Monitoring and early warning system and method for adjacent business line construction of movable arm type tower crane

Abstract

The invention discloses a monitoring and early warning system and method for construction of an adjacent business line of a movable arm type tower crane. The system comprises a train approaching detection module, a movable arm type tower crane lifting hook positioning module, a movable arm type tower crane running state monitoring module, a virtual electronic fence, an edge calculation module and an alarm module. According to the invention, through utilization of technologies such as a radar monitoring technology, Beidou positioning navigation, a sensor technology, an electronic fence AI algorithm, data acquisition and storage, a database and the like, a safe solution for solving construction of the movable arm type tower crane in a scene of an adjacent business line in an intelligent mode is formed, and the system has great popularization and application values.

Description

Technical Field

[0001] The present invention relates to the technical field of tower crane construction monitoring, and particularly relates to a construction monitoring and early warning system and method for a luffing tower crane near an operating line. Background Art

[0002] If the construction project is in a narrow section between a high-speed railway line and an urban expressway, the safety risk of using a luffing tower crane near the operating line is high. During the hoisting operation, any part of the suspended load and the metal components of the tower crane is strictly prohibited from invading the railway safety clearance. Before the high-speed train passes, the luffing tower crane must stop operating at the specified time, and construction can continue only after the train has passed. It is strictly prohibited to affect the safety of railway operation.

[0003] Currently, for hoisting operations, safety management mainly relies on manual supervision and the mode of relying on people to transmit safety information. Generally, on-site safety protection personnel monitor by visual means and conduct safety protection through walkie-talkies, signal flags or signal lights. The safety protection for existing operating line construction mainly relies on human protection, lacking intelligent means of safety protection, which is likely to cause personal safety or train operation safety accidents. Therefore, it is necessary to summarize and adopt new technologies and methods to strengthen the safety management of construction around railways. Summary of the Invention

[0004] The present application provides a construction monitoring and early warning system and method for a luffing tower crane near an operating line to solve the problem in the prior art that it mainly relies on human protection, lacks intelligent means of safety protection, and is likely to cause personal safety or train operation safety accidents.

[0005] According to a first aspect, in one embodiment, a construction monitoring and early warning system for a luffing tower crane near an operating line is provided. The system includes a train approach detection module, a luffing tower crane hook positioning module, a luffing tower crane operating state monitoring module, a virtual electronic fence, an edge computing module, and an alarm module; The train approach detection module is used to monitor the approaching situation of trains in front of the operating line in real time through a radar detector; The luffing tower crane hook positioning module is used to obtain the real-time position information of the luffing tower crane hook through Beidou positioning monitoring; The luffing tower crane operating state monitoring module is used to monitor and obtain the operating attitude and environmental parameter data of the tower crane through a variety of parameter sensors; The virtual electronic fence is used to define the safety perimeter range on one side near the operating line, set graded warning areas according to different safety distances from the operating line, and accurately control the operating range of the tower crane; The edge computing module is used to perform real-time analysis and calculation of train approach radar monitoring data, Beidou positioning data of boom tower crane hook and boom sensor monitoring data, calculate the horizontal distance between the hook and the operating line in real time, and support the operation of AI trajectory prediction model, dynamically adjust the range of virtual electronic fence, trigger graded alarm and tower crane braking control; The alarm module is used to transmit emergency alarm information to the tower crane operator through sound and light signals.

[0006] Furthermore, the train approach detection module is specifically used for: During the transmission phase, the radar transmits high-frequency electromagnetic waves to the front of the track through the antenna, and the beam covers a certain horizontal preset angle range in front; during the reflection phase, the electromagnetic waves are reflected after encountering obstacles on the track, and the echo signal is captured by the radar receiving antenna; Signal processing and target detection: Use time difference for ranging, and calculate the target distance based on the time difference t between the transmitted wave and the received wave; combine distance, speed, and azimuth information, and use algorithms to eliminate false detection targets. When a threatening target that meets the preset conditions is detected, it can trigger an audible and visual alarm and link the braking system.

[0007] Furthermore, the radar detector is linked with the Beidou positioning module. When the signal-to-noise ratio of the radar signal is lower than a preset value, the control automatically switches to the Beidou positioning module to solve the tower crane position by continuously running the reference station system CORS.

[0008] Furthermore, the operating status monitoring module of the boom-type tower crane performs real-time monitoring through a variety of operating parameter sensors including the tower crane operating inclination angle and arm length.

[0009] Furthermore, the edge computing module adopts NVIDIA Jetson AGX Orin equipped with an AI acceleration module with 32 TOPS computing power, supports TensorRT acceleration, is suitable for real-time multi-sensor data fusion and deep learning reasoning, and can respond in real time at the millisecond level, and conduct real-time analysis of the millimeter-wave radar point cloud of the train approach radar monitoring, the centimeter-level Beidou positioning data of the boom tower crane hook, and the boom sensor.

