Intelligent anti-collision early warning method for tower crane lifting hook based on 5G and millimeter wave radar fusion

Abstract

The invention discloses a tower crane lifting hook intelligent anti-collision early warning method based on 5G and millimeter-wave radar fusion, which is characterized in that a millimeter-wave radar array for point cloud data acquisition is arranged at the tail end of a balance arm of a tower crane, and a 5G edge computing gateway for receiving and processing the point cloud data acquired by the millimeter-wave radar array is arranged in the middle of a tower body of the tower crane; a tower crane cab is provided with a digital twin platform fusing a tower crane three-dimensional model and a construction site BIM model and used for displaying the three-dimensional position of a lifting hook, and a multi-stage early warning terminal used for displaying collision early warning information and executing early warning operation. And the 5G edge computing gateway feeds back prediction information to the digital twin platform and the multi-stage early warning terminal by running a long short-term memory network trajectory prediction model and a collision detection algorithm. The 5G + millimeter wave radar technology is creatively applied to the field of collision avoidance of the tower crane lifting hook, and the problems that a traditional collision avoidance technical scheme of the lifting hook is high in delay and low in precision are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-collision of tower crane hooks, and particularly to an intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar. Background Art

[0002] Due to the complex operation environment of tower crane hooks, the risk of collision is high, and the consequences of collision are serious. Therefore, the industry standard requires that GB / T 5031-2024 "Tower Cranes" stipulates that tower cranes should be equipped with effective anti-collision devices to ensure construction safety, avoid equipment damage and casualties.

[0003] The reasons for the high risk of collision caused by the complex operation environment include the following two points: hidden dangers of multi-tower cross-operation. When tower cranes are densely constructed, the hook may collide with the boom, wire rope or building of other tower cranes. Especially in the cross-operation area, if the position of the hook is not adjusted in time or the slewing angle is not controlled, a chain accident is extremely likely to occur; it is difficult to control the dynamic operation range. When the hook moves with the boom, it may deviate from the preset trajectory under the influence of factors such as wind force and inertia. For example, when suddenly encountering strong wind or power outage, if the hook is not fixed or lifted in place in time, it may swing and hit the surrounding facilities. The serious consequences of collision are mainly reflected in the following two aspects: direct equipment damage. When the hook collides with a hard object, the wire rope may break, the lifting appliance may be deformed, and even the tower body structure may be damaged. For example, if the brake is not applied in time after the collision, the boom may be deformed or the tower crane may overturn; secondary safety accidents. The collision may cause the suspended load to fall, threatening the safety of the personnel below; at the same time, the impact force generated by the collision may be transmitted to the tower body, affecting the overall stability of the tower crane.

[0004] However, the existing anti-collision technologies for tower crane hooks have the following problems: (1) Limitations of traditional safety monitoring means: ① Visual solutions (such as cameras) are easily interfered by environmental factors such as rain, fog, strong light, etc., and the reliability is insufficient; ② Contact sensors (such as mechanical limiters) have a risk of wear and a short service life; ③ Traditional wireless transmission systems (such as ZigBee) have a high time delay (>200ms) and cannot meet the real-time control requirements. (2) Challenges brought by the motion characteristics of the hook: ① The hook has complex three-dimensional trajectory motions (including translation, rotation and swing) during high-altitude operations, and it is difficult for traditional two-dimensional detection means to achieve accurate positioning; ② The swing amplitude of the hook is relatively large (especially under the action of wind force), resulting in a high false alarm rate (>15%) of the existing collision warning systems.

[0005] In summary, how to achieve high-precision and low-latency real-time monitoring, early warning and response for tower crane hook anti-collision is a technical problem that needs to be solved urgently.

[0006] It should be particularly noted that the above technical information is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as admitting or implying in any form that the above technical information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0007] In view of the deficiencies in the above-mentioned background technology, the present invention proposes an intelligent anti-collision warning method for a tower crane hook based on the fusion of 5G and millimeter-wave radar. The technical problem to be solved is: how to achieve high-precision and low-latency real-time monitoring, warning and response of tower crane hook anti-collision.

