A crane load monitoring system and method for suppressing swaying

Abstract

This invention relates to the field of automation control technology, specifically to a crane load monitoring system and method for suppressing swaying. It aims to address the shortcomings of existing sway suppression schemes, which suffer from control lag, diminished effectiveness, and increased oscillation, and fail to proactively suppress swaying at the root cause of the crane's motion. The system includes a sensing module, a coupled model calculation module, a feedforward control module, a feedback correction module, and an execution adaptation module. The coupled model calculation module proactively calculates the load swaying trend based on the crane's motion parameters; the feedforward control module generates compensation commands in advance based on the predicted sway angle; and the feedback correction module performs closed-loop correction using the actual sway angle. By adopting the above technical solution, this application can achieve efficient, proactive, and full-process suppression of crane load swaying, weakening swaying at its source, improving operational efficiency, and lowering the operational threshold.

Description

Technical Field

[0001] This invention relates to the field of crane control technology, and more specifically, to a crane load monitoring system and method for suppressing swaying. Background Technology

[0002] Cranes, as important lifting equipment, are widely used in industrial production, construction, and logistics transportation. During crane lifting operations, load swaying is a common and unavoidable phenomenon, especially during hoisting, moving, or stopping operations, when the load sways due to inertia. This swaying not only increases working time but can also pose a threat to the surrounding environment and personnel safety, especially in confined spaces or complex working conditions where the swaying problem is more pronounced.

[0003] During the lifting process of large cranes, load swaying caused by crane movement accounts for more than 70%. This mainly includes the centrifugal force coupling of the crane's slewing mechanism during start-up and shutdown (when the crane rotates, the centrifugal force and Coriolis force are superimposed, causing the load to sway in a spiral manner) and the load swaying caused by the inertial force of the crane's acceleration and deceleration (typically, the greater the change in acceleration, the more obvious the swaying amplitude. For example, an emergency stop operation can cause the sway angle to instantly expand to the safe threshold >5°). This type of swaying will cause the unloading operation to be suspended, requiring the operator to manually eliminate the swaying, which takes more than 30% or even higher of the entire handling process.

[0004] Current crane load sway suppression technologies for addressing the aforementioned problems suffer from high costs, complex retrofitting processes, long installation cycles, poor adaptability, slow response times, and low efficiency, hindering widespread practical application. This invention relates to a crane load monitoring method and system for suppressing swaying, aiming to resolve the safety hazards and efficiency issues arising from load swaying during lifting operations in existing cranes. Summary of the Invention

[0005] The purpose of this invention is to provide a crane load monitoring method and system for suppressing swaying, so as to solve the technical problems described in the background art, such as control lag, effect attenuation and even aggravation of oscillation caused by system delay in existing sway suppression schemes based on pure a posteriori feedback control, and to overcome the fundamental defect that it fails to actively suppress swaying from the root cause of the crane's own movement.

[0006] To achieve the above-mentioned objectives, this invention provides a crane load monitoring system for suppressing swaying. The system includes: a sensing module, a coupled model calculation module, a feedforward control module, a feedback correction module, and an execution adaptation module. A defined data communication and control logic connection is established between the sensing module, the coupled model calculation module, the feedforward control module, the feedback correction module, and the execution adaptation module.

