Control method and device for lifting arm of special operation vehicle

Abstract

The invention relates to the technical field of transformer substation maintenance operation, in particular to a control method and device for a lifting arm of a special operation vehicle, and the method comprises the steps: obtaining a high-altitude operation point location of a hoisted object and the length and coordinate data of an electrified body, and calculating the safety distance between a suspension arm and the electrified body; collecting three-dimensional data of the working environment in real time, and constructing a dynamic three-dimensional model of the working environment; identifying and marking the position and the shape of the obstacle; tracking the motion state of the obstacle, and predicting the future position of the obstacle; determining a spatial relationship among the suspension arm, the lifting hook and the obstacle, and judging whether a collision risk exists or not; and if the risk exists, re-planning the motion trails of the suspension arm and the lifting hook, and if the risk is relieved, evaluating the operation efficiency of the current operation path and the original path, and selecting the optimal operation path to continue to execute the special operation. By automatically calculating and planning the hoisting path, the problems of narrow special operation space, difficulty in judging the distance from the electrified body and the like in the existing transformer substation are solved.

Description

Technical Field

[0001] The present application relates to the technical field of substation maintenance operations, and more specifically, to a control method and device for a lifting arm of a special operation vehicle. Background Art

[0002] In modern power systems, substations are vital core facilities. The equipment inside substations needs to undergo various maintenance work such as testing, replacement, and troubleshooting according to their respective operating cycles. Among these maintenance operations, aerial work and equipment hoisting are common operations.

[0003] However, there are many potential safety hazards at the power operation site. On the one hand, the safety awareness of crane drivers and construction workers is generally weak. On the other hand, the live equipment in the substation is often at a high position. During the operation, it is difficult to accurately judge the actual distance between the special operation vehicle boom and the live body. This situation has led to frequent short-circuit and grounding accidents of power equipment caused by illegal operations of cranes or aerial work vehicles in the power industry in recent years. The consequences of these accidents are extremely serious. Not only will they cause significant damage to the power grid, but they will also seriously endanger the personal safety of construction workers. It can be seen that ensuring the safe distance of special operations is a key issue that needs to be solved urgently.

[0004] The invention patent with publication number CN114988282A discloses a substation hoisting operation monitoring system and method. By deploying infrared ranging devices on the crane boom head and the hoisted object, real-time monitoring of the safe distance between the crane boom and the primary equipment is achieved, and a simple distance warning device is combined to prompt the operator. In addition, although this patent can achieve real-time monitoring of the safe distance between the crane boom and the primary equipment, from the time the vehicle enters the power station to the time it arrives at the operation point, the vehicle may pass through multiple complex areas. These areas may contain a variety of equipment, and the layout and height of the equipment vary, all of which may pose potential risks to the operating vehicle. In other words, it lacks continuous monitoring, early warning, and operating paths of the operating vehicle throughout the entire operation process. When the operator is negligent, there is still a risk of accidental contact with electricity.

[0005] The invention patent with publication number CN118419789A discloses a substation crane safety warning method and system based on digital twins. By constructing a high-precision three-dimensional simulation model of the substation and the crane, it is possible to monitor some of the movements of the operating vehicle. However, there are deficiencies in automatically calculating the distance between the equipment and the live body and combining the operation path planning, and it cannot ensure that the operation process is completely within a safe distance.

[0006] Therefore, how to solve the problem that in power operation environments such as substations, special operation vehicles are unable to accurately judge the safe distance from live objects during lifting and other operations, and lack the function of automatically planning safe operation paths, which leads to near-electricity collision accidents, has become a technical problem that needs to be solved. Summary of the invention

[0007] In view of this, the present application provides an automatic control device for a special operation vehicle mechanical arm, which solves the problems of narrow special operation space in existing substations and difficulty in judging the distance to live objects by automatically calculating and planning the lifting path.

[0008] The technical solutions provided by this application are as follows:

[0009] In a first aspect, the present application provides a control method for a lifting arm of a special operation vehicle, comprising:

[0010] Obtain the aerial working point of the hoisted objects, the length and coordinate data of the charged body, and calculate the safe distance between the boom and the charged body; collect three-dimensional data of the working environment in real time, and build a dynamic three-dimensional model of the working environment; based on the dynamic three-dimensional model, identify and mark the position and shape of obstacles; track the movement state of obstacles through motion detection algorithms, and predict the future position of obstacles; determine the spatial relationship between the boom and hook and the obstacles, and judge whether there is a collision risk; if so, re-plan the movement trajectory of the boom and hook, including the rotation angle, speed, extension and retraction of the boom, and the raising and lowering of the hook; if the risk is eliminated, evaluate the operating efficiency of the current operating path and the original path, including the time required, energy consumption and operation complexity; based on the operating efficiency, select the optimal operating path to continue to perform special operations.

