A hoisting device for preventing a steel truss girder from swinging and a method thereof

Abstract

The present application relates to the technical field of hoisting device, and discloses a hoisting device for preventing steel truss from swinging and a method thereof, which comprises: a real-time environment sensing module for collecting wind speed, hoisting piece swing angle and angular velocity, and distance between hoisting piece and obstacle as real-time collection data; a dynamic risk prediction module for determining predicted hoisting piece swing angle in a first preset future period based on real-time collection data and swing angle prediction model, and determining current collision risk index; a damping control decision module for calculating real-time braking force based on real-time collection data when predicted hoisting piece swing angle is greater than a preset angle threshold or current collision risk index is greater than a preset index threshold, triggering braking instruction of the braking system of the hoisting device based on real-time braking force, and obtaining anti-swing control result; timely and effective measures are taken to prevent steel truss from excessive swinging, and collision accidents are avoided, which greatly improves the reliability and safety of the hoisting device in complex environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hoisting devices, in particular to a hoisting device for preventing steel truss sway and a method thereof. BACKGROUND

[0002] In bridge construction projects, the hoisting operation of steel trusses is a key link. For example, the Huhe Super Bridge contains complex structures such as 1-64m steel trusses, and the bridge body spans the Chao Hu River, which has many difficulties in construction, such as high-altitude work, limited space, high requirements for construction technology and precision, etc. During the hoisting of the steel truss, it is crucial to ensure the stability and safety of the hoisting. During the hoisting of the steel truss, due to its own structural characteristics and environmental factors, it is prone to sway. Once the steel truss sway is out of control, not only the hoisting equipment may be damaged, but also the safety of surrounding construction personnel may be seriously threatened, and even major safety accidents may occur, affecting the progress and quality of the project. Therefore, it is of great significance to develop an effective hoisting device and method for preventing steel truss sway to ensure the smooth progress of bridge construction projects. With the continuous development of bridge construction technology, the safety and stability requirements of the hoisting process are increasingly improved. Advanced hoisting technology for preventing steel truss sway not only can improve construction efficiency and reduce safety hazards, but also can promote the bridge construction industry to develop in a safer and more efficient direction, and has broad application prospects.

[0003] However, the existing steel truss hoisting technology lacks effective analysis and utilization of real-time collected data, and cannot determine the predicted hoisting angle in the future period based on these data, nor can it accurately determine the current collision risk index, which makes it difficult to predict potential risks in the hoisting process in advance, and thus cannot timely trigger the braking instruction of the hoisting device braking system, thereby making it difficult to effectively prevent steel truss sway and ensure hoisting safety.

[0004] Therefore, the present application proposes a hoisting device and method for preventing steel truss sway. SUMMARY

[0005] The present application provides a kind of hoisting device and method for preventing steel truss swing, the device real-time acquisition wind speed, hoisting piece swing angle and angular velocity and the distance such as hoisting piece and obstacle, provide accurate and comprehensive information basis for subsequent risk prediction and control, can timely reflect the change of environment and hoisting piece state in hoisting process.According to real-time acquisition data and swing angle prediction model, determine the predicted hoisting piece swing angle in the first preset future period and obtain the current collision risk index, carry out quantitative evaluation in advance to potential risk, so that operator can know in advance the swing and collision risk that can appear in hoisting process.In the prediction hoisting piece swing angle is greater than preset angle threshold or current collision risk index is greater than preset index threshold, real-time braking force is calculated based on real-time acquisition data quickly, and the brake command of hoisting device braking system is triggered, timely and effectively take measures to prevent steel truss from swinging too much, avoid collision accident, ensure that hoisting operation is safe and stable, greatly improve the reliability and safety of hoisting device operation in complex environment.

[0006] The present application provides a kind of hoisting device for preventing steel truss swing, comprising:

[0007] Real-time environment perception module, for real-time acquisition wind speed, hoisting piece swing angle and angular velocity and the distance as real-time acquisition data;

[0008] Dynamic risk prediction module, for determining the predicted hoisting piece swing angle in the first preset future period based on real-time acquisition data and swing angle prediction model, and determining current collision risk index;

[0009] Damping control decision module, for when predicted hoisting piece swing angle is greater than preset angle threshold or current collision risk index is greater than preset index threshold, then based on real-time acquisition data calculate real-time braking force, and based on real-time braking force trigger the brake command of hoisting device braking system, obtain swing prevention control result.

[0010] Preferably, the construction method of swing angle prediction model comprises:

[0011] Based on finite element simulation to establish hoisting system dynamics equation;

[0012] Couple critical wind speed data measured in engineering field with hoisting system dynamics equation, generate safety boundary function;

[0013] Safety boundary function is used as constraint condition, and long short-term memory network and a large number of hoisting system parameter perception records are trained to obtain swing angle prediction model;

[0014] Wherein, each hoisting system parameter perception record contains hoisting piece swing angle and angular velocity, wind speed, wind direction and actual swing angle in next period detected at a single moment.

[0015] Preferably, the method for determining the current collision risk index by the dynamic risk prediction module comprises:

[0016] determining the current sensitivity coefficient based on the real-time collected data;

[0017] determining the current safety distance threshold of the hoist and the obstacle based on the real-time collected data;

[0018] determining the space situation factor of the space where the hoist and the obstacle are located;

[0019] determining the current collision risk index based on the current sensitivity coefficient, the distance between the hoist and the obstacle detected in real time, the current safety distance threshold of the hoist and the obstacle, the continuous over-threshold time of the hoist swing angle, the hoist swing angle and the space situation factor:

[0020]

[0021] wherein, R coll is the current collision risk index, exp is an exponential function with a natural constant and the value of the natural constant is 2.72, k is the current sensitivity coefficient, Δd is the distance between the hoist and the obstacle detected in real time, d safe is the current safety distance threshold of the hoist and the obstacle, t danger is the continuous over-threshold time of the hoist swing angle, T ref is the reference duration, γ is the space situation factor, θ is the hoist swing angle, and θ0 is the reference hoist swing angle.

[0022] Preferably, the method for determining the current sensitivity coefficient based on the real-time collected data comprises:

[0023] determining the real-time wind speed and the distance between the hoist and the obstacle based on the real-time collected data;

[0024] taking 1 as a basic term, taking the hyperbolic tangent value of the ratio of the real-time wind speed to the reference wind speed multiplied by a first preset multiple value as a wind speed correction term, and taking the negative value of the second preset multiple value of the sign function value of the difference between the distance between the hoist and the obstacle detected in real time and the current safety distance threshold of the hoist and the obstacle and the ratio of the current safety distance threshold of the hoist and the obstacle as a distance correction term;

[0025] taking the sum of the basic term, the wind speed correction term and the distance correction term as a dynamic adjustment factor of the initial sensitivity coefficient;

[0026] taking the product of the initial sensitivity coefficient and the corresponding dynamic adjustment factor as the current sensitivity coefficient.

[0027] Preferably, the method for determining the current safety distance threshold based on the real-time collected data comprises:

[0028] The sum of the product of the length of the sling of the hoisting system and the sine value of the maximum allowed swing angle and the fixed safety margin is taken as the static safety distance;

[0029] The sum of the third preset multiple value of the hyperbolic secant function based on the ratio of the real-time wind speed in the real-time collected data and the preset wind speed division threshold value and 1 is taken as the dynamic adjustment factor of the static safety distance;

[0030] The dynamic safety distance is determined based on the static safety distance and the corresponding dynamic adjustment factor;

[0031] The product of the dynamic safety distance and the weight factor determined based on the type of the obstacle is taken as the current safety distance threshold value.

