Real-time safe distance monitoring method and system for field operation and storage medium

Abstract

The invention provides a real-time safe distance monitoring method and system for field operation and a storage medium, and the method comprises the following steps: calculating the distance between a field operator and a potential dangerous object or region as a first distance based on a real-time image of the field operation, and executing the subsequent steps if the first distance is smaller than a first set value; otherwise, continuing to calculate the first distance in real time; based on the real-time three-dimensional position data of the field operation, calculating the distance between the field operation personnel and the potential dangerous object or area as a second distance; performing data fusion on the first distance and the second distance to obtain a third distance; if the third distance is smaller than the second set value, alarm operation is executed; otherwise, continuing to calculate the first distance in real time. According to the invention, the technical advantages and advancement of various intelligent detection methods are fully combined, and the safety distance of field operation is effectively monitored in real time.

Description

Technical Field

[0001] The present invention belongs to the technical field of on-site operation safety support, and in particular relates to a real-time safety distance monitoring method, system and storage medium for on-site operations. Background Art

[0002] At present, the main problems in the safety management and control of UHV on-site operations are "insufficient intelligent means, and human control is greater than machine control". Safety distance monitoring is an important technical means to ensure the personal safety of operators. However, several major safety accidents in on-site near-electricity operations in recent years have exposed the problems of insufficient technical means for safety distance monitoring and poor technical performance. The existing monitoring methods either lack accuracy or have a large amount of calculations, resulting in slow detection speed, and cannot effectively monitor the safety distance of on-site operations in real time. At the same time, the safety distance monitoring technology of the existing technology cannot provide real-time early warning and alarm for the safety distance of operators based on the detection results, resulting in insufficient prevention of dangerous operations. Summary of the invention

[0003] The purpose of the present invention is to solve the shortcomings of the above-mentioned background technology and to provide a real-time safety distance monitoring method, system and storage medium for on-site operations, which fully combines the technical advantages and advancement of various intelligent detection methods to effectively monitor the safety distance of on-site operations in real time.

[0004] The technical solution adopted by the present invention is: a real-time safety distance monitoring method for field operations, comprising the following steps:

[0005] Based on the real-time image of the on-site operation, the distance between the on-site operator and the potentially dangerous object or area is calculated in real time as a first distance, and if the first distance is less than a first set value, subsequent steps are executed;

[0006] Based on the real-time three-dimensional position data of the on-site operation, the distance between the on-site operator and the potentially dangerous object or area is calculated in real time as the second distance;

[0007] The first distance and the second distance are data-fused to obtain a third distance; if the third distance is less than the second set value, an alarm operation is performed.

[0008] In the above technical solution, a binocular camera is used to obtain real-time images of on-site operations.

[0009] In the above technical solution, the process of calculating the distance between the on-site workers and the potential dangerous objects or areas as the first distance includes: marking the on-site workers and the potential dangerous objects or areas in the two-dimensional image acquired in real time by the binocular camera; converting the marked two-dimensional image into a three-dimensional depth map, and obtaining key depth data of the marked on-site workers and the potential dangerous objects or areas based on the marking; locating the center point and contour boundary of the workers and the potential dangerous objects or areas through the key depth data, and then calculating the minimum spatial Euclidean distance between the workers and the potential dangerous objects or areas as the first distance.

[0010] In the above technical solution, Beidou real-time dynamic carrier phase (RTK) differential positioning modules are respectively configured on potential dangerous objects or areas, and on-site workers, and the three-dimensional position data of on-site workers and potential dangerous objects or areas are obtained through the Beidou RTK differential positioning module.

[0011] In the above technical scheme, the process of calculating the distance between the on-site workers and the potentially dangerous object or area as the second distance includes: extracting the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area based on the three-dimensional position data of the on-site workers and the potentially dangerous object or area; calculating the relative position between the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area as the second distance based on the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area.

[0012] In the above technical solution, the first distance and the second distance are fused by the Kalman filter algorithm to obtain the third distance.

[0013] In the above technical solution, the first distance x 双目 The second distance x 三维 The process of data fusion to obtain the third distance x includes:

[0014] By the first distance x 双目 The dynamic distribution variance σ 双目 and the second distance x 三维 The dynamic distribution variance σ 三维 The Kalman gain coefficient k is calculated,

[0015] in,

[0016] The third distance x is calculated using the following formula: x = x 双目 + k·(x 三维 -x 双目 ).

