Journal
SENSORS
Volume 22, Issue 15, Pages -Publisher
MDPI
DOI: 10.3390/s22155605
Keywords
low-cost sensors; NodeMCU; Allan variance; noise reduction; influence line measurement; structural health monitoring
Funding
- Spanish Ministry of Economy and Competitiveness [BIA2017-86811-C2-1-R, BIA2017-86811-C2-2-R]
- FEDER funds
- Secretaria d' Universitats i Recerca de la Generalitat de Catalunya, Catalunya, Spain [2017 SGR 1482]
- Spanish Agencia Estatal de Investigacion del Ministerio de Ciencia Innovacion y Universidades grant
- Fondo Social Europeo [PRE2018-083238]
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This paper presents a novel low-cost inclinometer, LARA, which incorporates five gyroscopes and five accelerometers to measure inclination. LARA utilizes IoT technology for wireless data streaming and achieves high accuracy. Experimental results show that LARA is suitable for structural damage detection on 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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