Method and system for controlling the operating posture of a bridge crane

Abstract

The present application relates to a kind of bridge crane operating posture control method and control system, for heavy precise hoisting in narrow space, method includes: obtaining operating area space constraint information generates space map, determines hoisting path and path width;Planning the driving mechanism along the path center line travel trajectory, mark direction switching node and calculate the walking distance of each straight section;According to the width of the next section path, determine the maximum allowable swing range;Combining walking distance and swing space, formulate speed control scheme, ensure that heavy swing is not over limit when direction switches.The present application actively plans swing space and intelligently adjusts motion parameters, significantly improves hoisting efficiency while ensuring safety.

Description

Technical Field

[0001] This invention relates to the field of bridge crane operation control technology, and in particular to a bridge crane operation posture control method and control system. Background Technology

[0002] Bridge cranes, as a common material handling equipment, are mainly composed of a bridge spanning the work area, a crane trolley that moves the bridge, a crane carriage that moves along the bridge, and a lifting device suspended below the crane carriage. This structural feature gives them significant advantages in large-scale material handling in fixed locations such as factory workshops and warehouses.

[0003] However, when bridge cranes perform precision lifting operations in confined spaces, the swaying problem caused by inertia of the hoisted load becomes particularly prominent. Traditional technologies mainly focus on how to prevent or reduce this swaying. Common methods include improving the mechanical structure to increase system damping, using an active anti-sway control system to adjust the length of the hoisting rope in real time, or deliberately reducing the operating speed during operation.

[0004] While these methods can alleviate the swaying problem to some extent, they have obvious limitations: mechanical structure improvements often increase equipment complexity and cost; active anti-sway control has extremely high requirements for sensor accuracy and control system response speed; and simply reducing the operating speed will significantly affect work efficiency; more importantly, existing technologies generally ignore the spatial constraints of the working environment and fail to organically combine anti-sway control with the geometric characteristics of the specific work path, making it difficult to balance operating efficiency and anti-sway accuracy in narrow spaces. Summary of the Invention

[0005] Therefore, the technical problem to be solved by the present invention is to overcome the problems of low efficiency and complex control of bridge cranes when operating in narrow spaces due to passive suppression of sway in the prior art. The present invention provides a bridge crane working posture control method and control system that can significantly improve lifting efficiency while ensuring safety by actively planning the sway space and intelligently adjusting motion parameters in combination with path constraints.

[0006] To address the aforementioned technical problems, this invention provides a method for controlling the working posture of a bridge crane, used for the precise lifting of heavy objects in confined spaces, comprising the following steps:

[0007] Acquire spatial constraint information of the work area, generate a spatial map containing obstacle locations and safety boundaries, and determine the hoisting path and path width based on the spatial map;

[0008] The travel trajectory of the bridge crane drive mechanism is determined based on the hoisting path and path width, so that the drive mechanism runs along the centerline of the hoisting path;

[0009] In the hoisting path, the position where the direction of motion of the drive mechanism changes is marked as the direction switching node, and the travel distance of the drive mechanism in each straight motion segment is determined according to the spacing between adjacent direction switching nodes.

[0010] When the drive mechanism changes the direction of motion at the direction switching node, it determines the maximum spatial range in which the heavy object can swing due to inertia based on the path width of the next linear motion segment at the direction switching node.

[0011] Based on the travel distance of the drive mechanism in each linear motion segment and the maximum allowable space range for the swing of the load, determine the speed control scheme of the drive mechanism in each linear motion segment so that when the drive mechanism stops at the direction switching node and changes the direction of motion, the swing range of the suspended load will not exceed the path width.

[0012] In one embodiment of the present invention, obtaining the spatial constraint information of the work area specifically includes the following steps:

[0013] Multiple directional detection units are deployed at the boundary of the work area. Each directional detection unit is independently configured to transmit and receive detection signals. The initial detection direction formed by the multiple directional detection units covers the entire range of the work area, and the multiple directional detection units are synchronized through a communication link.

[0014] Each directional detection unit transmits multi-frequency detection signals at preset time intervals and receives environmental reflected signals. Based on the intensity deviation and delay time of the reflected signals, a preliminary set of detection points is generated, and each detection point includes coordinate position and signal characteristics.

[0015] The consistency of signal characteristics between the same detection point is verified based on different directional detection units. When the density of detection points is lower than the preset threshold or the signal characteristics deviate from the standard value, the area is determined to be an abnormal area and a correction command is triggered.

[0016] Adjust the detection direction of the relevant adjustable detection unit or increase the detection signal frequency to perform supplementary scanning, obtain a corrected detection point set, and eliminate detection blind spots;

[0017] By integrating the initial and corrected detection point sets, a spatial map is generated through spatial interpolation and boundary fitting. This spatial map identifies the location of obstacles and determines the safety boundaries.

[0018] In one embodiment of the present invention, determining the hoisting path and path width based on a spatial map includes the following steps:

[0019] Based on the obstacle location information in the spatial map, fit the minimum bounding geometry of each obstacle and calculate the minimum distance between each geometry;

[0020] Select a starting point and an ending point in the spatial map, and generate an initial path based on the minimum spacing of the obstacle geometry. This initial path consists of several straight line segments and direction switching nodes.

[0021] For each straight segment of the initial path, scan the spatial map along its extension direction to obtain the distance between obstacles on both sides of that segment.

[0022] Calculate the minimum safety margin for this path segment based on the motion error compensation value of the drive mechanism of the bridge crane;

[0023] Subtract the minimum safety margin from the obstacle spacing to obtain the usable width of the path segment, which is then used as the final path width for that segment.

[0024] In one embodiment of the present invention, determining the travel trajectory of the bridge crane drive mechanism based on the hoisting path and path width, and causing the drive mechanism to run along the centerline of the hoisting path, includes the following steps:

[0025] A dynamic local coordinate system is established with the starting point of the hoisting path as the origin and along the extension direction of the hoisting path. The coordinate system direction is updated at each switching node in each direction.