[0017] The present invention provides a real-time safety distance monitoring system for field operations, comprising a first distance calculation module, a second distance calculation module and a third distance calculation module:

[0018] The first distance calculation module is used to calculate the distance between the on-site workers and the potentially dangerous object or area in real time as the first distance based on the real-time image of the on-site operation, and start the second distance calculation module if the first distance is less than the first set value;

[0019] The second distance calculation module is used to calculate the distance between the on-site operator and the potential dangerous object or area in real time as the second distance based on the real-time three-dimensional position data of the on-site operation;

[0020] The third distance calculation module performs data fusion of the first distance and the second distance to obtain a third distance; if the third distance is less than the second set value, an alarm operation is executed.

[0021] In the above technical solution, the first distance calculation module uses a binocular camera to obtain real-time images of on-site operations.

[0022] In the above technical scheme, the process in which the first distance calculation module calculates the distance between the on-site workers and the potentially dangerous objects or areas as the first distance includes: marking the on-site workers and the potentially dangerous objects or areas in the two-dimensional image acquired in real time by the binocular camera; converting the marked two-dimensional image into a three-dimensional depth map, and obtaining key depth data of the marked on-site workers and the potentially dangerous objects or areas based on the marking; locating the center point and contour boundary of the workers and the potentially dangerous objects or areas through the key depth data, and then calculating the minimum spatial Euclidean distance between the workers and the potentially dangerous objects or areas as the first distance.

[0023] In the above technical solution, the second distance calculation module includes a Beidou real-time dynamic carrier phase (RTK) differential positioning module; the Beidou RTK differential positioning module is respectively configured on the potential dangerous object or area, and the on-site worker body, and the second distance calculation module obtains the three-dimensional position data of the on-site worker and the potential dangerous object or area through the Beidou RTK differential positioning module.

[0024] In the above technical scheme, the process of the second distance calculation module calculating the distance between the on-site workers and the potentially dangerous object or area as the second distance includes: extracting the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area based on the three-dimensional position data of the on-site workers and the potentially dangerous object or area; calculating the relative position between the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area as the second distance based on the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area.

[0025] In the above technical solution, the third distance calculation module obtains the third distance by performing data fusion of the first distance and the second distance through the Kalman filter algorithm.

[0026] In the above technical solution, the third distance calculation module calculates the first distance x 双目 The second distance x 三维 The process of data fusion to obtain the third distance x includes:

[0027] By the first distance x 双目 The dynamic distribution variance σ 双目 and the second distance x 三维 The dynamic distribution variance σ 三维 The Kalman gain coefficient k is calculated,

[0028] in,

[0029] The third distance x is calculated using the following formula: x = x 双目 + k·(x 三维 -x 双目 ).

[0030] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the real-time safety distance monitoring method for on-site operations described in the above technical solution is implemented.

[0031] The present invention also provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the real-time safety distance monitoring method for on-site operations described in the above technical solution by executing the computer instructions.

[0032] The beneficial effects of the present invention are as follows: the present invention discloses a technical performance optimization method based on real-time safety distance monitoring of on-site operations, constructs a complete real-time distance detection system, fully combines the technical advantages and advancement of a variety of intelligent detection methods, and effectively monitors the safety distance of on-site operations in real time. The detection system formed by the present invention through the organically complementary combination of two detection methods can not only effectively avoid detection delays caused by excessive computational burden, but also ensure high accuracy of monitoring, and ensure the balance between technical response speed and accuracy. In the detection of safe distance at the work site, the present invention has the advantages of fast detection speed, high measurement accuracy, and strong response timeliness, which effectively guarantees the safety of on-site workers and improves the safety and reliability of the work site. During preliminary detection, a low computational burden method is used for rapid identification and response, and a more accurate three-dimensional spatial position recognition method is used only when potential danger is detected, effectively saving computing costs.

[0033] Furthermore, the present invention uses a binocular camera to obtain real-time images of on-site operations, effectively ensuring that the camera monitoring screen has a complete operation monitoring range while also having a higher picture clarity.

