Sensor-based wind-resistant control method and system for a crane

Abstract

The application relates to the technical field of intelligent safety control of hoisting machinery, and discloses a crane wind resistance control method and system based on a sensor, the method comprising the following steps: obtaining an initial instantaneous wind speed sequence through a wind speed sensor and preprocessing the initial instantaneous wind speed sequence to obtain an average wind speed; calculating a target lateral thrust according to the average wind speed and a windward parameter of a hoisted object; calculating an initial longitudinal tension according to a rotation pulse sequence of a hoist and the mass of the hoisted object; performing vector fusion on the target lateral thrust and the initial longitudinal tension to obtain a stress deflection angle; if the stress deflection angle is greater than a preset deflection threshold, generating an abnormal early warning signal, determining a speed reduction amplitude according to the abnormal early warning signal, and outputting a running speed reduction instruction according to the speed reduction amplitude. The method can automatically control hoist speed reduction according to environmental changes.

Description

Technical Field

[0001] This invention relates to the field of intelligent safety control technology for lifting machinery, and in particular to a sensor-based method and system for wind-resistant control of cranes. Background Technology

[0002] Currently, with the large-scale development of the port freight industry, remote control systems for port container cranes have been widely implemented. Container cranes often carry out lifting operations around the clock at open-air terminals, where wind speeds are highly random and gusts are frequent.

[0003] In one existing technology, wind speed monitoring is involved in the safe shutdown control of cranes, but a speed control logic linking wind speed signals and hoist operating parameters has not yet been established. Remote operators rely solely on on-site visuals and anemometer readings, manually adjusting the hoisting mechanism's operating speed based on their operational experience. Lacking automated control logic linking wind load and lifting tension, they cannot accurately calculate lateral wind thrust based on measured wind speeds, nor can they couple lateral wind thrust with vertical tension to assess the risk of wire rope tension overload and container swaying. Consequently, they cannot autonomously issue speed control commands based on abnormal forces. When sudden gusts of wind strike, the strong winds exert lateral impact forces on suspended containers. If the hoisting hoist continues at its original lifting speed, the lateral wind thrust and vertical lifting tension combine, easily causing the wire rope to exceed its limits, resulting in significant cargo swaying and even collisions with surrounding facilities.

[0004] Existing technologies have the problem that cranes cannot automatically control the speed reduction of the winch according to environmental changes. Summary of the Invention

[0005] This invention provides a sensor-based method and system for controlling the wind resistance of cranes, in order to solve the problem that cranes cannot automatically control the speed reduction of the winch according to environmental changes.

[0006] In a first aspect, to solve the above-mentioned technical problems, the present invention provides a sensor-based crane wind resistance control method, comprising: An initial instantaneous wind speed sequence is obtained by using a wind speed sensor, and the average wind speed is obtained by preprocessing the initial instantaneous wind speed sequence. The windward parameters and air density of the lifted load are obtained, and the target lateral thrust is calculated based on the average wind speed, the air density, and the windward parameters. The rotation pulse sequence of the winch and the mass of the lifted load are obtained. The instantaneous acceleration is calculated based on the rotation pulse sequence, and the initial longitudinal tension is calculated in combination with the mass of the lifted load. The target lateral thrust and the initial longitudinal tension are vector-fused to obtain a superimposed force characteristic vector, and the force deflection angle is calculated based on the superimposed force characteristic vector. If the force deflection angle is greater than the preset deflection threshold, an abnormal warning signal is generated. The deceleration range is determined based on the abnormal warning signal, and a deceleration command is output based on the deceleration range.

[0007] In a second aspect, the present invention provides a sensor-based crane wind-resistant control system, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described above.

[0008] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0009] Compared with the prior art, the present invention has the following beneficial effects: (1) This invention collects the original instantaneous wind speed sequence from the site and sequentially performs multi-layer data optimization processing, including timestamp alignment, removal of abnormal wind speed values, interpolation filling of missing data, and smoothing with a fixed window sliding mean. It relies on standardized data processing logic to filter out wind speed spikes caused by on-site turbulence disturbances and sensor hardware noise. In the open-air operation environment of ports, natural gusts are highly random and instantaneous wind speeds fluctuate greatly. Unprocessed raw wind speed data contains a large number of invalid extreme values. Directly using it for wind load calculation will cause serious deviations in the lateral thrust results, which in turn leads to distortion of the entire set of force analysis data. This invention abandons the crude mode of directly using the original collected wind speed for calculation. Instead, it uses the filtered and optimized stable wind speed as a benchmark and combines fixed parameters such as air density, windward area of ​​heavy objects, and drag coefficient to accurately solve for air dynamic pressure and lateral wind thrust, eliminating the calculation error caused by abnormal wind speed data from the source.

[0010] (2) This invention collects the pulse signal of the hoist spindle and converts it into the real-time operating linear speed. It obtains the instantaneous lifting acceleration through differential calculation, and accurately calculates the longitudinal lifting force of the hoist by combining the weight of the load and the gravitational acceleration. Then, it realizes the fusion and packaging of the lateral wind thrust and the longitudinal tension through vector calculation of the orthogonal coordinate system, and constructs a superimposed force characteristic vector containing multi-dimensional parameters. In the existing traditional remote control mode, the wind load and the mechanical lifting force belong to two independent calculation systems. The staff can only rely on visual observation and experience to estimate the two forces separately, which cannot realize the bidirectional force coupling quantification and makes it difficult to accurately determine the actual load state of the wire rope. This invention realizes the integrated quantitative analysis of wind load and mechanical lifting load, transforming the abstract wire rope force risk into a quantifiable force deflection angle, and getting rid of the subjective error brought about by manual experience estimation.