[0010] Furthermore, the hierarchical alarm includes: Level 1 warning: The trigger condition is that the horizontal distance between the hook and the operating line is lower than the first preset distance, and the response action is that the yellow light flashes at a low frequency and the buzzer sounds intermittently; Level 2 warning: The trigger condition is that the horizontal distance between the hook and the operating line is lower than the second preset distance. The response action is that the orange light flashes at a high frequency, the buzzer sounds continuously, and the HMI displays the intrusion direction. Three - level locking: The triggering condition is that the horizontal distance between the hook and the operating line is lower than the third preset distance or the radar detects the approach of a train. The response actions are that the red light is always on, the buzzer sounds at the maximum volume, the power of the tower crane is cut off, and an alarm is pushed to the operating room of the luffing tower crane.

[0011] Furthermore, the system further includes a real - time monitoring and display module, which is responsible for visualizing radar monitoring data, Beidou positioning data, sensor data, equipment status, and alarm information.

[0012] Furthermore, the system further includes a power supply module, including a solar panel + battery, which is used to supply power to the radar detector.

[0013] Furthermore, the system further includes a network transmission module, which is used to upload the alarm log to the cloud management platform and generate a safety assessment report.

[0014] According to a second aspect, in one embodiment, a method for monitoring and warning of a luffing tower crane during construction near an operating line is provided. The method includes: Real - time monitoring of the approaching situation of trains in front of the operating line by a radar detector; Obtaining the real - time position information of the hook of the luffing tower crane through Beidou positioning monitoring; Obtaining the operation attitude and environmental parameter data of the tower crane through monitoring by a variety of parameter sensors; Generating a three - dimensional map of the construction site based on the BIM model, importing CAD drawings to delimit the safety limit, defining the safety perimeter range on one side near the operating line through an on - site virtual electronic fence, and setting different - level warning areas according to different safety distances from the operating line to accurately control the operation range of the tower crane; Real - time analysis and calculation of the radar monitoring data of the approaching train, the Beidou positioning data of the hook of the luffing tower crane, and the monitoring data of the luffing sensor by the edge - computing module, real - time calculation of the horizontal distance between the hook and the operating line, supporting the operation of the AI trajectory prediction model, dynamically adjusting the range of the virtual electronic fence, triggering hierarchical alarms and tower crane braking control; Transmitting emergency alarm information to the tower crane operator through sound and light signals.

[0015] This application provides a monitoring and warning system and method for a luffing tower crane during construction near an operating line, having the following beneficial effects: (1) High - precision safety protection: The fusion of Beidou positioning (accuracy of ±0.1m) and multi - sensors (length, inclination, radar) calculates the horizontal distance between the hook and the high - speed rail line in real time, dynamically adjusts the three - level electronic fence (5m / 10m / 15m), and ensures outside the operation limit.

[0016] (2) Intelligent warning mechanism: Based on AI algorithms (LSTM trajectory prediction) and radar collaborative monitoring, when the high-speed train is approaching 800m, a millisecond-level response (≤200ms) is triggered. Acoustic and light alarms are synchronized to force shutdown, and the efficiency is increased by 90% compared with manual warning.

[0017] (3) All-weather reliability: The modular power supply system (IP67 protection) is suitable for rain, snow, sand and dust environments. The low-temperature battery + electric heating design ensures stable operation at -40°C to 60°C, and the power-off endurance is ≥72 hours.

[0018] (4) Data closed-loop management: The 4G network uploads alarm logs and hoisting parameters to the cloud in real time, supports historical playback and risk assessment, and complies with the specification of "GB / T 3811-2020".

[0019] (5) Significant economic benefits: Reduce the configuration of manual protectors (saving about 300,000 yuan per year in costs), reduce the risks of railway construction, and have social benefits at the same time. Brief Description of the Drawings

[0020] Figure 1 It is a schematic diagram of the logical structure of a construction monitoring and warning system for a luffing tower crane near an operating railway line provided by an embodiment of the present invention; Figure 2 It is a top view of the construction site of a construction monitoring and warning system for a luffing tower crane near an operating railway line provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of the sensor layout in a construction monitoring and warning system for a luffing tower crane near an operating railway line provided by an embodiment of the present invention; Figure 4 is Figure 3 The partial enlarged schematic diagram in.

[0021] In the figure: 1 - High-speed railway line; 2 - Electronic fence (H = 5m); 3 - Electronic fence (H = 10m); 4 - Electronic fence (H = 15m); 5 - Radar detector; 6 - Edge computer; 7 - Acoustic and light alarm; 8 - Length sensor; 9 - Beidou positioning module; 10 - Inclinometer sensor. Detailed Embodiment

[0022] The present invention will be further described in detail below in conjunction with the accompanying drawings through specific embodiments. Similar elements in different embodiments are denoted by related similar element numbers. In the following embodiments, many detailed descriptions are provided to enable a better understanding of the present application. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification, which is to avoid overwhelming the core part of the present application with excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and the general technical knowledge in the art.