[0034] Furthermore, the present invention converts the two-dimensional image acquired by the binocular camera into a depth image so as to obtain the distance between the on-site workers and the potentially dangerous objects or areas, thereby ensuring the acquisition accuracy of the first distance.

[0035] Furthermore, the present invention adopts the Beidou RTK differential positioning module to obtain the three-dimensional position data of potentially dangerous objects or areas and on-site workers, effectively ensuring the accuracy and effectiveness of the three-dimensional position data acquisition.

[0036] Furthermore, the present invention extracts the corresponding coordinate positions based on the three-dimensional position data of the potential dangerous object or area and the on-site workers, and then calculates their relative distance as the second distance, effectively ensuring the calculation accuracy.

[0037] Furthermore, the present invention fuses the preliminary depth data obtained by the binocular camera with the high-precision three-dimensional position data through the Kalman filtering algorithm, thereby further optimizing the safety distance detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments to facilitate a clear understanding of the present invention, but they do not constitute a limitation on the present invention.

[0040] Example 1

[0041] like Figure 1 As shown, the present invention provides a real-time safety distance monitoring method for field operations, comprising the following steps:

[0042] Based on the real-time image of the on-site operation, the distance between the on-site operator and the potentially dangerous object or area is calculated in real time as the first distance, and if the first distance is less than the first set value, the subsequent steps are executed; otherwise, the first distance is continued to be calculated in real time;

[0043] Based on the real-time three-dimensional position data of the on-site operation, the distance between the on-site operator and the potentially dangerous object or area is calculated as the second distance;

[0044] The first distance and the second distance are data-fused to obtain a third distance; if the third distance is less than the second set value, an alarm operation is performed; otherwise, no alarm operation is performed, and the first distance is continued to be calculated in real time.

[0045] Specifically, a binocular camera is used to obtain real-time images of on-site operations.

[0046] Preferably, according to the actual situation of the on-site operation area, choose a suitable binocular camera installation position to ensure that the camera monitoring screen has a complete operation monitoring range and also has a high picture clarity. If the installation position is far away, the camera field of view is wider and the safety distance detection area is more complete. If the installation position is close, the image obtained by the camera is clearer and the safety distance detection result is more accurate. After the installation is completed, the focal length, principal point coordinates, distortion and other parameters of the camera can be calibrated to ensure the registration accuracy of the left and right images.

[0047] Specifically, the process of calculating the distance between on-site workers and potentially dangerous objects or areas as the first distance includes: marking on-site workers and potentially dangerous objects or areas in a two-dimensional image acquired in real time by a binocular camera; converting the marked two-dimensional image into a three-dimensional depth map, and obtaining key depth data of the marked on-site workers and potentially dangerous objects or areas based on the marking; locating the center points and contour boundaries of the workers and the potentially dangerous objects or areas through the key depth data; and calculating the minimum spatial Euclidean distance between the workers and the potentially dangerous objects or areas as the first distance through the center points and contour boundaries of the workers and the potentially dangerous objects or areas.

[0048] Preferably, after the binocular camera is set up, the real-time data of the binocular camera is used to quickly convert the two-dimensional image into three-dimensional depth information through a parallax algorithm and generate a depth image. The depth data in the depth image is used to calculate the distance between the on-site workers and the potentially dangerous objects or areas. If the first distance detected is less than the preset safety threshold (i.e., the first set value), the subsequent three-dimensional space position recognition detection mechanism is triggered. After the three-dimensional space position recognition detection mechanism is triggered, a high-precision three-dimensional space position recognition system is started, and accurate three-dimensional position data, i.e., the precise coordinates of the workers and the potentially dangerous objects or areas, are obtained through the Beidou RTK differential positioning module.

[0049] Specifically, Beidou RTK differential positioning modules are respectively configured on the potential dangerous objects or areas, and the on-site workers themselves, and the three-dimensional position data of the on-site workers and the potential dangerous objects or areas are obtained through the Beidou RTK differential positioning modules.