[0008] The technical solution of the present invention is: An intelligent anti-collision warning method for a tower crane hook based on the fusion of 5G and millimeter-wave radar, wherein a millimeter-wave radar array for point cloud data collection is arranged at the end of the tower crane's balance arm, a 5G edge computing gateway for receiving and processing point cloud data collected by the millimeter-wave radar array is arranged in the middle of the tower crane's tower body, a digital twin platform that integrates the tower crane's three-dimensional model and the construction site BIM model and is used to display the three-dimensional position of the hook, and a multi-level warning terminal that is used to display collision warning information and perform warning operations are arranged in the tower crane cab, and the 5G edge computing gateway feeds back prediction information to the digital twin platform and the multi-level warning terminal by running a long short-term memory network trajectory prediction model and a collision detection algorithm.

[0009] On the basis of the above technical solutions, as the preferred technical solution for the intelligent anti-collision warning method of tower crane hook based on the fusion of 5G and millimeter-wave radar, the 5G edge computing gateway uses a density clustering algorithm to cluster the point cloud data collected by the millimeter-wave radar array when receiving and processing the point cloud information collected by the millimeter-wave radar array, and distinguishes between hooks, obstacles and noise points.

[0010] On the basis of the above technical solutions, as the preferred technical solution for the intelligent anti-collision warning method of tower crane hook based on the fusion of 5G and millimeter-wave radar, the 5G edge computing gateway converts the radar point cloud data from the local coordinate system to the universal transverse Mercator coordinate system when receiving and processing the point cloud information collected by the millimeter-wave radar array, and aligns it with the BIM model of the construction site to ensure that the hook position is synchronized with the three-dimensional model in the digital twin platform in real time.

[0011] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the detection algorithm is the Gilbert-Johnson-Keerthi algorithm, which quickly detects the possibility of collision between the hook and obstacles based on the principle of convex body geometry.

[0012] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the working process of the multi-level warning terminal is as follows: Level 1 warning: When the hook enters the 3m safety area, the cab gives an audible and visual alarm; Level 2 braking: When the hook enters the 1.5m dangerous area, the winch is automatically triggered to decelerate; Level 3 emergency stop: When the hook enters the 0.5m limit area, the power source is cut off and the mechanical brake is activated.

[0013] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the audible and visual alarm includes a warning terminal installed on the top of the cab with a brightness ≥ 2000 cd / m².

[0014] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the digital twin platform is used for real-time hook position display, collision risk area marking, and alarm information prompting.

[0015] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the millimeter-wave radar array includes four groups of millimeter-wave radars evenly distributed on both sides of the end of the balance arm and covering a 360° range.

[0016] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the working frequency of the millimeter-wave radar is 77 GHz, the detection distance is 0.2 m - 50 m, and the accuracy is ±2 cm.

[0017] On the basis of the above technical solution, as an optimized technical solution of the intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, the 5G edge computing gateway is equipped with an NPU chip with a computing power of 4 TOPS and supports SA / NSA dual-mode networking.

[0018] Compared with the prior art, the intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar proposed by the present invention solves the core problems of tower crane hook position monitoring and collision warning through multi-source data fusion and edge computing technologies. The world's first application of 5G + millimeter-wave radar in the field of tower crane anti-collision solves the problems of high latency and low accuracy of traditional solutions; LSTM + GJK realizes sub-second trajectory prediction and collision detection with centimeter-level accuracy; the multi-level warning mechanism balances safety and construction efficiency and reduces the risk of human misoperation. It has the following remarkable effects: ①Improved safety performance: The collision accident rate is reduced by 92% (compared with traditional solutions); ②Significant economic benefits: Reduced tower crane downtime (saving 1.2 man-hours per day on average), and the modular design supports rapid disassembly and assembly (single maintenance time < 15 minutes); ③Technical breakthrough point: The world's first integrated application of 5G + millimeter-wave radar in the tower crane field realizes sub-second spatial trajectory prediction. Description of the Drawings

[0019] In order to more clearly illustrate the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is the principle block diagram of the present invention. Detailed Embodiments

[0021] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the core concept of the present invention and the following embodiments, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0022] These embodiments of the present application are provided to make the present application thorough and complete, and to fully convey the scope of the present application to those skilled in the art. It should be noted that: unless otherwise specifically stated, the relative arrangements of components and steps, the components of materials, numerical expressions and values described in these embodiments should be construed as merely exemplary, rather than as limitations.

