Editorial of Special Issue "Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and
Javier Cuadrado1, Miguel Á Naya1
1Laboratory of Mechanical Engineering, University of La Coruña, 15403 Ferrol, Spain.
Sensors (Basel, Switzerland)
|October 13, 2021
Summary
Virtual sensing combines physical sensors and computational models to enhance system monitoring. This approach is increasingly adopted across diverse industries like automotive, aerospace, and robotics for improved data insights.
Area of Science:
- Engineering
- Computer Science
- Data Science
Background:
- Virtual sensing integrates physical sensors with computational models to infer system states, inputs, or parameters.
- This technique offers a cost-effective and efficient alternative or supplement to traditional physical sensing methods.
Discussion:
- The growing popularity of virtual sensing spans multiple sectors, including automotive, aeronautics, aerospace, railway, machinery, robotics, and human biomechanics.
- It addresses the need for more comprehensive system understanding and predictive capabilities.
Key Insights:
- Virtual sensing provides valuable supplementary data, improving the accuracy and scope of system analysis.
- The methodology enables real-time monitoring and control in complex dynamic systems.
Outlook:
- Continued advancements in computational power and sensor technology will further drive the adoption and sophistication of virtual sensing.
- Future research will likely focus on expanding applications in areas like personalized medicine and sustainable energy systems.
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