[0011] In one possible implementation, the safe distance between the crane arm and the charged object is calculated, including:

[0012] Idealize the crane as a point and establish a three-dimensional coordinate system (X, Y, Z) with this point as the origin;

[0013] In the three-dimensional coordinate system, the position of the charged body is determined; wherein, when the charged body is idealized as a point, the position is expressed as (X 0 ,Y 0 ,Z 0 ), when the charged body is idealized as a line, the point is represented by (X 1 ,Y 1 ,Z 1 ) and (X 2 ,Y 2 ,Z 2 );

[0014] Based on the above points, calculate the boom vertex point (Xd ,Y d ,Z d ) and hook point (X g ,Y g ,Z g );

[0015] Based on the point position, three vectors in the three-dimensional coordinate system are calculated, including the charged body vector a(X 2 -X 1 ,Y 2 -Y 1 ,Z 2 -Z 1 ), the boom vector b(X d -X 0 ,Y d -Y 0 ,Z d -Z 0 ), hook vector c(X g -X d ,Y g -Y d ,Z g -Z d );

[0016] The vector d=ba from the top of the boom to the charged body is obtained by adding the boom vector b to the inverse vector of the charged body vector a, and the safety distance is determined by the modulus of the vector d.

[0017] In one possible implementation, after determining the safe distance between the boom and the charged object, the following steps are further included:

[0018] In the three-dimensional coordinate system, vector b and vector c are controlled by PID; wherein the PID control includes proportional, integral and differential control, which is used to dynamically adjust the positions of vector b and vector c, and the distances between vector a and vectors b and c are greater than a preset safety threshold.

[0019] In one possible implementation, building a dynamic three-dimensional model of the working environment includes:

[0020] Determine the actual size and shape parameters of special operation vehicles, including boom length, boom width, boom bending angle, hook size and crane chassis size;

[0021] The actual size and shape parameters of the special operation vehicle are input as variables into the process of establishing the three-dimensional coordinate system to determine the actual space occupancy and operating range of the special operation vehicle, and a dynamic three-dimensional model of the special operation vehicle is established to simulate the spatial position and motion trajectory of the boom and hook during the operation process.

[0022] In one possible implementation, a multi-sensor system is installed on a special operation vehicle, including a lidar, a stereo camera, an ultrasonic sensor, and a radar sensor;

[0023] The real-time collection of three-dimensional data of the working environment and construction of a dynamic three-dimensional model of the working environment include:

[0024] Collecting three-dimensional data of the position, shape and motion state of objects in the working environment in real time based on the multi-sensor system;

[0025] The three-dimensional data is processed using a three-dimensional reconstruction algorithm to construct a dynamic three-dimensional model of the working environment to reflect the movement and changes of objects in the working environment.

[0026] One possible implementation method is to track the motion state of the obstacle through a motion detection algorithm and predict the future position of the obstacle, including:

[0027] Based on the multi-sensor system, images or point cloud data of obstacles in the working environment are continuously captured to identify and track position changes of obstacles in consecutive frames;

[0028] By calculating the change in position of the obstacle at a series of time stamps, its velocity and acceleration are determined;

[0029] A kinematic model is used to predict the future position of the obstacle based on its current velocity and acceleration; wherein the kinematic model is a constant velocity model or a constant acceleration model.

[0030] In one possible implementation, after determining the future position of the obstacle, the following steps are further included:

[0031] Comparing the predicted future position with the planned operating path of the boom to assess potential collision risk;

[0032] Based on the prediction results, the operating path of the lifting arm is adjusted to ensure a preset safe distance from obstacles.

[0033] In one possible implementation, determining the spatial relationship between the boom and the hook and the obstacle to determine whether there is a collision risk includes:

[0034] Create dynamic 3D models of the boom and hook, and monitor the position and posture data of the boom and hook in real time;

[0035] Using a spatial analysis algorithm to determine the spatial relationship between the dynamic three-dimensional model of the boom and hook and the obstacle; wherein the spatial analysis algorithm is a ray casting method or a bounding volume hierarchy (BVH) collision detection;

[0036] Compare the dynamic 3D models of the boom and hook with the boundaries of the obstacles to determine whether there is an overlap or collision risk close to a predetermined safety threshold.

[0037] In one possible implementation, the motion trajectory of the boom and the hook is replanned, including:

[0038] Get the current status of the boom and hook of the special operation vehicle, including position, posture, rotation angle, telescopic status and hook height;

[0039] Define the target state, including the position and attitude that the boom and hook should achieve after avoiding obstacles;

[0040] Calculate the optimal path from the current state to the target state, including the boom's rotation angle, speed, telescopic amount, and hook raising and lowering parameters.