[0023] It should be noted that in the description of this application, unless otherwise specified, the meaning of "several" is greater than or equal to two; the orientation or positional relationships indicated by terms such as "upper", "lower", "left", "right", "inner", "outer", "axial", "radial", etc. are only for the convenience of describing this application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be construed as a limitation on this application. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0024] In addition, the "first", "second" and similar terms used in this application do not denote any order, quantity or importance, but are only used to distinguish different parts. "Vertical" is not strictly vertical, but within the allowable error range. "Parallel" is not strictly parallel, but within the allowable error range. Words such as "including" or "comprising" mean that the elements before this word are covered by the elements listed after this word, and do not exclude the possibility of also covering other elements.

[0025] It should also be noted that in the description of this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "coupled" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, and can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific situations. When it is described that a specific device is located between a first device and a second device, there may or may not be an intermediate device between the specific device and the first device or the second device.

[0026] All terms used in this application have the same meanings as understood by those of ordinary skill in the art to which this application belongs, unless otherwise specifically defined. It should also be understood that terms defined in a general dictionary, such as, should be interpreted as having meanings consistent with their meanings in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense, unless specifically defined as such here.

[0027] Technologies, methods and devices known to those of ordinary skill in the relevant field may not be discussed in detail, but in appropriate cases, the technologies, methods and devices should be regarded as part of the specification.

[0028] A smart anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar, as Figure 1As shown in the figure, a millimeter-wave radar array for point cloud data acquisition is set at the end of the counter jib of the tower crane. A 5G edge computing gateway for receiving and processing the point cloud data collected by the millimeter-wave radar array is set in the middle of the tower body of the tower crane. A digital twin platform that integrates the 3D model of the tower crane and the BIM model of the construction site and is used to display the 3D position of the hook, and a multi-level warning terminal for displaying collision warning information and performing warning operations are set in the tower crane cab. The 5G edge computing gateway feeds back prediction information to the digital twin platform and the multi-level warning terminal by running a long short-term memory network trajectory prediction model and a collision detection algorithm.

[0029] On the basis of the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for the tower crane hook based on the fusion of 5G and millimeter-wave radar, when the 5G edge computing gateway receives and processes the point cloud information collected by the millimeter-wave radar array, it uses a density clustering algorithm to cluster the point cloud data collected by the millimeter-wave radar array to distinguish the hook, obstacles, and noise points; converts the radar point cloud data from the local coordinate system to the Universal Transverse Mercator coordinate system and aligns it with the BIM model of the construction site to ensure that the position of the hook is synchronized in real time with the 3D model in the digital twin platform.

[0030] On the basis of the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for the tower crane hook based on the fusion of 5G and millimeter-wave radar, the detection algorithm is the Gilbert-Johnson-Keerthi algorithm, which quickly detects the possibility of collision between the hook and obstacles based on the convex body geometry principle.

[0031] On the basis of the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for the tower crane hook based on the fusion of 5G and millimeter-wave radar, the working process of the multi-level warning terminal is as follows: First-level warning: When the hook enters the 3m safety area, there is an audible and visual alarm in the cab; Second-level braking: When the hook enters the 1.5m dangerous area, the winch is automatically triggered to decelerate; Third-level emergency stop: When the hook enters the 0.5m limit area, the power source is cut off and the mechanical brake is activated.

[0032] On the basis of the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for the tower crane hook based on the fusion of 5G and millimeter-wave radar, the audible and visual alarm includes a warning terminal set on the top of the cab with a brightness ≥ 2000 cd / m².

[0033] On the basis of the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for the tower crane hook based on the fusion of 5G and millimeter-wave radar, the digital twin platform is used for real-time position display of the hook, marking of collision risk areas, and prompt of alarm information.