[0026] During the movement of the drive mechanism along the hoisting path, the lateral deviation between its actual position and the center line of the path is monitored in real time.

[0027] When there is a lateral deviation in the drive mechanism, a correction command is generated to adjust the direction of movement of the drive mechanism so that it moves closer to the center line.

[0028] The corrected motion data of the drive mechanism is used as an executable trajectory command to ensure that it runs strictly along the centerline of the hoisting path.

[0029] In one embodiment of the present invention, the maximum spatial range in which the weight is allowed to swing due to inertia does not exceed 80% of the path width of the next motion segment.

[0030] In one embodiment of the present invention, determining the speed control scheme of the drive mechanism in each linear motion segment includes the following steps:

[0031] When the travel distance of the linear motion segment exceeds the minimum safe braking distance, the speed control scheme is set to a three-stage control, including:

[0032] Initial acceleration phase: Accelerate to the first speed v with a preset acceleration a1;

[0033] Constant speed segment: Maintain the initial speed v while traveling;

[0034] Final deceleration phase: Decelerate to a stop at a preset deceleration rate a2;

[0035] The first velocity v is determined based on the maximum spatial range in which the weight is allowed to swing at the direction switching node, and satisfies v≤√(a2·Lmax), where Lmax is the maximum spatial range in which the weight is allowed to swing.

[0036] In one embodiment of the present invention, when the travel distance of the linear motion segment is less than the minimum safe braking distance, the speed control scheme is set to a two-stage control, including:

[0037] Acceleration phase: Accelerate to the adjusted second speed v' using the preset acceleration a1;

[0038] Deceleration phase: Decelerate to a stop at a preset deceleration rate a2;

[0039] The adjusted speed v' satisfies: v'≤√[2a1a2D / (a1+a2)] and v'≤√(a2·Lmax), where D is the walking distance.

[0040] In one embodiment of the present invention, the mass of the hoisted object is obtained, and the acceleration a1 and deceleration a2 are dynamically adjusted according to the mass of the hoisted object, wherein: the larger the mass of the hoisted object, the smaller the absolute values ​​of the acceleration a1 and deceleration a2.

[0041] In one embodiment of the present invention, when the drive mechanism reaches the direction switching node, the following steps are further included:

[0042] Real-time detection of the actual swing amplitude of the suspended load;

[0043] Compare the actual swing amplitude with the maximum allowable spatial range for the weight to swing.

[0044] If the actual swing amplitude exceeds the maximum spatial range, the motion control scheme of the drive mechanism is adjusted, including at least one of the following methods:

[0045] Extend the stopping time of the drive mechanism at the direction switching node, and start the next motion segment only after the swing of the heavy object has decayed to a safe range;

[0046] Reduce the speed of the drive mechanism in the next motion segment;

[0047] Adjust the acceleration or deceleration of the next motion segment to reduce the swing amplitude of the weight.

[0048] To address the aforementioned technical problems, the present invention also provides a bridge crane operating posture control system for implementing the above control method, comprising:

[0049] The spatial information acquisition module is used to acquire spatial constraint information of the work area and generate a spatial map containing obstacle locations and safety boundaries.

[0050] The path planning module is used to determine the hoisting path and path width based on the spatial map;

[0051] The trajectory generation module is used to determine the travel trajectory of the bridge crane drive mechanism based on the hoisting path and path width, so that the drive mechanism runs along the centerline of the hoisting path;

[0052] The node marking module is used to mark the position where the movement direction of the drive mechanism changes as a direction switching node, and to determine the travel distance of the drive mechanism in each linear motion segment based on the spacing between adjacent direction switching nodes.

[0053] The swing space calculation module is used to determine the maximum spatial range in which the weight can swing due to inertia at the direction switching node, based on the path width of the next linear motion segment.

[0054] The motion control module is used to determine the speed control scheme of the drive mechanism in each linear motion segment based on the travel distance of the drive mechanism in each linear motion segment and the maximum space range in which the load can swing, so that when the drive mechanism stops and changes the direction of motion at the direction switching node, the swing range of the suspended load does not exceed the path width.

[0055] The technical solution of the present invention has the following advantages compared with the prior art:

[0056] The bridge crane operation posture control method described in this invention shifts from passively suppressing sway to actively planning and managing the sway space. This method first establishes a spatial map including obstacle locations and safety boundaries to accurately quantify the available space range of the hoisting path. When determining the driving mechanism's travel trajectory, it pays special attention to the handling of direction-switching nodes—these nodes are not only turning points where the direction of movement changes, but also key decision points for sway control. By pre-calculating the straight-line motion segment distance between adjacent nodes and dynamically determining the maximum allowable sway space range in conjunction with the path width, the motion control parameters of the driving mechanism can be adjusted.

[0057] The core of the control strategy of this invention lies in: instead of eliminating swaying, it combines path planning with precise calculations to constrain the swaying within the allowable range of the path width, thereby achieving natural kinetic energy conversion at the direction switching node; when the drive mechanism stops and turns, the swaying energy of the weight is just absorbed by the path width without producing a cumulative effect.

[0058] This space-adaptive control method avoids the complex modifications to the mechanical structure required by traditional anti-sway technology, and breaks through the efficiency bottleneck caused by simply relying on deceleration. It significantly improves hoisting efficiency in narrow spaces while ensuring operational safety. Attached Figure Description

[0059] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein:

[0060] Figure 1 This is a flowchart of the steps of the bridge crane operation posture control method of the present invention;

[0061] Figure 2 This is a flowchart illustrating the steps of obtaining spatial constraint information of the work area according to the present invention;

[0062] Figure 3 This is a flowchart illustrating the steps of the intelligent path planning method based on spatial modeling of the present invention.