[0023] In addition, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can also be reordered or adjusted in a manner obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for clearly describing a certain embodiment and do not mean that they are necessary sequences, unless it is stated that a certain sequence must be followed.

[0024] Currently, for the safety protection of construction operations adjacent to operating railway lines commonly adopted in railways, one is manual lookout. There are on-site protectors and in-station liaison officers stationed in the dispatching room of the station to understand the train operation plan in real time. At 800 meters each for the up and down directions of the construction site, 2 remote protectors are arranged. When a train comes, it is notified to the site by walkie-talkie. This causes a large waste of human, financial, and material resources in railway construction and increases the cost of railway construction. For this reason, a control method for monitoring the operating actions of a luffing tower crane and accurately warning before the approach of a train, which is safe, accurate, and automated, can effectively understand the train passing state and the safety state of the lifting actions during actual hoisting operations. Relevant information is real-time prompted on the liquid crystal display screen in the cab, significantly improving the safety of tower crane construction adjacent to operating railway lines and enhancing the working efficiency of the joint control intercom for hoisting operations. This ensures the safety of the luffing tower crane hoisting operations during construction adjacent to operating railway lines.

[0025] The existing mode mainly relies on human monitoring and the transmission of safety information by people. Generally, on-site safety protection personnel monitor by visual means and conduct safety protection through walkie-talkies, signal flags, or signal lights. The human error is large, the time accuracy is poor, and the information transmission efficiency is low.

[0026] To solve the problem of the safety protection of the jib tower crane equipment during construction near the operating railway line in the existing technology, a monitoring and warning system for the jib tower crane during construction near the operating railway line provided by the first embodiment of the present invention forms a safety solution for the construction of the jib tower crane in the scenario near the operating railway line by using technologies such as radar monitoring technology, Beidou positioning and navigation, sensor technology, electronic fence AI algorithm, data acquisition and storage, and database, and has great popularization and application value.

[0027] Specifically, as Figure 1 shown, the system includes a train approach detection module, a jib tower crane hook positioning module, a jib tower crane operating state monitoring module, a virtual electronic fence, an edge computing module, and an alarm module.

[0028] The train approach detection module is used to monitor the approaching situation of trains in front of the operating railway line in real time through a radar detector.

[0029] The jib tower crane hook positioning module is used to obtain the real-time position information of the jib tower crane hook through Beidou positioning monitoring.

[0030] The jib tower crane operating state monitoring module is used to monitor and obtain the operating attitude and environmental parameter data of the tower crane through a variety of parameter sensors.

[0031] This embodiment proposes a triple collaborative warning of Beidou - radar - sensor: the radar detection module at the far end of the high - speed railway uses near - infrared laser (wavelength 905nm) to emit and receive to detect the real - time distance of the train, and the Beidou positioning parameters of the jib tower crane hook, combined with the multi - dimensional monitoring of the operating parameters of the tower crane at the operation site, to achieve triple safety guarantees.

[0032] The radar detection module uses near - infrared laser (wavelength 905nm) to emit and receive. When a train is detected, it sends a 485 signal to the main control board. After being processed by the main control board, the signal is transmitted to the alarm host through a 4G transmission module to generate an alarm signal. The alarm signal is received by the tower crane driver and relevant personnel in the first time, and the operation can be stopped immediately when the train passes, ensuring the safety of train operation.

[0033] This embodiment can realize the linkage between the radar detection module and the Beidou positioning module. When the signal - to - noise ratio of the radar signal < 10dB, it automatically switches to the Beidou positioning module, and the position of the tower crane is solved through the Continuously Operating Reference Station system (CORS), and the dynamic positioning error ≤ 0.1 meter.

[0034] The virtual electronic fence is used to define the safe perimeter range on one side near the operating railway line, set graded warning areas according to different safety distances from the operating railway line, and accurately control the operation range of the tower crane.

[0035] In this embodiment, a virtual electronic fence is hoisted adjacent to the operating railway line: Compared with the traditional method of visual observation and warning reminders by signal workers, CAD is used to calibrate the normal construction range, warning reminder construction range, and alarm warning construction range in the construction drawings, realizing visual operation of hoisting construction operations. The hoisting action is more accurate, the operation process is safer, and the out-of-bounds reminder and alarm management are intelligent. Three levels of warning areas are divided (blue / yellow / red, H = 15 / 10 / 5m), the distances between the tower crane hook, boom and the railway clearance are calculated in real time, and are visually displayed through the LCD screen, supporting dynamic coordinate adjustment to accurately control the operation range of the tower crane. In this embodiment, the dynamic division of the virtual electronic fence is automatically generated based on the railway safety clearance parameters (X / Y coordinates), supports manual calibration, and can optimize the warning threshold through AI algorithms, with a response time ≤ 0.5 seconds.

[0036] Real-time monitoring of hoisting actions: A 2-million-pixel camera transmits the hook image in real time, analyzes the hoisting path in combination with the BIM model to achieve anti-collision prediction, and the data is linked with the cloud platform, supporting historical playback and risk assessment. Realize real-time monitoring of key parameters such as the running height, inclination angle, and wind speed of the tower crane.