[0011] (3) After triggering an early warning due to an excessive force deflection angle, this invention automatically extracts the wind speed change gradient from the historical wind speed sequence differential, and calculates the dynamic safety margin by linking the real-time operating linear speed of the winch. Based on the margin gap, it automatically calculates the reasonable speed reduction range and issues a generator speed adjustment command, eliminating the need for manual intervention by remote operators. Traditional port container crane remote control systems rely entirely on operators closely monitoring the screen and observing the wind speed instrument before manually adjusting the speed. When gusts occur, there is a significant lag in personnel response, often resulting in a sudden increase in wind force while the winch maintains its original lifting speed. This invention establishes a closed-loop control logic linking wind speed changes with equipment operating speed, which can adjust the lifting speed in real time to match wind force changes, buffer the impact of the spreader swing caused by wind load, and reduce the safety hazards of wire rope overload breakage and cargo falling. Attached Figure Description

[0012] Figure 1 This is a schematic flowchart of the sensor-based crane wind resistance control method provided in the first embodiment of the present invention; Figure 2 This is a two-dimensional broken line trend chart of force deflection angle and early warning trigger provided in the first embodiment of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] Reference Figure 1 The first embodiment of the present invention provides a sensor-based crane wind resistance control method, comprising the following steps: S11, the initial instantaneous wind speed sequence is obtained through the wind speed sensor, and the initial instantaneous wind speed sequence is preprocessed to obtain the average wind speed; S12, obtain the windward parameters and air density of the lifted load, and calculate the target lateral thrust based on the average wind speed, the air density and the windward parameters; S13, obtain the rotation pulse sequence of the winch and the mass of the hoisted object, calculate the instantaneous acceleration based on the rotation pulse sequence, and calculate the initial longitudinal tension based on the mass of the hoisted object; S14, the target lateral thrust and the initial longitudinal tension are vector-fused to obtain a superimposed force characteristic vector, and the force deflection angle is calculated based on the superimposed force characteristic vector; S15, if the force deflection angle is greater than the preset deflection threshold, an abnormal warning signal is generated, the deceleration range is determined according to the abnormal warning signal, and the operation deceleration command is output according to the deceleration range.

[0015] In step S11, an initial instantaneous wind speed sequence is acquired using a wind speed sensor, the initial instantaneous wind speed sequence is smoothed to obtain a target wind speed sequence, and the target wind speed sequence is arithmetically averaged to obtain the average wind speed, including: The initial instantaneous wind speed sequence is aligned according to the timestamps to obtain the aligned wind speed sequence; Traverse the wind speed values ​​in the aligned wind speed sequence, remove the wind speed values ​​whose change exceeds a preset change limit, and interpolate and fill the aligned wind speed sequence after removal to obtain a continuous wind speed sequence. The continuous wind speed sequence is subjected to moving mean filtering using a sliding window of fixed length to obtain the target wind speed sequence; The average wind speed is obtained by calculating the arithmetic mean of the wind speed data in the target wind speed sequence.

[0016] In one implementation, this embodiment preprocesses the raw wind speed data collected by the sensor to obtain a target wind speed sequence that can be used for subsequent aerodynamic analysis, and further calculates the average wind speed. Specifically, this includes four sub-steps: timestamp alignment, outlier removal and interpolation filling, moving average filtering, and arithmetic mean.

[0017] It should be noted that after obtaining the initial instantaneous wind speed sequence, each wind speed data point in the sequence is first bound to its corresponding acquisition timestamp, forming a time-wind speed pair. Since the sensor may experience slight clock drift or data loss at different sampling periods, the system resamples and aligns all data points using a unified time base and the system clock in milliseconds, resulting in an aligned wind speed sequence. This alignment operation ensures that the time intervals between adjacent data points are consistent in subsequent processing, providing an effective prerequisite for differential operations and sliding window filtering.

[0018] Furthermore, the wind speed values ​​in the aligned wind speed sequence are traversed, and the change in wind speed between the current and previous values ​​is calculated. Referring to the gust factor in GB / T 3811 "Crane Design Code" or the wind speed fluctuation statistics in IEC 61400, at a sampling frequency of 1 Hz, the change in adjacent wind speeds at the leading edge of a normal gust typically does not exceed 30%. Therefore, the preset change limit is set to 30%. When the change exceeds 30%, the current wind speed value is determined to be an abnormal extreme value and is removed. The aligned wind speed sequence after removal is then interpolated to obtain a continuous wind speed sequence. After removing outliers, data gaps occur at the original positions. Interpolation is used to fill the gaps, taking the two valid wind speed values ​​before and after the gap point, and calculating the filling value according to the time interval ratio to obtain a continuous wind speed sequence.

[0019] It should be noted that a fixed-length sliding window is used to perform moving average filtering on the continuous wind speed sequence. The length of the sliding window can be set to 5 sampling points, and the window moves point by point along the time axis. The 5 sampling points are typically set between 0.1 Hz and 1 Hz based on the turbulence frequency of the port wind speed signal. The 5 sampling points correspond to a 5-second duration. When the sampling frequency is 1 Hz, it can effectively suppress high-frequency noise from the sensor while retaining the true trend of gust changes, avoiding excessive smoothing that leads to wind load response lag. At each window position, the wind speed value within the window is arithmetically averaged, and the result is used as the filtered wind speed value at the center point of the window. The arithmetic mean of all wind speed data in the target wind speed sequence is calculated, that is, the wind speed values ​​at each time point in the sequence are summed and then divided by the sequence length to obtain the average wind speed.

[0020] For example, the wind farm data acquisition system uses an ultrasonic anemometer deployed on the top of the wind measurement tower to continuously collect 600 seconds of external environmental wind speed data at a sampling frequency of 1 Hz, constructing an initial instantaneous wind speed sequence containing 600 discrete data points. For instance, the wind speed is recorded as 8.5 m / s in the first second, 12.3 m / s in the second second, and 7.2 m / s in the third second. The system first binds each wind speed value to the acquisition timestamp and aligns them according to a unified time axis to obtain an aligned wind speed sequence. Then, it iterates through the sequence and detects that the wind speed of 12.3 m / s in the second second has a change of 44.7% compared to 8.5 m / s in the first second, exceeding the preset change limit of 30%, so this abnormal extreme value is removed. The missing data in the second second is filled using linear interpolation, taking the average of 8.5 m / s in the first second and 7.2 m / s in the third second, 7.85 m / s, as the filler value, to obtain a continuous wind speed sequence.

