other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0075] See also Figure 1 As shown, an embodiment of the present application provides a method for identifying a hazard source of hot work based on a mobile device. The method for identifying a hazard source of hot work based on a mobile device includes:

[0076] Based on the spatial characteristics of the hot work area, the mobile device is controlled to perform visual acquisition of the hot work area to obtain an image of the work area; the image of the work area is subjected to a first recognition process to determine the existence characteristics of the object in the hot work area;

[0077] Performing a second recognition process on the working area image to determine the spark movement characteristics inside the hot work area; based on the spark movement characteristics, predicting the spark movement trend inside the hot work area;

[0078] Based on the existence characteristics of the object and the movement trend of the spark, the hazard source that may cause a fire accident inside the hot work area is identified; based on the associated physical characteristics of the hazard source inside the hot work area, a warning reminder operation is performed.

[0079] The beneficial effects of the above-mentioned embodiments are as follows: the method for identifying hazardous sources of hot work based on a movable device is based on the spatial characteristics of the hot work area, controls the movable device to perform visual acquisition of the hot work area, obtains an image of the work area, and identifies the object existence characteristics of the hot work area, marks the combustible materials and hot work equipment inside the area, and provides a reliable basis for the subsequent identification of fire accidents; it also identifies the spark movement characteristics inside the hot work area from the image of the work area, thereby predicting the spark movement trend inside the hot work area, and accurately predicting the movement dynamics of the spark inside the area; then, based on the object existence characteristics and spark movement trend, it identifies the hazardous sources that may cause fire accidents inside the hot work area, and based on the associated physical characteristics of the hazardous sources inside the hot work area, performs warning reminder operations, realizes automated global spark movement monitoring and hazard source identification, and timely discovers potential fire safety hazards in the hot work area and improves the safety of hot work.

[0080] In another embodiment, based on the spatial characteristics of the hot work area, the mobile device is controlled to perform visual acquisition of the hot work area to obtain an image of the work area; and the image of the work area is first recognized and processed to determine the existence characteristics of the object in the hot work area, including:

[0081] Controlling the movable device to perform non-contact scanning detection on the surrounding adjacent areas of the hot work area to obtain the obstacle distribution position characteristics of the surrounding adjacent areas; based on the obstacle distribution position characteristics, determining the distribution characteristics of the allowed passage paths in the surrounding adjacent areas, and using them as the spatial characteristics of the hot work area; based on the distribution characteristics of the allowed passage paths, controlling the movable device to move along the allowed passage paths while performing visible light vision collection and thermal infrared vision collection inside the hot work area to obtain visible light images of the work area and thermal infrared images of the work area;

[0082] Pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the working area to obtain pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the working area, so as to determine the existence characteristics of objects inside the hot work area; wherein, the existence characteristics of the objects include the existence characteristics of the combustible materials and the hot work equipment inside the hot work area; the existence characteristics of the combustible materials include the position and three-dimensional shape of the combustible materials; the existence characteristics of the hot work equipment include the operation action parameter characteristics of the hot work equipment.

[0083] The beneficial effect of the above embodiment is that other devices are not allowed to enter the hot work area under normal circumstances, so that sparks generated during the hot work can be prevented from splashing onto other devices and causing fire or explosion. For this reason, if it is necessary to visually monitor the hot work area, it can only be visually photographed from the periphery of the hot work area. At the same time, limited by the spatial environment outside the hot work area, in order to enable robots and other mobile devices to continuously and stably move around the hot work area while taking comprehensive and accurate visual photos of the inside of the hot work area, the mobile device is first controlled to perform non-contact scanning and detection of the surrounding adjacent areas of the hot work area, wherein the non-contact scanning and detection can be but not limited to laser radar scanning and detection, and the obstacle distribution position characteristics of the surrounding adjacent areas of the hot work area are obtained. The obstacle distribution position characteristics characterize the relative distance and relative orientation of the obstacles in the peripheral space of the hot work area. The distribution characteristics of the allowed passage paths in the surrounding adjacent areas are determined, which are used as the spatial characteristics of the hot work area. In this way, the paths that allow the mobile devices to move continuously and stably in the peripheral space of the hot work area can be determined in all directions. Based on the distribution characteristics of the allowed passage path, the movable device is controlled to move along the allowed passage path while performing visible light vision acquisition and thermal infrared vision acquisition inside the hot work area to obtain visible light images and thermal infrared images of the work area, so as to provide reliable image data for visual analysis of the physical state of the combustibles, hot work equipment and sparks inside the hot work area. In addition, pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the work area to obtain the pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the work area, so as to determine the existence characteristics of objects inside the hot work area and accurately determine the physical state of the combustibles and hot work equipment inside the hot work area.