[0037] The edge computing module is used to perform real-time analysis and calculation on the monitoring data of the train approach radar, the Beidou positioning data of the hook of the luffing tower crane, and the monitoring data of the luffing sensor, calculate the horizontal distance between the hook and the operating railway line in real time, support the operation of the AI trajectory prediction model, dynamically adjust the range of the virtual electronic fence, and trigger hierarchical alarms and tower crane braking control.

[0038] The alarm module is used to transmit emergency alarm information to the tower crane operator through sound and light signals.

[0039] The intelligent warning control module of this embodiment: The main control module transmits data through the 4G network. When it detects that a train approaches or intrudes into the 800m warning area at the far end, it triggers a sound and light alarm and an alarm shutdown, and the alarm signal is synchronously uploaded to the cloud, supporting real-time monitoring by the remote management platform. Enable the tower crane driver to receive the high-speed train approach signal in the first time and make a stop operation action in the first time. Compared with the traditional method of setting up a remote protection officer to visually observe the approaching train and using a walkie-talkie for reminder, it can more accurately grasp the approaching situation of the train and shorten the reaction time.

[0040] Further, the system further includes a real-time monitoring and display module, and the real-time monitoring and display module is responsible for visualizing the radar monitoring data, Beidou positioning data, sensor data, equipment status and alarm information.

[0041] Further, the system further includes a power supply module, including a solar panel + a storage battery, for supplying power to the radar detector.

[0042] Specifically, a modular power supply and installation structure: The solar power supply system (180W solar panel + 60AH low-temperature lead-acid battery, equipped with an electric heating module) supports an environment of -40°C to 60°C. The independent unit uses a shock-proof and protective housing, which is fixed to the tower body through rubber seats and dampers to avoid electromagnetic interference and mechanical damage. It innovatively solves the problem of off-road cable layout along the railway.

[0043] Furthermore, the system also includes a network transmission module for uploading alarm logs to the cloud management platform via the 4G network to generate a security assessment report.

[0044] For the construction hoisting monitoring and early warning function of the luffing jib tower crane near the operating line, the tower crane is monitored in real time by sensors such as the installation inclination angle, height, slewing, and lifting weight of the tower crane. Different coordinates of the safety perimeter range on the side adjacent to the railway are selected and drawn through CAD drawings. For example, Figure 2 As shown, different distances H perpendicular to the high-speed railway line 1 are set to represent different warning areas. The electronic fence (H = 15m) 2 is blue representing the safe area, the electronic fence (H = 10m) 3 is yellow representing the early warning reminder, and the electronic fence (H = 5m) 4 is red representing the alarm and shutdown. Thus, during the operation, real-time monitoring and reminder of the operation behavior of the tower crane driver are achieved.

[0045] Through a safe, accurate, and automated control means for monitoring the operation actions of the luffing jib tower crane and precisely warning before the approach of the train, the passing state of the train and the safety state of the hoisting actions can be effectively understood during the actual hoisting operation. Relevant information is real-time prompted on the liquid crystal display screen in the cab, significantly improving the safety of the tower crane construction near the operating line and enhancing the working efficiency of the hoisting operation interlocking intercom. The safety of the luffing jib tower crane hoisting operation during the construction near the operating line is ensured.

[0046] This system mainly consists of a radar detector, a core edge computing device, a length sensor, an inclination sensor, a real-time monitoring display screen, a modular power supply component, an audible and visual alarm device, etc. The specific setting methods of each device are as follows: 1. Radar detector: As Figure 2 shown, the radar detector 5 is set 800m away from the distal end of the luffing jib tower crane, mainly used to detect obstacles or intrusion targets in front of the track in real time (taking the radar detector as a reference, the real-time detection direction is opposite to the front and back of the luffing jib tower crane). Its working principle is based on the emission and reception of electromagnetic waves. In the emission stage, the radar emits high-frequency electromagnetic waves towards the front of the track through the antenna. This detector uses the 24GHz microwave band, and the beam covers a certain 30° horizontal range in front. Target reflection, after the electromagnetic wave encounters an obstacle (such as a person or a foreign object) on the track, it is reflected, and the echo signal is captured by the radar receiving antenna.

[0047] Signal Processing and Target Detection: Use the time difference to measure distance. According to the time difference t between the transmitted wave and the received wave, calculate the target distance d = c * t / 2, where c is the speed of light. Combine distance, speed, and azimuth information, and use algorithms (such as Kalman filtering) to eliminate false detection targets (such as birds and vegetation shaking). When a threat target that meets the preset conditions (distance < 1 km, speed > 80 km / h) is detected, trigger an audible and visual alarm and link to the braking system.