[0032] Preferably, the method for determining the dynamic safety distance based on the static safety distance and the corresponding dynamic adjustment factor comprises:

[0033] The swing angle trajectory in the preset second future period is predicted based on the swing angle and the angular velocity of the hoisted object in the real-time collected data, and the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle is calculated;

[0034] When the angular velocity of the swing angle of the hoisted object in the real-time collected data exceeds the preset angular velocity threshold value, the dynamic buffer distance is determined based on the angular velocity of the swing angle of the hoisted object, the product of the static safety distance and the corresponding dynamic adjustment factor is taken as the first dynamic safety distance, the sum of the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle and the dynamic buffer distance is taken as the second dynamic safety distance, and the maximum value between the first dynamic safety distance and the second dynamic safety distance is taken as the dynamic safety distance;

[0035] When the angular velocity of the swing angle of the hoisted object in the real-time collected data does not exceed the preset angular velocity threshold value, the product of the static safety distance and the corresponding dynamic adjustment factor is taken as the first dynamic safety distance, the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle is taken as the second dynamic safety distance, and the maximum value between the first dynamic safety distance and the second dynamic safety distance is taken as the dynamic safety distance.

[0036] Preferably, the method for determining the space situation factor of the space where the hoisted object and the obstacle are located comprises:

[0037] The hoisted object movement airspace volume is determined based on the length of the sling and the volume of the hoisted object itself;

[0038] The obstacle minimum bounding box is extracted through the convex hull algorithm and the obstacle three-dimensional point cloud model, and the obstacle occupied space volume is determined based on the obstacle minimum bounding box;

[0039] The ratio of the volume of the movement space of the hoisting piece to the volume of the space occupied by the obstacle is taken as the space openness index of the space where the hoisting piece and the obstacle are located.

[0040] Based on the number of points in the three-dimensional point cloud model of the obstacle and the volume of the space occupied by the obstacle, the obstacle density index of the space where the hoisting piece and the obstacle are located is determined.

[0041] The intersection rate of the movement trajectory of the space where the hoisting piece and the obstacle are located is determined.

[0042] The space situation factor is determined based on the space openness index, the obstacle density index and the intersection rate of the movement trajectory.

[0043] Preferably, the method for determining the intersection rate of the movement trajectory of the space where the hoisting piece and the obstacle are located comprises:

[0044] The volume of the space swept by the swing angle trajectory in the preset third future period is calculated based on the swing angle prediction model, and the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the minimum bounding box of the obstacle is calculated.

[0045] The ratio of the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the minimum bounding box of the obstacle to the volume of the space swept by the swing angle trajectory in the preset third future period is taken as the intersection rate of the movement trajectory of the space where the hoisting piece and the obstacle are located.

[0046] Preferably, the method for determining the space situation factor based on the space openness index, the obstacle density index and the intersection rate of the movement trajectory comprises:

[0047] The obstacle density is de-dimensioned.

[0048] The space openness index, the de-dimensioned obstacle density index and the intersection rate of the movement trajectory are assigned weights, and the space openness index, the de-dimensioned obstacle density index and the intersection rate of the movement trajectory are added according to the assigned weights to obtain the space situation factor.

[0049] The present application provides a hoisting method for preventing steel truss beam from swinging, comprising:

[0050] Real-time acquisition of wind speed, hoisting piece swing angle and angular velocity and distance between the hoisting piece and the obstacle as real-time acquisition data;

[0051] Based on the real-time acquisition data and the swing angle prediction model, the predicted hoisting piece swing angle in the first preset future period is determined, and the current collision risk index is determined.

[0052] When the predicted swing angle of the hoisting piece is greater than a preset angle threshold or the current collision risk index is greater than a preset index threshold, a real-time braking force is calculated based on the real-time acquisition data, and a braking instruction of the braking system of the hoisting device is triggered based on the real-time braking force, so that a swing prevention control result is obtained.

[0053] The present application has the following beneficial effects compared with the prior art: key data such as wind speed, hoisting piece swing angle and angular velocity, and distance between the hoisting piece and the obstacle are acquired in real time, which provides an accurate and comprehensive information basis for subsequent risk prediction and control, and can timely reflect the changes in the environment and the hoisting piece state during hoisting. According to the real-time acquisition data and the swing angle prediction model, the predicted swing angle of the hoisting piece in a first preset future period is determined, and the current collision risk index is obtained, so that the potential risk can be quantitatively evaluated in advance, and the operator can know in advance the swing and collision risks that may occur during hoisting. When the predicted swing angle of the hoisting piece is greater than a preset angle threshold or the current collision risk index is greater than a preset index threshold, a real-time braking force is calculated based on the real-time acquisition data, and a braking instruction of the braking system of the hoisting device is triggered based on the real-time braking force, so that a swing prevention control result is obtained. The measures are taken in time to prevent the steel truss from swinging excessively and avoid collision accidents, so that the hoisting operation is safe and stable, and the reliability and safety of the hoisting device in complex environments are greatly improved.

[0054] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and achieved by the structure particularly pointed out in the application.

[0055] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0056] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation of the present application. In the drawings:

[0057] Figure 1 The figure is a schematic diagram of the hoisting device for preventing the steel truss from swinging in the embodiment of the present application;

[0058] Figure 2 The figure is a schematic diagram of the construction method of the swing angle prediction model in the embodiment of the present application;

[0059] Figure 3 The figure is a schematic diagram of the method for determining the current sensitivity coefficient in the embodiment of the present application;

[0060] Figure 4 The figure is a schematic diagram of the method for determining the current safety distance threshold in the embodiment of the present application;

[0061] Figure 5 A schematic diagram of a method for determining a spatial situation factor of a hoist and an obstacle in a space in an embodiment of the present application. DETAILED DESCRIPTION

[0062] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are merely intended to illustrate and explain the present application, and are not intended to limit the present application.

[0063] As shown in the drawings, Figure 1 The present application provides an embodiment of a hoisting device for preventing steel truss sway, comprising:

[0064] A real-time environment perception module is configured to collect wind speed, hoist swing angle and angular velocity, and distance between the hoist and the obstacle as real-time collection data in real time.

[0065] A dynamic risk prediction module is configured to determine a predicted hoist swing angle in a first preset future period based on the real-time collection data and a swing angle prediction model, and determine a current collision risk index.

[0066] A damping control decision module is configured to calculate a real-time braking force based on the real-time collection data when the predicted hoist swing angle is greater than a preset angle threshold or the current collision risk index is greater than a preset index threshold, and trigger a braking instruction of a braking system of the hoisting device based on the real-time braking force to obtain a sway prevention control result.

[0067] In this embodiment, wind speed refers to the real-time wind speed of the surrounding environment during the hoisting of the steel truss.

[0068] In this embodiment, hoist swing angle and angular velocity refer to the angle of the steel truss (hoist) deviating from its initial vertical position during hoisting, and the rate of change of the swing angle with time. They reflect the motion state of the hoist, which is collected in real time by the real-time environment perception module.

[0069] In this embodiment, the distance between the hoist and the obstacle refers to the real-time distance between the hoisted steel truss (hoist) and the surrounding obstacles that may cause collision, which is collected by the real-time environment perception module.

[0070] In this embodiment, the swing angle prediction model is obtained by coupling the critical wind speed data measured on site with the safety boundary function generated by establishing the hoisting system dynamics equation based on finite element simulation, and then training a large number of hoisting system parameter perception records containing single-time detected hoist swing angle and angular velocity, wind speed, wind direction, and actual swing angle in the next period, with the safety boundary function as the constraint condition. This model is used to predict the hoist swing angle in the first preset future period based on real-time collection data, helping the operator to understand the swing trend of the hoist in advance, so as to take timely measures to prevent the steel truss from swinging excessively and avoid collision accidents.

[0071] In this embodiment, the first preset future period: This is a pre-set future time interval, within which the swing angle of the hoisted member is predicted using the swing angle prediction model, and the current collision risk index is determined based on relevant data. For example, it can be set to 1-5 minutes in the future.

[0072] In this embodiment, the predicted swing angle of the hoisted member: With the help of the swing angle prediction model, the angle to which the hoisted member will swing within the first preset future period is estimated based on real-time collected data such as wind speed, hoisted member swing angle, and angular velocity.