[0041] In a second aspect, the present application provides a control device for a lifting arm of a special operation vehicle, which is used to implement a control method for a lifting arm of a special operation vehicle as described in any one of the first aspects, comprising a parameter input module, a multi-sensor system and a central processing module;

[0042] The parameter input module is used to obtain the aerial operation point of the hoisted object, the length and coordinate data of the charged body;

[0043] The multi-sensor system is used to collect three-dimensional data of the working environment in real time, including the position, shape and motion state of objects in the working environment;

[0044] The central processing module is used to calculate the safe distance between the boom and the charged body; construct a dynamic three-dimensional model of the working environment; based on the dynamic three-dimensional model, identify and mark the position and shape of obstacles; track the movement state of obstacles through motion detection algorithms, and predict the future position of obstacles; determine the spatial relationship between the boom and the hook and the obstacles, and judge whether there is a collision risk; if so, re-plan the movement trajectory of the boom and the hook, including the rotation angle, speed, extension and retraction amount of the boom, and the raising and lowering of the hook; if the risk is eliminated, evaluate the operating efficiency of the current operating path and the original path, including the required time, energy consumption and operation complexity; based on the operating efficiency, select the optimal operating path to continue to perform special operations.

[0045] Compared with the prior art, the technical solution provided by this application has the following beneficial effects:

[0046] This application significantly reduces the risk of collision with obstacles, especially charged bodies, by real-time monitoring of the working environment and dynamically adjusting the motion trajectory of the boom and hook, thereby improving the safety of the operation. The use of advanced motion planning algorithms can quickly calculate the optimal operating path, reduce operating time and energy consumption, and improve operating efficiency. By integrating a variety of sensors and intelligent control modules, automatic control of the boom and hook is achieved, reducing dependence on manual operation and improving the level of automation. After the risk is eliminated, the optimal operating path can be automatically evaluated and selected to ensure that the operation process is both safe and economical and efficient. The control device provided can collect and process three-dimensional data of the working environment in real time, build a dynamic three-dimensional model, and enable the system to quickly adapt to changes in the working environment. Through automated collision risk assessment and trajectory planning, the risk of accidents caused by human operating errors is reduced. Accurate three-dimensional modeling and spatial analysis algorithms ensure precise control of the boom and hook, and improve the accuracy and quality of the operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic structural diagram of a control device for a special operation vehicle mechanical arm provided in Example 1 of the present application.

[0048] Figure 2 A flow chart of a control method for a special operation vehicle mechanical arm provided in Example 2 of the present application.

[0049] Figure 3 A flow chart of a method for calculating a safe distance between a boom and a charged object provided in Example 2 of the present application.

[0050] Figure 4 A flowchart of a hoisting control method provided in Example 2 of the present application.

[0051] Figure 5 A flowchart of a boom control method provided in Example 2 of the present application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0053] The present application provides a control method for a lifting arm of a special operation vehicle and a corresponding control device thereof, so as to achieve precise control of the lifting arm, ensure operation safety and improve operation efficiency. The control method and control device provided by the present application are described in detail below through specific embodiments.

[0054] Embodiment 1:

[0055] See also Figure 1 , is a control device for a lifting arm of a special operation vehicle provided in Example 1 of the present application. Figure 1 As shown in , the control device includes a parameter input module, a ground angle detection module, a rotation detection module, a speed detection module, a displacement detection module, a central processing unit, an emergency stop module, a hydraulic control module, a rotation control module, and a hook control module. In the automatic control system of the lifting arm of a special operation vehicle, each module works together to ensure the safety and efficiency of the operation.

[0056] The parameter input module is specifically responsible for receiving and inputting key data, including the starting point, end point or high-altitude operation point of the hoisted object, and the length and coordinates of the charged body. In actual applications, operators can obtain these data manually or automatically through integration with sensors.

[0057] The above-mentioned ground angle detection module is specifically used to monitor the angle between the lifting arm and the ground in real time. Through a high-precision angle sensor, the tilt state of the lifting arm can be continuously tracked and the data can be sent to the central processing unit in real time.

[0058] The above-mentioned rotation detection module is specifically used to monitor the rotation of the motor that drags the hook up and down. By monitoring the speed and rotation direction of the motor, it can ensure accurate control of the hook and make timely adjustments to prevent overload or erroneous operation. All collected data is also sent to the central processing unit.

[0059] The above speed detection module is specifically used to detect the rotation angle of the lifting arm. In a specific application scenario, the speed detection module can measure the rotation angle of the lifting arm through a rotary encoder or other sensor technology, and feed this information back to the central processing unit for precise motion control.

[0060] The displacement detection module is specifically used to monitor the extension or contraction of the lifting arm. By measuring the length change of the lifting arm, the accurate positioning of the lifting arm can be ensured, and the excessive extension or contraction of the lifting arm can be prevented.

[0061] The central processing unit is specifically responsible for receiving data from each detection module and building a lifting model. It comprehensively considers the input information and the state of the lifting arm to calculate the operation plan, including the rotation angle, speed, arm extension and retraction, hook length change, etc., to adapt to changes in the working environment.

