Crane electricity approaching early warning system and using method thereof

Abstract

The invention discloses a crane electricity approaching early warning system and a using method thereof, and belongs to the technical field of electricity approaching detection. The system mainly comprises a sensing unit and a cloud end collaborative network, the sensing unit is connected with a control unit, the control unit is connected with a grading alarm unit, and the grading alarm unit is in communication connection with the cloud end collaborative network. The distance between the suspension arm and the electric wire can be judged in real time through multi-source sensing fusion, AI visual recognition and a dynamic digital twinborn model, and the core beneficial effect of the invention is that three-level guarantee from early warning to limitation and then active intervention is constructed, and cooperation is realized through sound and light, a force feedback handle and the cloud.

Description

Technical Field

[0001] This invention relates to the field of proximity detection technology, and more specifically, to a crane proximity warning system and its usage method. Background Technology

[0002] In hoisting operations near power lines, traditional safety measures mainly rely on the driver's visual observation and experience, supplemented by simple distance alarms or electric field alarms. These systems generally suffer from problems such as limited perception dimensions, poor anti-interference capabilities, static and rigid safety distance judgments, passive and lacking hierarchical warning methods, inability to form a closed-loop linkage with the vehicle control system, and isolated and difficult-to-trace data throughout the safety management process. This leads to frequent crane-to-power-line collision accidents, causing significant economic losses and personal injury. Existing technology, application CN119349444A, discloses a crane boom proximity detection device and its detection method, employing a distributed deployment of dual-mode and single-mode host systems, but it lacks visual recognition capabilities, predictive capabilities, and situational awareness. Therefore, there is currently a lack of a comprehensive proximity warning solution that can achieve all-round perception, intelligent dynamic risk assessment, human-machine collaborative hierarchical early warning, and cloud-based collaborative supervision. Summary of the Invention

[0003] The purpose of this invention is to provide a crane proximity warning system and its usage method to solve the problems mentioned in the background art.

[0004] This invention is achieved through the following technical solution: A crane proximity warning system includes: a sensing unit and a cloud-edge-device collaborative network. The sensing unit is connected to a control unit, and the control unit is connected to a hierarchical alarm unit. The hierarchical alarm unit is communicatively connected to the cloud-edge-device collaborative network. The sensing unit includes a sensing terminal deployed on the crane boom for synchronously collecting distance information, electric field information, and visual image information of the target. The control unit includes an onboard computing terminal and a navigation module for running a dynamic digital twin model of the crane's operating environment and calculating the dynamic safety envelope between the crane boom and the energized target based on the information from the sensing unit and the real-time crane pose data from the navigation module. The hierarchical alarm unit includes a local alarm module, a remote alarm module, and an active intervention module. The active intervention module is connected to the crane's electronic control system. The cloud-edge-device collaborative network connects the control unit to a cloud-based safety monitoring platform via a 5G communication module.

[0005] Furthermore, the sensing terminal is fixed on the boom, which includes a main boom, a secondary boom, and a hook; the main boom, the secondary boom, and the hook are all equipped with sensing terminals.

[0006] Furthermore, several of the aforementioned sensing terminals include a main controller, which is connected to an environmental sensor, a radar module, a proximity sensor, and a vision sensor.

[0007] Furthermore, the main controller includes a wireless communication module, which connects to the vehicle-mounted computing terminal.

[0008] Furthermore, the local alarm module includes a display, an audible and visual alarm, and a force feedback motor; the force feedback motor is connected to an operating handle.

[0009] Furthermore, the graded alarm unit adopts a three-level response dynamic threshold mechanism, specifically including: when the distance between the boom and the safety envelope is greater than 10 meters, the audible and visual alarm is triggered intermittently, the operating handle vibrates slightly, the display shows a yellow warning, and the boom's movement speed is limited to below 0.5 m / s; when the distance between the boom and the safety envelope is in the range of 5-10 meters, the audible and visual alarm is triggered continuously, the operating handle vibrates at high frequency to lock the boom's degree of freedom of movement towards the energized target; when the distance between the boom and the safety envelope is less than 5 meters, the active intervention module is triggered to cut off the boom drive circuit.