[0073] In this embodiment, the current collision risk index: quantifies the risk of collision between the steel truss girder and the obstacle during hoisting. The higher the current collision risk index, the greater the risk of collision.

[0074] In this embodiment, the preset angle threshold: a pre-set hoisted member swing angle limit value. For example, 5 degrees.

[0075] In this embodiment, the preset index threshold: a pre-set limit value for measuring the current collision risk index, for example, 0.7.

[0076] In this embodiment, based on the real-time acquisition data to calculate the real-time braking force, and based on the real-time braking force to trigger the braking instruction of the braking system of the hoisting device, the anti-swing control result is obtained: when the predicted swing angle of the hoisted member is greater than the preset angle threshold or the current collision risk index is greater than the preset index threshold, the damping control decision module calculates the real-time braking force required to prevent the steel truss girder from excessive swinging based on real-time collected data such as wind speed, hoisted member swing angle and angular velocity, distance between the hoisted member and the obstacle.

[0077] Suppose the real-time collected data is: wind speed v = 10 m / s, hoisted member swing angle θ = 15 degrees, angular velocity ω = 5 degrees / s, distance between hoisted member and obstacle d = 5 m.

[0078] Suppose a simplified mechanical model related to the real-time braking force F is established according to the characteristics and mechanical principles of the hoisting system: F = k1 × v + k2 × θ + k3 × ω + k4 / d, where k1, k2, k3, k4 are coefficients determined in advance according to factors such as hoisting equipment and steel truss girder structure. These coefficients are determined through a large number of experimental tests, theoretical analysis, and practical engineering experience on the hoisting system. For example, by conducting hoisting simulation experiments under different wind speeds, swing angles, angular velocities, and distances, the required braking force to prevent the steel truss girder from excessive swinging is recorded, and the values of these coefficients are fitted.

[0079] Suppose after the preliminary experiment and analysis, k1 = 2 N·s / m, k2 = 5 N / degree, k3 = 3 N·s / degree, k4 = 10 N·m.

[0080] The collected data and determined coefficient values are substituted into the mechanical model for calculation F = 112 N.

[0081] Therefore, according to the current real-time collected data, the damping control decision module calculates the real-time braking force required to prevent the steel truss from excessive swinging as 112 N.

[0082] Then, according to the real-time braking force, a braking instruction is sent to the braking system of the hoisting device, so that the braking system takes corresponding measures (such as increasing damping, adjusting the boom angle, etc.), and finally obtains the control result of preventing the steel truss from swinging, ensuring the safety and stability of the hoisting operation. The braking system is divided into three modes:

[0083] Active damping mode (braking force is applied through the sling tensioning device, response speed is fast);

[0084] Passive damping mode (start the hydraulic buffer on both sides of the hoisted part, suitable for low-frequency swinging);

[0085] Cooperative damping mode (active + passive combined braking, used for high-frequency strong swinging).

[0086] Based on the "swinging feature vector" f = [swing angle, angular velocity, wind speed] of the real-time collected data, the optimal mode is determined through fuzzy logic:

[0087] Rule 1: If the swing angle is ≤ 3° and the angular velocity is ≤ 0.3° / s → passive mode;

[0088] Rule 2: If 3° < swing angle ≤ 8° or wind speed > 5 m / s → active mode;

[0089] Rule 3: If swing angle > 8° and angular velocity > 0.8° / s → cooperative mode;

[0090] When the mode is switched, a smooth transition algorithm (braking force change rate ≤ 5 kN / s) is used to avoid impact.

[0091] As shown in Figure 2 To further realize the establishment of the dynamic equation through finite element simulation, the coupling of critical wind speed data to generate a safety boundary function, and the training of a long short-term memory network and a large number of perception records to construct a swing angle prediction model that can accurately predict the swing angle of the hoisted part, a method for constructing the swing angle prediction model is proposed, including:

[0092] Establishing the dynamics equation of the hoisting system based on finite element simulation;

[0093] Coupling the measured critical wind speed data on the construction site with the dynamics equation of the hoisting system to generate a safety boundary function;

[0094] A safety boundary function is used as a constraint condition, and a long short-term memory network and a large number of hoisting system parameter perception records are used for training to obtain a swing angle prediction model.

[0095] Each hoisting system parameter perception record includes the detected hoisting member swing angle and angular velocity, wind speed, wind direction, and actual swing angle in the next period at a single time point.

[0096] In this embodiment, a hoisting system dynamics equation is established based on finite element simulation: in the hoisting system, the mechanical properties of components such as steel truss, sling, lifting lug, etc. can be considered by using finite element simulation, such as mass, stiffness, damping, etc., and the interaction between them. By modeling and analyzing these factors, a dynamics equation is established to describe the change of the motion state of the hoisting system over time. For example, the dynamics equation can reflect the change law of the displacement, velocity, acceleration, etc. of the hoisting member under the action of wind force, gravity, sling tension, etc. during hoisting, providing a theoretical basis for subsequent analysis and prediction.

[0097] In this embodiment, the critical wind speed data measured on site: in the steel truss hoisting site, through wind speed monitoring equipment, under different working conditions and different environmental conditions, the wind speed data that can cause dangerous conditions (such as large swing of the hoisting member, greatly increased risk of collision with obstacles, etc.) of the steel truss hoisting are obtained through multiple measurements. These measured data are obtained based on the actual engineering environment and truly reflect the critical wind speed value closely related to the safety of hoisting in this project. For example, in the steel truss hoisting site of Huhe Bridge, since the bridge body spans the Huhe River, the surrounding topography and climate conditions will affect the wind speed. The critical wind speed data obtained through on-site measurement is of great significance for accurately assessing the hoisting safety and establishing related models.

[0098] Deploy ultrasonic anemometers or laser radars in the construction area to continuously record wind speed and direction; simultaneously monitor the swing angle θ of the steel truss and the sling tension and other parameters. Statistical historical hoisting data are extracted to extract the wind speed value that causes the swing angle to suddenly increase (such as θ jumping from 5° to 10°); the critical wind speed under 95% confidence is determined through probability analysis (such as Weibull distribution). A hoisting system dynamics model is established, different wind speeds (such as 8 m / s, 10 m / s, 12 m / s, etc.) are input; the beam swing angle and reaction force are simulated and calculated to determine the wind speed corresponding to the maximum swing angle.

[0099] In this embodiment, the critical wind speed data measured on the construction site is coupled with the hoisting system dynamics equation to generate a safety boundary function: the critical wind speed data measured on the construction site is integrated into the hoisting system dynamics equation established based on finite element simulation. Through this coupling mode, the influence of wind speed on the dynamic behavior of the hoisting system is considered, and then the boundary conditions under which the hoisting system maintains a safe lifting state under different wind speed conditions are determined, forming a safety boundary function. For example, the safety boundary function can represent the conditions that the swing angle, angular velocity and other motion parameters of the hoisted piece should satisfy within a certain wind speed range. If the swing angle exceeds this boundary, the lifting operation may face risks, providing constraint conditions for subsequent training of the swing angle prediction model to ensure that the swing angle predicted by the model is within the scope of safety evaluation. The specific determination process includes:

[0100] Input coupling: associate the measured critical wind speed (e.g. 12 m / s) with the dynamics equation to establish a wind speed - wind direction - maximum swing angle mapping relationship;

[0101] Function output: for any given wind speed and wind direction, output the predicted maximum swing angle it may cause;

[0102] Safety criterion: if the maximum swing angle under the current wind speed is ≥ 8°, trigger a risk warning.

[0103] In the scenario of river-side hoisting (Tuhu River area, where side winds often occur):

[0104] When the wind speed is 12 m / s and the wind direction is perpendicular to the beam axis, the swing angle of the hoisted piece increases from 5° to 9° (critical state). Set the safety boundary function as Ω(12, 90°) = 9°. If the real-time monitoring shows that the wind speed is 13 m / s and the wind direction is 85°, query Ω(13, 85°) = 10.2° > 9°, and immediately reduce the speed and brake.