[0007] Specifically, the sensing module is used to measure and acquire key kinematic and dynamic parameters and load attitude parameters in real time during crane operation. The sensing module physically comprises: a dual-axis tilt sensor, a rotary encoder, a luffing stroke encoder, a hoisting stroke encoder, and a current sensor. The dual-axis tilt sensor is mounted on the load's lifting device or hook assembly, fixed by a magnetic adsorption base to ensure its measurement reference plane is closely aligned with the vertical direction of the load. This dual-axis tilt sensor is a capacitive accelerometer sensor based on microelectromechanical systems (MEMS) technology, with a measurement range set to ±15 degrees and a static measurement accuracy better than ±0.1 degrees. It integrates temperature compensation and signal conditioning circuits, outputting a filtered and calibrated angle signal. The rotary encoder is an incremental photoelectric rotary encoder, physically fixed on the transmission output shaft of the crane's slewing mechanism, used to accurately measure the angular displacement of the upper structure of the crane relative to the lower chassis. The rotary encoder has a resolution set to 1024 lines per revolution, and its output signal is a two-phase quadrature pulse signal (A and B). By counting and frequency detection of this pulse signal, the slewing angular position, slewing angular velocity ω, and slewing angular acceleration α can be determined. Both the luffing stroke encoder and the hoisting stroke encoder are wire-type linear displacement sensors, installed on the sides of the luffing mechanism drum and the hoisting mechanism drum of the crane, respectively. The end of their wire ropes rotates synchronously with the drums. The luffing stroke encoder is used to measure the radial displacement of the trolley or boom to determine the current luffing amplitude r, and calculates the radial velocity v of the luffing mechanism based on its displacement change rate. r The lifting stroke encoder is used to measure the released length of the wire rope, thereby determining the current height of the load suspension point and the effective length L of the wire rope. The measurement range of both stroke encoders is set to 0 to 50 meters, with a measurement accuracy better than ±0.5 mm. The current sensor is a closed-loop current sensor based on the Hall effect, physically installed in series with one phase of the three-phase power supply circuit of the AC asynchronous motor driving the lifting or luffing mechanism. The rated measurement range of this current sensor is set to 0 to 500 amperes, with a measurement accuracy of ±1% of full scale. Its function is to monitor the operating current of the drive motor in real time. This current signal has a definite functional relationship with the motor's output torque and the load's acceleration, thereby indirectly measuring the load's acceleration a(t) in the lifting or luffing direction.

[0008] Furthermore, the coupled model calculation module, feedforward control module, and feedback correction module are integrated into a single embedded controller. This embedded controller (with a high-performance microcontroller unit (MCU) at its core) is installed in the electrical control cabinet of the crane's central operator's cab and fixed via DIN rails. Each sensor in the sensing module is connected to its corresponding interface on the embedded controller via shielded cables.

[0009] Furthermore, the coupled model calculation module, as a set of fixed algorithm programs running on the embedded controller, has the core function of receiving real-time multi-source data from the sensing module and, based on a preset rigid body dynamics model, quantitatively calculating the load swaying trend induced by the active motion of the crane. This module is logically divided into two parallel sub-modules: a centrifugal force-Coriolis force coupled sway angle calculation sub-module and an inertial force sway angle calculation sub-module.

[0010] Furthermore, the centrifugal force-Coriolis force coupled swing angle calculation submodule is specifically designed to calculate the predicted swing angle θ1(t) in the tangential plane generated by the combined action of centrifugal force, Coriolis force, and tangential inertial force during the combined operation of slewing and luffing motions of the crane. The calculation performed by this submodule follows the following integral formula:

[0011]

[0012] In this formula, θ1(t) is the swing angle predicted at time t, which is generated by the coupling of rotation and amplitude. For the variable in the integration time The rotational angular velocity measured by the rotary encoder at any given time; for The angular acceleration at time t, which is determined by the relationship between the two sides. Obtained by performing time differentiation; for The amplitude measured by the amplitude-changing stroke encoder at any given time; for The radial velocity of the amplitude-changing mechanism at a given time is determined by the... The time derivative is obtained; k1 and k2 are pre-calibrated dimensionless correction coefficients used to compensate for errors caused by model simplification and unmodeled dynamics. The integral operation is performed iteratively within the MCU using discretized numerical integration methods (such as the trapezoidal rule or Simpson's rule) at fixed time steps (e.g., 10 milliseconds).

[0013] Furthermore, the inertial force swing angle calculation submodule is specifically designed to calculate the predicted swing angle θ2(t) in the direction of motion caused by the translational inertial force of the load during the crane's lifting, lowering, or horizontal acceleration / deceleration movements. The calculation performed by this submodule follows the formula:

[0014]

[0015] In this formula, θ2(t) is the swing angle predicted at time t by the translational inertial force; a(t) is the horizontal or vertical acceleration of the load at time t; g is the gravitational acceleration, which is set to 9.8 m / s²; L is the current effective length of the wire rope measured by the lifting stroke encoder at time t; L0 is the maximum working length of the wire rope configured for the crane, which is a fixed parameter pre-stored in the controller; k3 is a pre-calibrated length correction coefficient related to the wire rope length, whose physical meaning is to characterize the influence of the wire rope's own elasticity and mass distribution on the swing period.