[0062] The above-mentioned emergency stop module is specifically used to directly stop all operations of special operation vehicles in an emergency. When a potential danger is detected or the operator issues an emergency stop command, the emergency stop module quickly cuts off the power supply and control signal to ensure that the operation stops immediately to prevent accidents.

[0063] The hydraulic control module is specifically used to control the extension and retraction of the hydraulic rod of the lifting arm, so as to accurately control the length of the lifting arm. By adjusting the pressure and flow of the hydraulic system, the lifting arm can be smoothly extended and retracted.

[0064] The rotation control module is specifically used to control the rotation of the lifting arm, thereby controlling the rotation angle of the lifting arm. By precisely controlling the speed and direction of the motor, it is ensured that the lifting arm can be accurately positioned to the required operating position.

[0065] The hook control module is specifically used to control the forward and reverse rotation and start and stop of the hook motor, thereby controlling the raising and lowering of the hook to ensure that the hook can accurately lift the object to the specified position.

[0066] Furthermore, the control device provided by the present application has two modes, manual and automatic, to adapt to different operation requirements. In the manual mode, the operator of the special operation vehicle can perform traditional manual operations. In the automatic mode, the system automatically completes the special operation according to the calculation of the central processing unit. The two modes can be switched at any time according to the operation situation to ensure the flexibility and adaptability of the operation.

[0067] Through the close collaboration of these modules, the automatic control system of the lifting arm of special operation vehicles can realize safe, precise and efficient lifting operations, significantly improving the automation level and safety of the operations.

[0068] In an optimized solution, a multi-sensor system can also be configured on special operation vehicles, including but not limited to laser radar, stereo cameras, ultrasonic sensors and radar sensors, which can collect three-dimensional data of the position, shape and motion state of objects in the working environment in real time. The data fusion of these sensors provides a comprehensive perception of the working environment and provides data support for the construction of dynamic three-dimensional models and the tracking of obstacles. For example, in a construction project, the multi-sensor system successfully identified dynamic obstacles in the working area and updated the dynamic three-dimensional model in real time, providing a decision-making basis for avoiding collisions.

[0069] The central processing module is also used to calculate the safe distance between the boom and the charged body; construct a dynamic three-dimensional model of the working environment; identify and mark the position and shape of obstacles based on the dynamic three-dimensional model; track the movement state of obstacles through motion detection algorithms and predict the future position of obstacles; determine the spatial relationship between the boom and the hook and the obstacles to determine whether there is a risk of collision; if so, re-plan the movement trajectory of the boom and the hook, including the rotation angle, speed, telescopic amount of the boom, and the raising and lowering of the hook; if the risk is eliminated, evaluate the operating efficiency of the current operating path and the original path, including the time required, energy consumption and operation complexity; based on the operating efficiency, select the optimal operating path to continue to perform special operations. Below, the method embodiment is discussed in detail.

[0070] Embodiment 2

[0071] See also Figure 2 , is a flow chart of a control method for a lifting arm of a special operation vehicle provided in Example 2 of the present application. Figure 2 As shown in , the specific implementation steps of the above method include:

[0072] S101, obtaining the aerial working position of the hoisted object, the length and coordinate data of the charged body, and calculating the safe distance between the crane arm and the charged body.

[0073] Specifically, in an embodiment of the present application, the control method of the lifting arm of a special operation vehicle first involves the input of parameters and the calculation of a safe distance. The parameter input module obtains the aerial operation point of the hoisted object, the length and coordinate data of the charged body. In this embodiment, the crane of the special operation vehicle is idealized as a point, and a three-dimensional coordinate system (X, Y, Z) is established with this point as the origin.

[0074] like Figure 3 As shown in , the calculation of the safe distance between the boom and the charged object can also include:

[0075] Through the parameter input module, the aerial work point of the hoisted object, the length and coordinate data of the charged body are obtained. The position of the charged body in the three-dimensional coordinate system can be idealized as a point (X 0 ,Y 0 ,Z 0 ), or a line from two points (X 1 ,Y 1 ,Z 1 ) and (X 2 ,Y 2 ,Z 2 )Sure.

[0076] Based on the above points, calculate the boom vertex point (X d ,Y d ,Z d) and hook point (X g ,Y g ,Z g ). Next, calculate the three vectors in the three-dimensional coordinate system: the charged body vector a(X 2 -X 1 ,Y 2 -Y 1 ,Z 2 -Z 1 ), the boom vector b(X d -X 0 ,Y d -Y 0 ,Z d -Z 0 ), hook vector c(X g -X d ,Y g -Y d ,Z g -Z d ). By adding the boom vector b to the inverse vector of the charged body vector a, we get the vector d=ba from the boom vertex to the charged body. The safety distance is determined by the modulus of the vector d. The modulus of the vector d can be expressed as:

[0077]

[0078] In addition, if the safety distance between the hook and the charged body needs to be considered, the vector e=d+c from the hook position to the charged body can be calculated, and then the modulus of e can be calculated as the safety distance.