[0084] In another embodiment, controlling the travel speed of the movable device includes:

[0085] Controlling the movable device to perform non-contact scanning of the hot work area at a preset initial travel speed;

[0086] Extract the number of features acquired by each scanning of the mobile device and the area of ​​the scanning area corresponding to the unit time;

[0087] Obtaining a feature evaluation coefficient according to the number of features acquired by each scanning of the mobile device and the area of ​​the scanning region corresponding to a unit time;

[0088] The characteristic evaluation coefficient is obtained by the following formula:

[0089]

[0090] Among them, J01 represents the characteristic evaluation coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; N b V represents the standard deviation of the number of features obtained per m unit time; mbi represents the standard deviation of the running speed corresponding to the i-th unit time of the mobile operation of the mobile device; n represents the number of scans of the mobile device; S b V represents the standard deviation of the scan area corresponding to m unit time; nbi represents the standard deviation of the running speed corresponding to the i-th scanning of the mobile operation of the movable device;

[0091] Extracting the distribution density of the obstacles and combustibles;

[0092] Obtaining an object distribution density coefficient according to the distribution density of the obstacle and the combustible position;

[0093] The object distribution density coefficient is obtained by the following formula:

[0094]

[0095] Among them, J 02 represents the object distribution density coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; S b represents the standard deviation of the scanning area corresponding to the i-th unit time; M ai represents the distribution density of obstacles corresponding to the i-th unit time; M ki represents the distribution density of the combustible position corresponding to the i-th unit time; M abi represents the standard deviation of the obstacle distribution density corresponding to the i-th unit time; M kbi Represents the standard deviation of the distribution density of the combustible position corresponding to the i-th unit time;

[0096] The moving speed of the movable device is dynamically adjusted using the characteristic evaluation coefficient and the object distribution density coefficient, wherein the adjusted moving speed is obtained by the following formula:

[0097]

[0098] Among them, V t represents the travel speed after adjustment; V0 represents the travel speed before adjustment; J 01 represents the characteristic evaluation coefficient; J 02 Represents the object distribution density coefficient.

[0099] The beneficial effect of the above embodiment is that the continuity and initial efficiency of the scan are ensured by controlling the movable device to perform non-contact scanning of the hot work area according to the preset initial travel speed. The number of features scanned each time and the area of ​​the scanned area corresponding to the unit time are extracted, and the feature evaluation coefficient is calculated accordingly, so that the effectiveness and comprehensiveness of the scan can be dynamically evaluated. This helps to adjust the scanning strategy according to the actual scanning situation, thereby improving the accuracy and efficiency of the scan. The object distribution density coefficient is calculated according to the distribution density of the obstacles and combustible positions. This step takes into account the complexity and variability of the on-site environment. By dynamically adjusting the travel speed, it can be ensured that the movable device can slow down when facing high-density obstacles or combustibles, so as to scan these key areas more carefully, and the scan can be accelerated in relatively open areas, thereby improving the overall scanning efficiency. Dynamically adjusting the travel speed also helps to reduce missed scans or mis-scans caused by excessive speed, and improves the accuracy and safety of the scan. The combined use of the feature evaluation coefficient and the object distribution density coefficient provides a comprehensive evaluation basis for adjusting the travel speed of the movable device. This comprehensive evaluation method not only considers the efficiency and accuracy of the scan itself, but also the complexity and variability of the on-site environment, thereby achieving more intelligent decision-making. Through the formulaic calculation method, the accuracy and repeatability of the speed adjustment can be ensured, and the stability and reliability of the entire system can be improved. In high-risk environments such as hot work, it is crucial to accurately control the travel speed of the movable device. The above technical solution dynamically adjusts the travel speed, which not only ensures the comprehensiveness and accuracy of the scan, but also avoids the safety risks caused by improper speed. At the same time, by improving the scanning efficiency, the entire operation cycle can be shortened, thereby reducing operating costs and improving overall efficiency.

[0100] In summary, the technical effects of the above technical solutions in terms of performance indicators are mainly reflected in improving scanning efficiency and accuracy, dynamically adjusting the travel speed to adapt to the environment, comprehensive evaluation and intelligent decision-making, and improving operation safety and efficiency. These effects together constitute the significant advantages of this technical solution in practical applications.

[0101] In another embodiment, a second recognition process is performed on the working area image to determine the spark movement characteristics inside the hot work area; based on the spark movement characteristics, the spark movement trend inside the hot work area is predicted, including:

[0102] Perform object temperature recognition on the thermal infrared image of the operation area to determine the spark motion characteristics generated by the hot work equipment in the hot work area during the entire visual acquisition process; wherein the spark motion characteristics include the motion trajectory characteristics of the spark in the air and the distribution characteristics of the spark landing position;

[0103] Based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation between the spark movement and the working action of the hot work equipment is determined; based on the correlation, the spark movement trend within the hot work area in the future time period is predicted; wherein, the spark movement trend includes the changing trend of the spark's running trajectory in the air and the changing trend of the spark's landing position.