[0021] Next, the system sets a sliding window of length 5 to perform moving average filtering on the continuous wind speed sequence. When the center of the window corresponds to the 3rd second, the window covers the wind speed values ​​from the 1st to the 5th second (after filling, they are 8.5, 7.85, 7.2, 9.1, and 8.8). The arithmetic mean is calculated as (8.5 + 7.85 + 7.2 + 9.1 + 8.8) / 5 = 8.29 meters per second, which is used as the wind speed value for the 3rd second in the filtered target wind speed sequence. This process is repeated for all 600 data points to obtain the smoothed target wind speed sequence. Finally, the arithmetic mean of all 600 wind speed data points in the target wind speed sequence is calculated to obtain the average wind speed.

[0022] It is worth noting that this embodiment implements a complete data preprocessing workflow from raw instantaneous wind speed acquisition to smoothed wind speed sequences and then to average wind speed. Timestamp alignment ensures the accuracy of data timing, outlier removal and interpolation filling eliminate missing data from sensor acquisition, and moving average filtering effectively suppresses high-frequency noise. The final average wind speed provides stable and reliable basic parameters for subsequent lateral thrust calculations.

[0023] In step S12, the windward parameters and air density of the lifted load are obtained, and the target lateral thrust is calculated based on the average wind speed, the air density, and the windward parameters, including: The windward projected area and drag coefficient of the heavy object are obtained as the windward parameters; The air dynamic pressure is calculated using the air dynamic pressure formula based on the average wind speed and the air density. The target lateral thrust is obtained by multiplying the aerodynamic pressure with the windward projected area and the drag coefficient.

[0024] In one implementation, this embodiment calculates the target lateral thrust acting on the lifted load based on the average wind speed, combined with air density and the windward parameters of the load. Specifically, this includes three sub-steps: obtaining the windward parameters, solving for the air dynamic pressure, and performing a multiplication operation.

[0025] It should be noted that the windward parameters include the windward projected area of ​​the load and the drag coefficient. The windward projected area refers to the projected area of ​​the load on a plane perpendicular to the wind direction, and its value varies with the load's attitude and shape. The drag coefficient is a dimensionless parameter characterizing the obstruction of airflow by the load's shape, and is related to the load's geometry and surface roughness. The windward projected area of ​​the load is obtained as follows: First, the real-time spatial attitude of the load is acquired. A dual-axis tilt sensor is installed on the lifting device to measure the swing angle of the lifting device (and the load) relative to the vertical direction in real time. This swing angle is decomposed into two components: one parallel and one perpendicular to the wind direction. Simultaneously, the real-time wind direction is obtained through a wind vane and anemometer installed on the top of the crane boom. The system calculates the effective windward projected area based on the standard windward area of ​​the load, the swing angle measured by the tilt sensor, and the angle between the wind direction and the crane track using trigonometric functions. For example, the effective area is calculated by multiplying the frontal area by the absolute value of the cosine of the first swing angle, then multiplying the side area by the absolute value of the sine of the second swing angle, and finally adding these two products together. For non-standard shaped loads, the system defaults to using the largest outer contour envelope as the calculation benchmark, and the operator manually inputs the equivalent frontal and side projected areas through the human-machine interface before operation.

[0026] It is worth further clarification that the drag coefficient is derived from publicly available knowledge in the field of aerodynamics, based on the shape of the object. For standard rectangular containers, this coefficient is set according to industry-standard empirical values; for other shaped objects, values ​​are derived by analogy with standard shapes that are similar in appearance; for example, 1.2 is used for rectangular containers, 1.0 for cylindrical tanks, 0.6 for spherical or streamlined objects, and 1.8 for irregular or complex-shaped objects. Those skilled in the art will understand that the above empirical values ​​are common knowledge in the field of aerodynamics and do not require determination through additional experiments.

[0027] It is worth noting that the average wind speed and air density are substituted into the aerodynamic pressure formula to obtain the aerodynamic pressure. The aerodynamic pressure formula is based on Bernoulli's principle; specifically, the aerodynamic pressure equals half the air density multiplied by the square of the average wind speed. The air density is assumed to be 1.225 kg / m³, based on standard atmospheric pressure and dry air at 15°C. When the ambient temperature deviates from 15°C by more than ±10°C, a temperature correction is applied using 1.225 × (273.15 + 15) / (273.15 + t), where t is the measured ambient temperature. The obtained aerodynamic pressure is multiplied by the windward projected area and the drag coefficient to obtain the target lateral thrust; the target lateral thrust equals the aerodynamic pressure multiplied by the windward projected area multiplied by the drag coefficient. This thrust is perpendicular to the windward side of the object and aligns with the wind direction.

[0028] For example, the target wind speed sequence is read, and a data segment of the first ten seconds before the current moment is extracted to calculate the average wind speed value. Assuming the current average wind speed is 8.75 meters per second and the local standard air density parameter is 1.225 kilograms per cubic meter, the aerodynamic pressure characteristic value of the current flow field is calculated to be 46.89 Pascals by substituting it into the aerodynamic pressure calculation relationship.