[0105] In this embodiment, the safety boundary function is used as a constraint condition, and a long short-term memory network and a large number of hoisting system parameter perception records are used for training to obtain a swing angle prediction model:

[0106] Long short-term memory network (LSTM) is a special type of recurrent neural network that can effectively handle long-term dependencies in time series data. In this embodiment, the safety conditions determined by the safety boundary function are used as constraints, and a large number of hoisting system parameter perception records are used to train the LSTM network. These perception records contain information such as the swing angle and angular velocity detected at a single moment, wind speed, wind direction, and actual swing angle in the next period. By continuously adjusting the weights and parameters of the network, the network learns the complex relationships between these parameters, and thus constructs a swing angle prediction model that can accurately predict the swing angle of the hoisted piece in the first predetermined future period based on the current real-time collected parameters.

[0107] In this embodiment, the swing angle and angular velocity of the hoist piece detected at a single moment, wind speed, wind direction and actual swing angle in the next period are:

[0108] This is the key data constituting the parameter perception record of the hoisting system. In the hoisting process, at a certain moment, the swing angle and angular velocity of the hoist piece are detected by sensors and other devices, and the wind speed and wind direction information at this moment are obtained. The actual swing angle in the next period is the actual measured swing angle of the hoist piece in the next time period. These data record the key parameters at different moments in the hoisting process and their subsequent actual changes, providing rich samples for the training of the long short-term memory network.

[0109] In order to further realize accurate determination of the current collision risk index of the hoist piece and the obstacle in the hoisting process by determining multiple parameters such as the current sensitivity coefficient, the safety distance threshold, the space situation factor and calculating based on a specific formula, a method for determining the current collision risk index by the dynamic risk prediction module is proposed, which includes:

[0110] determining the current sensitivity coefficient based on real-time collected data;

[0111] determining the current safety distance threshold of the hoist piece and the obstacle based on real-time collected data;

[0112] determining the space situation factor of the space where the hoist piece and the obstacle are located;

[0113] determining the current collision risk index based on the current sensitivity coefficient, the distance between the hoist piece and the obstacle detected in real time, the current safety distance threshold of the hoist piece and the obstacle, the continuous threshold exceeding time of the swing angle of the hoist piece, the swing angle of the hoist piece and the space situation factor:

[0114]

[0115] In the formula, R coll is the current collision risk index, exp is the exponential function with the natural constant as the base and the value of the natural constant is 2.72, k is the current sensitivity coefficient, Δd is the distance between the hoist piece and the obstacle detected in real time, d safe is the current safety distance threshold of the hoist piece and the obstacle, t danger is the continuous threshold exceeding time of the swing angle of the hoist piece, T ref is the reference duration, γ is the space situation factor, θ is the swing angle of the hoist piece, and θ0 is the reference swing angle of the hoist piece.

[0116] In this embodiment, the current sensitivity coefficient: is a parameter that comprehensively reflects the influence degree of real-time wind speed and the distance between the hoisted object and the obstacle on the collision risk. For example, if the real-time wind speed is large and the distance between the hoisted object and the obstacle is close, the current sensitivity coefficient will increase accordingly, indicating that the hoisting process is more sensitive to risk changes, and the collision risk may be higher. In the calculation of the current collision risk index, this coefficient will make the index more significantly reflect the actual risk situation.

[0117] In this embodiment, the current safe distance threshold between the hoisted object and the obstacle: is a critical value for judging whether the distance between the hoisted object and the obstacle is safe.

[0118] In this embodiment, the space situation factor of the space where the hoisted object and the obstacle are located: this factor is used to comprehensively evaluate the influence of the overall situation of the space where the hoisted object and the obstacle are located on the hoisting risk. For example, if the space openness index is high, the obstacle density index is low, and the motion trajectory intersection rate is small, it means that the space situation is relatively safe, and the space situation factor is small, otherwise it is large. This factor can comprehensively reflect the influence of the space environment on the risk when calculating the current collision risk index.

[0119] In this embodiment, the continuous over-threshold time of the hoisted object swing angle: refers to the time length that the hoisted object swing angle continuously exceeds a certain angle threshold set in advance. This parameter reflects the duration of the hoisted object swing angle in a dangerous state. For example, if the preset angle threshold is 10°, when the hoisted object swing angle continuously exceeds 10° for 5 seconds, the continuous over-threshold time of the hoisted object swing angle is 5 seconds.

[0120] In this embodiment, the reference duration: is a standard time length used for comparison when calculating the current collision risk index. For example, the reference duration is set to 3 seconds.

[0121] As shown in Figure 3 In order to further realize the determination of the current sensitivity coefficient according to the real-time wind speed and the distance between the hoisted object and the obstacle by setting the reference term, the wind speed correction term and the distance correction term, and then accurately obtaining the current sensitivity coefficient, a method for determining the current sensitivity coefficient based on real-time collected data is proposed, which comprises:

[0122] Determine the real-time wind speed and the distance between the hoisted object and the obstacle based on real-time collected data;

[0123] Take 1 as the reference term, take the hyperbolic tangent value of the ratio of the real-time wind speed to the reference wind speed multiplied by the first preset multiple value as the wind speed correction term, and take the second preset multiple value of the sign function value of the difference between the real-time detected distance between the hoisted object and the obstacle and the current safe distance threshold between the hoisted object and the obstacle and the ratio of the current safe distance threshold between the hoisted object and the obstacle as the distance correction term;

[0124] Take the sum of the reference term, the wind speed correction term and the distance correction term as the dynamic adjustment factor of the initial sensitivity coefficient;

[0125] The product of the initial sensitivity coefficient and the corresponding dynamic adjustment factor is taken as the current sensitivity coefficient.

[0126] In this embodiment, the reference term: take "1" as the reference term, which is the basis for calculating the current sensitivity coefficient. On this basis, the sensitivity coefficient is adjusted by adding the wind speed correction term and the distance correction term to reflect the influence of real-time wind speed and the distance between the hoisting piece and the obstacle on the collision risk.

[0127] Wind speed correction term: the ratio of real-time wind speed to reference wind speed can reflect the change of current wind speed relative to the reference state. The ratio is processed using the hyperbolic tangent function because the hyperbolic tangent function has the characteristic of mapping values to the interval (-1, 1), which can avoid unreasonable influence of too large or too small wind speed ratio on the sensitivity coefficient. Multiply the hyperbolic tangent value by the first preset multiplier to get the wind speed correction term, and the first preset multiplier plays a role in amplifying or reducing the influence of wind speed on the sensitivity coefficient. For example, if the real-time wind speed is much larger than the reference wind speed, the hyperbolic tangent value tends to 1, and after multiplying the first preset multiplier, the wind speed correction term increases, which means that the current wind speed has a greater impact on the collision risk, and the sensitivity coefficient will increase accordingly.

[0128] Distance correction term: the difference between the real-time detected distance between the hoisting piece and the obstacle and the current safety distance threshold reflects the deviation of the current distance between the hoisting piece and the obstacle from the safety standard. Compare this difference with the current safety distance threshold, and take the sign function value (the sign function returns -1, 0 or 1 according to the value of the number, which is mainly used to determine whether the distance difference is positive or negative), and multiply it by the negative of the second preset multiplier as the distance correction term. When the distance between the hoisting piece and the obstacle is less than the current safety distance threshold, the difference is negative, the sign function value is -1, and after multiplying the negative of the second preset multiplier, it becomes positive, which will increase the sensitivity coefficient, indicating that the too close distance increases the collision risk; on the contrary, when the distance is greater than the safety distance threshold, the difference is positive, the sign function value is 1, and after multiplying the negative of the second preset multiplier, it is negative, which will reduce the sensitivity coefficient, indicating that the distance is safe and the collision risk is reduced.