[0104] The beneficial effect of the above embodiment is that the thermal infrared image of the operation area is to characterize the temperature of all objects inside the hot work area. By identifying the temperature of the object in the thermal infrared image of the operation area, the spark generation and movement inside the hot work area are dynamically tracked, and the spark movement characteristics generated by the hot work equipment inside the hot work area during the entire visual acquisition process are determined, so as to accurately determine the movement trajectory and landing range of the sparks generated during the operation of the hot work equipment. In addition, the operation action posture of the hot work equipment itself during the operation process will affect the movement trajectory and landing range of the sparks, and there is a certain correlation between the two. Therefore, based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation between the spark movement and the operation action of the hot work equipment is determined, and then based on the correlation, the spark movement trend inside the hot work area in the future time period is predicted, so as to effectively predict the change trend of the running trajectory of the sparks generated in the hot work area in the future time period due to the operation of the hot work equipment and the change trend of the spark landing position, and provide a reliable basis for the subsequent accurate identification of the dangerous sources inside the hot work area.

[0105] In another embodiment, based on the existence characteristics of the object and the movement trend of the spark, identifying the hazard source that may cause a fire accident in the hot work area; based on the associated physical characteristics of the hazard source in the hot work area, performing a warning reminder operation, including:

[0106] Compare the position of the combustibles in the hot work area with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks in the hot work area; based on the location distribution information of the contact event, identify the dangerous source of the possible fire accident in the hot work area;

[0107] Based on the characteristics of personnel activities within the hot work area, determine whether the hazard source is under effective human monitoring. If not, send a warning reminder message containing the location information of the hazard source to the platform; if not, do not send a warning reminder message to the platform.

[0108] The beneficial effect of the above embodiment is that if the sparks generated by the hot work equipment during operation contact the combustibles, the combustibles will catch fire, and the combustibles will become the source of danger inside the hot work area. Specifically, the position of the combustibles inside the hot work area is compared with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks inside the hot work area; based on the location distribution information of the contact event, the dangerous source of the possible fire accident inside the hot work area is identified, so that the dangerous source that causes the fire inside the hot work area can be accurately and comprehensively located and identified. In addition, based on the personnel activity characteristics of the dangerous source inside the hot work area, it is judged whether the dangerous source is in an effective human monitoring state, wherein the personnel activity characteristics can be but not limited to the line of sight direction of the personnel inside the hot work area. If the line of sight of the personnel inside the hot work area is toward the dangerous source, it is judged that the dangerous source is in an effective human monitoring state; otherwise, it is judged that the dangerous source is not in an effective human monitoring state. When the hazard source is not under effective human monitoring, a warning reminder message containing the location information of the hazard source will be sent to the platform, so that potential fire safety hazards in the hot work area can be discovered in time and the safety of hot work can be improved.

[0109] See also Figure 2 As shown, an embodiment of the present application provides a system for identifying hazard sources of hot work based on a mobile device. The system for identifying hazard sources of hot work based on a mobile device includes:

[0110] A visual acquisition control module is used to control the mobile device to perform visual acquisition on the hot work area based on the spatial characteristics of the hot work area to obtain an image of the work area;

[0111] A first image recognition module is used to perform a first recognition process on the image of the operation area to determine the existence characteristics of objects in the hot work area;

[0112] A second image recognition module is used to perform a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area;

[0113] A spark movement prediction module, used to predict the spark movement trend inside the hot work area based on the spark movement characteristics;

[0114] A hazard source identification module, used to identify the hazard source that may cause a fire accident inside the hot work area based on the existence characteristics of the object and the movement trend of the spark;

[0115] The warning reminder operation control module is used to perform a warning reminder operation based on the associated physical characteristics of the hazard source within the hot work area.

[0116] The beneficial effects of the above-mentioned embodiments are as follows: the system for identifying hazardous sources of hot work operations based on a movable device controls the movable device to perform visual acquisition of the hot work operation area based on the spatial characteristics of the hot work operation area, obtains an image of the operation area, and identifies the object existence characteristics of the hot work operation area, marks the combustible materials and hot work operation equipment inside the area, and provides a reliable basis for the subsequent identification of fire accidents; it also identifies the spark movement characteristics inside the hot work operation area from the image of the operation area, thereby predicting the spark movement trend inside the hot work operation area, and accurately predicting the movement dynamics of the spark inside the area; then, based on the object existence characteristics and spark movement trend, it identifies the hazardous sources that may cause fire accidents inside the hot work area, and based on the associated physical characteristics of the hazardous sources inside the hot work area, performs warning reminder operations, realizes automated global spark movement monitoring and hazard source identification, and timely discovers potential fire safety hazards in the hot work area and improves the safety of hot work operations.