[0063] Figure 4 This is a flowchart of the steps of the high-precision trajectory tracking control scheme of the present invention;

[0064] Figure 5 This is a flowchart of the steps of the adaptive speed control strategy based on the length of the motion segment in this invention;

[0065] Figure 6 This is a flowchart of the steps of the security control mechanism based on real-time detection in this invention;

[0066] Figure 7 This is a structural framework diagram of the bridge crane operation posture control system of the present invention. Detailed Implementation

[0067] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0068] Reference Figure 1 As shown, this invention discloses a method for controlling the working posture of a bridge crane, used for precise lifting of heavy objects in confined spaces, comprising the following steps:

[0069] Acquire spatial constraint information of the work area, generate a spatial map containing obstacle locations and safety boundaries, and determine the hoisting path and path width based on the spatial map;

[0070] This step is the foundation of the entire control method. Its core lies in digitizing the working environment to ensure that the planning of the hoisting path conforms to the actual spatial constraints. Traditional anti-sway control often only focuses on the movement of the crane itself, while ignoring the impact of environmental constraints on sway. The control method of this invention can quantify the path width by establishing an accurate spatial map, thereby providing key spatial parameters for subsequent sway control. This not only avoids the risk of collision, but also optimizes path selection and improves hoisting efficiency.

[0071] The travel trajectory of the bridge crane drive mechanism is determined based on the hoisting path and path width, so that the drive mechanism runs along the centerline of the hoisting path;

[0072] Specifically, since the path width directly affects the allowable range of the load's swing, the drive mechanism can maximize the use of available space by running along the centerline. If the drive mechanism deviates from the centerline, the load may swing closer to obstacles, increasing the risk of collision. This step ensures that the crane always runs on the optimal path, providing a stable reference for subsequent swing control, reducing unnecessary adjustments, and improving operational stability.

[0073] In the hoisting path, the position where the direction of motion of the drive mechanism changes is marked as the direction switching node, and the travel distance of the drive mechanism in each straight motion segment is determined according to the spacing between adjacent direction switching nodes.

[0074] Specifically, the direction switching node is a critical control point because the drive mechanism stops at the direction switching node, and the weight will swing forward relative to the drive mechanism due to inertia. Coincidentally, at the direction switching node, the weight's swing is most likely to exceed the safe range due to the presence of obstacles in front. By marking these nodes and calculating the distance between adjacent nodes, the system can accurately divide the linear motion segments, providing a segmentation basis for subsequent speed control. Traditional methods often ignore the special influence of the turning point, leading to accumulated or sudden increases in swing. However, this method, through segmented control, ensures that each segment of motion can be optimized independently, improving the precision of control.

[0075] When the drive mechanism changes the direction of motion at the direction switching node, it determines the maximum spatial range in which the heavy object can swing due to inertia based on the path width of the next linear motion segment at the direction switching node.

[0076] The core of this step lies in dynamically adjusting the allowable swing space. Since the width of different path segments may vary, traditional fixed anti-sway strategies may lead to excessive deceleration or uncontrolled swing. This method adjusts the allowable swing range in real time according to the width of the next path segment to ensure that the heavy object does not exceed the limit of the next path segment when turning. This can make full use of the space and avoid the impact of overly conservative control strategies on efficiency.

[0077] Based on the travel distance of the drive mechanism in each linear motion segment and the maximum allowable space range for the swing of the load, determine the speed control scheme of the drive mechanism in each linear motion segment so that when the drive mechanism stops and changes the direction of motion at the direction switching node, the swing range of the suspended load will not exceed the path width.

[0078] The final step integrates all the previous calculations and achieves precise anti-sway through intelligent speed control. Traditional methods usually use fixed deceleration or open-loop control, which is difficult to adapt to different loads and path conditions. This method combines the walking distance and the allowable swing range to dynamically adjust the speed curve, ensuring that the heavy object decelerates naturally when turning, and the swing energy is absorbed by the path width rather than forcibly suppressed. This ensures safety and avoids the efficiency loss caused by frequent starts and stops.

[0079] The technical solution of this application achieves refined control over the hoisting process of bridge cranes through environmental perception, path optimization, segmented control, and dynamic speed adjustment. Compared with traditional anti-sway technology, this invention actively manages sway rather than passively suppresses it, making full use of the path width as a sway buffer space to avoid over-reliance on mechanical damping or forced deceleration. It also adopts a segmented dynamic optimization strategy to formulate differentiated control strategies for different straight segments and turning points to improve adaptability. By deeply integrating environmental perception and motion control, the anti-sway strategy is matched with specific operating scenarios to achieve a balance between safety and efficiency.

[0080] Based on the above embodiments, the core technology of the present invention lies in managing the swing of heavy objects by combining environmental perception and intelligent control. However, in actual engineering applications, the key step of "obtaining spatial constraint information of the work area" may have insufficient environmental perception accuracy. Traditional environmental detection methods often use fixed sensors or single detection devices, which are prone to generating blind spots in complex and narrow spaces and are difficult to cope with dynamically changing work environments. This will result in insufficient accuracy of the generated spatial map, which in turn affects the effectiveness of subsequent path planning and anti-sway control.

[0081] To address this problem, the present invention also proposes a technical solution for obtaining spatial constraint information of the work area to generate a spatial map containing obstacle locations and safety boundaries, referring to... Figure 2 As shown, it includes:

[0082] Deployment of directional detection units: Multiple directional detection units are deployed at the boundary of the work area. Each directional detection unit is independently configured to transmit and receive detection signals. The initial detection direction formed by multiple directional detection units covers the entire range of the work area, and the multiple directional detection units are synchronized through communication links.

[0083] High-precision environmental modeling is achieved through a distributed intelligent detection system. This solution first deploys multiple directional detection units at the boundary of the work area. These units not only have the ability to independently transmit and receive detection signals, but can also work collaboratively through communication links. This distributed architecture ensures that the detection range can completely cover the entire work area, avoiding the inherent field-of-view limitations of a single sensor.