[0016] Furthermore, the feedforward control module, as another core algorithm program running on the embedded controller, functions to receive the predicted swing angles θ1(t) and θ2(t) output from the coupled model calculation module, and based on this prediction information, generate proactive, compensatory control commands in advance. This module is logically divided into two parallel sub-modules: a rotation operation compensation amount generation sub-module and an acceleration / deceleration operation compensation amount generation sub-module.

[0017] Furthermore, the slewing operation compensation generation submodule is used by the slewing feedforward submodule to generate the slewing operation compensation amount based on formula (3):

[0018]

[0019] Where, k p ∈[0.8,1.2] is the proportionality coefficient. For t+T predicted by the centrifugal force-Coriolis force coupling submodule d Constant swing angle, T d To delay execution, T d =100ms;

[0020] The compensation amount generation submodule is used to generate acceleration / deceleration operation compensation amounts based on formula (4):

[0021]

[0022] Where, k i ∈[0.05,0.1]s -1 The integral coefficient is... For predictions based on the inertial force swing submodule It is always swaying.

[0023] Furthermore, the function of the feedback correction module is to calculate the feedback control quantity based on formula (5):

[0024]

[0025] Where, k d ∈[0.1,0.3]s are the differential coefficients. To determine the error between the measured swing angle and the target swing angle, The measured swing angle is collected by a dual-axis tilt sensor. To set the angle for the target, The error rate of change is the difference between the two errors divided by the sampling time.

[0026] It should be further explained that in the algorithm of this scheme, the proportionality coefficient k p Integral coefficient k i Differential coefficient k d It is a core control parameter, and its value directly affects the anti-sway effect (such as the convergence speed of the swing angle, stability, etc.) and k p k i k d These are personalized parameters for the equipment, meaning different cranes (tonnage, type) and different scenarios (load, environment) require different values. Before use, they must be determined through three practical steps: "initial setting → on-site debugging → data saving." The specific operation method is to first set an initial value according to the range in this solution, generally an intermediate value. Adjust one parameter at a time (change range ≤ 10%), recording the swing angle curve, until the parameters after debugging stably meet the control targets of "swing angle suppression rate ≥ 90%, convergence time ≤ 12s." Based on the parameter characteristics, focus on adjusting k during the no-load stage. p At this time, the load inertia is small, and the change in swing angle is mainly controlled by proportional adjustment (k). p ) Dominant, if only because of k p Improper handling leading to slow convergence / oscillation does not require adjustment of k. i k d ; During the full-load phase, the focus is on adjusting k i The residual pendulum angle is determined by the integral element (k) i The responsible party is to compensate for any remaining swing angle after stabilization; if there is still residual swing angle after stabilization, k should be adjusted first. i Instead of k p (To avoid disrupting the already tuned dynamic response); during the emergency stop phase, focus on adjusting k. d The sudden change in the swing angle is caused by the differential element (k) d Suppress; if the sudden stop increases significantly, prioritize adjusting k. d Instead of other parameters.

[0027] The function of the execution adaptation module (14) is to calculate and output the total control quantity based on formula (6):

[0028]

[0029] Where sat() is the saturation function, umin u max These are the minimum and maximum control limits allowed by the actuator, respectively.

[0030] As another aspect of the invention, the invention also provides a crane load monitoring method for suppressing swaying, the method being implemented on a crane equipped with the aforementioned system. Upon initial deployment, the method includes a critical system parameter calibration step, as well as a real-time control step that is cyclically executed during routine operations.

[0031] The purpose of the system parameter calibration step is to determine three key correction coefficients k1, k2, and k3 for the coupled model calculation module. This step specifically includes:

[0032] S01: Calibration of the centrifugal force-Coriolis force coupling coefficient k1. First, control the crane to operate without lifting or luffing (i.e., v...). r Under the condition of ω = 0, a known, constant angular velocity ω (e.g., 0.5 radians / second) is used for uniform rotation, while maintaining a fixed amplitude r (e.g., 15 meters). After uniform rotation continues for a set time T (e.g., 10 seconds), the maximum value of the stable tangential swing angle θ1 = 1.2 rad is recorded by the dual-axis tilt sensor. Subsequently, the value of the coefficient k1 is calculated using formula (1). .