[0117] In another embodiment, the visual acquisition control module is used to control the mobile device to perform visual acquisition on the hot work area based on the spatial characteristics of the hot work area to obtain an image of the work area, including:

[0118] Controlling the movable device to perform non-contact scanning detection on the surrounding adjacent areas of the hot work area to obtain the obstacle distribution position characteristics of the surrounding adjacent areas; based on the obstacle distribution position characteristics, determining the distribution characteristics of the allowed passage paths in the surrounding adjacent areas, and using them as the spatial characteristics of the hot work area; based on the distribution characteristics of the allowed passage paths, controlling the movable device to move along the allowed passage paths while performing visible light vision collection and thermal infrared vision collection inside the hot work area to obtain visible light images of the work area and thermal infrared images of the work area;

[0119] The first image recognition module is used to perform a first recognition process on the image of the operation area to determine the existence characteristics of the object in the hot work area, including:

[0120] Pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the working area to obtain pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the working area, so as to determine the existence characteristics of objects inside the hot work area; wherein, the existence characteristics of the objects include the existence characteristics of the combustible materials and the hot work equipment inside the hot work area; the existence characteristics of the combustible materials include the position and three-dimensional shape of the combustible materials; the existence characteristics of the hot work equipment include the operation action parameter characteristics of the hot work equipment.

[0121] The beneficial effect of the above embodiment is that other devices are not allowed to enter the hot work area under normal circumstances, so that sparks generated during the hot work can be prevented from splashing onto other devices and causing fire or explosion. For this reason, if it is necessary to visually monitor the hot work area, visual photography of the interior can only be performed outside the hot work area. At the same time, limited by the spatial environment outside the hot work area, in order to enable mobile devices such as robots to continuously and stably move outside the hot work area while performing comprehensive and accurate visual photography inside the hot work area, the mobile device is first controlled to perform non-contact scanning and detection of the surrounding adjacent areas of the hot work area, wherein the non-contact scanning and detection can be but not limited to laser radar scanning and detection, and the obstacle distribution position characteristics of the surrounding adjacent areas of the hot work area are obtained. The obstacle distribution position characteristics characterize the relative distance and relative orientation of the obstacles in the peripheral space of the hot work area. The distribution characteristics of the allowed passage paths in the surrounding adjacent areas are determined, which are used as the spatial characteristics of the hot work area. In this way, the paths that allow the mobile devices to move continuously and stably in the peripheral space of the hot work area can be fully determined. Based on the distribution characteristics of the allowed passage path, the movable device is controlled to move along the allowed passage path while performing visible light vision acquisition and thermal infrared vision acquisition inside the hot work area to obtain visible light images and thermal infrared images of the work area, so as to provide reliable image data for visual analysis of the physical state of the combustibles, hot work equipment and sparks inside the hot work area. In addition, pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the work area to obtain the pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the work area, so as to determine the existence characteristics of objects inside the hot work area and accurately determine the physical state of the combustibles and hot work equipment inside the hot work area.

[0122] In another embodiment, controlling the travel speed of the movable device includes:

[0123] Controlling the movable device to perform non-contact scanning of the hot work area at a preset initial travel speed;

[0124] Extract the number of features acquired by each scanning of the mobile device and the area of ​​the scanning area corresponding to the unit time;

[0125] Obtaining a feature evaluation coefficient according to the number of features acquired by each scanning of the mobile device and the area of ​​the scanning region corresponding to a unit time;

[0126] The characteristic evaluation coefficient is obtained by the following formula:

[0127]

[0128] Among them, J01 represents the characteristic evaluation coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; N b V represents the standard deviation of the number of features obtained per m unit time; mbi represents the standard deviation of the running speed corresponding to the i-th unit time of the mobile operation of the mobile device; n represents the number of scans of the mobile device; S b V represents the standard deviation of the scan area corresponding to m unit time; nbi represents the standard deviation of the running speed corresponding to the i-th scanning of the mobile operation of the movable device;

[0129] Extracting the distribution density of the obstacles and combustibles;

[0130] Obtaining an object distribution density coefficient according to the distribution density of the obstacle and the combustible position;

[0131] The object distribution density coefficient is obtained by the following formula:

[0132]

[0133] Among them, J 02 represents the object distribution density coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; S b represents the standard deviation of the scanning area corresponding to the i-th unit time; M ai represents the distribution density of obstacles corresponding to the i-th unit time; M ki represents the distribution density of the combustible position corresponding to the i-th unit time; M abi represents the standard deviation of the obstacle distribution density corresponding to the i-th unit time; M kbi Represents the standard deviation of the distribution density of the combustible position corresponding to the i-th unit time;

[0134] The moving speed of the movable device is dynamically adjusted using the characteristic evaluation coefficient and the object distribution density coefficient, wherein the adjusted moving speed is obtained by the following formula:

[0135]

[0136] Among them, V t represents the travel speed after adjustment; V0 represents the travel speed before adjustment; J 01 represents the characteristic evaluation coefficient; J 02 Represents the object distribution density coefficient.