[0050] Preferably, after starting the three-dimensional space position identification and detection mechanism, the system first accurately locates the equipment in the monitoring area. Through the Beidou real-time dynamic carrier phase (RTK) differential positioning module, the system can obtain high-precision three-dimensional position data of the equipment. This module combines satellite signals with ground reference station signals, and involves data synchronization, coordinate transformation and real-time updating. The positioning accuracy can reach centimeters, ensuring that the specific location of each device is accurately marked in the system. On-site workers can wear smart wearable devices containing positioning devices (such as smart safety helmets, auxiliary positioning badges or bracelets). These devices will collect and send the location information of the workers in real time, and calculate the precise three-dimensional coordinates of each worker by receiving this location information.

[0051] Specifically, the process of calculating the distance between the on-site workers and the potentially dangerous object or area as the second distance includes: extracting the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area based on the three-dimensional position data of the on-site workers and the potentially dangerous object or area; calculating the relative position between the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area as the second distance based on the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area.

[0052] Preferably, after obtaining the three-dimensional position data of the equipment and personnel, the system enters the safe distance monitoring stage. First, the system automatically calculates the distance between the operator and the potentially dangerous object or area. By calculating the Euclidean space distance between two points and combining it with the real-time updated three-dimensional coordinates, the system can continuously monitor the relative position of the operator and the equipment.

[0053] Specifically, the first distance and the second distance are fused to obtain the third distance through the Kalman filter algorithm. The preliminary depth data obtained by the binocular camera is fused with the high-precision three-dimensional position data through the Kalman filter algorithm to further optimize the accuracy of safety distance detection. The measured precise distance is compared with the safety standard. If the detected distance is still less than the safety range, a further alarm prompt is triggered.

[0054] Specifically, the first distance x 双目 The second distance x 三维 The process of data fusion to obtain the third distance x includes:

[0055] By the first distance x 双目 The dynamic distribution variance σ 双目 and the second distance x 三维 The dynamic distribution variance σ 三维 The Kalman gain coefficient k is calculated,

[0056] in,

[0057] The third distance x is calculated using the following formula: x = x 双目 + k·(x 三维 -x 双目 ).

[0058] Example 2

[0059] The present invention provides a real-time safety distance monitoring method for field operations. According to the actual field operation conditions, a suitable installation angle and area are selected, a calibrated binocular camera is installed, and a preliminary distance detection is performed by generating a depth image. The preliminary safety distance monitoring is performed by the binocular camera, and ordinary precision detection is performed by virtue of its rapid recognition advantage. When it is detected that the operation distance is close to or less than the safety requirement threshold, a high-precision three-dimensional space position recognition system is started, including Beidou real-time dynamic carrier phase (RTK) differential positioning, a laser radar module, etc., to obtain more accurate three-dimensional position data, and realize the absolute coordinate to achieve centimeter-level precision distance detection. Then, through data fusion technology, the preliminary depth data of the binocular camera is fused with the high-precision position data to achieve centimeter-level precision distance measurement. Finally, the measurement result is compared with the preset safety threshold to determine whether it exceeds the safety range, and a high-level alarm system is triggered when the danger is confirmed, and the measurement data is recorded for subsequent safety analysis and work optimization. The detection system formed by the organically complementary combination of the two detection methods can not only effectively avoid the detection delay caused by excessive calculation burden, but also ensure the high precision of monitoring. The method specifically includes the following steps:

[0060] Step 1: Set up the binocular camera

[0061] According to the actual situation of the on-site operation area, choose the appropriate binocular camera installation location to ensure that the camera monitoring screen has a complete operation monitoring range and also has a high picture clarity. After the installation is completed, the camera's focal length, principal point coordinates, distortion and other parameters can be calibrated to ensure the registration accuracy of the left and right images.

[0062] Step 2: Binocular camera safety distance detection

[0063] After the on-site binocular camera is set up, the safe distance between the on-site workers and the equipment is quickly and preliminarily detected using the binocular camera safe distance detection method. The detection results of this method are generally accurate, but the detection speed is fast, which can avoid detection delays caused by excessive computational burden to a certain extent. The overall detection process can be divided into three main steps: electrical object analysis, binocular depth perception, and safe distance measurement.