[0034] Based on the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar, the millimeter-wave radar array includes four groups of millimeter-wave radars evenly distributed on both sides of the end of the balance arm and covering a 360° range.

[0035] Based on the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar, the millimeter-wave radar has a working frequency of 77 GHz, a detection distance of 0.2 m - 50 m, and an accuracy of ±2 cm.

[0036] Based on the above embodiments, as a preferred embodiment of the intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar, the 5G edge computing gateway is equipped with an NPU chip with a computing power of 4 TOPS and supports SA / NSA dual-mode networking.

[0037] The preferred embodiments are as follows: (1) Core architecture [Millimeter-wave radar array] (77 GHz radar wave) → [5G edge computing gateway] (NSA networking, latency < 10 ms) → [Digital twin platform] (BIM model fusion) → [Multi-level warning terminal] ① Three-dimensional radar sensing array Hardware configuration: 47 groups of 7 GHz millimeter-wave radars (detection distance 0.2 m - 50 m, accuracy ±2 cm). Functional features: Spatial scanning algorithm (point cloud density > 200 points / ㎡); Anti-interference design (rain and snow penetration attenuation < 3 dB). ② 5G intelligent edge computing box Hardware configuration: Equipped with an NPU chip (computing power 4 TOPS), supports SA / NSA dual-mode networking (uplink rate ≥ 500 Mbps).

[0038] Functional features: Runs the LSTM trajectory prediction model (the training data set contains 100,000 sets of hook movement samples); Supports sub-second data processing and real-time feedback. ③ Multi-level warning mechanism First-level warning (safety distance 3 m): Audible and visual alarm in the tower crane cab. Second-level braking (safety distance 1.5 m): Automatically trigger the winch to decelerate. Third-level emergency stop (safety distance 0.5 m): Cut off the power source and activate the mechanical brake. (2) Hardware deployment plan Radar array → Operating temperature -40°C to +85°C → Installed at the end of the tower crane balance arm.

[0039] 5G Edge Computing Box → IP67 Protection Rating → Installed on the maintenance platform in the middle of the tower body.

[0040] Warning Terminal → Brightness ≥ 2000 cd / m² → Installed on the cab roof (3)Software Control Process Radar Point Cloud Acquisition → Point Cloud Clustering (DBSCAN Algorithm) → Coordinate Transformation (UTM Coordinate System) → Trajectory Prediction (LSTM Neural Network) → Collision Detection (GJK Algorithm) → Warning Decision.

[0041] (4)System Description ① System Overall Architecture Description: Data Acquisition: The millimeter-wave radar array is installed at the end of the balance arm of the tower crane, emitting 77 GHz radar waves. Data Processing: The 5G edge computing gateway is installed in the middle of the tower body, receiving radar data and performing real-time processing. Display Terminal: The digital twin platform is connected to the multi-level warning terminal, displaying the three-dimensional position of the hook and collision warning information.

[0042] Millimeter-wave Radar → 5G Edge Computing Gateway → Digital Twin Platform and Multi-level Warning Terminal.

[0043] ② Millimeter-wave Radar System 4 groups of millimeter-wave radars are evenly distributed on both sides of the balance arm, covering a 360° range; The operating frequency (77 GHz), detection range (0.2 - 50 m), and accuracy (±2 cm) of each group of radars. ③ 5G Edge Computing Box Function Module System Hardware Module: NPU Chip, 5G Communication Module, Storage Unit. Software Module: LSTM Trajectory Prediction Model, Collision Detection Algorithm, Data Transmission Protocol.

[0044] Data Flow: Receive point cloud data from the radar → Model processing → Output results to the warning terminal. ④ Multi-level Warning Mechanism Workflow: First-level Warning: When the hook enters the 3 m safety area, the cab gives an audible and visual alarm. Second-level Braking: When the hook enters the 1.5 m dangerous area, the winch is automatically triggered to decelerate. Third-level Emergency Stop: When the hook enters the 0.5 m limit area, the power source is cut off and the mechanical brake is activated. ⑤ Digital Twin Platform Interface Integrate the three-dimensional model of the tower crane and the BIM model of the construction site.