[0029] Subsequently, the real-time swing angle of the load is obtained through a dual-axis tilt sensor mounted on the spreader. Assuming the load is a 20-foot standard container with a frontal area of ​​30 square meters and a side area of ​​18 square meters, the system obtains that the current wind direction forms a 30-degree angle with the container's front. Based on geometric projection relationships, the effective windward projected area is calculated: frontal area multiplied by the cosine of 30 degrees plus side area multiplied by the sine of 30 degrees, i.e., 30 multiplied by 0.866 plus 18 multiplied by 0.5, equals 25.98 plus 9, resulting in an effective windward projected area of ​​34.98 square meters. The drag coefficient is set to 1.2 based on the container's shape and publicly available aerodynamic knowledge. The computational core performs continuous multiplication of the aerodynamic pressure characteristic value of 46.89 Pascals with the effective windward projected area of ​​34.98 square meters and the drag coefficient of 1.2 to calculate the target lateral thrust acting on the surface of the lifted load at the current moment.

[0030] In step S13, the rotation pulse sequence of the winch and the mass of the lifted load are obtained. Instantaneous acceleration is calculated based on the rotation pulse sequence, and the initial longitudinal tension is calculated in conjunction with the mass of the lifted load. This includes: Obtain the rotation pulse sequence of the winch spindle and the effective winding radius of the winch drum. Determine the spindle angular velocity based on the rotation pulse sequence. Multiply the spindle angular velocity by the effective winding radius to obtain the current operating linear speed. The current operating linear speed is smoothed and filtered to obtain the filtered operating linear speed. Obtain the filtered linear velocity corresponding to the previous sampling time, and perform a first-order backward difference operation between the filtered linear velocity at the previous sampling time and the filtered linear velocity at the current sampling time to obtain the instantaneous acceleration. The initial longitudinal tension is calculated by reading the mass of the object fed back by the weighing sensor, multiplying the mass of the object by the sum of the gravitational acceleration constant and the instantaneous acceleration.

[0031] In one implementation, this embodiment calculates the initial longitudinal tension generated by the wire rope during lifting based on the rotational pulse sequence of the winch spindle and the mass of the load. Specifically, this includes converting the current operating linear speed, differentially solving for the instantaneous acceleration, and calculating the initial longitudinal tension.

[0032] It should be noted that the system acquires the rotational pulse sequence of the winch spindle and the effective winding radius of the winch drum. The rotational pulse sequence is acquired in real-time by a high-precision absolute encoder or incremental encoder mounted on the winch spindle, with each pulse corresponding to a fixed rotation angle of the spindle. The effective winding radius refers to the actual winding radius of the wire rope on the drum. This parameter varies with the number of layers of wire rope on the drum and can be calculated in real-time by the system based on the current number of rotations of the winch mechanism and the drum's geometric parameters, or read from the equipment parameter table. The system determines the current angular velocity of the spindle based on the rotational pulse sequence, counts the number of pulses acquired per unit time, and calculates the angular velocity of the spindle in radians per second by combining the rotation angle corresponding to each pulse. Multiplying the spindle angular velocity by the effective winding radius yields the current linear speed of the winch mechanism in meters per second.

[0033] In one implementation, the effective winding radius is directly taken as the nominal winding radius of the drum, which is the sum of the drum's radius and the wire rope's radius, and is a fixed value. Specifically, in the actual control systems of most port cranes, the radius variation caused by multiple layers of winding has a small impact on the final control result and is usually ignored in engineering. Therefore, the system directly uses this fixed radius as the effective winding radius to calculate the current operating linear speed.

[0034] In another implementation, the effective winding radius can also be obtained by multiplying the current number of wire rope layers on the drum (starting from the first layer) by the wire rope diameter, and then adding the drum radius; a fixed nominal radius is used by default, and it is automatically switched to a dynamic calculation value when the crane is equipped with a layer detection device.

[0035] It is worth further explaining that, upon obtaining the linear velocity at the previous sampling moment, the system caches the calculated linear velocity value at each sampling moment in memory. To avoid instability in instantaneous acceleration calculation caused by noise from direct differential amplification measurement, in a preferred embodiment, the current linear velocity obtained from the rotational pulse sequence is filtered before calculating the instantaneous acceleration. Specifically, the system maintains a linear velocity data queue of length 5 in memory. Each time a new current linear velocity value is obtained, it is stored at the tail of the queue, and the oldest value at the head of the queue is removed. Then, the arithmetic mean of the 5 linear velocity values ​​in the queue is calculated to obtain a filtered linear velocity. Finally, a first-order backward difference operation is performed using the filtered linear velocities from two adjacent sampling moments, and the difference is divided by the sampling period to calculate the instantaneous acceleration. This instantaneous acceleration reflects the rate of change of velocity of the weight in the vertical direction, i.e., the real-time acceleration during lifting or lowering.

[0036] Further, the mass of the load is read from the load cell. The load cell, mounted on the hook or lifting device, measures the static load mass of the suspended object in real time, in kilograms. The gravitational acceleration constant is obtained, typically 9.81 m / s², which can be fine-tuned based on the latitude of the crane's installation location. The initial longitudinal tension is calculated by multiplying the mass of the load by the sum of the gravitational acceleration constant and the instantaneous acceleration. The initial longitudinal tension equals the mass of the load multiplied by the sum of the gravitational acceleration constant and the instantaneous acceleration. The sum of the gravitational acceleration constant and the instantaneous acceleration reflects the total acceleration of the load in the vertical direction.

[0037] It is important to clarify that, in order to accurately calculate the instantaneous acceleration, the rotational pulse sequence of the winch spindle must be collected at a fixed, equally spaced sampling period. The sampling period is a preset constant time length, such as 50 milliseconds, 100 milliseconds, or 200 milliseconds. The selection of the sampling period depends on the minimum time interval of the encoder output pulses and the interruption response capability of the control system. It is typically one-tenth of the minimum interval between adjacent encoder pulses to ensure the numerical stability of the acceleration differential calculation. In typical port crane configurations, a period of 50 to 200 milliseconds can meet the control accuracy requirements; the specific value is automatically configured based on the encoder model during system initialization. When performing the first-order backward differential operation, the difference between the current operating linear speed and the operating linear speed at the previous sampling time is first calculated. Then, this difference is divided by the fixed sampling period, and the quotient is the instantaneous acceleration. If the sampling period fluctuates unexpectedly due to system interruption or sensor delay, the system will ignore the data from the current sampling period and use the instantaneous acceleration calculated from the previous valid sampling period until the sampling stabilizes.