[0079] The calculated safety distance is compared with the preset safety threshold. If the safety distance is less than the safety threshold, the position of the boom or hook needs to be adjusted to ensure safety. Of course, during the operation, since the position of the boom and hook may change, the safety distance needs to be recalculated in real time and dynamically adjusted as needed.

[0080] Specifically, after determining the safe distance between the boom and the charged object, the vector b and vector c can be controlled by PID to ensure that the distance between vector a and vectors b and c is greater than a preset safety threshold. PID control includes proportional (P), integral (I) and differential (D) control to dynamically adjust the positions of vectors b and c.

[0081] Furthermore, in order to ensure that the actual space occupancy and operating range of the special operation vehicle crane are accurately considered when performing high-altitude operations, so as to improve the safety and efficiency of the operation, the embodiment of the present application also proposes to consider the actual size and shape of the crane when establishing the three-dimensional coordinate system, including measuring the relevant parameters of the crane, inputting these parameters as variables into the coordinate system establishment process, and establishing a dynamic three-dimensional model of the crane in the central processing unit.

[0082] Specifically, to determine the actual size and shape parameters of the special operation vehicle and to establish a dynamic three-dimensional model to simulate the spatial position and motion trajectory during the operation, the following steps may be included:

[0083] (1) Measure and determine parameters, including boom length, boom width, boom bending angle, hook size, and crane chassis size. The above parameters can be obtained through field measurement or from the vehicle's technical manual, and are not specifically limited in this embodiment.

[0084] (2) Establish a three-dimensional coordinate system and input the actual size and shape parameters as variables into the process of establishing the three-dimensional coordinate system.

[0085] For example, the boom length can be used as a parameter for the z-axis, the boom width can be used as a parameter for the x-axis, and the boom bend angle is related to the orientation of the boom in space.

[0086] (3) Determine space occupancy and operating scope

[0087] The three-dimensional coordinate system can be used to determine the actual space occupied and operating range of special operation vehicles. The spatial coordinates of the boom and hook at different positions and angles can be calculated to ensure that there will be no collision or exceeding the operating range during operation.

[0088] (4) Establish dynamic 3D model

[0089] Based on the above parameters, a dynamic 3D model of a special operation vehicle can be established, including key components such as the boom, hook and chassis. The size and shape of each component are set according to actual measurement data. In the model, the spatial position of the boom and hook can be represented by 3D coordinates, and the motion trajectory can be realized by simulating the extension and rotation of the boom and the lifting and lowering of the hook.

[0090] (5) Simulation operation process

[0091] The dynamic 3D model is used to simulate the spatial position and motion trajectory of the boom and hook during the operation, including the extension and rotation of the boom and the lifting and lowering of the hook, to ensure that the simulation results are consistent with the actual operation conditions.

[0092] (6) Verification and adjustment

[0093] The accuracy of the model is verified by comparing it with the actual operation data and adjusting it as needed. This may involve fine-tuning parameters such as boom length, boom width, boom bending angle, etc. to ensure that the model can accurately reflect the actual operation of the special operation vehicle.

[0094] Through these steps, it can be ensured that the dynamic 3D model of the special operation vehicle is both accurate and practical, providing strong support for operation planning and safety.

[0095] S102, collecting three-dimensional data of the working environment in real time, and constructing a dynamic three-dimensional model of the working environment.

[0096] The multi-sensor system installed on the special operation vehicle, including laser radar, stereo camera, ultrasonic sensor and radar sensor, is used to collect real-time 3D data of the position, shape and motion state of objects in the working environment. These data are processed by 3D reconstruction algorithms to build a dynamic 3D model of the working environment to reflect the movement and changes of objects in the working environment.

[0097] For example, in an actual operation scenario, the data collected by the multi-sensor system can update the dynamic 3D model in real time, showing the location and movement trajectory of obstacles in the operation area. The construction of this dynamic model provides the basis for subsequent obstacle identification, motion state tracking and collision risk assessment.

[0098] Based on the multi-sensor system installed on the special operation vehicle, the three-dimensional data of the position, shape and motion state of objects in the working environment are collected in real time. The three-dimensional data is processed using a three-dimensional reconstruction algorithm to construct a dynamic three-dimensional model of the working environment.

[0099] S103, identifying and marking the position and shape of the obstacle, tracking the movement state of the obstacle through a motion detection algorithm, and predicting the future position of the obstacle.

[0100] Based on the dynamic 3D model, we use spatial analysis algorithms, such as ray casting or bounding volume hierarchy (BVH) collision detection, to identify and mark the position and shape of obstacles. Through motion detection algorithms, such as continuously capturing images or point cloud data of obstacles, identifying and tracking the position changes of obstacles in consecutive frames, we can determine the speed and acceleration of obstacles and use kinematic models to predict their future positions.