[0084] The direction-shifting detection unit performs sequential spatial scanning: each direction-shifting detection unit transmits multi-frequency detection signals at preset time intervals and receives environmental reflected signals. Based on the intensity deviation and delay time of the reflected signals, a preliminary set of detection points is generated, and each detection point includes coordinate position and signal characteristics.

[0085] In practice, each detection unit transmits detection signals containing multiple frequency bands at preset time intervals. This multi-frequency detection strategy can effectively distinguish obstacles of different materials and improve the identification of environmental features. The preliminary detection point set generated based on the intensity deviation and delay time of the reflected signal not only contains spatial coordinate information but also records the signal characteristics of the object surface, providing an important basis for subsequent data verification.

[0086] Identify abnormal areas in the initial detection point set: Verify the consistency of signal characteristics between the same detection points based on different directional detection units. When the density of detection points is lower than the preset threshold or the signal characteristics deviate from the standard value, the area is determined to be an abnormal area and a correction command is triggered.

[0087] To ensure the reliability of the detection data, a data verification mechanism was specially designed. By comparing the consistency of signal characteristics of different detection units at the same detection point, abnormal data can be identified and eliminated. When the system detects that the density of detection points in a certain area is insufficient or the signal characteristics are abnormal, it will intelligently trigger the correction process. This process reflects the system's adaptive capability.

[0088] Dynamic repeated detection is performed on abnormal areas: the detection direction of the relevant adjustable detection unit is adjusted or the detection signal frequency is increased, and supplementary scanning is performed to obtain a corrected detection point set to eliminate detection blind spots; more complete spatial data is obtained through supplementary scanning. This dynamic adjustment mechanism effectively solves the detection blind spot problem that traditional methods are prone to when facing complex structures or reflective surfaces, and significantly improves the robustness of environmental modeling.

[0089] Generate a spatial map: Integrate the calibrated initial and corrected detection point sets, and generate a spatial map through spatial interpolation and boundary fitting. This spatial map marks the location of obstacles and determines the safety boundaries.

[0090] After data acquisition and verification, the system generates the final spatial map through spatial interpolation algorithms and boundary fitting techniques. This process fully considers the actual needs of the industrial site: spatial interpolation can smoothly process discrete detection point data and build a continuous environmental model; boundary fitting accurately marks the outline of obstacles and safe operating boundaries.

[0091] Compared with conventional detection methods, the method in this embodiment has three significant advantages: first, it achieves blind-spot-free full-coverage scanning through multi-unit collaborative detection; second, it ensures data reliability by utilizing multi-frequency signals and cross-validation; and third, the adaptive correction mechanism ensures stable operation of the system in complex environments. This enables the generated spatial map to accurately reflect the real constraints of the work area, providing a reliable data foundation for path planning and anti-shake control.

[0092] From a technical perspective, each design element of the method in this embodiment addresses key issues in environmental perception. The distributed detection unit layout solves the spatial coverage problem, the multi-frequency signal design improves feature recognition capabilities, the dynamic correction mechanism ensures data integrity, and intelligent data processing optimizes map generation quality. The synergistic effect of these technical features enables the entire system to stably acquire high-precision spatial constraint information in actual industrial environments, thereby effectively supporting the implementation of the control method described in this invention.

[0093] It should be noted that the technical solution of this application is different from the existing technology in generating trajectory paths. Because the swing space of the heavy object needs to be accurately reserved when planning the path, this application not only needs to determine the hoisting path based on the spatial map, but also needs to analyze the path width in order to convert the spatial map data into the hoisting path planning scheme that can be executed by this invention.

[0094] Traditional path planning methods often treat obstacles simply as points or regular geometric shapes, ignoring the mechanical errors and dynamic swaying characteristics of cranes in actual movement. This may lead to safety hazards or overly conservative issues in the actual execution of the planned path. In particular, for large equipment such as bridge cranes, the inherent characteristics of their drive mechanism, such as positioning errors and transmission clearances, as well as the swaying characteristics of the suspended load, will significantly affect the actual usable safe working space.

[0095] To address this key technical problem, this invention also proposes an intelligent path planning method based on accurate spatial modeling, referring to... Figure 3 As shown, this method includes the following steps:

[0096] Extracting obstacle outlines from the spatial map: First, the generated high-precision spatial map is subjected to depth processing. By fitting the minimum bounding geometry of the obstacles, the complex environmental constraints are transformed into computable geometric relationships. This process not only retains the accuracy advantage of the original spatial map, but also simplifies the subsequent computational complexity through geometric abstraction. When calculating the minimum spacing between each geometry, the system comprehensively considers the three-dimensional spatial relationships to ensure that the planned path has sufficient safety space at any height level.

[0097] This approach, based on minimum bounding geometry, is particularly suitable for regular-shaped obstacles commonly found in industrial settings, such as equipment and columns, and can maximize available workspace while ensuring safety.

[0098] Determine the initial feasible path: When generating the initial path, the system will automatically generate the optimal path composed of straight segments and direction switching nodes based on the starting point, ending point and obstacle geometry information. This method pays special attention to the characteristics of the straight segments of the path, in order to adapt to the basic movement mode of the bridge crane and reduce unnecessary turning operations.

[0099] Calculate the dynamic width of each segment of the path: For each straight path segment, the system will perform a spatial scan along its extension direction to accurately obtain the actual distance between obstacles on both sides of the path segment; this step makes full use of the fine spatial map data provided by the present invention, realizing millimeter-level gap detection capability, and providing accurate input for subsequent safety margin calculation.

[0100] Motion error compensation: Considering the various uncertainties in the actual operation of bridge cranes, the concept of motion error compensation value is introduced. This parameter comprehensively considers the positioning accuracy of the drive mechanism, the backlash of the transmission system, structural deformation and other mechanical characteristics, as well as the response delay of the control system and other electrical characteristics. It is dynamically adjusted based on experimental data or historical operating data. The minimum safety margin calculated based on this compensation value can effectively cover the deviations that may be caused by the movement of the equipment itself, and fundamentally avoid safety hazards caused by mechanical errors.