[0038] For example, the rotational pulse signal of the hoist mechanism's main shaft is acquired in real time using a high-precision absolute encoder. Assume that the system calculates the main shaft's rotational angular velocity to be 2.09 radians per second during the current sampling period. The control system retrieves the effective winding radius of the hoist drum from the equipment register. Assume the wire rope is currently on the first layer of the drum, with an effective winding radius of 0.45 meters. The system multiplies the main shaft angular velocity of 2.09 radians per second by the effective winding radius of 0.45 meters to calculate the current linear velocity as 0.94 meters per second. The microprocessor extracts the linear velocity data from the previous sampling moment. Assume the previous sampling moment was 50 milliseconds ago, at which time the linear velocity was 0.91 meters per second. Using a first-order backward difference operation: subtracting the previous sampling moment's linear velocity of 0.91 meters per second from the current linear velocity of 0.94 meters per second yields a difference of 0.03 meters per second. Dividing this difference by the sampling time interval of 0.05 seconds, the instantaneous acceleration of the current mechanical lifting is calculated to be 0.6 meters per second squared. The dynamics calculation unit reads the static load mass of the lifted object from the load cell, assuming the current mass is 12,500 kg. The gravitational acceleration constant of 9.81 m / s² is obtained. Adding the gravitational acceleration constant to the instantaneous acceleration yields a total acceleration of 10.41 m / s². Multiplying the object mass of 12,500 kg by the total acceleration of 10.41 m / s², the initial longitudinal tension is calculated to be 130,125.0 Newtons.

[0039] It is worth noting that this embodiment realizes a complete calculation process from the winch rotation pulse sequence and the mass of the load to the initial longitudinal tension. The linear speed of operation is converted by encoder pulse counting, the instantaneous acceleration is solved by first-order backward differential, and the longitudinal tension is calculated using dynamic equations. This allows for the quantification of the vertical mechanical load applied to the load by the winch mechanism during the lifting process.

[0040] It should be noted that, to avoid interference from longitudinal tension changes caused by operator-initiated acceleration / deceleration commands on the force deflection angle calculation, and to ensure that the speed reduction command is triggered only by wind load disturbances rather than normal operational dynamic loads, this method first determines the operating status of the winch before performing the speed reduction magnitude calculation and outputting the speed reduction command. Specifically, the system reads the speed command signal from the winch inverter in real time and obtains the current actual operating linear speed fed back by the encoder. When the speed command signal remains unchanged for N consecutive sampling periods, where N is a preset positive integer ranging from 3 to 10, and the deviation of the current actual operating linear speed from the speed command signal is less than a preset deviation threshold (1% of the rated speed), the winch is determined to be in a steady-speed operating state. If the winch is determined to be in a steady-speed operating state, the subsequent steps of wind speed change gradient extraction, dynamic safety margin calculation, and speed reduction magnitude determination are continued; if the winch is determined to be in a non-steady-speed operating state, the system skips the speed reduction magnitude calculation and command output for the current sampling period and waits for the next sampling period to re-determine the steady-speed condition.

[0041] In step S14, the target lateral thrust and the initial longitudinal tension are vector-fused to obtain a superimposed force characteristic vector. The force deflection angle is calculated based on the superimposed force characteristic vector, including: Establish an orthogonal coordinate system, mapping the target lateral thrust to lateral coordinate components and the initial longitudinal tension to vertical coordinate components; The resultant force modulus is obtained by performing a square root operation on the sum of the squares of the horizontal coordinate components and the vertical coordinate components. The horizontal coordinate components, the vertical coordinate components, and the resultant force modulus are packaged together to generate a superimposed force feature vector; The force deflection angle is calculated using the arctangent function based on the ratio of the horizontal coordinate component to the vertical coordinate component in the superimposed force characteristic vector.

[0042] In one implementation, this embodiment performs vector fusion of the target lateral thrust calculated in step S12 and the initial longitudinal tension calculated in step S13 to generate a superimposed force characteristic vector, and calculates the force deflection angle based on this characteristic vector. This characteristic vector comprehensively reflects the overall force state of the heavy object under the combined action of horizontal wind load and vertical mechanical tension.

[0043] It should be noted that in this embodiment, an orthogonal coordinate system is established with the lifting point or the center of gravity of the weight as the origin. The horizontal direction is the x-axis, and the vertical direction is the y-axis. The target lateral thrust obtained in step S12 is mapped to a lateral coordinate component, the direction of which is consistent with the wind direction, and the value is equal to the magnitude of the target lateral thrust. The initial longitudinal tension obtained in step S13 is mapped to a vertical coordinate component, the direction of which is vertically upward, and the value is equal to the magnitude of the initial longitudinal tension. Through the above mapping, two mutually perpendicular forces are transformed into two orthogonal components in the coordinate system. The square root of the sum of the squares of the lateral and vertical coordinate components is performed to obtain the resultant force modulus. The lateral, vertical, and resultant force modulus components are packaged together to generate a superimposed force feature vector. This feature vector can be organized in the form of an array, structure, or data frame, containing force information in the above three dimensions.

[0044] Further, based on the ratio of the lateral to the vertical coordinate components in the superimposed force feature vector, the force deflection angle is calculated using the arctangent function. The force deflection angle reflects the angle between the resultant force direction and the vertical direction. The lateral coordinate component is divided by the vertical coordinate component to obtain the ratio, and then the arctangent function is applied to this ratio to obtain the force deflection angle, in degrees. When the lateral thrust is zero, the force deflection angle is zero, indicating that the resultant force direction is vertically downward; when the lateral thrust increases, the force deflection angle increases accordingly, indicating that the resultant force direction deviates from the vertical direction. This force deflection angle is used in subsequent steps to compare with a deflection threshold to determine whether there is any abnormal risk in the current force state.