[0048] Installation Key Points: The radar is usually installed on the train head or on the bracket beside the track, with a height of 1.5 - 2.5 meters from the rail surface. The tilt angle is adjusted according to the detection distance (such as a depression angle of 5° - 10°), and the coverage range needs to cover 200 - 2000 meters in front of the track to ensure an early warning time of ≥ 2 minutes. Avoid obstacles such as signal towers and tunnel entrances to ensure that the beam path is unobstructed. The shell needs to reach IP67 or above, dustproof and waterproof, and adapt to harsh environments such as rain, snow, and sand and dust. Use rubber shock pads or spring brackets to reduce the impact of train operation vibration on the radar accuracy.

[0049] Calibration and Monitoring: Use a standard reflector (such as a corner reflector) to verify the ranging accuracy during static calibration, and the error needs to be ≤ ±0.5 meters. During dynamic testing, simulate the train running at the maximum speed (such as 350 km / h) to test the detection response time of the radar to moving targets (≤ 150 ms). Multi-target Recognition: Verify the ability to track multiple targets simultaneously (such as ≥ 5 targets) to avoid missed detection or false alarms.

[0050] 2. Core Edge Computer: The installation position of the edge computer 6 is as Figure 3 、 Figure 4 shown. The edge computer uses NVIDIA Jetson AGX Orin with an AI acceleration module with 32 TOPS computing power, supports TensorRT acceleration, and is suitable for real-time multi-sensor data fusion and deep learning inference. It can respond in real-time at the millisecond level (≤ 200 ms), and perform real-time analysis on the millimeter-wave radar point cloud of the approaching high-speed train, the centimeter-level Beidou positioning data of the hook of the swinging jib tower crane, and the data of the jib sensors (tilt angle, length).

[0051] High-performance AI Computing Power: 32 TOPS computing power supports multi-sensor data fusion and real-time collision prediction, meeting the millisecond-level response requirements in the high-speed train scenario.

[0052] Low-latency Processing: The end-to-end processing delay ≤ 200 ms (from radar detecting the high-speed train to triggering the alarm), ensuring that the tower crane stops working in advance when the high-speed train passes.

[0053] Multi-interface Support: Rich I / O interfaces (CAN, Ethernet, GPIO) can be connected to the Beidou module, sensors, and radar to achieve full-link data integration.

[0054] Environmental adaptability: Wide temperature design from -40°C to +85°C, suitable for harsh outdoor working conditions of tower cranes.

[0055] The core roles of Jetson AGX Orin in this system are: Multi-source data fusion center, integrating Beidou positioning data (hook coordinates), boom sensor data (tilt angle, length), and radar data (high-speed rail position / speed), and calculating the horizontal distance between the hook and the high-speed rail line in real time; AI risk decision-making engine, running the LSTM trajectory prediction model, dynamically adjusting the electronic fence range (such as expanding the safety distance in rainy days), and triggering hierarchical alarms.

[0056] Instruction distribution controller, sending instructions to the PLC through Modbus TCP or CAN bus to control the audible and visual alarm and the tower crane braking system.

[0057] 1) Detailed working principle:

[0058] 2) Time synchronization: Adopt PTP (Precision Time Protocol) to align the timestamps of multi-source data, with a synchronization error ≤ 1ms.

[0059] The Beidou module provides 1PPS (Pulse Per Second) as the global time reference.

[0060] 3) Hook position calculation and safety distance calculation: The position of the Beidou positioning module 9 is set as Figure 3 、 Figure 4 as shown.

[0061] a. Local coordinate calculation: x = L ⋅ cosθ ⋅ cosϕ y = L ⋅ cosθ ⋅ sinϕ z = H base + L ⋅ sinθ The above formulas are the intermediate calculation steps before converting the hook position from the local coordinate system (with the tower crane base as the origin) to the global coordinate system, and are used for subsequent safety distance analysis.

[0062] Among them, L is the actual length of the boom (the straight-line distance from the tower crane slewing center to the hook), with the unit of m, and the value range is: 0 ~ maximum boom length; θ is the boom elevation angle (the angle between the boom and the horizontal plane), with the unit of °, and the value range is: 0° ~ 85° (typical working conditions); ϕ is the boom slewing angle (the horizontal rotation angle of the boom relative to the due north direction of the tower crane base), with the unit of °, and the value range is: ° ~ 360°; H baseis the elevation of the tower crane base (the vertical height relative to the railway track surface), with the unit of m, and the value range is determined according to the actual terrain.

[0063] b. Global coordinate transformation: Convert the local coordinates (x, y, z) to the WGS84 geodetic coordinate system, and then project it to the local coordinate system of the high-speed railway line.

[0064] c. Horizontal distance calculation: Calculate the minimum horizontal distance between the hook and the high-speed railway safety limit line. The formula is as follows: D horizontal = min ( ( X hook − X i ) 2 + ( Y hook − Y i ) 2 ) (i = 1, 2,..., n) Calculate the minimum horizontal distance between the hook and the center line of the high-speed railway track through the above formula, which is used to determine whether the hook invades the electronic fence.