[0101] Generate the final hoisting path and path width: Subtract this dynamic safety margin from the precisely measured obstacle spacing. The final path width ensures absolute safety while avoiding the path narrowing problem caused by excessive conservatism in traditional methods.

[0102] From a technical mechanism perspective, each technical feature in this embodiment addresses key challenges in path planning. Specifically, minimum circumscribed geometric fitting ensures the accuracy of environmental modeling, straight segment scanning enables precise measurement of path gaps, and motion error compensation bridges the gap between theory and practice. The organic combination of these technical features ensures that the planned hoisting path conforms to the motion characteristics of the equipment while making full use of available space.

[0103] Especially in confined space operation scenarios, this refined path planning method can significantly improve operation efficiency. This means that the crane can operate at a higher speed while still ensuring safety, directly improving the overall efficiency of hoisting operations. At the same time, since the path width calculation already includes compensation for equipment motion errors, when actually implementing the control method described in this invention, the system can more confidently approach the edge of the planned path, leaving more space for the swing of the hoisted load.

[0104] A key challenge in practical implementation is ensuring that the drive mechanism strictly follows the planned centerline trajectory. Traditional control methods typically employ absolute position control in a global coordinate system, which can easily accumulate errors after long-distance operation or multiple turns. Especially in confined spaces, even minor trajectory deviations can lead to insufficient swing space for the suspended load, or even collision risks. Furthermore, as large mechanical equipment, the slippage of the drive wheels and the clearance in the transmission system of bridge cranes affect trajectory tracking accuracy, and traditional control methods often fail to adequately consider these practical factors.

[0105] To address this key technical problem, this invention also proposes a high-precision trajectory tracking control scheme in a dynamic local coordinate system, referring to... Figure 4 As shown, the control scheme includes the following steps:

[0106] Establish a reference coordinate system for the path centerline: By adopting a dynamic local coordinate system with the path starting point as the origin, the complex global positioning problem is transformed into a relatively simple local trajectory tracking problem. The design of updating the coordinate system direction at each direction switching node effectively eliminates the error accumulation problem caused by multiple turns in the traditional method. This dynamic reference system transformation method is particularly suitable for equipment such as bridge cranes that require frequent turns, and can always maintain the consistency between control commands and the current direction of movement, greatly improving the control accuracy during the turning process.

[0107] Calculate the real-time offset of the drive mechanism: During the actual operation of the drive mechanism, the system monitors its lateral deviation from the path centerline in real time through high-precision sensors. Unlike the traditional method that only monitors positional deviation, this solution pays special attention to the key parameter of lateral deviation, because it is crucial for the swing space management of the suspended heavy load.

[0108] Dynamic adjustment of the drive mechanism's direction of motion: When a lateral deviation is detected, the system generates an intelligent correction command. This correction is not a simple on / off control, but a gradual adjustment based on the magnitude and trend of the deviation, ensuring that the drive mechanism smoothly moves toward the centerline. This control strategy avoids trajectory oscillations caused by over-adjustment and can quickly eliminate deviations, making it particularly suitable for the precise control of large inertia systems such as bridge cranes.

[0109] Outputting the final travel trajectory: The process of converting the corrected motion data into executable trajectory commands fully considers the mechanical characteristics of the bridge crane, comprehensively considering physical constraints such as the acceleration capability and maximum speed of the drive mechanism, to generate control commands that both conform to equipment performance and accurately track the centerline. This command generation method based on physical constraints fundamentally avoids the common problem in traditional control where "the command is feasible but the equipment cannot execute it," greatly improving the practicality of control. The final achievement of strictly running along the centerline provides a solid foundation for swing space management, ensuring that the actual swing range is always controlled within the pre-calculated safe area.

[0110] From a technical mechanism perspective, each technical feature in the above control scheme specifically addresses key issues in trajectory tracking. Specifically, the establishment of a dynamic local coordinate system eliminates error accumulation, real-time lateral deviation monitoring captures the core of control, intelligent correction commands achieve smooth adjustment, and command generation based on physical constraints ensures feasibility. The synergistic effect of these technical features enables large equipment such as bridge cranes to achieve trajectory tracking accuracy comparable to precision machine tools. Especially when operating in confined spaces, this high-precision trajectory control can fully utilize the path width, providing maximum safe swing space for the suspended load, directly improving operational efficiency and safety.

[0111] In practical applications, the maximum allowable spatial range for the load to swing due to inertia is set to no more than 80% of the path width of the next movement segment. This proportional parameter is determined based on in-depth dynamic analysis and extensive engineering practice verification. From a physical mechanism perspective, the 80% ratio setting has multiple technical advantages: First, this ratio reserves a 20% safety buffer space for emergencies, which can effectively cope with uncertainties such as sensor errors, control delays, and environmental interference; second, the 80% utilization rate can ensure efficient use of space resources and avoid control risks caused by being too close to the boundary; most importantly, this ratio matches the swing characteristics of typical loads of bridge cranes, which can ensure that the kinetic energy of the load is fully absorbed without rebound when the direction is changed.

[0112] When the drive mechanism can be precisely controlled to run along the centerline, 80% path width utilization means that a 10% safety margin is reserved on each side. From an engineering perspective, this 80% parameter setting fully considers various disturbance factors in actual operation. For example, when the path width is 1 meter, the allowable swing range is 0.8 meters, which means that even if there is a positioning error or measurement deviation at the level of 10 centimeters, there is still a 10-centimeter safety margin. This design gives the system good robustness and can adapt to the operational needs under different working conditions. In addition, the 80% ratio also allows operators to intuitively judge the safety status. When the swing amplitude is detected to be close to this threshold, the system can issue an early warning or automatically intervene to adjust, greatly improving operational safety.