[0033] S02: Calibration of the angular acceleration coupling coefficient k2. First, the crane is controlled to rotate uniformly from rest with a known, constant angular acceleration α (e.g., 0.1 radians / second²) under conditions of no lifting and no luffing, while maintaining a fixed luffing amplitude r (e.g., 15 meters). After the uniform acceleration rotation continues for a set time T (e.g., 10 seconds), the maximum value of the stable tangential swing angle θ2 = 0.8 rad, measured by the dual-axis tilt sensor, is recorded. Then, the value of coefficient k2 is calculated using formula (2). .

[0034] S03: Calibration of the wire rope length correction factor k3. First, control the crane to lift or lower at a known, constant acceleration a (e.g., 0.5 m / s²) under conditions of no slewing and no luffing, for a set time T (e.g., 5 seconds). During this process, record the maximum working length L0 (e.g., 30 m) and the current wire rope length L (e.g., 15 m), and measure the maximum stable swing angle θ3 = 0.6 rad using a dual-axis tilt sensor. Calculate using formula (3) .

[0035] After completing the above calibration, the calculated values ​​of k1, k2, and k3 are written into the embedded controller as fixed parameters, and the crane load monitoring system described in this invention can then be run. The specific method is as follows:

[0036] S1. Real-time acquisition of multi-source information - The crane's rotational angular velocity ω and angular acceleration are acquired through the sensing module (10). Amplitude r, radial velocity v of the amplitude transformer r The lifting height L, the acceleration a in the lifting or luffing direction, and the load swing angle θ;

[0037] S2. Based on the parameters collected in step S1, the predicted swing angles θ1(t) and θ2(t) are calculated by substituting them into formulas (1) and (2) respectively and the pre-stored calibration coefficients k1, k2, and k3 through the coupled model calculation module.

[0038] S3. Substitute θ1(t) obtained in step S2 into formula (3) to generate the slewing operation compensation amount u1, and substitute θ2(t) into formula (4) to generate the acceleration / deceleration operation compensation amount u2.

[0039] S4. Based on the load swing angle θ and target swing angle θ collected in step S1 ref The error e = 0 is substituted into formula (5) to generate the feedback control quantity u. f ;

[0040] S5. Combine u1 and u2 obtained in step S3 with u obtained in step S4. f Substitute into formula (6) to calculate the total control quantity u, and output it to the original control system of the crane through the execution adapter module to realize the source suppression and process correction of sway.

[0041] By combining the aforementioned systems and methods, this invention constructs a dual-closed-loop control architecture that integrates forward-looking kinematic prediction of the crane with real-time feedback of load attitude. Its core lies in establishing and calibrating a dynamic coupling model between the crane's own motion and the load's sway response. This allows the system to predict the amplitude and direction of the sway before it occurs based on the upcoming operational commands, and to apply precise counter-compensation forces in advance. This significantly reduces the sway at its source, thereby achieving efficient and proactive control of the crane load sway and improving operational efficiency. Attached Figure Description

[0042] Figure 1 This is a system block diagram of the crane load monitoring system for suppressing swaying according to the present invention.

[0043] Figure 2 This is a schematic diagram showing the installation positions of each measurement sensor in the sensing module of the system of the present invention.

[0044] Figure 3 This is a schematic diagram of the electrical signal connection between the sensing module and the embedded controller in the system of this invention.

[0045] Figure 4 This is a schematic diagram of the control logic combining feedforward control and feedback correction in the system of this invention.

[0046] Figure 5 This is a flowchart illustrating the system parameter calibration steps in the method of this invention.

[0047] Figure 6 This is a schematic diagram of the system operation process corresponding to the actual operation of the method of the present invention.