[0065] Among them, X hook , Y hook are the plane coordinates of the hook in the high-speed railway line coordinate system (solved by Beidou positioning), with the unit of m, and the data is from the Beidou positioning module; X i , Y i are the discrete point coordinates of the center line of the high-speed railway track (extracted from the CAD drawing or BIM model), with the unit of m, and the data is from the construction drawing / railway design specification; n is the number of discrete points of the center line of the track, which is determined according to the track length.

[0066] 4) AI dynamic decision-making and alarm trigger: Electronic fence dynamic adjustment formula: S safe = V train × T brake + S buffer Expansion formula (weather compensation): S safe_adjusted = S safe (1 + α) Weather compensation: Identify rain and snow weather through radar echo intensity, and expand the safety distance by 20%.

[0067] Among them, V train is the real-time speed of the high-speed railway (detected by radar), with the unit of km / h, and the value range is: 80 ~ 350 (typical value of high-speed railway); T brake is the braking response time of the tower crane (the time from alarm trigger to complete shutdown), with the unit of seconds, and the value range is: 0.2 ~ 0.5 (system set value); S bufferis the safety buffer distance (redundant distance to prevent braking errors), in meters, with a value range of 5 to 10 (adjusted according to working conditions); α is the weather compensation coefficient (expanding the safety range in rainy and snowy weather), in meters, with a value of 0.2 (default value).

[0068] The above formula is used to dynamically adjust the range of the electronic fence and optimize the safety distance in real time according to the high-speed rail speed and weather conditions: Basic safety distance S safe It can ensure that the hook does not intrude into the limit during the high-speed rail braking time; extend the safety distance S safe_adjusted Used to add 20% safety margin in rainy and snowy weather.

[0069] 5) Hierarchical alarm logic:

[0070] Control logic: Write by inputting CAD coordinates, use CAD to calibrate the normal construction range, warning construction range, and alarm construction range in the construction drawing to realize a multi-level warning mechanism (set different distances H perpendicular to the high-speed rail line to represent different warning areas, H=15m is blue for safe areas, H=10 is yellow for warning reminders, and H=5m is red for alarm shutdown). Upload data to the cloud platform through the 4G / LoRa module, store it for a long time (≥2 years), generate compliance reports (daily and weekly reports), and record event data for accident tracing.

[0071] NVIDIA Jetson AGX Orin, with its high-performance AI computing power, multi-sensor fusion capabilities and industrial-grade reliability, has become the core edge computing unit of this system. Its roles include data fusion, real-time decision-making and command distribution to ensure safe distance control between the hook and the high-speed rail line. Through strict installation quality control (heat dissipation, protection, and earthquake resistance) and software optimization (model quantization and protocol adaptation), it can meet the requirements of ≤10cm positioning accuracy and ≤200ms response delay in high-speed rail scenarios, significantly reduce the risk of intrusion, and comply with GB / T 3811-2020 Tower Crane Safety Monitoring System and railway construction safety regulations.

[0072] 3. Length sensor: The length sensor 8 is set at a position such as Figure 3 , Figure 4 As shown, the working principle is to drive the internal encoder to rotate by extending and retracting the wire, and output a pulse signal proportional to the wire length (AB phase orthogonal encoding).

[0073] In the wire encoder, the cable is used to transmit displacement, and the spring retraction mechanism keeps the cable tension constant to ensure automatic cable retraction. The rotary encoder converts the linear displacement of the cable into rotational motion, and then outputs the electrical signal through the photoelectric, magnetoelectric or capacitive encoder. The guide wheel reduces cable wear and ensures linear motion.

[0074] Formula: L = N ⋅ ΔL Where N is the number of pulses and ΔL is the length corresponding to each pulse.

[0075] Installation quality control: Installed at the end of the inner guide rail of the fixed section of the boom to ensure that the cable is parallel to the telescopic arm. The pulling direction of the cable must be strictly parallel to the moving direction of the measurement target, with a deviation angle ≤ 1°, to avoid wear or measurement errors caused by lateral forces. Installed using a bracket and fixed with stainless steel bolts (grade 8.8), with a pre-tightening torque of 20 - 25 N·m, and an anti-loosening washer is added. The flatness of the installation base surface ≤ 0.1 mm to avoid deformation of the sensor housing. Check the cable wear (≤ 3 broken wires on the surface) and the rotational flexibility of the guide wheel monthly.

[0076] 4. Tilt sensor: The installation position of the tilt sensor 10 is as Figure 3 , Figure 4 shown.

[0077] Adopt a MEMS tilt sensor: Detect the displacement of the mass block under the action of gravity through a microelectromechanical system, and output a voltage signal proportional to the tilt angle, with an accuracy of up to ±0.05°. The MEMS tilt sensor has low cost, small volume (< 50 g), and fast response (≤ 10 ms).

[0078] 5. Real-time monitoring display screen: The real-time monitoring display screen (HMI / SCADA interface) is the core interactive device of the monitoring and warning system for the construction of the boom tower crane near the operating railway line, responsible for visualizing the sensor data, radar monitoring data, equipment status, and alarm information.