[0113] This invention proposes a motion control scheme for the drive mechanism based on the walking distance and the allowable swing range. In practical engineering applications, how to formulate the optimal speed curve for different lengths of movement segments has become a technical problem that urgently needs to be solved. Traditional control methods often use fixed speed or simple segmented control, which cannot be dynamically adjusted according to the actual path characteristics and load characteristics, resulting in either low operating efficiency or excessive braking during short-distance movement, causing the heavy object to swing violently.

[0114] To address this key technical problem, this invention proposes an adaptive speed control strategy based on the length of the motion segment, referring to... Figure 5 As shown, a three-stage speed control scheme was designed for long-distance movement segments (i.e., the distance of the movement segment is greater than the minimum safe braking distance), which fully considers the dynamic characteristics of the bridge crane and the swing law of the load.

[0115] The initial acceleration phase uses a preset acceleration a1 to ensure a smooth start and avoid excessive instantaneous acceleration that could cause violent swaying of the load. The constant speed phase maintains a scientifically calculated initial speed v, precisely calculated based on the maximum allowable sway space Lmax at the direction switching node, satisfying the key constraint v ≤ √(a2·Lmax). From a physical perspective, this upper speed limit formula ensures that the load's sway amplitude will not exceed the preset safety range during deceleration. The final deceleration phase uses a preset deceleration a2 to ensure a smooth stop of the drive mechanism at the direction switching node, while simultaneously controlling the load's sway within a safe range. This three-stage control system ensures both operational efficiency and safety during steering, making it particularly suitable for precise control of long-distance straight-line motion.

[0116] A two-stage optimized control scheme was proposed for short-distance movement segments (i.e., movement segments shorter than the minimum safe braking distance). Within a limited space, the control strategy is intelligently adjusted to organically connect the acceleration and deceleration processes. The adjusted second speed v' is determined by dual constraints: v'≤√[2a1a2D / (a1+a2)] must be satisfied to ensure that the entire acceleration and deceleration process can be completed within the limited travel distance D, and v'≤√(a2·Lmax) must be satisfied to ensure swing safety. The control strategy is dynamically adjusted according to different working conditions. The two-stage control avoids the awkward situation where deceleration begins before the speed has increased during short-distance movement. The optimal operating speed for a given distance was found through optimization calculation, maximizing the efficiency of short-distance hoisting.

[0117] From the perspective of control mechanism, the constraint formulas for the first velocity v and the second velocity v' are both derived from an in-depth analysis of the dynamics of the simple pendulum system. This ensures that during the deceleration phase, when the kinetic energy of the swinging weight is completely converted into potential energy, the swing amplitude is exactly equal to Lmax. This calculation of control parameters based on the physical model has higher reliability and adaptability compared to the traditional empirical setting method.

[0118] In practical applications, the system intelligently selects the appropriate solution based on the real-time calculated travel distance, ensuring that the optimal speed control strategy can be adopted for both long-distance transportation and short-distance adjustments. This adaptive feature greatly improves the system's work efficiency, especially in hoisting operations on complex paths, saving operation time. At the same time, because the speed scheme strictly follows physical constraints, the swing of the load is always controlled within a safe range, significantly improving the safety of operations in confined spaces.

[0119] In practical engineering applications, different load masses can also have a certain dynamic impact on motion control. Traditional control methods usually use fixed acceleration and deceleration parameters. This static setting method cannot adapt to the change of working conditions from light load to heavy load. When the load mass is large, fixed parameters may cause excessive inertial forces during start-up and braking, which will not only aggravate the swing of the load and increase the risk of collision, but may also cause additional load on the crane's mechanical structure and affect the service life of the equipment. Especially in the environment of confined space operation, the dynamic impact of this mass change is more significant, and there is an urgent need for an intelligent control strategy that can adapt to load changes.

[0120] To address this key technical issue, this invention also proposes a motion dynamic parameter adjustment scheme based on mass perception. First, real-time mass information of the hoisted object is obtained through reliable methods such as weighing sensors or torque estimation. This step provides key input parameters for subsequent intelligent control. According to basic principles of physics, the mass of the object directly affects the inertial characteristics of the system: the greater the mass, the greater the inertial force generated by the same acceleration. Based on this mechanism, this embodiment proposes a dynamic control method that reduces the absolute values ​​of acceleration a1 and deceleration a2 as the mass of the hoisted object increases. This negative correlation adjustment strategy has a solid physical basis and can ensure that the inertial force generated by the system is always within a reasonable range under different mass loads.

[0121] From a control implementation perspective, this dynamic adjustment scheme is achieved by establishing a mass-acceleration mapping relationship. Specifically, the system presets a baseline acceleration parameter and then dynamically adjusts it based on the ratio of the current load mass to the rated load. For example, when the load reaches 80% of the rated load, the acceleration may be adjusted to 60% of the baseline value. This nonlinear adjustment relationship fully considers the torque characteristics of the crane motor and the actual load conditions, ensuring both safety and efficiency under heavy load conditions. It is particularly noteworthy that the adjustment of deceleration a2 is usually more cautious than that of acceleration a1, because the kinetic energy during braking needs to be absorbed by the swing space, and excessive deceleration may cause the load to swing beyond the safe range.

[0122] After the system selects a three-stage or two-stage control scheme based on the length of the motion segment, it can dynamically adjust the acceleration and deceleration parameters according to different load masses, ensuring that these control schemes can adapt to different load conditions. For example, under heavy load conditions, although the maximum operating speed v may decrease due to the decrease in deceleration a2, the acceleration a1 also decreases accordingly, making the entire motion process smoother and effectively controlling the swing amplitude of the heavy object. This synergistic effect enables the system to maintain excellent control performance across the entire operating range.