[0045] For example, the vector synthesis engine receives the target lateral thrust value and the initial longitudinal tension value from the previous data stream. Assume that the target lateral thrust is 1969.2 Newtons and the initial longitudinal tension is 130125.0 Newtons at the current moment.

[0046] The system establishes an orthogonal coordinate system with the lifting point as the spatial origin, the horizontal axis pointing in the horizontal wind direction, and the vertical axis pointing vertically upward. The target lateral thrust of 1969.2 Newtons is mapped to a lateral coordinate component, and the initial longitudinal tension of 130125.0 Newtons is mapped to a vertical coordinate component. The matrix operator performs a square root operation on these two orthogonal components: calculating the sum of the squares of 1969.2 and 130125.0, and then taking the square root of the sum to obtain the resultant force modulus of 130139.9 Newtons. The system packages the lateral coordinate component of 1969.2 Newtons, the vertical coordinate component of 130125.0 Newtons, and the resultant force modulus of 130139.9 Newtons into a superimposed force characteristic vector containing the above three parameters.

[0047] Subsequently, based on the ratio of the horizontal coordinate component to the vertical coordinate component in the superimposed force feature vector, the force deflection angle is calculated using the arctangent function: dividing 1969.2 by 130125.0 and taking the arctangent function of this ratio, the force deflection angle is approximately 0.87 degrees. This force deflection angle will be output to step S15 for comparison with the deflection threshold.

[0048] It should be noted that this embodiment realizes the vector fusion of the target lateral thrust and the initial longitudinal tension, as well as the calculation of the force deflection angle. By establishing an orthogonal coordinate system, the two mutually perpendicular forces are mapped into coordinate components. The resultant force modulus is solved using the square root operation. The force information of the three dimensions is packaged to generate a superimposed force feature vector. Then, the force deflection angle is calculated using the arctangent function.

[0049] In step S15, if the force deflection angle is greater than a preset deflection threshold, an abnormality warning signal is generated. The deceleration range is determined based on the abnormality warning signal, and an operation deceleration command is output based on the deceleration range, including: Based on the abnormal warning signal, the wind speed change gradient is extracted from the initial instantaneous wind speed sequence; Obtain the response time constant of the speed adjustment of the winch drive system, and calculate the wind impact rise time based on the wind speed change gradient; Calculate the ratio of the wind impact rise time to the response time constant, and use the ratio as a dynamic safety margin; Obtain the current load rate. If the dynamic safety margin is less than or equal to the preset safety threshold, calculate the speed reduction based on the difference between the preset safety threshold and the dynamic safety margin, combined with the current load rate and the current operating line speed. A speed reduction command is generated and output based on the stated speed reduction magnitude.

[0050] In one implementation, after calculating the force deflection angle in step S14, this embodiment compares the force deflection angle with a preset deflection threshold. When the force deflection angle is greater than the preset deflection threshold, it indicates that the resultant force direction of the current lateral wind thrust and longitudinal tension has deviated from the vertical direction and exceeded the safety limit. The wire rope is at risk of tension overload or the heavy object swinging and becoming unstable, and the system generates an abnormal warning signal.

[0051] It should be noted that the preset deflection threshold is an angle limit pre-set according to the crane safety operation specifications, used to determine whether there is an abnormal risk of stress on the wire rope. When the force deflection angle does not exceed this threshold, it indicates that the current stress state is within the safe range, the system does not generate a warning signal, and continues to execute the next monitoring cycle. In lifting operations, the force deflection angle θ reflects the degree of deviation between the resultant force direction and the vertical direction. According to the wire rope tension calculation formula T=mg / cosθ, when the deflection angle θ increases, the wire rope tension T increases non-linearly. Taking the typical operating conditions of a container crane as an example, when the deflection angle reaches 3 degrees, the wire rope tension is approximately 1.001 times that of the static load, and the impact is negligible; when the deflection angle reaches 10 degrees, the tension increases to 1.015 times that of the static load; when the deflection angle reaches 30 degrees, the tension increases to 1.155 times that of the static load; the above tension amplification is a static theoretical value. However, the more dangerous factor during lifting is the inertial impact of swinging. According to statistics from crane swing tests, when the deflection angle exceeds 4-5 degrees, the additional dynamic load generated by the swinging of the load can cause the instantaneous tension of the wire rope to reach 1.3-1.5 times the static load. Therefore, the default preset deflection threshold for the lifting rope of container cranes is 3 degrees; it can be adjusted within the range of 3 to 5 degrees according to the rated lifting capacity of the crane and the safety factor of the wire rope. The larger the rated lifting capacity or the lower the safety factor, the smaller the threshold value should be. For cranes with a rated lifting capacity of less than 50 tons, the threshold can be 5 degrees; for 50 tons to 200 tons, it can be 4 degrees; and for more than 200 tons, it can be 3 degrees.

[0052] Furthermore, in response to the abnormal warning signal, the system extracts the wind speed change gradient from the initial instantaneous wind speed sequence. The wind speed change gradient reflects the drastic change in wind speed over time, and is measured in meters per second squared. Specifically, the system extracts a historical target wind speed sequence within a time window of 10 seconds prior to the current moment, performs a first-order difference operation on the wind speed values ​​at adjacent sampling moments in the sequence, divides the difference result by the sampling period to obtain the wind speed change gradient in meters per second squared, and extracts the maximum wind speed change gradient as a quantitative indicator of the degree of abrupt change in the current wind field.