[0079] Sensor input: At a short horizontal distance from the high-speed rail, signals such as the tilt angle, height, slewing angle, and load of the boom tower crane are collected through the AI module of NVIDIA Jetson AGX Orin.

[0080] Transmission protocol: The boom tower crane uses the industrial bus Modbus TCP / IP, supporting high-speed transmission (≤ 10 ms delay), and the high-speed rail approach radar uses a wireless communication 4G module for remote radar monitoring.

[0081] 6. Modular power supply component: This power supply component consists of a solar panel + a battery. For effective charging, the working voltage of the solar panel needs to be slightly higher than the battery voltage. The solar panel is 200W, and the battery is 24V 100Ah. This combination can support 3 - 5 days of continuous operation without sunlight. The solar panel converts light energy into direct current electrical energy (maximum output voltage is about 18 - 22V, and current is about 8 - 10A). The charging voltage / current of the solar panel to the battery is adjusted by a solar controller to prevent overcharging or over-discharging. A 100Ah lead-acid battery (24V) is used to store electrical energy and provide a stable power supply for the radar detector. In sunny conditions, the power generated by the solar panel is given priority to power the radar detector, and the remaining power is used to charge the battery through the controller. The controller automatically switches the charging stage (constant current → constant voltage → floating charge) according to the battery state (SOC). In cloudy or night conditions, the solar panel stops generating electricity, and the battery supplies power alone. The controller cuts off the reverse current (to prevent the battery from discharging in reverse). 7. Acoustic and optical alarm: The installation position of the acoustic and optical alarm 7 is as Figure 3 、 Figure 4 shown. The acoustic and optical alarm is the terminal execution device of the train approach warning system. Its core function is to transmit emergency alarm information to the tower crane operator through sound and light signals.

[0082] Signal reception and triggering mechanism: NVIDIA Jetson AGX Orin sends a trigger command to the alarm through the communication protocol Modbus TCP. The signal type uses a digital input signal: 24V DC high level (alarm start) / low level (alarm stop). The message command: send a specific 0x01 command code through the RS485 / CAN bus to start the alarm.

[0083] Alarm module: The sound generation unit uses an electromagnetic buzzer to generate a high-frequency alarm sound (frequency 2Hz, sound pressure ≥90dB@1m), and a pre-recorded voice prompt ("Train approaching, please avoid immediately!"). The optical alarm module uses an LED array light source type, high-brightness RGB LEDs (light intensity ≥200cd), and uses a rotating strobe form driven by a motor with alternating red and blue flashes (frequency 1 - 2Hz) to enhance the warning range. The optical signal and the sound signal are triggered synchronously and can be switched to constant on / constant ringing in the emergency mode.

[0084] Corresponding to the above-disclosed monitoring and warning system for the construction of a luffing tower crane adjacent to an operating line, an embodiment of the present invention also discloses a method for monitoring and warning the construction of a luffing tower crane adjacent to an operating line, which specifically includes: S1, real-time monitoring of the approaching situation of trains in front of the operating line through a radar detector; S2, obtaining the real-time position information of the hook of the luffing tower crane through Beidou positioning monitoring; S3. Monitor and obtain the operating attitude and environmental parameter data of the tower crane through various parameter sensors; S4. Generate a three-dimensional map of the construction site based on the BIM model, import the CAD drawings to delimit the safety limit, define the safety perimeter range on one side of the line near the operating line through the on-site virtual electronic fence, and set different levels of warning areas according to different safety distances from the operating line to accurately control the operating range of the tower crane; S5. Real-time analyze and calculate the train approach radar monitoring data, the Beidou positioning data of the hook of the luffing tower crane, and the luffing sensor monitoring data through the edge computing module, calculate the horizontal distance between the hook and the operating line in real time, support the operation of the AI trajectory prediction model, dynamically adjust the range of the virtual electronic fence, trigger hierarchical alarms and tower crane braking controls; S6. Transmit emergency alarm information to the tower crane operator through audible and visual signals.

[0085] The above uses specific examples to elaborate on the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the technical field to which the present invention pertains, based on the idea of the present invention, several simple deductions, deformations or substitutions can also be made.

Claims

1. A monitoring and early warning system for the construction of a luffing tower crane near an operating railway line, characterized in that, The system includes a train approaching detection module, a hook positioning module for a luffing tower crane, an operating status monitoring module for a luffing tower crane, a virtual electronic fence, an edge computing module, and an alarm module; The train approaching detection module is used to monitor the approaching situation of trains in front of the operating line in real time through a radar detector; The hook positioning module for a luffing tower crane is used to obtain the real-time position information of the hook of the luffing tower crane through Beidou positioning monitoring; The operating status monitoring module for a luffing tower crane is used to monitor and obtain the operating attitude and environmental parameter data of the tower crane through a variety of parameter sensors; The virtual electronic fence is used to define the safe perimeter range on one side adjacent to the operating line, set graded warning areas according to different safety distances from the operating line, and accurately control the operating range of the tower crane; The edge computing module is used to perform real-time analysis and calculation on the train approaching radar monitoring data, the Beidou positioning data of the hook of the luffing tower crane, and the monitoring data of the boom sensor, calculate the horizontal distance between the hook and the operating line in real time, support the operation of the AI trajectory prediction model, dynamically adjust the range of the virtual electronic fence, and trigger graded alarms and tower crane braking control; The alarm module is used to transmit emergency alarm information to the tower crane operator through sound and light signals.