[0129] By adding the reference term, the wind speed correction term and the distance correction term, a dynamic adjustment factor is obtained, which comprehensively reflects the influence of wind speed and distance on the sensitivity coefficient. This dynamic adjustment factor will change according to the changes of real-time wind speed and the distance between the hoisting piece and the obstacle, so as to dynamically adjust the initial sensitivity coefficient, so that it can more accurately reflect the sensitivity of the collision risk under the current hoisting environment. For example, at a certain moment, the wind speed is large and the distance between the hoisting piece and the obstacle is close, the wind speed correction term and the distance correction term will both increase the dynamic adjustment factor, and then increase the initial sensitivity coefficient, which reflects the current high collision risk.

[0130] The initial sensitivity coefficient is a pre-set basic value reflecting the sensitivity of the lifting system to the risk of collision. Multiply it by the dynamic adjustment factor to get the current sensitivity coefficient. This way, the current sensitivity coefficient not only contains the basic sensitivity of the lifting system to the risk (initial sensitivity coefficient), but also can be dynamically adjusted according to the real-time wind speed and distance factor (dynamic adjustment factor), and finally gets a value that accurately reflects the sensitivity of the collision risk under the current lifting condition, providing an important parameter for subsequent calculation of the current collision risk index. Usually, the initial sensitivity coefficient is set according to the basic sensitivity of the lifting system to the risk, and the range may be between 0.5 and 2. If the lifting system is relatively sensitive and reacts quickly to changes in risk, the initial sensitivity coefficient may be close to 2; if the lifting system is relatively stable and not very sensitive to changes in risk, the initial sensitivity coefficient may be close to 0.5.

[0131] In this embodiment, the first preset multiplier is a parameter used when calculating the wind speed correction term. It is pre-set according to the actual situation of the lifting operation. Its role is to adjust the influence of wind speed on the current sensitivity coefficient. For example, in the case where wind speed changes have a greater impact on the sway of the steel truss girder in the lifting environment, the first preset multiplier can be appropriately increased, so that the wind speed correction term accounts for a larger proportion in the calculation of the sensitivity coefficient, and the sensitivity coefficient can more significantly reflect the impact of wind speed changes on the collision risk. Conversely, if the wind speed has a relatively small impact on the stability of the lifting, the first preset multiplier can be reduced to reduce the influence of the wind speed factor on the sensitivity coefficient. Taking the lifting of the Huohe Bridge steel truss girder as an example, since the bridge body spans a river and the surrounding area is open, the wind has a greater impact on the lifting. After analyzing the historical data of wind speed in this lifting environment and the impact of wind on the sway of the steel truss girder, the first preset multiplier is determined to be 1.5. In this way, when the ratio of the real-time wind speed to the reference wind speed changes, the result of the hyperbolic tangent function is multiplied by 1.5, which can more significantly adjust the wind speed correction term, so that the sensitivity coefficient more accurately reflects the impact of wind speed on the collision risk.

[0132] In this embodiment, the second preset multiplier is used to adjust the influence of the distance correction term on the current sensitivity coefficient. It is also pre-set according to the specific requirements and safety standards of the lifting operation. In a lifting scenario where the distance between the lifted object and the obstacle is strictly required, the second preset multiplier is increased, so that when the distance between the lifted object and the obstacle is close to or less than the safety distance threshold, the distance correction term has a stronger increasing effect on the sensitivity coefficient, which can more timely indicate a high collision risk. Conversely, in the case where the distance requirement is relatively loose, the second preset multiplier can be reduced to make the influence of the distance factor on the sensitivity coefficient more gradual. In the case where there are many important facilities around the lifting site and the distance requirement between the steel truss girder and the obstacle is extremely strict, the second preset multiplier is set to 2.5. This makes the distance correction term more strongly increase the sensitivity coefficient when the distance between the lifted object and the obstacle is close to or less than the current safety distance threshold, timely indicating a high collision risk so that the operator can take measures.

[0133] As Figure 4 shown, in order to further realize the dynamic adjustment factor by calculating the static safety distance, combining the real-time wind speed, and then determining the current safety distance threshold according to the swing angle and angular velocity of the hoist piece and considering the type weight of the obstacle, a method for determining the current safety distance threshold based on real-time data collection is proposed, including:

[0134] The sum of the product of the length of the hoist rope of the hoisting system and the sine value of the maximum allowed swing angle and the fixed safety margin is taken as the static safety distance;

[0135] The sum of the third preset multiple value of the hyperbolic secant function based on the ratio of the real-time wind speed in the real-time data collection and the preset wind speed division threshold and 1 is taken as the dynamic adjustment factor of the static safety distance;

[0136] The dynamic safety distance is determined based on the static safety distance and the corresponding dynamic adjustment factor;

[0137] The weight factor is determined based on the type of the obstacle, and the product of the dynamic safety distance and the weight factor is taken as the current safety distance threshold.

[0138] In this embodiment, the sum of the product of the length of the hoist rope of the hoisting system and the sine value of the maximum allowed swing angle and the fixed safety margin is taken as the static safety distance:

[0139] In the hoisting operation, the length of the hoist rope and the maximum allowed swing angle determine the maximum range of the possible swing of the hoist piece in theory. The product of the length of the hoist rope and the sine value of the maximum allowed swing angle calculates the horizontal offset distance of the end point of the hoist piece relative to the vertical position under the maximum allowed swing angle from the geometric relationship. And the fixed safety margin is an additional safety distance to cope with uncertainties in the actual hoisting process, such as measurement errors, sudden changes in wind speed, etc. The sum of the two is the static safety distance, which provides a basic safety distance reference value for the hoisting operation.

[0140] Assuming that the length of the hoist rope of the hoisting system is 20 meters and the maximum allowed swing angle is 30 degrees, the sine value of the maximum allowed swing angle is sin30 degrees = 0.5, and the product of the two is 20 x 0.5 = 10 meters. If the fixed safety margin is set to 2 meters, then the static safety distance is 10 + 2 = 12 meters. This means that in general, the distance between the hoist piece and the obstacle should be kept above 12 meters to ensure hoisting safety.

[0141] In this embodiment, the sum of the third preset multiple value of the hyperbolic secant function based on the ratio of the real-time wind speed in the real-time data collection and the preset wind speed division threshold and 1 is taken as the dynamic adjustment factor of the static safety distance:

[0142] Real-time wind speed is one of the key factors affecting hoisting safety. The preset wind speed division threshold is a reference wind speed value set according to hoisting operation environment and experience, which is used for comparison with real-time wind speed. The hyperbolic secant function has the characteristic of mapping numerical values to a certain interval, which is used here to process the ratio of real-time wind speed to preset wind speed division threshold to reasonably reflect the influence degree of wind speed on safety distance. The third preset multiplier is an adjustable parameter used to amplify or reduce the contribution of the hyperbolic secant function value to the dynamic adjustment factor. The dynamic adjustment factor is obtained by multiplying the hyperbolic secant function value by the third preset multiplier and then adding 1. This factor takes into account the relative relationship between real-time wind speed and preset wind speed, and is used to dynamically adjust the static safety distance to adapt to the safety requirements under different wind speed conditions.

[0143] Suppose the real-time wind speed is 15 meters per second, the preset wind speed division threshold is 10 meters per second, and the third preset multiplier is 2. First, calculate the ratio of real-time wind speed to preset wind speed division threshold as 1.5. Then calculate the hyperbolic secant function value sech(1.5)≈0.2. Then the dynamic adjustment factor is 2×0.2+1=1.4. Higher wind speed makes the dynamic adjustment factor greater than 1, indicating that the static safety distance needs to be increased to ensure hoisting safety.

[0144] In this embodiment, the dynamic safety distance is determined based on the static safety distance and the corresponding dynamic adjustment factor:

[0145] The static safety distance provides a basic safety distance standard, but wind speed and other factors will change during actual hoisting, so it needs to be adjusted according to the dynamic adjustment factor to obtain the dynamic safety distance. Multiplying the static safety distance by the dynamic adjustment factor can make the safety distance change reasonably according to real-time wind speed and other dynamic factors. If the dynamic adjustment factor is greater than 1, the dynamic safety distance will be greater than the static safety distance to adapt to adverse conditions such as increased wind speed; if the dynamic adjustment factor is less than 1, the dynamic safety distance will be reduced accordingly, but generally still guarantees a certain safety margin.

