Abstract
One of the most critical components of the US transportation system is railroads, accommodating transportation for 48% of the nation’s total modal tonnage. Despite such vital importance, more than half of the railroad bridges, an essential component of railroad infrastructure in maintaining the flow of the network, were built before 1920; as a result, bridges comprise one of the most fragile components of the railroad system. Current structural inspection practice does not ensure sufficient information for both short- and long-term condition assessment while keeping the operation cost low enough for mandatory annual inspection. In this paper, we document the development process of an autonomous, affordable system for monitoring railroad bridges using the wireless smart sensor (WSS) so that a complete end-to-end monitoring solution can provide relevant information directly from the bridges to the end-users. The system’s main contribution is to capture the train-crossing event efficiently and eliminate the need for a human-in-the-loop for remote data retrieval and post-processing. In the proposed system, an adaptive strategy combining an event-based and schedule-based framework is implemented. The wireless system addresses the challenges of remote data retrieval by integrating 4G-LTE functionality into the sensor network and completes the data pipeline with a cloud-based data management and visualization solution. This system is realized on hardware, software, and framework levels. To demonstrate the efficacy of this system, a full-scale monitoring campaign is reported. By overcoming the challenges of monitoring railroad bridges wirelessly and autonomously, this system is expected to be an essential tool for bridge engineers and decision-makers.
Highlights
Railroads are a critical component of US transportation and economy
The railroads carry 48% of the nation’s total modal tonnage while emitting the least amount of greenhouse gas compared to waterborne, truck, and air (O’Rourke et al 2015; Preliminary Data, 2017)
This section presents the integration process of a 4G LTE modem to the wireless smart sensor (WSS) platform and a framework proposal of an energy-efficient framework to coordinate the communication between the gateway and sensor nodes to sustain the network, retrieve and upload data reliably over long-term deployments
Summary
Railroads are a critical component of US transportation and economy. On average, the railroads carry 48% of the nation’s total modal tonnage while emitting the least amount of greenhouse gas compared to waterborne, truck, and air (O’Rourke et al 2015; Preliminary Data, 2017). This requirement suggests an ideal sensor node that can capture railroad bridge vibration data under excitation (i.e., train-crossing events) immediately upon detecting the event and keeping up with all the functions at a predefined time with minimal energy wasted To address these issues, a system was developed using: 1) ADXL362: a low-cost, lowpowered accelerometer that features an ultralow-power, 3-axis MEMS accelerometer consumes less than 2 μA at a 100 Hz output data rate and 270 nA when in motiontriggered wake-up mode (Analog Devices 2016) and 2) DS3231m: MEMS-based realtime clock with a temperature compensated crystal oscillator for highly accurate timekeeping of ±5 ppm (±0.432 s/day) (Maxim Integrated, 2015). We present the integration process of a 4G LTE modem to the WSS platform and a framework proposal of an energy-efficient framework to coordinate the communication between the gateway and sensor nodes to sustain the network, retrieve and upload data reliably over long-term deployments. Future work will present the implementation of more advanced data analysis methods for structural condition assessment
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