[0010] Furthermore, the vehicle-mounted computing terminal is connected to the display; the vehicle-mounted computing terminal includes an AI vision module for identifying and classifying power transmission lines, towers, and insulators.

[0011] A method for using a crane proximity warning system includes the following steps: S1: The target's distance, electric field, and visual image information are simultaneously acquired through a multi-source fusion sensing unit; S2: Utilize AI visual recognition technology to identify charged targets and estimate their voltage levels non-contactly based on insulator characteristics; S3: In the control unit, drive the digital twin model, integrate pose information, environmental parameters and voltage level, and calculate the dynamic safety envelope. S4: Based on the trajectory prediction algorithm, predict the future motion trajectory of the boom and perform collision detection with the dynamic safety envelope; generate graded risk assessment results; S5: Based on the risk assessment results, simultaneously trigger local and remote graded alarms and execute a coordinated response from visual early warning and tactile feedback to proactive intervention by the crane's electronic control system.

[0012] Furthermore, in step S5, when a level 3 alarm is triggered, the on-board computing terminal sends a motion restriction command frame to the crane's electronic control system to impose a hard speed limit on the dangerous direction movement of the boom; it automatically transmits the perception data and video recordings, including a period of time before and after the alarm, to the cloud-based safety monitoring platform via the 5G network, and immediately sends alarm notifications to all preset remote alarm modules.

[0013] Compared with the prior art, the beneficial effects of the present invention are: This invention uses multi-source sensing fusion, AI visual recognition, and dynamic digital twin models to determine the distance between the boom and the power line in real time. Its core beneficial effect is to build a three-level protection system from early warning to restriction and then active intervention. Through sound and light, force feedback handles, and cloud collaboration, it upgrades passive alarms to proactive prevention and control throughout the entire process, effectively preventing electric shock accidents and allowing managers to keep abreast of the on-site safety status, thus improving operational safety. Attached Figure Description

[0014] Figure 1 This is a flowchart of the present invention; Figure 2 This is a schematic diagram of the structure of the present invention; Figure 3 This is a schematic diagram of the sensing terminal of the boom of the present invention; Figure 4 This is a schematic diagram of the sensing terminal of the hook of the present invention.

[0015] In the diagram: 1. Sensing terminal; 2. Crane base; 3. Proximity sensor; 4. Vision sensor; 5. Environmental sensor; 6. Radar module; 7. Main boom; 8. Auxiliary boom; 9. Hook. Detailed Implementation

[0016] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Based on the embodiments in this application, other similar embodiments obtained by those skilled in the art without creative effort should all fall within the scope of protection of this application. Furthermore, directional terms mentioned in the following embodiments, such as "up," "down," "left," and "right," are only for reference to the directions in the accompanying drawings; therefore, the directional terms used are for illustrative purposes and not for limiting the invention.

[0017] The present invention will now be further described in conjunction with the accompanying drawings.

[0018] Example 1: A crane proximity warning system, such as Figures 1-4As shown, it includes: a sensing unit and a cloud-edge-device collaborative network. The sensing unit is connected to a control unit, and the control unit is connected to a hierarchical alarm unit. The hierarchical alarm unit is communicatively connected to the cloud-edge-device collaborative network. The sensing unit includes a sensing terminal 1 deployed on the crane boom, used to synchronously collect distance information, electric field information, and visual image information of the target. The control unit includes an on-board computing terminal and a navigation module, used to run a dynamic digital twin model of the crane's operating environment, and calculate the dynamic safety envelope between the boom and the charged target based on the information from the sensing unit and the real-time pose data of the crane from the navigation module. The hierarchical alarm unit includes a local alarm module, a remote alarm module, and an active intervention module. The active intervention module is connected to the crane's electronic control system. The cloud-edge-device collaborative network connects the control unit to the cloud-edge-device safety monitoring platform via a 5G communication module.