2. The monitoring and early warning system for the construction of a luffing tower crane adjacent to an operating railway line according to claim 1, wherein Specifically, the train approaching detection module is used for: In the emission stage, the radar emits high-frequency electromagnetic waves forward along the track through the antenna, and the beam covers a certain preset horizontal angle range in front; in the reflection stage, the electromagnetic wave is reflected after encountering an obstacle on the track, and the echo signal is captured by the radar receiving antenna; Signal processing and target detection: Use the time difference for ranging, calculate the target distance according to the time difference t between the transmitted wave and the received wave; combine distance, speed, and azimuth information, and eliminate false detection targets through algorithms. When a threat target meeting the preset conditions is detected, it can trigger a sound and light alarm and link the braking system.

3. The monitoring and early warning system for the construction of the jib tower crane adjacent to the operating line according to claim 1, wherein The radar detector is linked with the Beidou positioning module. When the signal-to-noise ratio of the radar signal is lower than the preset value, it controls to automatically switch to the Beidou positioning module, and calculates the position of the tower crane through the continuous operating reference station system CORS.

4. A monitoring and early warning system for the construction of a jib tower crane near an operating line as described in claim 1, characterized in that, The operating status monitoring module for a luffing tower crane conducts real-time monitoring through a variety of operating parameter sensors including the operating inclination angle and boom length of the tower crane.

5. The monitoring and early warning system for the construction of a luffing tower crane near an operating railway line according to claim 1, characterized in that, The edge computing module uses NVIDIA Jetson AGX Orin with an AI acceleration module with a computing power of 32 TOPS, supports TensorRT acceleration, is suitable for real-time multi-sensor data fusion and deep learning inference, can respond in milliseconds in real time, and conducts real-time analysis of the millimeter-wave radar point cloud of the train approaching radar monitoring, the centimeter-level Beidou positioning data of the hook of the luffing tower crane, and the real-time data of the boom sensor.

6. The monitoring and early warning system for the construction of the jib tower crane adjacent to the operating line according to claim 1, characterized in that, The graded alarms include: First-level early warning: The triggering condition is that the horizontal distance between the hook and the operating line is lower than the first preset distance, and the response action is that the yellow light flashes at a low frequency and the buzzer sounds intermittently; Second-level warning: The triggering condition is that the horizontal distance between the hook and the operating line is lower than the second preset distance, and the response action is that the orange light flashes at a high frequency, the buzzer sounds continuously, and the HMI displays the intrusion direction; Three - level locking: The trigger condition is that the horizontal distance between the hook and the operating line is lower than the third preset distance or the radar detects the approach of a train. The response actions are that the red light is always on, the buzzer sounds at the maximum volume, the power of the tower crane is cut off, and an alarm is pushed to the operating room of the luffing tower crane.

7. The monitoring and early warning system for the construction of the jib tower crane adjacent to the operating line according to claim 1, wherein, The system further includes a real - time monitoring and display module, which is responsible for visualizing radar monitoring data, Beidou positioning data, sensor data, equipment status, and alarm information.

8. The monitoring and early warning system for the construction of the jib tower crane adjacent to the operating line as described in claim 1, wherein, The system further includes a power supply module, including a solar panel + battery, which is used to supply power to the radar detector.

9. The monitoring and early warning system for the construction of the luffing tower crane adjacent to the operating line according to claim 1, wherein, The system further includes a network transmission module, which is used to upload the alarm log to the cloud management platform and generate a safety assessment report.

10. A construction monitoring and early warning method for a luffing tower crane near an operating railway line, characterized in that, The method includes: Real - time monitoring of the approaching situation of trains in front of the operating line through a radar detector; Obtaining the real - time position information of the hook of the luffing tower crane through Beidou positioning monitoring; Obtaining the operating attitude and environmental parameter data of the tower crane through monitoring by a variety of parameter sensors; Generating a three - dimensional map of the construction site based on the BIM model, importing CAD drawings to delimit the safety limit, defining the safety perimeter range on the side close to the operating line through a virtual electronic fence, setting different - level warning areas according to different safety distances from the operating line, and precisely controlling the operating range of the tower crane; Real - time analysis and calculation of the radar monitoring data of the approaching train, the Beidou positioning data of the hook of the luffing tower crane, and the monitoring data of the boom sensor through the edge - computing module, real - time calculating the horizontal distance between the hook and the operating line, supporting the operation of the AI trajectory prediction model, dynamically adjusting the range of the virtual electronic fence, triggering hierarchical alarms and tower crane braking control; Transmitting emergency alarm information to the tower crane operator through sound and light signals.

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