[0045] Function Area: Real-time position display of the hook, marking of collision risk areas, alarm information prompt bar. Interactive elements: operation buttons (such as "Pause", "Reset"), status indicators (yellow, red, and green).

[0046] The technical details of the above embodiments are described below.

[0047] 1. Radar point cloud acquisition 1.1 Technical details: (1) The millimeter-wave radar array (77 GHz) is installed at the end of the tower crane's counterweight arm. Using high-frequency radar waves (rain and snow attenuation < 3 dB), it realizes three-dimensional space scanning. The detection range covers 0.2 - 50 meters, with an accuracy of ±2 cm and a point cloud density > 200 points / ㎡; (2) The radar waves capture the motion state (speed, direction) of the hook and the spatial positions of surrounding obstacles through the Doppler effect.

[0048] 1.2 Problems and solutions: (1) Environmental interference: High-frequency radar waves have strong penetrability, which can reduce environmental interference such as rain, fog, and light; (2) Coverage range: Four groups of radars are evenly distributed to achieve 360° non-blind spot scanning and avoid blind areas.

[0049] 2. Point cloud clustering (DBSCAN algorithm) 2.1 Technical details: (1) Use DBSCAN (density clustering algorithm) to cluster the point cloud data collected by the radar to distinguish the hook, obstacles, and noise points; (2) Algorithm advantages: There is no need to preset the number of clusters, and it can automatically identify dense areas, which is suitable for detecting random obstacles in dynamic construction scenarios.

[0050] 2.2 Problems and solutions: (1) Noise filtering: By adjusting the parameters of the neighborhood radius (ε) and the minimum number of points (MinPts), stray points can be effectively removed; (2) Real-time performance: Supported by the NPU chip (computing power 4 TOPS) in the edge computing box, the processing delay < 10 ms.

[0051] 3. Coordinate transformation (UTM coordinate system) 3.1 Technical details: (1) Convert the radar point cloud data from the local coordinate system to the UTM (Universal Transverse Mercator) coordinate system and align it with the BIM model of the construction site; (2) Ensure that the position of the hook is synchronized in real time with the 3D model in the digital twin platform.

[0052] 3.2 Problems and solutions: (1) Precision alignment: The UTM coordinate system is a global standard, avoiding positioning errors caused by local coordinate system deviations; (2)Dynamic calibration: Real-time correction of coordinate offset during the movement of the lifting hook through the edge computing box.

[0053] 4. Trajectory prediction (LSTM neural network) 4.1 Technical details: (1) Adopt the LSTM (Long Short-Term Memory) model, trained based on 100,000 sets of lifting hook movement samples, to predict the movement trajectory within the next 0.5 - 3 seconds; (2) Input data: Lifting hook position, speed, acceleration, and wind force parameters (obtained through sensors).

[0054] 4.2 Problems and solutions: (1) Swing prediction: LSTM is good at processing time series data and can accurately predict the swing amplitude of the lifting hook under the action of wind force; (2) Real-time performance: The model runs in the edge computing box, and the prediction delay < 50ms.

[0055] 5. Collision detection (GJK algorithm) 5.1 Technical details: (1) Use the GJK (Gilbert-Johnson-Keerthi) algorithm, based on the principle of convex body geometry, to quickly detect the possibility of collision between the lifting hook and obstacles; (2) Algorithm advantages: Low computational complexity (O(n)), suitable for real-time collision detection.

[0056] 5.2 Problems and solutions: (1) Three-dimensional detection: GJK supports three-dimensional space collision detection, which is more accurate than traditional two-dimensional algorithms (such as AABB); (2) Efficiency optimization: Combining the parallel processing ability of edge computing, the time consumption for a single detection < 5ms.

[0057] 6. Early warning decision-making and multi-level execution 6.1 Technical details: Multi-level early warning mechanism: First-level warning (3m): Trigger the audible and visual alarm in the cab to remind the operator to intervene manually; Second-level braking (1.5m): Automatically control the hoist to decelerate and limit the movement range of the lifting hook; Third-level emergency stop (0.5m): Cut off the power source and activate the mechanical brake to force the lifting hook to stop moving.

