Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system.

Area of Science:

• Marine Engineering
• Control Systems
• Vibration Analysis

Background:

• Accurate shafting alignment is critical for marine propulsion system safety and stability.
• Air spring vibration isolation systems (ASVISs) can mitigate noise and adjust alignment but face control challenges.

Purpose of the Study:

• To propose a digital twin (DT)-driven method for accurate marine shafting alignment control.
• To address the challenge of precisely controlling shafting alignment using ASVISs.

Main Methods:

• A neural network-based digital twin prediction model was developed to map air spring pressures to shafting alignment states.
• Shafting alignment control was formulated as a non-linear optimization problem, minimizing alignment error and balancing air spring loads.
• A genetic algorithm was employed for global optimization of air spring pressures, coupled with a PID-based soft-constrained controller for precise control policy generation.

Main Results:

• The digital twin model effectively described the relationship between air spring pressures and shafting alignment.
• The genetic algorithm successfully identified optimal air spring pressures to minimize alignment errors.
• The PID-based controller accurately generated control policies for real-world ASVIS implementation.

Conclusions:

• The proposed digital twin-driven method provides an effective solution for marine shafting alignment control.
• This approach enhances the performance of ASVISs in marine applications.
• The study validates the feasibility and effectiveness of the alignment control strategy in a real-world system.