[0137] The beneficial effect of the above embodiment is that the continuity and initial efficiency of the scan are ensured by controlling the movable device to perform non-contact scanning of the hot work area according to the preset initial travel speed. The number of features scanned each time and the area of ​​the scanned area corresponding to the unit time are extracted, and the feature evaluation coefficient is calculated accordingly, so that the effectiveness and comprehensiveness of the scan can be dynamically evaluated. This helps to adjust the scanning strategy according to the actual scanning situation, thereby improving the accuracy and efficiency of the scan. The object distribution density coefficient is calculated according to the distribution density of the obstacles and combustible positions. This step takes into account the complexity and variability of the on-site environment. By dynamically adjusting the travel speed, it can be ensured that the movable device can slow down when facing high-density obstacles or combustibles, so as to scan these key areas more carefully, and the scan can be accelerated in relatively open areas, thereby improving the overall scanning efficiency. Dynamically adjusting the travel speed also helps to reduce missed scans or mis-scans caused by excessive speed, and improves the accuracy and safety of the scan. The combined use of the feature evaluation coefficient and the object distribution density coefficient provides a comprehensive evaluation basis for adjusting the travel speed of the movable device. This comprehensive evaluation method not only considers the efficiency and accuracy of the scan itself, but also the complexity and variability of the on-site environment, thereby achieving more intelligent decision-making. Through the formulaic calculation method, the accuracy and repeatability of the speed adjustment can be ensured, and the stability and reliability of the entire system can be improved. In high-risk environments such as hot work, it is crucial to accurately control the travel speed of the movable device. The above technical solution dynamically adjusts the travel speed, which not only ensures the comprehensiveness and accuracy of the scan, but also avoids the safety risks caused by improper speed. At the same time, by improving the scanning efficiency, the entire operation cycle can be shortened, thereby reducing operating costs and improving overall efficiency.

[0138] In summary, the technical effects of the above technical solutions in terms of performance indicators are mainly reflected in improving scanning efficiency and accuracy, dynamically adjusting the travel speed to adapt to the environment, comprehensive evaluation and intelligent decision-making, and improving operation safety and efficiency. These effects together constitute the significant advantages of this technical solution in practical applications.

[0139] In another embodiment, the second image recognition module is used to perform a second recognition process on the image of the working area to determine the spark movement characteristics inside the hot work area, including:

[0140] Perform object temperature recognition on the thermal infrared image of the operation area to determine the spark motion characteristics generated by the hot work equipment in the hot work area during the entire visual acquisition process; wherein the spark motion characteristics include the motion trajectory characteristics of the spark in the air and the distribution characteristics of the spark landing position;

[0141] The spark movement prediction module is used to predict the spark movement trend inside the hot work area based on the spark movement characteristics, including:

[0142] Based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation between the spark movement and the working action of the hot work equipment is determined; based on the correlation, the spark movement trend within the hot work area in the future time period is predicted; wherein, the spark movement trend includes the changing trend of the spark's running trajectory in the air and the changing trend of the spark's landing position.

[0143] The beneficial effect of the above embodiment is that the thermal infrared image of the operation area is to characterize the temperature of all objects inside the hot work area. By identifying the temperature of the object in the thermal infrared image of the operation area, the spark generation and movement inside the hot work area are dynamically tracked, and the spark movement characteristics generated by the hot work equipment inside the hot work area during the entire visual acquisition process are determined, so as to accurately determine the movement trajectory and landing range of the sparks generated during the operation of the hot work equipment. In addition, the operation action posture of the hot work equipment itself during the operation process will affect the movement trajectory and landing range of the sparks, and there is a certain correlation between the two. Therefore, based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation between the spark movement and the operation action of the hot work equipment is determined, and then based on the correlation, the spark movement trend inside the hot work area in the future time period is predicted, so as to effectively predict the change trend of the running trajectory of the sparks generated in the hot work area in the future time period due to the operation of the hot work equipment and the change trend of the spark landing position, and provide a reliable basis for the subsequent accurate identification of the dangerous sources inside the hot work area.

