Sensing techniques based on accelerometers for modal parameters identification are among the most studied and applied in Structural Health Monitoring of civil structures. The advent of low-cost MEMS accelerometers and open-source electronic platforms, such as Arduino, have facilitated the design of low-cost systems suitable for modal identification, although there is still a lack of studies regarding practical application and comparison of commercially available low-cost accelerometers under SHM conditions. This work presents an experimental performance evaluation of six low-cost MEMS accelerometers for the identification of natural frequencies and damping ratios of a three-storey frame model and a reinforced concrete slab, as well as their noise characteristics. A low-cost Arduino-based data acquisition system was used. The results showed an overall good performance of the MEMS accelerometers, with identified natural frequencies errors within 1.02% and 7.76% of reference values, for the three-storey frame and concrete slab, respectively, and a noise density as low as 108 g/√Hz.

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Evaluation of low-cost MEMS accelerometers for SHM: frequency and damping identification of civil structures

Nowadays, low-cost accelerometers are getting more attention from civil engineers to make Structural Health Monitoring (SHM) applications affordable and applicable to a broader range of structures. The present accelerometers based on Arduino or Raspberry Pi technologies in the literature share some of the following drawbacks: (1) high Noise Density (ND), (2) low sampling frequency, (3) not having the Internet’s timestamp with microsecond resolution, (4) not being used in experimental eigenfrequency analysis of a flexible and a less-flexible bridge, and (5) synchronization issues. To solve these problems, a new low-cost triaxial accelerometer based on Arduino technology is presented in this work (Low-cost Adaptable Reliable Accelerometer—LARA). Laboratory test results show that LARA has a ND of 51 µg/√Hz, and a frequency sampling speed of 333 Hz. In addition, LARA has been applied to the eigenfrequency analysis of a short-span footbridge and its results are compared with those of a high-precision commercial sensor.

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Low-Cost Wireless Structural Health Monitoring of Bridges

Structural damage detection using inclinometers is getting wide attention from researchers. However, the high price of inclinometers limits this system to unique structures with a relatively high structural health monitoring (SHM) budget. This paper presents a novel low-cost inclinometer, the low-cost adaptable reliable angle-meter (LARA), which combines five gyroscopes and five accelerometers to measure inclination. LARA incorporates Internet of Things (IoT)-based microcontroller technology enabling wireless data streaming and free commercial software for data acquisition. This paper investigates the accuracy, resolution, Allan variance and standard deviation of LARA produced with a different number of combined circuits, including an accelerometer and a gyroscope. To validate the accuracy and resolution of the developed device, its results are compared with those obtained by numerical slope calculations and a commercial inclinometer (HI-INC) in laboratory conditions. The results of a load test experiment on a simple beam model show the high accuracy of LARA (0.003 degrees). The affordability and high accuracy of LARA make it applicable for structural damage detection on bridges using inclinometers.

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A Novel Wireless Low-Cost Inclinometer Made from Combining the Measurements of Multiple MEMS Gyroscopes and Accelerometers

Recent development of microelectromechanical systems (MEMS) accelerometers improved their performance. Coupled with their benefits of lower cost and smaller size, enabled their increased utilization in navigation, automotive and consumer devices. However, specification and testing methodologies of these devices are not robustly defined. This work investigates and defines a set of testing methodology for MEMS accelerometers, making use of a 3D printer based testing platform and a scalable inertial sensor testing board. Specification results show that Kionix KXRB5 and Invensense MPU6000 perform the best of the devices tested. Furthermore, commonly used inertial algorithms were applied to study the impact of accelerometer choice in an inertial navigation system (INS). Across a attitude estimation and dead reckoning tests, results indicate that noise density has little impact on performance after inertial algorithms are applied. Cross-axis, bias variability and step motion specification results are better indicators of performance after inertial algorithms are applied. Acknowledgements iii iii Acknowledgements I would like to thank my parents and sister for their continuous support throughout my years in undergraduate and graduate school. Your support and encouragement gave me the motivation to learn new things and pursue my interests. I would like to thank my supervisor, Prof. David A. Johns, for providing guidance and advice throughout the thesis and for all his insights during our weekly discussions throughout the project. I would like to thank you for your approach to the project, giving me a high degree of freedom and expression in this project. Finally, I would also like to thank you for giving me this opportunity to pursue this project, it was a humbling and extremely rewarding experience. I would also like to thank Peter Timmermans and Alon Green for your insight during the early stages of the project which helped shaped different aspects of the project. I learned a lot in regards to the considerations needed for transportation purposes. Finally, I would also like to thank Wahid Rahman, for giving me an outlet to discuss my ideas with.

Kei-Ming Kwong

Papers

MEMS Accelerometer Specifications and Their Impact in Inertial Applications