Anti-sway control system for crane hook-Weihua Crane

Anti-sway control system for crane hook

2025-07-29 07:36:40

The anti-sway control system of the crane hook is a key technology to improve handling efficiency and safety, especially in precision lifting or high-speed operations. The following are the core points of the system:

1. System composition

Sensor Module
- Inertial Measurement Unit (IMU) : Real-time monitoring of the hook's swing angle, angular velocity and acceleration.
- Vision sensor : Identify hook position and swing status through camera (optional auxiliary).
- Encoder : Detects the running speed and direction of the crane trolley/carriage.
Control unit
- PLC/dedicated controller : processes sensor data and executes control algorithms (such as PID, fuzzy control).
- Input and output module : receives instructions and outputs control signals.
Actuator
- Variable frequency drive : adjusts the motor speed to achieve smooth acceleration and deceleration.
- Brakes : Assists in emergency braking or precise parking.

2. Control strategy

PID Control
- Adjust the acceleration of the trolley/cart according to the swing feedback to suppress the swing (parameter tuning and optimization are required).
Input Shaping
- By modifying the timing of the control instructions (such as applying a delayed pulse), the swing energy is offset, and open-loop control is used without the need for continuous feedback.
Fuzzy control/adaptive control
- It is highly adaptable to nonlinear loads and variable rope length scenarios.
Model Predictive Control (MPC)
- Predict future states based on dynamic models and optimize control instructions.

3. Key technical challenges

External disturbances : wind loads, collisions, etc. need to be compensated by robust control algorithms.
Parameter changes : The length of the suspension rope and the load weight affect the system dynamics in real time, and the parameters need to be adjusted online.
Real-time requirements : High sampling frequency (such as above 100Hz) ensures fast response.

4. Application Effect

Swing reduction effect : A typical system can reduce the swing angle by more than 80% (e.g. from ±10° to ±2°).
Improved efficiency : allows higher operating speeds and shortens operating cycles.
Safety : Avoid load collision or overturning, suitable for precision scenes such as nuclear power and aerospace.

5. Development Trends

Digital twin : Optimize control parameters through virtual model simulation.
AI integration : Deep learning predicts swing patterns for enhanced adaptability.
Wireless sensing : less wiring, more flexibility.

Through a properly designed control system, cranes can achieve rapid and stable hook positioning under complex working conditions, balancing efficiency and safety. In actual applications, a customized solution is required based on the specific crane model (bridge crane, tower crane, etc.) and load characteristics.

1. System composition

Sensor Module
- Inertial Measurement Unit (IMU) : Real-time monitoring of the hook's swing angle, angular velocity and acceleration.
- Vision sensor : Identify hook position and swing status through camera (optional auxiliary).
- Encoder : Detects the running speed and direction of the crane trolley/carriage.
Control unit
- PLC/dedicated controller : processes sensor data and executes control algorithms (such as PID, fuzzy control).
- Input and output module : receives instructions and outputs control signals.
Actuator
- Variable frequency drive : adjusts the motor speed to achieve smooth acceleration and deceleration.
- Brakes : Assists in emergency braking or precise parking.

2. Control strategy

PID Control
- Adjust the acceleration of the trolley/cart according to the swing feedback to suppress the swing (parameter tuning and optimization are required).
Input Shaping
- By modifying the timing of the control instructions (such as applying a delayed pulse), the swing energy is offset, and open-loop control is used without the need for continuous feedback.
Fuzzy control/adaptive control
- It is highly adaptable to nonlinear loads and variable rope length scenarios.
Model Predictive Control (MPC)
- Predict future states based on dynamic models and optimize control instructions.

3. Key technical challenges

External disturbances : wind loads, collisions, etc. need to be compensated by robust control algorithms.
Parameter changes : The length of the suspension rope and the load weight affect the system dynamics in real time, and the parameters need to be adjusted online.
Real-time requirements : High sampling frequency (such as above 100Hz) ensures fast response.

4. Application Effect

Swing reduction effect : A typical system can reduce the swing angle by more than 80% (e.g. from ±10° to ±2°).
Improved efficiency : allows higher operating speeds and shortens operating cycles.
Safety : Avoid load collision or overturning, suitable for precision scenes such as nuclear power and aerospace.

5. Development Trends

Digital twin : Optimize control parameters through virtual model simulation.
AI integration : Deep learning predicts swing patterns for enhanced adaptability.
Wireless sensing : less wiring, more flexibility.

1. System composition

Sensor Module
- Inertial Measurement Unit (IMU) : Real-time monitoring of the hook's swing angle, angular velocity and acceleration.
- Vision sensor : Identify hook position and swing status through camera (optional auxiliary).
- Encoder : Detects the running speed and direction of the crane trolley/carriage.
Control unit
- PLC/dedicated controller : processes sensor data and executes control algorithms (such as PID, fuzzy control).
- Input and output module : receives instructions and outputs control signals.
Actuator
- Variable frequency drive : adjusts the motor speed to achieve smooth acceleration and deceleration.
- Brakes : Assists in emergency braking or precise parking.

2. Control strategy

PID Control
- Adjust the acceleration of the trolley/cart according to the swing feedback to suppress the swing (parameter tuning and optimization are required).
Input Shaping
- By modifying the timing of the control instructions (such as applying a delayed pulse), the swing energy is offset, and open-loop control is used without the need for continuous feedback.
Fuzzy control/adaptive control
- It is highly adaptable to nonlinear loads and variable rope length scenarios.
Model Predictive Control (MPC)
- Predict future states based on dynamic models and optimize control instructions.

3. Key technical challenges

External disturbances : wind loads, collisions, etc. need to be compensated by robust control algorithms.
Parameter changes : The length of the suspension rope and the load weight affect the system dynamics in real time, and the parameters need to be adjusted online.
Real-time requirements : High sampling frequency (such as above 100Hz) ensures fast response.

4. Application Effect

Swing reduction effect : A typical system can reduce the swing angle by more than 80% (e.g. from ±10° to ±2°).
Improved efficiency : allows higher operating speeds and shortens operating cycles.
Safety : Avoid load collision or overturning, suitable for precision scenes such as nuclear power and aerospace.

5. Development Trends

Digital twin : Optimize control parameters through virtual model simulation.
AI integration : Deep learning predicts swing patterns for enhanced adaptability.
Wireless sensing : less wiring, more flexibility.

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