[0144] In another embodiment, the hazard source identification module is used to identify the hazard source that may cause a fire accident inside the hot work area based on the existence characteristics of the object and the movement trend of the spark, including:

[0145] Compare the position of the combustibles in the hot work area with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks in the hot work area; based on the location distribution information of the contact event, identify the dangerous source of the possible fire accident in the hot work area;

[0146] The warning operation control module is used to perform a warning operation based on the associated physical characteristics of the hazard source within the hot work area, including:

[0147] Based on the characteristics of personnel activities within the hot work area, determine whether the hazard source is under effective human monitoring. If not, send a warning reminder message containing the location information of the hazard source to the platform; if not, do not send a warning reminder message to the platform.

[0148] The beneficial effect of the above embodiment is that if the sparks generated by the hot work equipment during operation contact the combustibles, the combustibles will catch fire, and the combustibles will become the source of danger inside the hot work area. Specifically, the position of the combustibles inside the hot work area is compared with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks inside the hot work area; based on the location distribution information of the contact event, the dangerous source of the possible fire accident inside the hot work area is identified, so that the dangerous source that causes the fire inside the hot work area can be accurately and comprehensively located and identified. In addition, based on the personnel activity characteristics of the dangerous source inside the hot work area, it is judged whether the dangerous source is in an effective human monitoring state, wherein the personnel activity characteristics can be but not limited to the line of sight direction of the personnel inside the hot work area. If the line of sight of the personnel inside the hot work area is toward the dangerous source, it is judged that the dangerous source is in an effective human monitoring state; otherwise, it is judged that the dangerous source is not in an effective human monitoring state. When the hazard source is not under effective human monitoring, a warning reminder message containing the location information of the hazard source will be sent to the platform, so that potential fire safety hazards in the hot work area can be discovered in time and the safety of hot work can be improved.

[0149] In general, the method and system for identifying hazardous sources of hot work based on a movable device controls the movable device to perform visual acquisition of the hot work area based on the spatial characteristics of the hot work area, obtains an image of the work area, and identifies the object existence characteristics of the hot work area, marks the combustibles and hot work equipment inside the area, and provides a reliable basis for the subsequent identification of fire accidents; it also identifies the spark movement characteristics inside the hot work area from the image of the work area, thereby predicting the spark movement trend inside the hot work area, and accurately predicting the movement dynamics of the spark inside the area; then, based on the object existence characteristics and spark movement trend, it identifies the hazardous sources that may cause fire accidents inside the hot work area, and based on the associated physical characteristics of the hazardous sources inside the hot work area, performs warning reminder operations, realizes automated global spark movement monitoring and hazard source identification, and timely discovers potential fire safety hazards in the hot work area and improves the safety of hot work.

[0150] The above is only a specific implementation of the present invention, and any other improvements made based on the concept of the present invention are considered to be within the protection scope of the present invention.

Claims

1. A method for identifying hazard sources of hot work based on a mobile device, characterized in that: include: Based on the spatial characteristics of the hot work area, the mobile device is controlled to perform visual acquisition of the hot work area to obtain an image of the work area; Performing a first recognition process on the image of the operation area to determine the existence characteristics of objects in the hot work area; Performing a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area; Based on the spark movement characteristics, predicting the spark movement trend inside the hot work area; Based on the existence characteristics of the object and the movement trend of the spark, identifying the dangerous source of possible fire accidents inside the hot work area; Based on the associated physical characteristics of the hazard source within the hot work area, a warning reminder operation is performed.

2. The method for identifying hot work hazards based on a mobile device according to claim 1, characterized in that: Based on the spatial characteristics of the hot work area, the mobile device is controlled to perform visual acquisition of the hot work area to obtain an image of the work area; the image of the work area is subjected to a first recognition process to determine the existence characteristics of objects in the hot work area, including: Controlling a movable device to perform non-contact scanning and detection of the surrounding adjacent areas of the hot work area to obtain the obstacle distribution position characteristics of the surrounding adjacent areas; based on the obstacle distribution position characteristics, determining the distribution characteristics of the allowed passage paths in the surrounding adjacent areas, and using them as the spatial characteristics of the hot work area; based on the distribution characteristics of the allowed passage paths, controlling the movable device to move along the allowed passage paths while performing visible light vision collection and thermal infrared vision collection inside the hot work area to obtain a visible light image of the work area and a thermal infrared image of the work area; Pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the working area to obtain pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the working area, so as to determine the existence characteristics of objects inside the hot work area; wherein the object existence characteristics include the existence characteristics of combustible materials and hot work equipment inside the hot work area; the existence characteristics of the combustible materials include the position and three-dimensional shape of the combustible materials; the existence characteristics of the hot work equipment include the operation action parameter characteristics of the hot work equipment.