[0064] Step 2.1: Analysis of electrical objects

[0065] First, the real-time image is analyzed through image processing technology to identify the workers and live equipment (i.e. potentially dangerous objects or areas) on site. The image recognition algorithm automatically detects and marks all relevant electrical objects, including the location of live equipment and the posture of workers.

[0066] Step 2.2: Binocular Depth Perception

[0067] Next, the system uses a disparity algorithm to match the left and right images to generate a disparity map. Based on the disparity map and calibrated camera parameters, the depth value of each pixel is calculated to generate a complete 3D depth map, thereby extracting key depth data including personnel and live equipment.

[0068] Step 2.3: Safety distance measurement

[0069] The center point and contour boundary of the operator and the live equipment are located through key depth data, and the minimum spatial Euclidean distance between the operator and each live equipment is calculated, that is, the actual distance between the two as the corresponding first distance. If the detected first distance is much larger than the preset safety threshold (i.e., the first set value), it will be judged as safe; if the detected first distance is close to or less than the preset safety threshold, it will be determined that there is a safety hazard, and the three-dimensional spatial position recognition detection mechanism in step 3 will be triggered to perform a more refined safety distance detection.

[0070] Step 3: 3D spatial position recognition and safety distance detection

[0071] Since the detection accuracy of the binocular camera safety distance detection method is average, the accuracy can be further improved through the three-dimensional space position recognition safety distance detection method to avoid false alarms and missed alarms. The overall detection process can be divided into three main steps: indoor and outdoor equipment positioning, personnel movement positioning and safety distance measurement.

[0072] Step 3.1: Locate the energized equipment

[0073] After starting the three-dimensional spatial position recognition and detection mechanism, the system first accurately locates the live equipment in the monitoring area. Each live equipment is equipped with a Beidou RTK differential positioning module. Through the Beidou RTK differential positioning module, high-precision three-dimensional position data of live equipment can be obtained. The Beidou RTK differential positioning module combines satellite signals with ground reference station signals, and involves data synchronization, coordinate transformation and real-time update. The positioning accuracy can reach centimeter level, ensuring that the specific location of each device is accurately marked in the system.

[0074] Step 3.2: Personnel movement positioning

[0075] At the same time, the system will perform high-precision positioning of the real-time position of the operator. Also using the Beidou RTK differential positioning module, the operator can wear smart wearable devices (such as smart helmets, auxiliary positioning badges or bracelets) containing the Beidou RTK differential positioning module. These devices will collect and send the operator's position information in real time, and by receiving this position information, the precise three-dimensional coordinates of each operator can be calculated.

[0076] Step 3.3: Safety distance measurement

[0077] After obtaining the three-dimensional position data of live equipment and personnel, the safety distance monitoring stage begins. First, the distance between the operator and the potentially dangerous object or area is automatically calculated. By calculating the Euclidean space distance between two points and combining it with the real-time updated three-dimensional coordinates, the system can continuously monitor the relative position of the operator and the equipment.

[0078] Step 4: Data Fusion

[0079] Through the two detection methods of step 2 binocular camera safety distance detection and step 3 three-dimensional space position recognition safety distance detection, two different distance detection results x can be obtained. 双目 and x 三维 Next, the detection results are fused through the Kalman filter algorithm.

[0080] Specifically, according to the known dynamic distribution variance σ of the results of the two detection methods 双目 and σ 三维 , find the Kalman gain coefficient

[0081] Through calculation, the fused result x = x 双目 + k·(x 三维 -x 双目 ) is the safety distance detection result.

[0082] Ultimately, the system will use the built-in safety threshold (i.e., the second set value) as the baseline. When the detected safety distance is less than the preset safety threshold, the early warning mechanism will be triggered and an alarm will be sounded. Through real-time, continuous data flow, it can ensure that potential safety hazards are identified and responded to in the shortest possible time.

[0083] Example 3

[0084] The present invention provides a real-time safety distance monitoring system for field operations, comprising a first distance calculation module, a second distance calculation module and a third distance calculation module:

[0085] The first distance calculation module is used to calculate the distance between the on-site operator and the potentially dangerous object or area in real time as the first distance based on the real-time image of the on-site operation, and if the first distance is less than the first set value, the second distance calculation module is started; otherwise, the second distance calculation module is not started;

[0086] The second distance calculation module is used to calculate the distance between the on-site operator and the potential dangerous object or area in real time as the second distance based on the real-time three-dimensional position data of the on-site operation;

[0087] The third distance calculation module performs data fusion of the first distance and the second distance to obtain a third distance; if the third distance is less than the second set value, an alarm operation is executed; otherwise, an alarm operation is not executed.