[0053] It should be noted that the response time constant of the winch drive system is an inherent parameter of the winch drive system, which can be obtained by consulting the technical manual of the winch inverter or motor. It represents the inherent delay time required from the issuance of the speed regulation command to the actual start of the change in motor speed.

[0054] The wind impact rise time is calculated based on the wind speed change gradient. Specifically, the average wind speed at the current moment is first obtained, and then the expected peak wind speed impact is determined. This peak value is set based on historical wind speed data or local meteorological statistics, typically 20 m / s, which is the normal shutdown wind speed threshold for port container cranes, or twice the current average wind speed. The expected peak wind speed impact is subtracted from the current average wind speed to obtain the expected total wind speed change. This total wind speed change is then divided by the wind speed change gradient to obtain the wind impact rise time.

[0055] Furthermore, if the dynamic safety margin is less than or equal to a preset safety threshold, it is determined that the response speed of the current winch drive system is insufficient to cope with sudden changes in wind speed, and speed reduction measures are required. In this case, the speed reduction magnitude is determined based on the difference between the preset safety threshold and the dynamic safety margin, combined with the current load rate and the current operating linear speed. Specifically, the difference is multiplied by 1 and summed with the current load rate to obtain a dynamic speed reduction coefficient, resulting in a total speed reduction ratio. This ratio is then multiplied by the current operating linear speed to obtain the speed reduction magnitude. If the speed reduction magnitude reaches 90% or more of the current operating linear speed, a braking stop command is directly output. The load rate is the ratio of the current lifting weight to the crane's rated lifting weight. An operating speed reduction command is generated and output based on the speed reduction magnitude. The operating speed reduction command includes speed reduction magnitude information and is sent to the winch's frequency converter in percentage or target speed value form to control the winch to reduce its current operating linear speed.

[0056] It should be noted that the preset safety threshold is a critical value used to determine whether the dynamic safety margin meets the safety conditions. The dynamic safety margin is the ratio of the wind impact rise time to the response time constant of the winch drive system, reflecting the adequacy of the drive system's response speed relative to the rate of wind speed change.

[0057] When the dynamic safety margin is greater than 1.5, it indicates that the wind impact rise time is much longer than the system response time, and the system has ample time to complete speed adjustment, which is considered safe. When the dynamic safety margin is between 1.0 and 1.5, it indicates that the wind impact rise time is close to the system response time, which poses a certain risk, and it is recommended to maintain early warning monitoring. When the dynamic safety margin is less than or equal to 1.0, it indicates that the wind speed change is faster than the response capability of the drive system, which is considered unsafe, and speed reduction measures must be taken.

[0058] In a preferred embodiment, to ensure the safety of the speed adjustment process, a preset safety threshold is set to 1.5, which is equivalent to reserving a 50% safety margin to cover non-ideal factors such as sensor delay, control link delay, and wind speed prediction deviation. This threshold can be adjusted by the system administrator according to the crane's rated lifting capacity, drive system performance, and operating environment requirements, and the value range is typically from 1.2 to 2.0. For high-performance drive systems or low-latency control links, the threshold can be reduced to 1.2; for older equipment or high-precision operating scenarios, the threshold can be increased to 2.0.

[0059] For example, assume the force deflection angle calculated in step S14 is 4.5 degrees, and the preset deflection threshold is 3.0 degrees. Since 4.5 degrees is greater than 3.0 degrees, the system generates an abnormal warning signal. In response to this warning signal, the system extracts the wind speed change gradient from the target wind speed sequence. Assuming the current average wind speed is 10 meters per second, the system extracts a wind speed change gradient of 2.5 meters per square second. The expected peak wind speed impact is set to 20 meters per second, the expected total wind speed change is 20 minus 10 equals 10 meters per second, and the wind impact rise time is 10 divided by 2.5, equals 4 seconds. Obtain the response time constant of the winch drive system, assuming this constant is 1.2 seconds. Calculate the dynamic safety margin: 4 divided by 1.2 equals 3.33. Assuming the preset safety threshold is 1.5, since 3.33 is greater than 1.5, the dynamic safety margin meets the preset safety condition, the system does not trigger a speed reduction, and only outputs a warning signal for the operator's reference.

[0060] In another example, assuming a wind speed gradient of 8 m / s², the wind impact rise time is 10 divided by 8, which equals 1.25 seconds. The dynamic safety margin is 1.25 divided by 1.2, which equals 1.04. Assuming a preset safety threshold of 1.5, since 1.04 is less than 1.5, the preset safety condition is not met. The current operating linear speed is 1.2 m / s, and the current load rate is 0.8. The deceleration rate is (1.5-1.04)×(1+0.8)×1.2, which equals 0.99 m / s. The system generates an operating deceleration command containing a deceleration rate of 0.99 m / s (or a deceleration ratio of 82.5%) and sends it to the winch frequency converter for execution.

[0061] It should be noted that after the system outputs the speed reduction command, it does not terminate the control process, but returns to the execution step S11, that is, to reacquire the initial instantaneous wind speed sequence and continue to execute all subsequent steps.

[0062] To further verify the effectiveness of the early warning mechanism based on force deflection angle proposed in this invention, an experiment simulating sudden gusts of wind was conducted in this embodiment; such as Figure 2 As shown, during the experiment, when approximately 8 seconds had elapsed, a sudden gust of wind caused the deflection angle of the lifted load (blue curve) to rapidly increase and exceed the preset warning threshold (red dashed line). At this point, the system accurately detected the abnormal force and immediately triggered an abnormal warning signal, corresponding to the position of the vertical red line in the figure. Subsequently, the control system executed a deceleration command based on the warning signal, causing the deflection angle of the load to quickly return to a safe range after a brief oscillation. The experimental results intuitively demonstrate that the present invention can capture dangerous working conditions in real time and respond promptly to ensure lifting safety.