[0019] Example 2: A crane proximity warning system, wherein the sensing terminals are fixed on the crane boom, which includes a main boom 7, a secondary boom 8, and a hook 9; each of the main boom 7, secondary boom 8, and hook 9 is equipped with a sensing terminal 1, the main boom 7 is fixed on a crane seat 2, and the crane seat 2 is fixed on a vehicle. The sensing terminals 1 include a main controller, which is connected to an environmental sensor 5, a radar module 6, a proximity sensor 3, and a vision sensor 4; the environmental sensor 5 includes a wind speed sensor. The main controller uses an embedded computing core based on an ARM or x86 architecture. The radar module 6 is a millimeter-wave radar module 6, with an operating frequency of 76-81 GHz and a detection range of not less than 150 meters, used to acquire distance data and relative speed of targets; the vision sensor 4 is connected to an AI vision module, including a wide-angle camera and a deep learning target detection algorithm running on it, used to identify and classify power lines, towers, and insulators.

[0020] The main controller includes a wireless communication module, which connects to the vehicle-mounted computing terminal. The local alarm module includes a display, an audible and visual alarm, and a force feedback motor; the force feedback motor is integrated into the operating handle. The graded alarm unit employs a three-level response dynamic threshold mechanism, specifically: when the distance between the boom and the safety envelope is greater than 10 meters, the audible and visual alarm is triggered intermittently, the operating handle vibrates slightly, the display shows a yellow warning, and the boom's movement speed is limited to below 0.5 m / s; when the distance between the boom and the safety envelope is between 5 and 10 meters, the audible and visual alarm is triggered continuously, the operating handle vibrates at high frequency, and the boom's freedom of movement towards the energized target is locked; when the distance between the boom and the safety envelope is less than 5 meters, the active intervention module is triggered to cut off the boom's drive circuit. The vehicle-mounted computing terminal is connected to the display; the vehicle-mounted computing terminal includes an AI vision module for identifying and classifying power lines, towers, and insulators. Other aspects are the same as in Embodiment 1.

[0021] A method for using a crane proximity warning system includes the following steps: S1: The multi-source fusion sensing unit synchronously collects the target's distance, electric field, and visual image information; the sensing terminals 1 deployed at various points on the boom are simultaneously activated, and the radar continuously scans the distance data of surrounding obstacles; the proximity sensor 3 monitors the spatial electric field intensity distribution; and the visual sensor 4 captures high-definition environmental images. All data is timestamped and transmitted to the vehicle-mounted computing terminal via a wireless network. S2: Utilizing AI visual recognition technology, identify energized targets and estimate their voltage levels non-contactly based on insulator characteristics; the AI ​​vision module of the vehicle terminal processes the input image in real time, first using a target detection algorithm to select potential energized targets such as transmission lines and towers. Then, focusing on insulator strings, it uses a pre-trained classification model to identify their type and non-contactly estimate the voltage level of the current line. S3: In the control unit, drive the digital twin model, fuse pose information, environmental parameters and voltage level, and calculate the dynamic safety envelope surface; the model fuses the multi-source sensing data in S1, the estimated voltage level in S2, the real-time pose of the crane provided by the navigation module and the real-time environmental parameters, and calculates in real time a non-uniform, dynamically changing three-dimensional safety envelope surface around the charged target. S4: Based on the trajectory prediction algorithm, predict the future motion trajectory of the boom and perform collision detection with the dynamic safety envelope; generate graded risk assessment results; S5: Based on the risk assessment results, simultaneously trigger local and remote graded alarms and execute a coordinated response from visual early warning and tactile feedback to proactive intervention by the crane's electronic control system.

[0022] In step S5, when a level 3 alarm is triggered, the on-board computing terminal sends a motion restriction command frame to the crane's electronic control system to impose a hard speed limit on the dangerous direction movement of the boom; it automatically transmits the perception data and video recordings, including a period of time before and after the alarm, to the cloud-based safety monitoring platform via the 5G network, and immediately sends alarm notifications to all preset remote alarm modules.

[0023] This invention overcomes the limitations of single sensors by integrating multi-source sensors and AI visual recognition, achieving accurate identification of energized targets and voltage level estimation. Based on digital twins and trajectory prediction, it achieves dynamic early warning, and its three-level response mechanism balances operational efficiency and safety, effectively preventing misoperation and accidents. Through 5G-enabled cloud-edge-device collaboration, it realizes digital and intelligent management of construction safety.