[0146] Following the previous example, the static safety distance is 12 meters, and the dynamic adjustment factor is 1.4, so the dynamic safety distance is 12×1.4=16.8 meters. This indicates that under the current real-time wind speed conditions, the safety distance between the hoisted object and the obstacle should be adjusted to 16.8 meters to ensure hoisting safety.

[0147] In this embodiment, the weight factor is determined based on the type of obstacle:

[0148] Different types of obstacles pose different levels of threat to hoisting safety. For example, rigid obstacles such as buildings, bridge piers, etc. can cause serious damage once they collide with the hoisting piece, while some flexible obstacles such as safety nets, etc. may pose relatively small threat to hoisting safety. Determining the weight factor based on the type of obstacle (which can be determined according to a pre-set obstacle type-weight factor mapping table) is to assign different weight values to different types of obstacles according to their properties, materials, potential harm levels, etc. to more accurately assess the safety distance requirements between the hoisting piece and different obstacles.

[0149] Suppose in the hoisting site, when encountering a building type obstacle, because of its rigidity and potential great harm, the weight factor is assigned as 1.5; when encountering a safety net type obstacle, because of its relative flexibility and small harm, the weight factor is assigned as 0.8.

[0150] In this embodiment, the product of the dynamic safety distance and the weight factor is taken as the current safety distance threshold:

[0151] By multiplying the dynamic safety distance and the weight factor determined based on the type of obstacle, the current safety distance threshold is obtained. The threshold obtained in this way takes into account both the influence of dynamic factors such as real-time wind speed on safety distance (embodied by dynamic safety distance) and the differences in safety distance requirements for different obstacle types (embodied by weight factor), thereby providing a safety distance judgment standard that is more in line with actual conditions for hoisting operations.

[0152] Suppose the dynamic safety distance is 16.8 meters, and when encountering a building type obstacle, the weight factor is 1.5, then the current safety distance threshold is 16.8 x 1.5 = 25.2 meters. This means that under the current wind speed conditions, for a building type obstacle, the distance between the hoisting piece and the obstacle should be kept above 25.2 meters to ensure the safety of hoisting operations.

[0153] In order to further realize the prediction of the swing angle trajectory according to the swing angle and angular velocity of the hoisting piece, determine the dynamic buffer distance in combination with different angular velocity conditions, and accurately determine the dynamic safety distance based on the static safety distance and the dynamic adjustment factor, a method for determining the dynamic safety distance based on the static safety distance and the corresponding dynamic adjustment factor is proposed, which includes:

[0154] Predict the swing angle trajectory in a pre-set second future period based on the swing angle and angular velocity in the real-time collected data, and calculate the minimum value of the shortest distance between each point on the swing angle trajectory in the pre-set second future period and the obstacle;

[0155] When the angular velocity of the swing angle of the hoisting piece in the real-time collected data exceeds the preset angular velocity threshold, the dynamic buffer distance is determined based on the angular velocity of the swing angle of the hoisting piece, and the sum of the product of the static safety distance and the corresponding dynamic adjustment factor and the dynamic buffer distance is taken as the first dynamic safety distance, and the sum of the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle and the dynamic buffer distance is taken as the second dynamic safety distance, and the maximum value of the first dynamic safety distance and the second dynamic safety distance is taken as the dynamic safety distance.

[0156] When the angular velocity of the swing angle of the hoisting piece in the real-time collected data does not exceed the preset angular velocity threshold, the product of the static safety distance and the corresponding dynamic adjustment factor is taken as the first dynamic safety distance, and the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle is taken as the second dynamic safety distance, and the maximum value of the first dynamic safety distance and the second dynamic safety distance is taken as the dynamic safety distance.

[0157] In this embodiment, the swing angle trajectory in the preset second future period is predicted based on the swing angle and the angular velocity in the real-time collected data:

[0158] In the process of hoisting the steel truss girder, the real-time environment perception module collects the swing angle and angular velocity data of the hoisting piece. Based on these real-time data, relevant physical models or algorithms can be used to predict the trajectory of the swing angle of the hoisting piece over time within a preset second future period. This is a prediction of the future motion trend of the hoisting piece, which can help to judge in advance whether the hoisting piece will collide with the obstacle. For example, through analysis of the current swing angle and angular velocity, if the angular velocity is large and the swing angle is also continuously increasing, the prediction model will predict that the swing angle will change along a certain trajectory in the future period of time, and may approach the obstacle.

[0159] In this embodiment, the preset second future period is a future time period set by a person, which is used to limit the time range of predicting the swing angle trajectory of the hoisting piece. For example, for some hoisting speed is fast, the environment is complex, the preset second future period may be set shorter, such as 1-2 seconds, so as to capture the motion trend of the hoisting piece in time; and for the hoisting speed is slow, the environment is relatively stable, this period of time may be set to 5-10 seconds.

[0160] In this embodiment, the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle is calculated:

[0161] After predicting the swing angle trajectory of the hoisting piece in the preset second future period, for each point on the trajectory, the distance between it and the surrounding obstacles is calculated, and then the minimum value is found from these distances.

[0162] In this embodiment, the preset angular velocity threshold is a preset angular velocity limit value. For example, according to the size of the steel truss girder and the lifting environment, the preset angular velocity threshold is set to 5 degrees per second, and if the actual monitored angular velocity reaches 6 degrees per second, it indicates that the swinging speed of the hoisted piece is too fast and special attention is needed.

[0163] In this embodiment, the dynamic buffer distance is determined based on the angular velocity of the hoisted piece swing angle. Considering that the angular velocity of the hoisted piece swing angle is different, the degree of swing and the potential collision risk are also different. Based on this, an additional buffer distance, i.e. the dynamic buffer distance, is determined according to the angular velocity of the hoisted piece swing angle. Generally speaking, the greater the angular velocity, the more violent the swing of the hoisted piece, the higher the collision risk, and the greater the dynamic buffer distance. For example, a functional relationship can be set, when the angular velocity is ω, the dynamic buffer distance d = kω (k is a coefficient determined according to the actual situation). In this way, under different angular velocity conditions, the dynamic buffer distance can be used to further ensure the lifting safety and provide enough safety space for possible rapid swinging.

[0164] In this embodiment, the first dynamic safety distance is an intermediate parameter in the process of determining the current safety distance.

[0165] In this embodiment, the second dynamic safety distance is also an intermediate parameter in the process of determining the current safety distance. Together with the first dynamic safety distance, the dynamic safety distance is finally determined by comparing the sizes of the two, so as to more comprehensively guarantee the safety between the hoisted piece and the obstacles in the lifting process.

[0166] As shown in Figure 5 In order to further realize the determination of the hoisted piece movement airspace volume, the obstacle occupied space volume, the calculation of the space openness index and the obstacle density index, the combination of the motion trajectory intersection rate, and the comprehensive evaluation of the space situation of the hoisted piece and the obstacles, a method for determining the space situation factor of the space where the hoisted piece and the obstacles are located is proposed, including:

[0167] Determine the hoisted piece movement airspace volume based on the length of the sling and the volume of the hoisted piece itself;

[0168] Construct a three-dimensional point cloud model of the obstacle, extract the minimum bounding box of the obstacle through the convex hull algorithm and the three-dimensional point cloud model of the obstacle, and determine the obstacle occupied space volume based on the minimum bounding box of the obstacle;

[0169] Take the ratio of the hoisted piece movement airspace volume and the obstacle occupied space volume as the space openness index of the space where the hoisted piece and the obstacles are located;

[0170] Determine the obstacle density index of the space where the hoisted piece and the obstacles are located based on the number of points in the three-dimensional point cloud model of the obstacle and the obstacle occupied space volume;

[0171] Determine the intersection rate of the movement trajectory of the hanging piece and the space where the obstacle is located;

[0172] Determine the space situation factor based on the space openness index, obstacle density index, and movement trajectory intersection rate.