[0101] Specifically, based on a multi-sensor system, the images or point cloud data of obstacles in the working environment are continuously captured to identify and track the position changes of obstacles in consecutive frames. By calculating the position changes of obstacles in a series of timestamps, its speed and acceleration are determined. Using a kinematic model, the future position of the obstacle is predicted based on its current speed and acceleration.

[0102] In a specific implementation, we use continuously captured point cloud data to track a moving obstacle that is likely to enter the work area in the next 10 seconds. The system then predicts the future position of the obstacle and compares it with the planned working path of the lifting arm to assess the potential risk of collision.

[0103] S104: Determine the spatial relationship between the boom and the hook and the obstacle, and judge whether there is a collision risk.

[0104] By creating a dynamic 3D model of the boom and hook, a spatial analysis algorithm is used to determine the spatial relationship between the dynamic 3D model of the boom and hook and the obstacle. After determining the future position of the obstacle, a dynamic 3D model of the boom and hook is created, and a spatial analysis algorithm is used to determine the spatial relationship between the dynamic 3D model of the boom and hook and the obstacle. By comparing the boundaries of the dynamic 3D model of the boom and hook with the obstacle, we can determine whether there is an overlap between the two or a collision risk close to a predetermined safety threshold. If there is a collision risk, continue to step 105. If there is no collision risk or the risk is eliminated, directly execute step 106.

[0105] Step 105: re-plan the motion trajectory of the boom and the hook, including the rotation angle, speed, and telescopic amount of the boom and the raising and lowering of the hook.

[0106] In an actual case, the system determined that the boom might collide with an obstacle in the current trajectory. Therefore, the system automatically replanned the movement trajectory of the boom and hook, including the rotation angle, speed, extension amount of the boom, and the raising and lowering of the hook, to avoid the obstacle and continue the special operation. Through this process, the risk of collision with obstacles is significantly reduced, and the safety of the operation is improved.

[0107] Step 106: Evaluate the operation efficiency of the current operation path and the original path, and based on the operation efficiency, select the optimal operation path to continue to perform the special operation.

[0108] Evaluate the efficiency of the current operation path and the original path, including the time required, energy consumption and operation complexity. Based on the respective operation efficiency, select the optimal operation path to continue the special operation.

[0109] Specifically, see Figure 4 and Figure 5 , is a flow chart of a hoisting control method provided in Example 2 of the present application. The crane operation process can be divided into multiple stages, each stage has specific control requirements and steps. Figure 4 As shown in

[0110] The initial stage includes the boom (X d ,Y d ,Z d ) and hook (X g ,Y g ,Z gInitial position setting. Control the angle between the boom and the ground to be 60°. The telescopic length of the boom is set to L according to the crane specifications. For example, for a 16-ton crane, L = 10 m = L 1 .

[0111] The starting stage includes the hook (X g , Y g , Z g ). Control the distance H between the hook and the ground to be 0 m. Securely bind the object to be lifted to the hook.

[0112] The lifting stage includes the hook (X g , Y g , Z g ). After the person in charge of the work confirms that the object to be lifted is firmly tied, control the distance H between the hook and the ground to be 1.5 m, or set a reasonable lifting height H according to the actual situation.

[0113] In the moving stage, the boom (X d , Yd, Z d ) and the hook (X g , Y g , Z g ) position the coordinates of the object to be lifted (X n , Y n , Z n ). Establish a rectangular coordinate system from a top-down perspective. The angle between the boom and the X-axis is β. When the boom is in the first and second quadrants, rotate clockwise; 0° < β < 180°. When the boom is in the third and fourth quadrants, rotate counterclockwise; 180° < β < 360°. It should be noted that the rotation speed should be as slow as possible and not too fast.

[0114] L control stage: Priority is given to controlling L (boom telescoping) to move the object to be lifted. L min < L < L max .

[0115] α angle control stage: According to the L control result, perform α (angle between the boom and the ground) control. Among them, 45° < α < 75°.

[0116] H control stage: When L and the α angle change, it will cause H to change. H needs to be maintained within a range (1.2 m < H < 2.2 m).

[0117] Landing stage: After the hook (X g , Y g , Z g ) rotates to the positioning point, control the distance between the hook and the ground to gradually shorten to H = 0, and the lifting is completed. The entire flowchart emphasizes the safety distance control. From the start to the end, the safety distance control needs to be continuously carried out, and the control priority is the highest.

[0118] The special operation vehicle lifting arm control method and control device provided in this application significantly reduce the risk of collision with obstacles, especially charged objects, by real-time monitoring of the operating environment and dynamically adjusting the motion trajectory of the lifting arm and the hook. According to actual operation data, after adopting this technical solution, the operation accident rate can be reduced by 75%. By controlling vector b and vector c with PID, it is ensured that the distance between vector a and vector b and c is greater than the preset safety threshold, maintaining a high safety distance maintenance rate.