[0024] The present invention has been described in detail above. The above description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of this application should still fall within the scope of the present invention.

Claims

1. A crane proximity electric warning system, characterized by: It includes: The system comprises a sensing unit and a cloud-edge-device collaborative network. The sensing unit is connected to a control unit, which in turn is connected to a hierarchical alarm unit. The hierarchical alarm unit is communicatively connected to the cloud-edge-device collaborative network. The sensing unit includes a sensing terminal (1) for synchronously collecting distance information, electric field information, and visual image information of the target. The control unit includes an on-board computing terminal and a navigation module for running a dynamic digital twin model of the crane's operating environment and calculating the dynamic safety envelope between the boom and the energized target based on the information from the sensing unit and the real-time pose data of the crane from the navigation module. The hierarchical alarm unit includes a local alarm module, a remote alarm module, and an active intervention module. The active intervention module is connected to the crane's electronic control system. The cloud-edge-device collaborative network connects the control unit to the cloud-edge-device safety supervision platform via a 5G communication module.

2. The crane proximity electric field warning system of claim 1, wherein: The sensing terminal is fixed on the boom, which includes a main boom (7), a secondary boom (8) and a hook (9); the main boom (7), the secondary boom (8) and the hook (9) are all equipped with sensing terminals (1).

3. The crane proximity electric hazard warning system of claim 2, wherein: The aforementioned sensing terminals (1) include a main controller, which is connected to an environmental sensor (5), a radar module (6), a proximity sensor (3), and a vision sensor (4).

4. The crane proximity electric hazard warning system of claim 3, wherein: The main controller includes a wireless communication module, which connects to the vehicle-mounted computing terminal.

5. The crane proximity electric hazard warning system of claim 1, wherein: The local alarm module includes a display, an audible and visual alarm, and a force feedback motor; the force feedback motor is connected to an operating handle.

6. The crane proximity electric hazard warning system of claim 1, wherein: The aforementioned graded alarm unit adopts a three-level response dynamic threshold mechanism, specifically including: when the distance between the boom and the safety envelope surface is greater than 10 meters, the audible and visual alarm is triggered intermittently, the operating handle vibrates slightly, the display shows a yellow warning, and the boom's movement speed is limited to below 0.5 m / s; when the distance between the boom and the safety envelope surface is in the range of 5-10 meters, the audible and visual alarm is triggered continuously, the operating handle vibrates at high frequency to lock the boom's degree of freedom of movement towards the energized target; when the distance between the boom and the safety envelope surface is less than 5 meters, the active intervention module is triggered to cut off the boom drive circuit.

7. The crane proximity electric hazard warning system of claim 1, wherein: The vehicle-mounted computing terminal is connected to the display; the vehicle-mounted computing terminal includes an AI vision module for identifying and classifying power transmission lines, towers and insulators.

8. A method of using a crane proximity electric warning system, characterized by: Using the crane proximity warning system according to any one of claims 1-7 includes the following steps: S1: The target's distance, electric field, and visual image information are simultaneously acquired through a multi-source fusion sensing unit; S2: Utilize AI visual recognition technology to identify charged targets and estimate their voltage levels non-contactly based on insulator characteristics; S3: In the control unit, drive the digital twin model, integrate pose information, environmental parameters and voltage level, and calculate the dynamic safety envelope. S4: Based on the trajectory prediction algorithm, predict the future motion trajectory of the boom and perform collision detection with the dynamic safety envelope; generate graded risk assessment results; S5: Based on the risk assessment results, simultaneously trigger local and remote graded alarms and feed back to the crane's electronic control system for proactive intervention and coordinated response.

9. The method of claim 8, wherein: In step S5, when a level 3 alarm is triggered, the on-board computing terminal sends a motion restriction command frame to the crane's electronic control system to impose a hard speed limit on the dangerous direction movement of the boom; it automatically transmits the perception data and video recordings, including a period of time before and after the alarm, to the cloud-based safety monitoring platform via the 5G network, and immediately sends alarm notifications to all preset remote alarm modules.

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