[0048] The attached diagram is labeled as follows: 1. Base; 2. Tower body; 3. Hoisting mechanism; 4. Operator's cab; 5. Counterweight boom; 6. Tower boom; 7. Counterweight; 8. Slewing mechanism; 9. Luffing mechanism; 91. Traveling trolley; 92. Hook assembly; 10. Sensing module; 11. Coupled model calculation module; 111. Centrifugal force-Coriolis force coupled swing angle calculation submodule; 112. Inertial force swing angle calculation submodule; 12. Feedforward control module; 121. Slewing operation compensation amount generation submodule; 122. Acceleration and deceleration operation compensation amount generation submodule; 13. Feedback correction module; 14. Execution adaptation module; 21. Dual-axis tilt sensor; 22. Slewing encoder; 23. Luffing stroke encoder; 24. Hoisting stroke encoder; 25. Current sensor; 30. Embedded controller. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the scope of protection of the invention.

[0050] Reference Figures 1 to 6 This invention discloses a crane load monitoring system and method for suppressing swaying. It mainly overcomes the control lag problem caused by the inherent time delay in signal transmission, calculation and processing and mechanical execution in traditional sway suppression technology by constructing a forward-looking prediction model and a real-time feedback correction model.

[0051] Example

[0052] QTZ80 tower crane retrofit: such as Figure 1 and 2 As shown, the system hardware of the present invention is installed on the aforementioned crane (the crane structure includes a base 1, a tower body 2, a hoisting mechanism 3, a cab 4, a counterweight boom 5, a tower boom 6, a counterweight 7, a slewing mechanism 8, and a luffing mechanism 9). A schematic diagram of the system architecture and specific installation location is shown below. Figure 1 and 2 As shown, the system includes a sensing module 10, a coupled model calculation module 11, a feedforward control module 12, a feedback correction module 13, and an execution adaptation module 14. These modules communicate and work collaboratively at high speed through a pre-defined, reliable data bus and logical link, forming a unified whole. The coupled model calculation module 11, feedforward control module 12, and feedback correction module 13 are highly integrated into a unified embedded controller 30. The sensing module 10 consists of multiple sensors distributed at key locations on the crane, such as… Figure 3 As shown, the components are a dual-axis tilt sensor 21, a rotary encoder 22, a variable amplitude stroke encoder 23, a lifting stroke encoder 24, and a current sensor 25.

[0053] The dual-axis tilt sensor 21 (model SCA61T, range ±15°, accuracy ±0.1°, power supply DC=5V) is mounted on the hook assembly 92 that directly supports the container via a high-strength neodymium iron boron magnetic adsorption base, and is further secured with a safety cable to ensure a rigid connection between the sensor and the spreader even during vigorous movement. The sensor is designed to withstand the harsh working environment of high salt spray and high humidity in ports. It integrates a high-precision temperature sensor and a digital temperature compensation algorithm, enabling automatic correction of measurement errors introduced by temperature drift within a wide temperature range of -40℃ to +85℃. Simultaneously, its built-in Kalman filter algorithm fuses the original acceleration signal, effectively filtering out high-frequency noise caused by motor vibration, structural resonance, etc., and finally outputs the real-time tilt angle θ to the embedded controller 30 in digital signal form via the CAN bus interface. meas .

[0054] The rotary encoder 22 (model E6B2-CWZ6C, resolution 1024 lines / turn, output AB phase pulses) is fixed to the end of the output shaft of the planetary reducer driving the rotary mechanism 8 via a customized coupling and bracket; the luffing stroke encoder 23 (model KTF1-2000, measuring range 0-20m, accuracy ±0.5mm) and the hoisting stroke encoder 24 are both heavy-duty pull-wire linear displacement sensors, which are installed on the side of the drum of the luffing mechanism 9 and the hoisting mechanism 3 of the crane, respectively, and the end of their pull ropes rotates synchronously with the drums; the current sensor 25 (model ACS712-50A, measuring range 0-50A, accuracy ±1% FS) is directly connected in series with one phase of the three-phase power supply cable of the AC asynchronous motor driving the hoisting mechanism or luffing mechanism, and can indirectly measure the acceleration a(t) of the load in the hoisting or luffing direction through the current signal.

[0055] The embedded controller 30 (model STM32H743, 400MHz, with 4 GPIO and 2 UART interfaces) is installed in the electrical control cabinet behind the crane cab 4 and is fixed by a standard DIN rail. The power supply is taken from the 24V DC power supply in the cabinet.