[0063] In summary, this invention discloses a sensor-based crane wind resistance control method, comprising: acquiring an initial instantaneous wind speed sequence through a wind speed sensor and preprocessing it to obtain an average wind speed; calculating the target lateral thrust based on the average wind speed, air density, and the windward parameters of the lifted load; calculating the initial longitudinal tension based on the rotation pulse sequence of the winch; performing vector fusion of the target lateral thrust and the initial longitudinal tension to obtain a superimposed force feature vector, and calculating the force deflection angle based on the superimposed force feature vector; generating an abnormal warning signal if the force deflection angle is greater than a deflection threshold, and outputting an operation speed reduction command based on the abnormal warning signal.

[0064] The second embodiment of the present invention provides a sensor-based crane wind-resistant control system, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described above.

[0065] It should be noted that the sensor-based crane wind-resistant control system provided in this embodiment of the invention is used to execute all the process steps of the sensor-based crane wind-resistant control method in the above embodiment. The working principles and beneficial effects of the two are one-to-one, so they will not be described again.

[0066] It should be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0067] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that 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 for those skilled in the art.

Claims

1. A sensor-based method for controlling the wind resistance of a crane, characterized in that, include: An initial instantaneous wind speed sequence is acquired using a wind speed sensor. The initial instantaneous wind speed sequence is then preprocessed to obtain an average wind speed, including: aligning the initial instantaneous wind speed sequence according to timestamps to obtain an aligned wind speed sequence; iterating through the wind speed values ​​in the aligned wind speed sequence, removing wind speed values ​​whose changes in adjacent wind speed values ​​exceed a preset limit, and interpolating and filling the removed aligned wind speed sequence to obtain a continuous wind speed sequence; applying a moving average filter to the continuous wind speed sequence to obtain a target wind speed sequence; and calculating the arithmetic mean of the wind speed data in the target wind speed sequence to obtain the average wind speed. The process of obtaining the windward parameters and air density of the lifted load, and calculating the target lateral thrust based on the average wind speed, air density, and windward parameters includes: obtaining the windward projected area and drag coefficient of the load as the windward parameters; calculating the aerodynamic pressure according to the aerodynamic pressure formula based on the average wind speed and air density; and multiplying the aerodynamic pressure by the windward projected area and the drag coefficient to obtain the target lateral thrust. Obtain the rotation pulse sequence of the winch and the mass of the lifted load, calculate the instantaneous acceleration based on the rotation pulse sequence, and calculate the initial longitudinal tension based on the mass of the lifted load; The target lateral thrust and the initial longitudinal tension are vector-fused to obtain a superimposed force characteristic vector, and the force deflection angle is calculated based on the superimposed force characteristic vector. If the force deflection angle is greater than a preset deflection threshold, an abnormal warning signal is generated. The deceleration magnitude is determined based on the abnormal warning signal, and an operation deceleration command is output based on the deceleration magnitude. This includes: extracting the wind speed change gradient from the initial instantaneous wind speed sequence based on the abnormal warning signal; obtaining the response time constant of the speed adjustment of the winch drive system; calculating the wind impact rise time based on the wind speed change gradient; calculating the ratio of the wind impact rise time to the response time constant, and using the ratio as a dynamic safety margin; obtaining the current load rate; if the dynamic safety margin is less than or equal to a preset safety threshold, calculating the deceleration magnitude based on the difference between the preset safety threshold and the dynamic safety margin, combined with the current load rate and the current operating linear speed; and generating and outputting an operation deceleration command based on the deceleration magnitude.

2. The sensor-based crane wind resistance control method according to claim 1, characterized in that, The process of acquiring the rotational pulse sequence of the winch and the mass of the lifted load, calculating the instantaneous acceleration based on the rotational pulse sequence, and calculating the initial longitudinal tension based on the mass of the lifted load includes: Obtain the rotation pulse sequence of the winch spindle and the effective winding radius of the winch drum. Determine the spindle angular velocity based on the rotation pulse sequence. Multiply the spindle angular velocity by the effective winding radius to obtain the current operating linear speed. The current operating linear speed is smoothed and filtered to obtain the filtered operating linear speed. Obtain the filtered linear velocity corresponding to the previous sampling time, and perform a first-order backward difference operation between the filtered linear velocity at the previous sampling time and the filtered linear velocity at the current sampling time to obtain the instantaneous acceleration. The initial longitudinal tension is calculated by reading the mass of the object fed back by the weighing sensor, multiplying the mass of the object by the sum of the gravitational acceleration constant and the instantaneous acceleration.

3. The sensor-based crane wind resistance control method according to claim 1, characterized in that, The step of vector fusion of the target lateral thrust and the initial longitudinal tension to obtain a superimposed force feature vector includes: Establish an orthogonal coordinate system, mapping the target lateral thrust to lateral coordinate components and the initial longitudinal tension to vertical coordinate components; The resultant force modulus is obtained by performing a square root operation on the sum of the squares of the horizontal coordinate components and the vertical coordinate components. The horizontal coordinate components, the vertical coordinate components, and the resultant force modulus are packaged together to generate a superimposed force feature vector.

4. The sensor-based crane wind resistance control method according to claim 3, characterized in that, The calculation of the force deflection angle based on the superimposed force feature vector includes: The force deflection angle is calculated using the arctangent function based on the ratio of the horizontal coordinate component to the vertical coordinate component in the superimposed force characteristic vector.

5. The sensor-based crane wind resistance control method according to claim 1, characterized in that, Extracting the wind speed change gradient from the initial instantaneous wind speed sequence includes: Extract the historical target wind speed sequence within the time window of the current moment within 10 seconds, perform a first-order difference operation on the wind speed values ​​of adjacent sampling moments in the sequence, divide the difference result by the sampling period to obtain the wind speed change gradient in meters per second squared, and extract the maximum wind speed change gradient as the wind speed change gradient.

6. A sensor-based crane wind-resistant control system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method according to any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method described in any one of claims 1 to 5.

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