[0123] From the perspective of engineering application effects, by dynamically adjusting the acceleration parameters, the structural dynamic load under heavy load conditions is effectively reduced, and the service life of the equipment is extended. Secondly, the adaptive deceleration control ensures that heavy objects of different masses can stop smoothly at the direction switching node, and the swing amplitude is always controlled within a safe range. Most importantly, this mass-adaptive control strategy greatly reduces the adjustment burden of operators. The system can automatically adapt to various lifting conditions, significantly improving the reliability and safety of operations in narrow spaces.

[0124] In actual operation, even with precise feedforward control, sudden factors (such as gusts of wind, load swaying, or mechanical transmission clearance) may cause the actual sway to exceed the expected range. This is especially true at the critical position of direction switching. Traditional open-loop control methods cannot cope with such real-time changes, which may lead to two risks: first, forcibly starting the next movement segment will aggravate the sway and cause a collision; second, excessively conservative waiting will significantly reduce work efficiency. This control blind spot is particularly prominent when working in narrow spaces, and a closed-loop control strategy that can monitor and adjust in real time is urgently needed.

[0125] To address this technical problem, the present invention also proposes a security control mechanism based on real-time detection, referring to... Figure 6 As shown, it includes the following steps:

[0126] First, a high-precision swing monitoring system is deployed at the critical location of the direction switching node. The actual swing amplitude of the suspended load is obtained in real time through detection methods such as visual sensors, inertial measurement units or laser rangefinders. This real-time feedback forms the basis of closed-loop control, enabling the system to overcome the limitations of traditional open-loop control.

[0127] In terms of technical implementation, the system compares the real-time detected swing data with the determined maximum allowable space range. This comparison process is not a simple threshold judgment, but rather a comprehensive consideration of multi-dimensional information such as swing phase and motion trend to ensure the accuracy of the decision.

[0128] When an excessive swing is detected, three intelligent adjustment strategies are provided. These strategies are dynamically selected based on the degree of swing exceeding the limit and the working scenario. Among them, the strategy of extending the stopping time utilizes the natural decay characteristics of the pendulum system, waiting for the system damping to consume the swing energy. This seemingly simple method is actually the most basic solution that conforms to the laws of physics, and is particularly suitable for slight exceedances. The strategy of reducing the speed of the next motion segment is based on the square proportional relationship between the swing amplitude and the motion speed. By appropriately reducing the speed, the safety of subsequent motion is ensured. This adjustment method achieves a good balance between time efficiency and control effect. The most refined is the acceleration adjustment strategy, which fundamentally reduces new excitation sources by modifying motion parameters.

[0129] From an engineering perspective, the real-time detection process employs multi-sensor fusion technology to ensure reliable acquisition of swing data under various lighting and operating conditions. The decision-making algorithm is not a simple binary judgment but has established a fuzzy control rule base, which can intelligently select adjustment methods based on factors such as the degree of exceeding limits and equipment status.

[0130] From a technical perspective, the innovation of the real-time detection safety control mechanism is reflected in three aspects: First, it enhances safety, as real-time monitoring and dynamic adjustment fundamentally eliminate the possibility of uncontrolled swaying; second, it optimizes efficiency, as the system selects the most economical adjustment strategy based on the actual situation to avoid unnecessary work interruptions; and most importantly, it enhances reliability, as this self-healing control system greatly reduces the need for operator intervention.

[0131] Reference Figure 7 As shown, in order to implement the above method, the present invention also provides a bridge crane working posture control system for implementing the above control method, comprising:

[0132] The spatial information acquisition module is used to acquire spatial constraint information of the work area and generate a spatial map containing obstacle locations and safety boundaries.

[0133] The path planning module is used to determine the hoisting path and path width based on the spatial map;

[0134] The trajectory generation module is used to determine the travel trajectory of the bridge crane drive mechanism based on the hoisting path and path width, so that the drive mechanism runs along the centerline of the hoisting path;

[0135] The node marking module is used to mark the position where the movement direction of the drive mechanism changes as a direction switching node, and to determine the travel distance of the drive mechanism in each linear motion segment based on the spacing between adjacent direction switching nodes.

[0136] The swing space calculation module is used to determine the maximum spatial range in which the weight can swing due to inertia at the direction switching node, based on the path width of the next linear motion segment.

[0137] The motion control module is used to determine the speed control scheme of the drive mechanism in each linear motion segment based on the travel distance of the drive mechanism in each linear motion segment and the maximum space range in which the load can swing, so that when the drive mechanism stops and changes the direction of motion at the direction switching node, the swing range of the suspended load does not exceed the path width.

[0138] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for controlling the working posture of a bridge crane, used for precise lifting of heavy objects in confined spaces, characterized in that, Includes the following steps: Acquire spatial constraint information of the work area, generate a spatial map containing obstacle locations and safety boundaries, and determine the hoisting path and path width based on the spatial map; The method for determining the hoisting path and path width based on a spatial map includes the following steps: Based on the obstacle location information in the spatial map, fit the minimum circumscribed geometry of each obstacle and calculate the minimum spacing between each geometry; select a start point and an end point in the spatial map, and generate an initial path based on the minimum spacing of the obstacle geometry, which consists of several straight segments and direction switching nodes; for each straight segment of the initial path, scan the spatial map along its extension direction to obtain the obstacle spacing on both sides of each straight segment; calculate the minimum safety margin for each straight segment based on the motion error compensation value of the bridge crane's drive mechanism; subtract the minimum safety margin from the obstacle spacing to obtain the usable width of each straight segment, which is then used as the final path width for each straight segment. The travel trajectory of the bridge crane drive mechanism is determined based on the hoisting path and path width, so that the drive mechanism runs along the centerline of the hoisting path; In the hoisting path, the position where the direction of motion of the drive mechanism changes is marked as the direction switching node, and the travel distance of the drive mechanism in each straight motion segment is determined according to the spacing between adjacent direction switching nodes. When the drive mechanism changes the direction of motion at the direction switching node, it determines the maximum spatial range in which the heavy object can swing due to inertia based on the path width of the next linear motion segment at the direction switching node. Based on the travel distance of the drive mechanism in each linear motion segment and the maximum allowable space range for the swing of the load, determine the speed control scheme of the drive mechanism in each linear motion segment so that when the drive mechanism stops and changes the direction of motion at the direction switching node, the swing range of the suspended load will not exceed the path width. When the drive mechanism reaches the direction switching node, the following steps are also included: real-time detection of the actual swing amplitude of the suspended load; comparison of the actual swing amplitude with the maximum allowable swing range of the load; if the actual swing amplitude exceeds the maximum allowable swing range, adjustment of the motion control scheme of the drive mechanism, including at least one of the following methods: extending the stopping time of the drive mechanism at the direction switching node, waiting for the swing of the load to decay to a safe range before starting the next motion segment; reducing the speed of the drive mechanism in the next motion segment; adjusting the acceleration or deceleration of the next motion segment to reduce the swing amplitude of the load.