[0056] The task of the above-described embodiment 1 is as follows: to lift a 40-foot standard container from a trailer under the quay crane and perform a combined motion of rotation and luffing to move the container directly above the target position in the ship's hold. Specific motion parameters are: lifting height L = 25 meters, trolley luffing from a radius of r = 15 meters to r = 35 meters, and average radial velocity v. r =1.0 m / s; simultaneously, the boom rotates from the 0-degree position to the 30-degree position, with an average angular velocity ω = 0.25 radians / s, and the maximum length of the wire rope L0 = 30 meters. The crane load monitoring system, used to suppress swaying, immediately begins operation the instant the operator issues the compound motion command. The sensing module 10 collects real-time speed and acceleration information for the slewing and luffing mechanisms. Based on this information, the coupled model calculation module 11 predicts the complex swaying trend that will occur due to the combined effects of centrifugal force, Coriolis force, and tangential and radial inertial forces within 10 milliseconds. Based on this advance prediction, the feedforward control module 12 immediately generates compensatory control commands u1 and u2, and fine-tunes the speeds of the slewing and luffing motors through the execution adaptation module 14. Throughout the entire motion, the actual sway angle measured by the dual-axis tilt sensor 21 is consistently suppressed within a very small range. When the motion ends and the trolley and slewing mechanism stop, the load reaches a stable state almost instantaneously because the swaying energy has been largely offset during the motion.

[0057] The specific operating parameters and basic settings are as follows:

[0058] Known conditions: Load characteristics: 40-foot standard container (weight ≈ 30 tons, within the rated load range of the crane);

[0059] Motion parameters: lifting height L=25m, maximum wire rope length L0=30m, luffing range: from r=15m to r=35m, average radial velocity v r =1.0m / s, amplitude change time t=(35-15) / 1=20s.

[0060] Rotation: From 0° to 30° (converted to 0.5236 radians), average angular velocity ω = 0.25 rad / s, rotation time t = 0.5236 / 0.25 = 2.09s (based on a total amplitude variation time of 20s, subsequent rotations will be treated as uniform rotation).

[0061] 3. Core parameter: k1= k2= k3=0.25; control parameter k p =0.9、k i =0.08s -1 k d =0.2s, it should be noted that k in this scheme p =0.9、k i =0.08s -1 k d =0.2s is the optimal solution determined through more than 20 on-site debugging for the QTZ80 tower crane. It meets the control objectives of "swing angle suppression rate ≥90%, convergence time ≤12s, and no oscillation" and can be adapted to other equipment using the same method.

[0062] Substitute the above parameters into formulas (1) to (6) respectively to calculate, and finally obtain u=-1, which is converted into the following specific operation actions: Rotary motor: voltage is reduced by 10% (from rated 380V to 342V), reducing the rotational acceleration; Amplitude motor: current is reduced by 8% (from rated 50A to 46A), slowing down the radial speed; Execution effect: the swing angle increase is controlled from the predicted 1.32rad to the actual 0.8rad (suppression rate of about 40%).

[0063] Comparative Example

[0064] The operation is the same as in Example 1, using the same crane to perform the exact same task, but the monitoring and control system of this invention is completely disabled. Control is entirely performed by a skilled operator with over five years of experience. The operator, relying on their extensive experience, attempts to suppress swaying through pre-operation and smooth start-stop. However, at the instant the slewing and luffing movements begin simultaneously, the enormous combined inertial force still causes significant swaying of the container. During the movement, after observing the swaying, the operator attempts to counteract it through reverse operations, but due to human reaction delays and the crane's own execution delays, the corrective operations often lag behind the phase of the swaying, sometimes even leading to more severe oscillations. After the crane moves above the target position and stops, the container continues to undergo large-amplitude, continuous pendulum motion. The operator has to spend extra time waiting for it to naturally decay to an acceptable level, or perform multiple small-range inching operations to forcibly stop the swaying.

[0065] Data Comparison

[0066] To more accurately evaluate the superiority of the technical solution of the present invention, the key performance indicators of the above embodiments and comparative examples were recorded and compared, and the results are shown in the table below:

[0067]

[0068] The comparative data in the table above clearly shows that, after adopting the technical solution of this invention, the load swaying of the crane during high-speed compound motion is suppressed by nearly 90%. More importantly, the load stabilization time is drastically reduced from more than 18 seconds to less than 2 seconds, greatly reducing the ineffective waiting time in the work cycle, thereby improving the efficiency of a single work cycle by more than 27%. This has significant economic value and practical significance for modern ports and logistics stations that pursue high efficiency.

