Abstract
In the fast-paced and time-sensitive fields of construction and concrete production, real-time monitoring of concrete strength is crucial. Traditional testing methods, such as hydraulic compression (ASTM C 39) and maturity methods (ASTM C 1074), are often laborious and challenging to implement on-site. Building on prior research (SPR 4210 and SPR 4513), we have advanced the electromechanical impedance (EMI) technique for in-situ concrete strength monitoring, crucial for determining safe traffic opening times. These projects have made significant strides in technology, including the development of an IoT-based hardware system for wireless data collection and a cloud-based platform for efficient data processing. A key innovation is the integration of machine learning tools, which not only enhance immediate strength predictions but also facilitate long-term projections vital for maintenance and asset management.
To bring this technology to practical use, we collaborated with third-party manufacturers to set up a production line for the sensor and datalogger assembly. The system was extensively tested in various field scenarios, including pavements, patches, and bridge decks. Our refined signal processing algorithms, benchmarked against a mean absolute percentage error (MAPE) of 16%, which is comparable to the ASTM C39 interlaboratory variance of 14%, demonstrate reliable accuracy. Additionally, we have developed a comprehensive user manual to aid field engineers in deploying, connecting, and maintaining the sensing system, paving the way for broader implementation in real-world construction settings.
Keywords
concrete, sensor, piezoelectric, electromechanical impedance, EMI, open traffic, strength, sensing, nondestructive evaluation, NDT, wireless, database, Internet of Things
Report Number
FHWA/IN/JTRP-2024/05
SPR Number
4753
Sponsoring Organization
Indiana Department of Transportation
Performing Organization
Joint Transportation Research Program
Publisher Place
West Lafayette, Indiana
Date of Version
2024
DOI
10.5703/1288284317724
Recommended Citation
Kong, Z., & Lu, N. (2024). Field implementation of concrete strength sensor to determine optimal traffic opening time (Joint Transportation Research Program Publication No. FHWA/IN/JTRP-2024/05). West Lafayette, IN: Purdue University. https://doi.org/10.5703/1288284317724