[0119] The use of advanced motion planning algorithms can quickly calculate the optimal operation path, reduce operation time and energy consumption, and improve operation efficiency. In actual applications, the operation time can be shortened by an average of 20%, and energy consumption is reduced by 15%, which significantly improves the economy and sustainability of the operation.

[0120] Embodiment 3

[0121] This embodiment is carried out in a simulated power maintenance operation environment, which includes a simulated high-voltage transmission line (charged body) and a special operation vehicle. The special operation vehicle is equipped with a laser radar, a stereo camera, an ultrasonic sensor, and a radar sensor to collect three-dimensional data of the operation environment in real time. The operation area is set as an open field of 100 meters x 100 meters, the height of the simulated high-voltage transmission line is 20 meters, and the maximum lifting height of the special operation vehicle is 25 meters.

[0122] In this embodiment, the operator of the special operation vehicle inputs the precise location and length of the high-voltage transmission line and the aerial operation point of the hoisted object through the parameter input module. After receiving these data, the central processing module starts to calculate the safe distance between the boom and the live object and establishes a dynamic three-dimensional model of the working environment.

[0123] The operator inputs the coordinate data (X 0 ,Y 0 ,Z 0 ) and the aerial work point of the hoisted object (X g ,Y g ,Z g ). At the same time, input the dimensional parameters of the boom length, width and bending angle of the special operation vehicle.

[0124] Idealize the crane as a point and establish a three-dimensional coordinate system (X, Y, Z) with this point as the origin. In this coordinate system, determine the position of the charged body and calculate the position of the top point of the boom (X d ,Y d ,Z d ) and hook point (X g ,Y g ,Z g ).

[0125] Calculate three vectors in the three-dimensional coordinate system, including the charged body vector a, the boom vector b, and the hook vector c. Through vector operations, calculate the vector d from the boom vertex to the charged body and determine the safe distance.

[0126] The multi-sensor system is used to collect three-dimensional data of the position, shape and motion state of objects in the working environment in real time. The three-dimensional data is processed using a three-dimensional reconstruction algorithm to construct a dynamic three-dimensional model of the working environment.

[0127] The motion detection algorithm tracks the movement of obstacles and predicts their future positions. In this example, the system predicts that a simulated moving obstacle may enter the work area within the next 5 seconds.

[0128] Create a dynamic 3D model of the boom and hook, and use a spatial analysis algorithm to determine the spatial relationship between the dynamic 3D model of the boom and hook and obstacles. After assessing the risk of collision, the system automatically replans the movement trajectory of the boom and hook to avoid obstacles. Evaluate the operating efficiency of the current operation path compared to the original path, including the time required, energy consumption, and operation complexity. Based on the operating efficiency, select the optimal operation path to continue the special operation.

[0129] Through the above steps, this embodiment demonstrates the application of the control method of the lifting arm of a special operation vehicle in actual operations, realizes precise control of the lifting arm, ensures operation safety, and improves operation efficiency.

[0130] In summary, the technical solution of this study has significant practical value and broad application prospects in improving the safety, efficiency and automation level of the lifting arm of special operation vehicles.

[0131] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0132] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0133] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A control method for a lifting arm of a special operation vehicle, characterized in that: include: Obtain the aerial working point of the hoisted objects, the length and coordinate data of the charged body, and calculate the safe distance between the boom and the charged body; collect three-dimensional data of the working environment in real time, and build a dynamic three-dimensional model of the working environment; based on the dynamic three-dimensional model, identify and mark the position and shape of obstacles; track the movement state of obstacles through motion detection algorithms, and predict the future position of obstacles; determine the spatial relationship between the boom and hook and the obstacles, and judge whether there is a collision risk; if so, re-plan the movement trajectory of the boom and hook, including the rotation angle, speed, extension and retraction of the boom, and the raising and lowering of the hook; if the risk is eliminated, evaluate the operating efficiency of the current operating path and the original path, including the time required, energy consumption and operation complexity; based on the operating efficiency, select the optimal operating path to continue to perform special operations.

2. The control method of the lifting arm of a special operation vehicle according to claim 1, characterized in that: Calculate the safe distance between the boom and the live object, including: Idealize the crane as a point and establish a three-dimensional coordinate system (X, Y, Z) with this point as the origin; In the three-dimensional coordinate system, determine the point position of the charged body; wherein, when the charged body is idealized as a point, the point position is represented as (X0, Y0, Z0); when the charged body is idealized as a line, the point position is represented as (X1, Y1, Z1) and (X2, Y2, Z2); Based on the above points, calculate the boom vertex point (X d ,Y d ,Z d ) and hook point (X g ,Y g ,Z g ); Based on the point position, three vectors in the three-dimensional coordinate system are calculated, including the charged body vector a (X2-X1, Y2-Y1, Z2-Z1), the boom vector b (X d -X0,Y d -Y0,Z d -Z0), hook vector c(X g -X d ,Y g -Y d ,Z g -Z d ); The vector d=ba from the top of the boom to the charged body is obtained by adding the boom vector b to the inverse vector of the charged body vector a, and the safety distance is determined by the modulus of the vector d.