[0088] Specifically, the first distance calculation module uses a binocular camera to obtain real-time images of on-site operations.

[0089] Specifically, the process of the first distance calculation module calculating the distance between the on-site workers and the potentially dangerous objects or areas as the first distance includes: converting the real-time two-dimensional image acquired by the binocular camera into three-dimensional depth information and generating a depth image; and using the depth data in the depth image to calculate the distance between the on-site workers and the potentially dangerous objects or areas as the first distance.

[0090] Specifically, the second distance calculation module includes a Beidou RTK differential positioning module; the Beidou RTK differential positioning module is respectively configured on the potential dangerous object or area, and the on-site worker body, and the second distance calculation module obtains the three-dimensional position data of the on-site worker and the potential dangerous object or area through the Beidou RTK differential positioning module.

[0091] Specifically, the process by which the second distance calculation module calculates the distance between the on-site workers and the potentially dangerous object or area as the second distance includes: extracting the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area based on the three-dimensional position data of the on-site workers and the potentially dangerous object or area; and calculating the relative position between the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area as the second distance based on the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area.

[0092] Specifically, the third distance calculation module uses a Kalman filter algorithm to fuse the first distance and the second distance to obtain a third distance.

[0093] Specifically, the third distance calculation module calculates the first distance x 双目 The second distance x 三维 The process of data fusion to obtain the third distance x includes:

[0094] By the first distance x双目 The dynamic distribution variance σ 双目 and the second distance x 三维 The dynamic distribution variance σ 三维 The Kalman gain coefficient k is calculated,

[0095] in,

[0096] The third distance x is calculated using the following formula: x = x 双目 + k·(x 三维 -x 双目 ).

[0097] Example 4

[0098] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the real-time safety distance monitoring method for on-site operations described in the above technical solution is implemented.

[0099] Example 5

[0100] The present invention also provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the real-time safety distance monitoring method for on-site operations described in the above technical solution by executing the computer instructions.

[0101] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0102] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0103] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0105] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

[0106] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

Claims

1. A real-time safety distance monitoring method for field operations, characterized in that: The following steps are involved: Based on the real-time image of the on-site operation, the distance between the on-site operator and the potentially dangerous object or area is calculated in real time as a first distance, and if the first distance is less than a first set value, subsequent steps are executed; Based on the real-time three-dimensional position data of the on-site operation, the distance between the on-site operator and the potentially dangerous object or area is calculated in real time as the second distance; The first distance and the second distance are data-fused to obtain a third distance; if the third distance is less than the second set value, an alarm operation is performed.

2. A real-time safety distance monitoring method for on-site operations according to claim 1, characterized in that: A binocular camera is used to obtain real-time images of on-site operations.

3. A real-time safety distance monitoring method for on-site operations according to claim 2, characterized in that: The process of calculating the distance between an on-site worker and a potentially dangerous object or area as a first distance includes: marking the on-site worker and the potentially dangerous object or area in a two-dimensional image acquired in real time by a binocular camera; converting the marked two-dimensional image into a three-dimensional depth map, and obtaining key depth data of the marked on-site worker and the potentially dangerous object or area based on the marking; locating the center point and contour boundary of the worker and the potentially dangerous object or area through the key depth data, and then calculating the minimum spatial Euclidean distance between the worker and the potentially dangerous object or area as the first distance.

4. The real-time safety distance monitoring method for field operations according to claim 1 is characterized in that: Beidou real-time dynamic carrier phase differential positioning modules are configured on potential dangerous objects or areas, and on-site workers respectively, and the three-dimensional position data of on-site workers and potential dangerous objects or areas are obtained through the Beidou RTK differential positioning module.