[0069] In summary, the crane load monitoring system and method for suppressing swaying of the present invention effectively solves the problems of control delay and incomplete suppression existing in the prior art, and achieves efficient active suppression of crane load swaying throughout the entire process. Those skilled in the art should understand that the above description is only a preferred embodiment of the present invention and does not constitute a limitation on the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0070] Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this invention shall be included within the scope of protection of this invention.

Claims

1. A crane load monitoring system for suppressing swaying, characterized in that, The system includes: a sensing module (10) for real-time acquisition of kinematic parameters, dynamic parameters and attitude parameters of suspended loads during the operation of the crane; The coupled model calculation module (11) is connected to the sensing module (10) and collects real-time parameters based on the sensing module (10). It also calculates the load prediction swing angle induced by the active movement of the crane in a forward-looking manner through a preset rigid body dynamics model. The feedforward control module (12) is connected to the coupled model calculation module (11) for receiving the predicted swing angle and generating an active, compensatory feedforward control command in advance based on the predicted swing angle. Feedback correction module (13) is connected to the sensing module (10) for receiving the real-time attitude parameters of the load collected by the sensing module (10) and generating feedback correction instructions to eliminate model errors and external disturbances based on the deviation between the real-time attitude parameters and the preset target attitude. And an adaptation module (14) is connected to the feedforward control module (12) and the feedback correction module (13) to synthesize the feedforward control command and the feedback correction command to form a total control command, and convert the total control command into a physical signal that can be recognized and executed by the original control system of the crane, so as to superimpose and correct the original operation command; The coupled model calculation module (11) includes a centrifugal force-Coriolis force coupled swing angle calculation submodule (111) and an inertial force swing angle calculation submodule (112). The centrifugal force-Coriolis force coupled swing angle calculation submodule (111) is used to calculate the first predicted swing angle θ1(t) in the tangential plane using formula (1) when the crane performs a combined rotation and luffing motion: Wherein, ω(τ), α(τ), r(τ) and vᵣ(τ) are the rotational angular velocity, rotational angular acceleration, amplitude change and radial velocity measured by the sensing module (10) at the integration time τ, respectively, k1 and k2 are pre-calibrated dimensionless correction coefficients, and the inertial force swing angle calculation submodule (112) is used to calculate the second predicted swing angle θ2(t) in the direction of motion by formula (2) when the crane is performing translational acceleration and deceleration motion: Where a(τ) is the acceleration of the hoisting / lamp mechanism at time τ, and g is the acceleration due to gravity, g = 9.8 m / s². 2 L is the current effective length of the wire rope, L0 is the maximum working length of the wire rope, and k3 is the pre-calibrated length correction coefficient.

2. The system according to claim 1, characterized in that, The sensing module (10) includes a dual-axis tilt sensor (21), which is mounted on the lifting device or hook assembly of the load and is used to measure the actual swing angle θ of the load in two orthogonal directions, namely tangential and radial, in real time. meas ; A rotary encoder (22) is installed on the slewing mechanism of the crane to measure the slewing angle position of the crane in real time and to analyze the slewing angular velocity ω and slewing angular acceleration α accordingly. A variable stroke encoder (23) is installed on the luffing mechanism of the crane to measure the radial displacement of the crane trolley or boom in real time to determine the luffing amplitude r, and to calculate the radial speed vᵣ of the luffing mechanism accordingly. A lifting stroke encoder (24) is installed on the crane lifting mechanism to measure the released length of the wire rope in real time to determine the current effective length L of the wire rope; And a current sensor (25), connected in series in the power supply circuit of the motor driving the hoisting mechanism or luffing mechanism, for real-time monitoring of the operating current of the drive motor, so as to indirectly measure the acceleration a of the load in the hoisting or luffing direction.