3. The method for identifying hot work hazards based on a mobile device according to claim 2, characterized in that: Control the travel speed of the movable device, including: Controlling the movable device to perform non-contact scanning of the hot work area at a preset initial travel speed; Extract the number of features acquired by each scanning of the mobile device and the area of ​​the scanning area corresponding to the unit time; Obtaining a feature evaluation coefficient according to the number of features acquired by each scanning of the mobile device and the area of ​​the scanning region corresponding to a unit time; The characteristic evaluation coefficient is obtained by the following formula: Among them, J 01 represents the characteristic evaluation coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; N b V represents the standard deviation of the number of features obtained per m unit time; mbi represents the standard deviation of the running speed corresponding to the i-th unit time of the mobile operation of the mobile device; n represents the number of scans of the mobile device; S b V represents the standard deviation of the scan area corresponding to m unit time; nbi represents the standard deviation of the running speed corresponding to the i-th scanning of the mobile operation of the movable device; Extracting the distribution density of the obstacles and combustibles; Obtaining an object distribution density coefficient according to the distribution density of the obstacle and the combustible position; The object distribution density coefficient is obtained by the following formula: Among them, J 02 represents the object distribution density coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; S b represents the standard deviation of the scanning area corresponding to the i-th unit time; M ai represents the distribution density of obstacles corresponding to the i-th unit time; M ki represents the distribution density of the combustible position corresponding to the i-th unit time; M abi represents the standard deviation of the obstacle distribution density corresponding to the i-th unit time; M kbi represents the standard deviation of the distribution density of the combustible position corresponding to the i-th unit time; the travel speed of the movable device is dynamically adjusted using the characteristic evaluation coefficient and the object distribution density coefficient, wherein the adjusted travel speed is obtained by the following formula: Among them, V t represents the travel speed after adjustment; V0 represents the travel speed before adjustment; J 01 represents the characteristic evaluation coefficient; J 02 Represents the object distribution density coefficient.

4. The method for identifying hot work hazards based on a mobile device according to claim 2, characterized in that: Performing a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area; Based on the spark movement characteristics, predicting the spark movement trend inside the hot work area includes: Performing object temperature recognition on the thermal infrared image of the operation area to determine the spark motion characteristics generated by the hot work equipment in the hot work area during the entire visual acquisition process; wherein the spark motion characteristics include the motion trajectory characteristics of the spark in the air and the distribution characteristics of the spark landing position; Based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation relationship between the spark movement and the working action of the hot work equipment is determined; based on the correlation relationship, the spark movement trend inside the hot work area in the future time period is predicted; wherein the spark movement trend includes the changing trend of the spark's running trajectory in the air and the changing trend of the spark's landing position.

5. The method for identifying hot work hazards based on a mobile device according to claim 4, characterized in that: Based on the existence characteristics of the object and the movement trend of the spark, identifying the dangerous source of possible fire accidents inside the hot work area; Based on the associated physical characteristics of the hazard source within the hot work area, a warning reminder operation is performed, including: Compare the position of the combustibles inside the hot work area with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks inside the hot work area; based on the location distribution information of the contact event, identify the dangerous source of the possible fire accident inside the hot work area; Based on the characteristics of personnel activities within the hot work area of ​​the hazardous source, determine whether the hazardous source is under effective human monitoring. If not, send a warning reminder message containing the location information of the hazardous source to the platform; if not, do not send a warning reminder message to the platform.

6. A hot work hazard identification system based on a mobile device, characterized in that: include: A visual acquisition control module, for controlling the mobile device to perform visual acquisition of the hot work area based on the spatial characteristics of the hot work area to obtain an image of the work area; A first image recognition module is used to perform a first recognition process on the image of the operation area to determine the existence characteristics of objects in the hot work area; A second image recognition module is used to perform a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area; A spark movement prediction module, used to predict the spark movement trend inside the hot work area based on the spark movement characteristics; A hazard source identification module, used to identify the hazard source that may cause a fire accident inside the hot work area based on the existence characteristics of the object and the movement trend of the spark; The warning operation control module is used to perform a warning operation based on the associated physical characteristics of the hazard source within the hot work area.