5. A real-time safety distance monitoring method for on-site operations according to claim 4, characterized in that: The process of calculating the distance between an on-site worker and a potentially dangerous object or area as a second distance includes: extracting the three-dimensional coordinate positions of the on-site worker and the potentially dangerous object or area based on the three-dimensional position data of the on-site worker and the potentially dangerous object or area; and calculating the relative position between the three-dimensional coordinate positions of the on-site worker and the potentially dangerous object or area as the second distance based on the three-dimensional coordinate positions of the on-site worker and the potentially dangerous object or area.

6. The real-time safety distance monitoring method for on-site operations according to claim 1, characterized in that: The first distance and the second distance are fused by the Kalman filter algorithm to obtain the third distance.

7. A real-time safety distance monitoring method for on-site operations according to claim 6, characterized in that: Set the first distance x 双目 The second distance x 三维 The process of data fusion to obtain the third distance x includes: By the first distance x 双目 The dynamic distribution variance σ 双目 and the second distance x 三维 The dynamic distribution variance σ 三维 The Kalman gain coefficient k is calculated, in, The third distance x is calculated using the following formula: x = x 双目 + k·(x 三维 -x 双目 ).

8. A real-time safety distance monitoring system for field operations, characterized in that: It includes a first distance calculation module, a second distance calculation module and a third distance calculation module: The first distance calculation module is used to calculate the distance between the on-site workers and the potentially dangerous object or area in real time as the first distance based on the real-time image of the on-site operation, and start the second distance calculation module if the first distance is less than the first set value; The second distance calculation module is used to calculate the distance between the on-site operator and the potential dangerous object or area in real time as the second distance based on the real-time three-dimensional position data of the on-site operation; The third distance calculation module performs data fusion of the first distance and the second distance to obtain a third distance; if the third distance is less than the second set value, an alarm operation is executed.

9. A real-time safety distance monitoring system for on-site operations according to claim 8, characterized in that: The first distance calculation module uses a binocular camera to obtain real-time images of on-site operations.

10. A real-time safety distance monitoring system for on-site operations according to claim 9, characterized in that: The process of the first distance calculation module calculating the distance between the on-site workers and the potential dangerous objects or areas as the first distance includes: marking the on-site workers and the potential dangerous objects or areas in the two-dimensional image acquired in real time by the binocular camera; converting the marked two-dimensional image into a three-dimensional depth map, and obtaining key depth data of the marked on-site workers and the potential dangerous objects or areas based on the marking; locating the center point and contour boundary of the workers and the potential dangerous objects or areas through the key depth data, and then calculating the minimum spatial Euclidean distance between the workers and the potential dangerous objects or areas as the first distance.

11. A real-time safety distance monitoring system for on-site operations according to claim 8, characterized in that: The second distance calculation module includes a Beidou real-time dynamic carrier phase differential positioning module; the Beidou RTK differential positioning module is respectively configured on the potential dangerous object or area, and the on-site worker body. The second distance calculation module obtains the three-dimensional position data of the on-site worker and the potential dangerous object or area through the Beidou RTK differential positioning module.

12. A real-time safety distance monitoring system for on-site operations according to claim 11, characterized in that: The process of the second distance calculation module calculating the distance between the on-site workers and the potentially dangerous object or area as the second distance includes: extracting the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area based on the three-dimensional position data of the on-site workers and the potentially dangerous object or area; calculating the relative position between the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area as the second distance based on the three-dimensional coordinate positions of the on-site workers and the potentially dangerous object or area.

13. A real-time safety distance monitoring system for on-site operations according to claim 8, characterized in that: The third distance calculation module uses the Kalman filter algorithm to fuse the first distance and the second distance to obtain the third distance.

14. A real-time safety distance monitoring system for on-site operations according to claim 13, characterized in that: The third distance calculation module calculates the first distance x 双目 The second distance x 三维 The process of data fusion to obtain the third distance x includes: By the first distance x 双目 The dynamic distribution variance σ 双目 and the second distance x 三维 The dynamic distribution variance σ 三维 The Kalman gain coefficient k is calculated, in, The third distance x is calculated using the following formula: x = x 双目 + k·(x 三维 -x 双目 ).

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the real-time safety distance monitoring method for field operations described in any one of claims 1 to 7 is implemented.

16. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the real-time safety distance monitoring method for field operations as described in any one of claims 1 to 7 by executing the computer instructions.

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