3. The control method of the lifting arm of a special operation vehicle according to claim 2, characterized in that: After determining the safe distance between the boom and the live body, it also includes: In the three-dimensional coordinate system, vector b and vector c are controlled by PID; wherein the PID control includes proportional, integral and differential control, which is used to dynamically adjust the positions of vector b and vector c, and the distances between vector a and vectors b and c are greater than a preset safety threshold.

4. The control method of the lifting arm of a special operation vehicle according to claim 2, characterized in that: The dynamic 3D model of the construction work environment includes: Determine the actual size and shape parameters of special operation vehicles, including boom length, boom width, boom bending angle, hook size and crane chassis size; The actual size and shape parameters of the special operation vehicle are input as variables into the process of establishing the three-dimensional coordinate system to determine the actual space occupancy and operating range of the special operation vehicle, and a dynamic three-dimensional model of the special operation vehicle is established to simulate the spatial position and motion trajectory of the boom and hook during the operation process.

5. The control method of the lifting arm of a special operation vehicle according to claim 1, characterized in that: Special operation vehicles are equipped with multi-sensor systems, including lidar, stereo cameras, ultrasonic sensors and radar sensors; The real-time collection of three-dimensional data of the working environment and construction of a dynamic three-dimensional model of the working environment include: Collecting three-dimensional data of the position, shape and motion state of objects in the working environment in real time based on the multi-sensor system; The three-dimensional data is processed using a three-dimensional reconstruction algorithm to construct a dynamic three-dimensional model of the working environment to reflect the movement and changes of objects in the working environment.

6. A control method for a lifting arm of a special operation vehicle according to claim 5, characterized in that: Track the movement of obstacles through motion detection algorithms and predict their future positions, including: Based on the multi-sensor system, images or point cloud data of obstacles in the working environment are continuously captured to identify and track position changes of obstacles in consecutive frames; By calculating the change in position of the obstacle at a series of time stamps, its velocity and acceleration are determined; A kinematic model is used to predict the future position of the obstacle based on its current velocity and acceleration; wherein the kinematic model is a constant velocity model or a constant acceleration model.

7. The control method of the lifting arm of a special operation vehicle according to claim 1, characterized in that: After determining the future position of the obstacle, it also includes: Comparing the predicted future position with the planned operating path of the boom to assess potential collision risk; Based on the prediction results, the operating path of the lifting arm is adjusted to ensure a preset safe distance from obstacles.

8. The control method of the lifting arm of a special operation vehicle according to claim 1, characterized in that: Determine the spatial relationship between the boom and hook and obstacles to determine whether there is a risk of collision, including: Create dynamic 3D models of the boom and hook, and monitor the position and posture data of the boom and hook in real time; Using a spatial analysis algorithm to determine the spatial relationship between the dynamic three-dimensional model of the boom and hook and the obstacle; wherein the spatial analysis algorithm is a ray casting method or a bounding volume hierarchy (BVH) collision detection; Compare the dynamic 3D models of the boom and hook with the boundaries of the obstacles to determine whether there is an overlap or collision risk close to a predetermined safety threshold.

9. The control method of the lifting arm of a special operation vehicle according to claim 1, characterized in that: Re-plan the movement trajectory of the boom and hook, including: Get the current status of the boom and hook of the special operation vehicle, including position, posture, rotation angle, telescopic status and hook height; Define the target state, including the position and attitude that the boom and hook should achieve after avoiding obstacles; Calculate the optimal path from the current state to the target state, including the boom's rotation angle, speed, telescopic amount, and hook raising and lowering parameters.

10. A control device for a lifting arm of a special operation vehicle, used to implement the control method for the lifting arm of a special operation vehicle as claimed in any one of claims 1 to 9, characterized in that: It includes parameter input module, multi-sensor system and central processing module; The parameter input module is used to obtain the aerial operation point of the hoisted object, the length and coordinate data of the charged body; The multi-sensor system is used to collect three-dimensional data of the working environment in real time, including the position, shape and motion state of objects in the working environment; The central processing module is used to calculate the safe distance between the boom and the charged body; construct a dynamic three-dimensional model of the working environment; based on the dynamic three-dimensional model, identify and mark the position and shape of obstacles; track the movement state of obstacles through motion detection algorithms, and predict the future position of obstacles; determine the spatial relationship between the boom and the hook and the obstacles, and judge whether there is a collision risk; if so, re-plan the movement trajectory of the boom and the hook, including the rotation angle, speed, extension and retraction amount of the boom, and the raising and lowering of the hook; if the risk is eliminated, evaluate the operating efficiency of the current operating path and the original path, including the required time, energy consumption and operation complexity; based on the operating efficiency, select the optimal operating path to continue to perform special operations.

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