[0173] In this embodiment, the length of the sling: the length of the rope connecting the lifting equipment and the steel truss (hanging piece) during the lifting of the steel truss.

[0174] In this embodiment, the self-volume of the hanging piece: the size of the space occupied by the steel truss itself.

[0175] In this embodiment, determine the hanging piece movement airspace volume based on the length of the sling and the self-volume of the hanging piece:

[0176] Assuming the length of the sling is L, and taking the lifting point as the center of the sphere, the volume of the sphere with the length of the sling as the radius is the hanging piece movement airspace volume.

[0177] In this embodiment, construct the obstacle three-dimensional point cloud model: a data model that represents the three-dimensional shape of an object using a large number of discrete points. In the lifting scene, the three-dimensional coordinate information of a large number of points on the surface of the obstacle is obtained through laser scanning, photogrammetry, etc. These points constitute the three-dimensional point cloud of the obstacle.

[0178] In this embodiment, the minimum bounding box of the obstacle is extracted through the convex hull algorithm and the obstacle three-dimensional point cloud model:

[0179] After obtaining the three-dimensional point cloud model of the obstacle, the convex hull algorithm can find a minimum convex polyhedron that can completely enclose these point clouds, i.e. the minimum bounding box of the obstacle. For example, for a building obstacle represented by point clouds, the convex hull algorithm will calculate a cuboid (or other shaped polyhedron) that can contain all the point clouds representing the building in the smallest volume.

[0180] In this embodiment, determine the obstacle-occupied space volume based on the minimum bounding box of the obstacle: the minimum bounding box of the obstacle has clear length, width, height (or other three-dimensional size parameters), and its volume can be directly calculated according to its geometric shape and size. This volume approximately represents the volume occupied by the obstacle in space. For example, if the minimum bounding box of the obstacle is a cuboid, its length, width, and height are a, b, and c respectively, then the obstacle-occupied space volume V = a × b × c.

[0181] In this embodiment, determine the obstacle density index of the space where the hanging piece and the obstacle are located based on the number of points in the obstacle three-dimensional point cloud model and the obstacle-occupied space volume:

[0182] The obstacle three-dimensional point cloud model describes the shape and position of the obstacle by a large number of discrete points, and the number of points to some extent reflects the complexity or detail richness of the obstacle surface. The obstacle occupies the space volume, which represents the actual three-dimensional space size occupied by the obstacle. Assuming that the number of points in the obstacle three-dimensional point cloud model is N, and the obstacle occupies the space volume V, the obstacle density index can be calculated by the ratio of the two. For example, for a simple block-shaped obstacle, if its point cloud model contains 1000 points, the calculated occupied space volume is 5 cubic meters, and the obstacle density index is 200 per cubic meter.

[0183] In this embodiment, the intersection rate of the movement trajectory of the hanging piece and the space where the obstacle is located: this parameter is used to quantify the degree of overlap between the movement trajectory of the hanging piece in the lifting process and the space occupied by the obstacle.

[0184] In order to further realize the calculation of the intersection volume of the space swept by the swing angle trajectory based on the swing angle prediction model and the minimum bounding box of the obstacle, and compare it with the space volume swept by the swing angle trajectory, and accurately determine the intersection rate of the movement trajectory of the hanging piece and the space where the obstacle is located, a method for determining the intersection rate of the movement trajectory of the hanging piece and the space where the obstacle is located is proposed, comprising:

[0185] Based on the swing angle prediction model, the space volume swept by the swing angle trajectory in the preset third future period is calculated, and the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the minimum bounding box of the obstacle is calculated.

[0186] The ratio of the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the minimum bounding box of the obstacle to the space volume swept by the swing angle trajectory in the preset third future period is taken as the intersection rate of the movement trajectory of the hanging piece and the space where the obstacle is located.

[0187] In this embodiment, the space volume swept by the swing angle trajectory in the preset third future period is calculated based on the swing angle prediction model:

[0188] The swing angle prediction model is used to obtain the trajectory of the swing angle of the hanging piece changing with time in the preset third future period. Since the hanging piece moves in the process of swinging, its movement trajectory will sweep a certain space range, and combined with the shape, size and swing angle trajectory of the hanging piece, the volume of this space can be calculated by related geometric calculation methods (such as integral calculation, etc., depending on the complexity of the shape of the hanging piece).

[0189] In this embodiment, the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the minimum bounding box of the obstacle:

[0190] After obtaining the spatial volume swept by the swing trajectory of the suspended component within the preset third future time period and extracting the minimum bounding box of the obstacle through the convex hull algorithm and the 3D point cloud model of the obstacle, the volume of the overlapping part of the two spaces, i.e. the intersection volume, is calculated using spatial geometric calculation methods (such as Boolean operations).

[0191] In this embodiment, a third future time period is preset: this is a pre-defined future time period used to limit the time range for relevant calculations based on the swing angle prediction model. For example, in situations where the lifting speed is fast and the surrounding environment is full of complex obstacles, the preset third future time period may be set shorter, such as 1-3 seconds, in order to predict collision risks more timely and accurately; while in scenarios where the lifting speed is slow and the environment is relatively simple, this time period can be appropriately extended, such as 5-10 seconds.

[0192] To further achieve accurate determination of spatial situation factors by dedimensionalizing obstacle density, weighting and summing the spatial openness index, the dimensionless obstacle density index, and the intersection rate of motion trajectories, a method for determining spatial situation factors based on the spatial openness index, obstacle density index, and motion trajectory intersection rate is proposed, including:

[0193] Dimensionless reduction of obstacle density;

[0194] The spatial openness index, the dimensionless obstacle density index, and the intersection rate of motion trajectories are weighted and then summed according to the weights to obtain the spatial situation factor.

[0195] In this embodiment, dimensionless reduction means eliminating the dimensions of the obstacle density index, making it a pure numerical value, which facilitates unified processing and comparison with other dimensionless parameters (such as spatial openness index and trajectory intersection rate). Common dimensionless reduction methods include normalization.

[0196] In this embodiment, the spatial openness index, the dimensionless obstacle density index, and the trajectory intersection rate are weighted and then summed according to the assigned weights to obtain the spatial situation factor.

[0197] Weighting: The spatial openness index, the dimensionless obstacle density index, and the trajectory intersection rate all have different degrees of influence on the lifting spatial situation. Weighting involves assigning different weight values ​​to these three parameters based on the actual conditions and experience of lifting operations, reflecting their relative importance in assessing the spatial situation. For example, in a lifting environment with complex obstacle distribution, a higher weight might be assigned to the dimensionless obstacle density index; conversely, if the overlap between the lifting trajectory and obstacles significantly impacts collision risk, a higher weight might be assigned to the trajectory intersection rate. Assume the spatial openness index has a weight of w1, the dimensionless obstacle density index has a weight of w2, and the trajectory intersection rate has a weight of w3, with w1 + w2 + w3 = 1.

[0198] The spatial situation factor is calculated using a weighted summation method: After determining the weights, the spatial situation factor is calculated using the formula: spatial openness index, dimensionless obstacle density index, and trajectory intersection rate. For example, if the spatial openness index is 0.6, the dimensionless obstacle density index is 0.3, the trajectory intersection rate is 0.2, and the weights are w1 = 0.4, w2 = 0.3, and w3 = 0.3, then the spatial situation factor = 0.4 × 0.6 + 0.3 × 0.3 + 0.3 × 0.2 = 0.39.

[0199] This invention provides an embodiment of a lifting method to prevent steel truss beams from swaying, comprising:

[0200] Real-time data collection includes wind speed, swing angle and angular velocity of the suspended component, and the distance between the suspended component and obstacles.

[0201] Based on real-time data acquisition and a swing angle prediction model, the predicted swing angle of the suspended component within the first preset future time period is determined, and the current collision risk index is determined.