3. The system according to claim 2, characterized in that, The dual-axis tilt sensor (21) is a capacitive accelerometer sensor based on microelectromechanical systems technology. Its measurement range is set to ±15 degrees, and it integrates a temperature compensation circuit and a Kalman filter algorithm for filtering out high-frequency noise. The rotary encoder (22) is an absolute multi-turn photoelectric rotary encoder. The variable amplitude stroke encoder (23) and the lifting stroke encoder (24) are both wire-type linear displacement sensors.

4. The system according to claim 1, characterized in that, The coupled model calculation module (11), the feedforward control module (12) and the feedback correction module (13) are integrated into an embedded controller (30) with a microcontroller unit as the core. The microcontroller unit is based on the ARM Cortex-M7 core and has a built-in floating-point arithmetic unit.

5. The system according to claim 1, characterized in that, The feedforward control module (12) includes a slewing operation compensation amount generation submodule (121) and an acceleration / deceleration operation compensation amount generation submodule (122). The slewing operation compensation amount generation submodule (121) is used by the slewing feedforward submodule to generate the slewing operation compensation amount based on formula (3): Where, k p ∈[0.8,1.2] is the proportionality coefficient. For t+T predicted by the centrifugal force-Coriolis force coupling submodule d Constant swing angle, T d To delay execution, T d =100ms; The compensation amount generation submodule (122) is used to generate acceleration / deceleration operation compensation amounts based on formula (4): Where ki∈[0.05,0.1]s −1 The integral coefficient is... The swing angle at time τ is predicted based on the inertial force swing submodule.

6. The system according to claim 5, characterized in that, The feedback correction module (13) is used to calculate the feedback control quantity based on formula (5): Where, k d ∈[0.1,0.3]s are the differential coefficients. To determine the error between the measured swing angle and the target swing angle, The measured swing angle is collected by a dual-axis tilt sensor. To set the angle for the target, The error rate of change is the difference between the two errors divided by the sampling time.

7. The system according to claim 6, characterized in that, The execution adaptation module (14) is used to calculate and output the total control quantity based on formula (6): Where sat() is the saturation function, u min u max These are the minimum and maximum control limits allowed by the actuator, respectively.

8. A crane load monitoring method for suppressing swaying, characterized in that, The method is based on the crane load monitoring system for suppressing swaying as described in claim 7, and includes the following steps: S1: Collect the crane's rotational angular velocity ω and angular acceleration through the sensing module (10). Amplitude r, radial velocity v of the amplitude transformer r The lifting height L, the acceleration a in the lifting or luffing direction, and the load swing angle θ; S2: Based on the parameters collected in step S1, the predicted swing angles θ1(t) and θ2(t) are calculated by substituting them into formulas (1) and (2) respectively through the coupled model calculation module. S3: Substitute θ1(t) obtained in step S2 into formula (3) to generate the slewing operation compensation amount u1, and substitute θ2(t) into formula (4) to generate the acceleration / deceleration operation compensation amount u2; S4: Based on the load swing angle θ and target swing angle θ collected in step S1 ref The error e = 0 is substituted into formula (5) to generate the feedback control quantity u. f ; S5: Combine u1 and u2 obtained in step S3 with u obtained in step S4. f Substitute into formula (6) to calculate the total control quantity u, and output it to the original control system of the crane through the execution adapter module.

9. The method according to claim 8, characterized in that, It also includes parameter calibration steps: S01: Under the condition of no lifting and no luffing, the crane rotates at a known and constant angular velocity ω, maintaining a fixed luffing amplitude r for a certain period of time T. Record the maximum value θ1 of the stable tangential swing angle measured by the dual-axis tilt sensor, and substitute it into k1=θ1 / (ω 2 k1 is obtained by calculating rT; S02: Under conditions of no lifting and no amplitude variation, the vehicle starts from rest and rotates uniformly with a known and constant angular acceleration α, maintaining a fixed amplitude variation r. After the uniformly accelerated rotation continues for a certain time T, the maximum value θ2 of the stable tangential swing angle measured by the dual-axis tilt sensor is recorded and substituted into... Calculated ; S03: Control the crane to perform lifting or lowering operations at a known, constant acceleration 'a' under conditions of no slewing and no luffing, for a certain period of time T. During this process, record the maximum working length L0 of the wire rope and the current wire rope length L, and measure the maximum stable swing angle θ3 using a dual-axis tilt sensor, then substitute it into... The calculated value is k3.

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