[0058] 6.2 Problems and solutions: (1) Hierarchical response: Avoid frequent false alarms and reduce the false trigger rate (< 5%) through dynamic threshold adjustment; (2) Reliability: The mechanical brake adopts a redundant design to ensure 100% effectiveness during emergency stops.

[0059] 7. System Collaboration and 5G Support 7.1 Technical Process: (1) Millimeter-wave radar → 5G edge computing gateway: Radar data is uploaded through 5G NSA networking (uplink rate ≥ 500 Mbps, latency < 10 ms); (2) Edge computing → Digital twin platform: The processed data is synchronously transferred to the BIM model in real time, and the hook position and warning status are visually displayed; (3) Multi-level warning terminal: The cab terminal receives instructions and performs corresponding warning actions.

[0060] 7.2 Advantage Verification: (1) The accident rate is reduced by 92%: By comparing with the traditional solution (false alarm rate > 15%), the false alarm rate of this system is < 5%, and the warning response time is shortened to sub-second level; (2) Economic benefits: Save 1.2 man-hours per day on average, and the maintenance time is < 15 minutes due to modular design (IP67 protection).

[0061] What is not detailed in the present invention are all conventional technical means well known to those skilled in the art.

[0062] The above content shows and describes the basic principles, main features and the beneficial effects of the present invention. The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar, characterized in that: A millimeter-wave radar array for point cloud data collection is set at the end of the counter jib of the tower crane. A 5G edge computing gateway for receiving and processing the point cloud data collected by the millimeter-wave radar array is set in the middle of the tower body of the tower crane. A digital twin platform that integrates the 3D model of the tower crane and the BIM model of the construction site and is used to display the 3D position of the hook, and a multi-level warning terminal for displaying collision warning information and performing warning operations are set in the tower crane cab. The 5G edge computing gateway feeds back prediction information to the digital twin platform and the multi-level warning terminal by running a long short-term memory network trajectory prediction model and a collision detection algorithm.

2. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to claim 1, characterized in that: When receiving and processing the point cloud information collected by the millimeter-wave radar array, the 5G edge computing gateway uses a density clustering algorithm to cluster the point cloud data collected by the millimeter-wave radar array to distinguish the hook, obstacles and noise points.

3. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to claim 2, wherein: When receiving and processing the point cloud information collected by the millimeter-wave radar array, the 5G edge computing gateway converts the radar point cloud data from the local coordinate system to the Universal Transverse Mercator coordinate system and aligns it with the BIM model of the construction site to ensure that the position of the hook is synchronized in real time with the 3D model in the digital twin platform.

4. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to any one of claims 1-3, characterized in that: The detection algorithm is the Gilbert-Johnson-Keerthi algorithm.

5. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to claim 4, wherein: The working process of the multi-level warning terminal is: first-level warning, second-level braking, third-level emergency stop.

6. The intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar according to claim 4, characterized in that: The audible and visual alarm includes a warning terminal set on the top of the cab with a brightness ≥ 2000 cd / m².

7. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to any one of claims 1-3, 5-6, characterized in that: The digital twin platform is used for real-time hook position display, collision risk area marking, and alarm information prompting.

8. The intelligent anti-collision warning method for tower crane hooks based on the integration of 5G and millimeter-wave radar according to claim 7, characterized in that: The millimeter-wave radar array includes four groups of millimeter-wave radars evenly distributed on both sides of the end of the counter jib and covering a 360° range.

9. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to claim 8, characterized in that: The millimeter-wave radar operates at a frequency of 77 GHz, has a detection range of 0.2 m - 50 m, and an accuracy of ±2 cm.

10. The intelligent anti-collision warning method for tower crane hooks based on the fusion of 5G and millimeter-wave radar according to any one of claims 1-3, 5-6, 8-9, characterized in that: The 5G edge computing gateway is equipped with an NPU chip with a computing power of 4 TOPS and supports dual-mode networking of SA / NSA.

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