Signal-based online acceleration and strain data fusion using B-splines and Kalman filter for full-field dynamic displacement estimation

Key Points

• Dynamic displacement estimation improves with the use of b-splines and Kalman filters, enhancing data analysis capabilities.
• Integrating acceleration and strain data can provide accurate full-field displacement measurements across various conditions.
• The method utilizes data fusion techniques for real-time signal processing, reducing errors in displacement estimates.
• Resulting from this analysis, investigation into optimizing sensor networks may significantly enhance structural monitoring.