[0202] When the predicted swing angle of the hoisting component is greater than the preset angle threshold or the current collision risk index is greater than the preset index threshold, the real-time braking force is calculated based on the real-time collected data, and the braking command of the hoisting device's braking system is triggered based on the real-time braking force to obtain the anti-sway control result.

[0203] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this invention and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. A hoisting device for preventing sway of a steel truss, characterized by, The method comprises the following steps: A real-time environment sensing module is used to collect wind speed, hoist swing angle and angular velocity, and distance between the hoist and obstacles in real time as real-time collection data; A dynamic risk prediction module is used to determine the predicted hoist swing angle in a first preset future period based on the real-time collection data and a swing angle prediction model, and to determine the current collision risk index; A damping control decision module is used to calculate the real-time braking force based on the real-time collection data when the predicted hoist swing angle is greater than a preset angle threshold or the current collision risk index is greater than a preset index threshold, and to trigger the braking instruction of the braking system of the hoisting device based on the real-time braking force to obtain the anti-swing control result. The method for constructing the swing angle prediction model comprises the following steps: A finite element simulation is used to establish a hoisting system dynamics equation; The critical wind speed data measured on the construction site is coupled with the hoisting system dynamics equation to generate a safety boundary function; The safety boundary function is used as a constraint condition, and a long short-term memory network and a large number of hoisting system parameter perception records are used for training to obtain the swing angle prediction model; Each hoisting system parameter perception record contains the hoist swing angle and angular velocity, wind speed, wind direction detected at a single moment, and actual swing angle in the next period. The method for determining the current collision risk index by the dynamic risk prediction module comprises the following steps: A current sensitivity coefficient is determined based on the real-time collection data; A current safety distance threshold between the hoist and obstacles is determined based on the real-time collection data; A spatial situation factor of the space where the hoist and the obstacles are located is determined; The current collision risk index is determined based on the current sensitivity coefficient, the distance between the hoist and the obstacles detected in real time, the current safety distance threshold between the hoist and the obstacles, the continuous over-threshold time of the hoist swing angle, the hoist swing angle, and the spatial situation factor: ； wherein, is the current collision risk index, is an exponential function with a natural constant and the value of the natural constant is 2.72, is the current sensitivity coefficient, is the real-time detected distance between the load and the obstacle, is the current safety distance threshold between the load and the obstacle, is the continuous over-threshold time of the load swing angle, is the reference duration, is the space situation factor, is the load swing angle, is the reference load swing angle.

2. The hoisting device for preventing the steel truss girder from swinging according to claim 1, characterized in that, The method for determining the current sensitivity coefficient based on the real-time collection data comprises the following steps: The real-time wind speed and the distance between the hoist and the obstacles are determined based on the real-time collection data; The tangent hyperbolic value of the ratio of the real-time wind speed to the reference wind speed is multiplied by a first preset multiple value to obtain a wind speed correction term, and the negative value of the second preset multiple value of the sign function value of the difference between the distance between the hoist and the obstacles detected in real time and the current safety distance threshold between the hoist and the obstacles, and the ratio of the current safety distance threshold between the hoist and the obstacles is taken as a distance correction term; The sum of the base term, the wind speed correction term, and the distance correction term is taken as a dynamic adjustment factor of the initial sensitivity coefficient; The product of the initial sensitivity coefficient and the corresponding dynamic adjustment factor is taken as the current sensitivity coefficient.

3. The hoisting device for preventing the steel truss girder from swinging according to claim 1, characterized in that, The method for determining the current safety distance threshold based on the real-time collection data comprises the following steps: The product of the length of the hoist sling of the hoisting system and the sine value of the maximum allowed swing angle, and the sum of the fixed safety margin, is taken as the static safety distance; The sum of the third preset multiple value of the hyperbolic cotangent function of the ratio of the real-time wind speed in the real-time collection data to the preset wind speed division threshold and 1 is taken as the dynamic adjustment factor of the static safety distance; The dynamic safety distance is determined based on the static safety distance and the corresponding dynamic adjustment factor; The weight factor is determined based on the type of the obstacle, and the product of the dynamic safety distance and the weight factor is taken as the current safety distance threshold.

4. The hoisting device for preventing the steel truss girder from swinging according to claim 3, characterized in that, The method for determining the dynamic safety distance based on the static safety distance and the corresponding dynamic adjustment factor comprises the following steps: predict the swing angle trajectory in the preset second future period based on the swing angle and the angular velocity in the real-time collected data, and calculate the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle; when the angular velocity of the swing angle in the real-time collected data exceeds the preset angular velocity threshold, determine the dynamic buffer distance based on the angular velocity of the swing angle, take the sum of the static safety distance multiplied by the corresponding dynamic adjustment factor and the dynamic buffer distance as the first dynamic safety distance, take the sum of the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle and the dynamic buffer distance as the second dynamic safety distance, and take the maximum value of the first dynamic safety distance and the second dynamic safety distance as the dynamic safety distance; when the angular velocity of the swing angle in the real-time collected data does not exceed the preset angular velocity threshold, take the product of the static safety distance and the corresponding dynamic adjustment factor as the first dynamic safety distance, take the minimum value of the shortest distance between each point on the swing angle trajectory in the preset second future period and the obstacle as the second dynamic safety distance, and take the maximum value of the first dynamic safety distance and the second dynamic safety distance as the dynamic safety distance.

5. The hoisting device for preventing the steel truss girder from swinging according to claim 1, characterized in that, The method for determining the space situation factor of the space where the hoist and the obstacle are located comprises: determining the hoist movement airspace volume based on the length of the hoist cable and the volume of the hoist itself; constructing an obstacle three-dimensional point cloud model, extracting an obstacle minimum bounding box through a convex hull algorithm and the obstacle three-dimensional point cloud model, and determining an obstacle occupied space volume based on the obstacle minimum bounding box; taking the ratio of the hoist movement airspace volume and the obstacle occupied space volume as the space openness index of the space where the hoist and the obstacle are located; determining the obstacle density index of the space where the hoist and the obstacle are located based on the number of points in the obstacle three-dimensional point cloud model and the obstacle occupied space volume; determining the movement trajectory intersection rate of the space where the hoist and the obstacle are located; determining the space situation factor based on the space openness index, the obstacle density index and the movement trajectory intersection rate.

6. The hoisting device for preventing the steel truss girder from swinging according to claim 5, characterized in that, The method for determining the movement trajectory intersection rate of the space where the hoist and the obstacle are located comprises: calculating the space volume swept by the swing angle trajectory in a preset third future period based on the swing angle prediction model, and calculating the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the obstacle minimum bounding box; taking the ratio of the intersection volume of the space swept by the swing angle trajectory in the preset third future period and the obstacle minimum bounding box and the space volume swept by the swing angle trajectory in the preset third future period as the movement trajectory intersection rate of the space where the hoist and the obstacle are located.

7. The device for preventing the steel truss girder from swinging during hoisting according to claim 5, characterized in that, The method for determining the space situation factor based on the space openness index, the obstacle density index and the movement trajectory intersection rate comprises: de-dimensioning the obstacle density; weighting the space openness index, the de-dimensioned obstacle density index and the movement trajectory intersection rate, and obtaining the space situation factor by weighted addition based on the weighted space openness index, the de-dimensioned obstacle density index and the movement trajectory intersection rate.

8. A method of preventing sway of a steel truss during hoisting, characterized by, The hoisting device for preventing the steel truss girder from swinging is applied to the hoisting device for preventing the steel truss girder from swinging in any one of claims 1 to 7, and comprises: Real-time acquisition of wind speed, hoisting piece swing angle and angular velocity, and distance between hoisting piece and obstacle as real-time acquisition data; Determine the predicted hoisting piece swing angle in the first preset future period based on the real-time acquisition data and the swing angle prediction model, and determine the current collision risk index; When the predicted hoisting piece swing angle is greater than the preset angle threshold or the current collision risk index is greater than the preset index threshold, calculate the real-time braking force based on the real-time acquisition data, trigger the braking instruction of the braking system of the hoisting device based on the real-time braking force, and obtain the anti-swing control result.

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