7. The hot work hazard identification system based on a mobile device as claimed in claim 6, characterized in that: The visual acquisition control module is used to control the mobile device to perform visual acquisition on the hot work area based on the spatial characteristics of the hot work area to obtain an image of the work area, including: Controlling a movable device to perform non-contact scanning and detection of the surrounding adjacent areas of the hot work area to obtain the obstacle distribution position characteristics of the surrounding adjacent areas; based on the obstacle distribution position characteristics, determining the distribution characteristics of the allowed passage paths in the surrounding adjacent areas, and using them as the spatial characteristics of the hot work area; based on the distribution characteristics of the allowed passage paths, controlling the movable device to move along the allowed passage paths while performing visible light vision collection and thermal infrared vision collection inside the hot work area to obtain a visible light image of the work area and a thermal infrared image of the work area; The first image recognition module is used to perform a first recognition process on the image of the operation area to determine the existence characteristics of objects in the hot work area, including: Pixel contour recognition and pixel chromaticity recognition are performed on the visible light image of the working area to obtain pixel contour distribution characteristics and pixel chromaticity distribution characteristics of the visible light image of the working area, so as to determine the existence characteristics of objects inside the hot work area; wherein the object existence characteristics include the existence characteristics of combustible materials and hot work equipment inside the hot work area; the existence characteristics of the combustible materials include the position and three-dimensional shape of the combustible materials; the existence characteristics of the hot work equipment include the operation action parameter characteristics of the hot work equipment.

8. The hot work hazard identification system based on a mobile device as claimed in claim 7, characterized in that: Control the travel speed of the movable device, including: Controlling the movable device to perform non-contact scanning of the hot work area at a preset initial travel speed; Extract the number of features acquired by each scanning of the mobile device and the area of ​​the scanning area corresponding to the unit time; Obtaining a feature evaluation coefficient according to the number of features acquired by each scanning of the mobile device and the area of ​​the scanning region corresponding to a unit time; The characteristic evaluation coefficient is obtained by the following formula: Among them, J 01 represents the characteristic evaluation coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; N b V represents the standard deviation of the number of features obtained per m unit time; mbi represents the standard deviation of the running speed corresponding to the i-th unit time of the mobile operation of the mobile device; n represents the number of scans of the mobile device; S b V represents the standard deviation of the scan area corresponding to m unit time; nbi represents the standard deviation of the running speed corresponding to the i-th scanning of the mobile operation of the movable device; Extracting the distribution density of the obstacles and combustibles; Obtaining an object distribution density coefficient according to the distribution density of the obstacle and the combustible position; The object distribution density coefficient is obtained by the following formula: Among them, J 02 represents the object distribution density coefficient; m represents the number of unit times experienced by the mobile device; S i represents the scanning area corresponding to the i-th unit time; S b represents the standard deviation of the scanning area corresponding to the i-th unit time; M ai represents the distribution density of obstacles corresponding to the i-th unit time; M ki represents the distribution density of the combustible position corresponding to the i-th unit time; M abi represents the standard deviation of the obstacle distribution density corresponding to the i-th unit time; M kbi represents the standard deviation of the distribution density of the combustible position corresponding to the i-th unit time; the travel speed of the movable device is dynamically adjusted using the characteristic evaluation coefficient and the object distribution density coefficient, wherein the adjusted travel speed is obtained by the following formula: Among them, V t represents the travel speed after adjustment; V0 represents the travel speed before adjustment; J 01 represents the characteristic evaluation coefficient; J 02 Represents the object distribution density coefficient.

9. The hot work hazard identification system based on a mobile device according to claim 7, characterized in that: The second image recognition module is used to perform a second recognition process on the image of the operation area to determine the spark movement characteristics inside the hot work area, including: Performing object temperature recognition on the thermal infrared image of the operation area to determine the spark motion characteristics generated by the hot work equipment in the hot work area during the entire visual acquisition process; wherein the spark motion characteristics include the motion trajectory characteristics of the spark in the air and the distribution characteristics of the spark landing position; The spark movement prediction module is used to predict the spark movement trend inside the hot work area based on the spark movement characteristics, including: Based on the spark movement characteristics and the existence characteristics of the hot work equipment, the correlation relationship between the spark movement and the working action of the hot work equipment is determined; based on the correlation relationship, the spark movement trend inside the hot work area in the future time period is predicted; wherein the spark movement trend includes the changing trend of the spark's running trajectory in the air and the changing trend of the spark's landing position.

10. The mobile device-based hot work hazard identification system according to claim 9, characterized in that: The hazard source identification module is used to identify the hazard source that may cause a fire accident inside the hot work area based on the object existence characteristics and the spark movement trend, including: Compare the position of the combustibles inside the hot work area with the three-dimensional shape and the movement trend of the sparks to determine the location distribution information of the contact event between the combustibles and the sparks inside the hot work area; based on the location distribution information of the contact event, identify the dangerous source of the possible fire accident inside the hot work area; The warning operation control module is used to perform a warning operation based on the associated physical characteristics of the hazard source inside the hot work area, including: Based on the characteristics of personnel activities within the hot work area of ​​the hazardous source, determine whether the hazardous source is under effective human monitoring. If not, send a warning reminder message containing the location information of the hazardous source to the platform; if not, do not send a warning reminder message to the platform.

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