This document proposes a multi-sensor data fusion system to enhance the analysis of concrete deterioration due to alkali-aggregate reaction (AAR). The system uses different sensor types like acoustic, electro-mechanical, optical, and embedded sensors to collect internal and external damage data. Feature extraction and a decentralized Kalman filter are used to fuse the heterogeneous sensor data. An artificial neural network then characterizes and quantifies the damage levels. The study expects to improve accuracy over single sensor systems and establish correlations between surface damage, internal damage, and gel concentration levels causing structural deterioration.

1. Multi-sensor data fusion system for enhanced analysis of deterioration in concrete structures Othman Sidek and S.A.Quadri Collaborative µ-electronic Design Excellence Centre Universiti Sains Malaysia Paper presented at PIERS Conference: Progress In Electromagnetic Research Symposium Proceedings, Suzhou, China, Sept. 12-16, 2011, 637

4. Multisensor data fusion provides significant advantages over single source data. The use of multiple types of sensors plays an important role in achieving reasonable accuracy and precision.

6. AAR Expansion in Concrete Structure Alkali-aggregate reaction is a term mainly referring to a reaction which occurs over time in concrete between the highly alkaline cement paste and non-crystalline silicon dioxide. It produces a gel that expands when in contact with the moisture in concrete, and can lead to the development of high tensile stresses and cracking of concrete. AAR is a serious problem that adversely affects the durability and integrity of concrete structures.

7. AAR Expansion in Concrete Structure AAR GEL

8. AAR Expansion in Concrete Structure AAR GEL

9. AAR Expansion in Concrete Structure AAR GEL

10. AAR Expansion in Concrete Structure AAR GEL

13. Hypothetical graph showing expansions (in percentage) in various samples

15. Figure showing experimental setup

18. Decentralized Kalman filter . The Kalman filter uses a system's dynamics model (i.e., physical laws of motion), known control inputs to that system, and measurements (such as from sensors) to form an estimate of the system's varying quantities (its state) that is better than the estimate obtained by using any one measurement alone. As such, it is a common sensor fusion algorithm. If raw data obtained sensors is fused it is Centralized Kalman filter. If processed data (features) are fused is called Decentralized Kalman filter . If raw data and features are fused it is called Hybrid Kalman filter

19. Data flow diagram

23. The root-mean-square deviation (RMSD) is used as the damage indexing Hypothetical graph showing damage level using single data source sensor system and data fusion system

24. Hypothetical graph showing correlation between external and internal damage level

25. Thanks