2. The bridge crane working posture control method according to claim 1, characterized in that: The process of obtaining the spatial constraint information of the work area specifically includes the following steps: Multiple directional detection units are deployed at the boundary of the work area. Each directional detection unit is independently configured to transmit and receive detection signals. The initial detection direction formed by the multiple directional detection units covers the entire range of the work area, and the multiple directional detection units are synchronized through a communication link. Each directional detection unit transmits multi-frequency detection signals at preset time intervals and receives environmental reflected signals. Based on the intensity deviation and delay time of the reflected signals, a preliminary set of detection points is generated, and each detection point includes coordinate position and signal characteristics. The consistency of signal characteristics between the same detection point is verified based on different directional detection units. When the density of detection points is lower than the preset threshold or the signal characteristics deviate from the standard value, the area is determined to be an abnormal area and a correction command is triggered. Adjust the detection direction of the relevant adjustable detection unit or increase the detection signal frequency to perform supplementary scanning, obtain a corrected detection point set, and eliminate detection blind spots; By integrating the initial and corrected detection point sets, a spatial map is generated through spatial interpolation and boundary fitting. This spatial map identifies the location of obstacles and determines the safety boundaries.

3. The bridge crane working posture control method according to claim 1, characterized in that: Determine the travel trajectory of the bridge crane's drive mechanism based on the hoisting path and path width, ensuring the drive mechanism runs along the centerline of the hoisting path. This includes the following steps: A dynamic local coordinate system is established with the starting point of the hoisting path as the origin and along the extension direction of the hoisting path. The coordinate system direction is updated at each switching node in each direction. During the movement of the drive mechanism along the hoisting path, the lateral deviation between its actual position and the center line of the path is monitored in real time. When there is a lateral deviation in the drive mechanism, a correction command is generated to adjust the direction of movement of the drive mechanism so that it moves closer to the center line. The corrected motion data of the drive mechanism is used as an executable trajectory command to ensure that it runs strictly along the centerline of the hoisting path.

4. The bridge crane working posture control method according to claim 1, characterized in that: The maximum spatial range within which the heavy object is allowed to swing due to inertia shall not exceed 80% of the path width of the next motion segment.

5. The bridge crane working posture control method according to claim 1, characterized in that: Determine the speed control scheme for the drive mechanism in each linear motion segment, including the following steps: When the travel distance of the linear motion segment exceeds the minimum safe braking distance, the speed control scheme is set to a three-stage control, including: Initial acceleration phase: Accelerate to the first speed v with a preset acceleration a1; Constant speed segment: Maintain the initial speed v while traveling; Final deceleration phase: Decelerate to a stop at a preset deceleration rate a2; The first velocity v is determined based on the maximum spatial range in which the weight is allowed to swing at the direction switching node, and satisfies v≤√(a2·Lmax), where Lmax is the maximum spatial range in which the weight is allowed to swing.

6. The bridge crane working posture control method according to claim 5, characterized in that: When the travel distance in the straight-line segment is less than the minimum safe braking distance, the speed control scheme is set to two-stage control, including: Acceleration phase: Accelerate to the adjusted second speed v' using the preset acceleration a1; Deceleration phase: Decelerate to a stop at a preset deceleration rate a2; The adjusted speed v' satisfies: v'≤√[2a1a2D / (a1+a2)] and v'≤√(a2·Lmax), where D is the walking distance.

7. The bridge crane working posture control method according to claim 5 or 6, characterized in that: The mass of the hoisted object is obtained, and the acceleration a1 and deceleration a2 are dynamically adjusted according to the mass of the hoisted object, wherein: the larger the mass of the hoisted object, the smaller the absolute values ​​of acceleration a1 and deceleration a2.

8. A bridge crane working posture control system, used to implement the control method described in any one of claims 1 to 7, characterized in that: include: The spatial information acquisition module is used to acquire spatial constraint information of the work area and generate a spatial map containing obstacle locations and safety boundaries. The path planning module is used to determine the hoisting path and path width based on the spatial map; The trajectory generation module is used to determine the travel trajectory of the bridge crane drive mechanism based on the hoisting path and path width, so that the drive mechanism runs along the centerline of the hoisting path; The node marking module is used to mark the position where the movement direction of the drive mechanism changes as a direction switching node, and to determine the travel distance of the drive mechanism in each linear motion segment based on the spacing between adjacent direction switching nodes. The swing space calculation module is used to determine the maximum spatial range in which the weight can swing due to inertia at the direction switching node, based on the path width of the next linear motion segment. The motion control module is used to determine the speed control scheme of the drive mechanism in each linear motion segment based on the travel distance of the drive mechanism in each linear motion segment and the maximum space range in which the load can swing, so that when the drive mechanism stops and changes the direction of motion at the direction switching node, the swing range of the suspended load does not exceed the path width.

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