Infrasound monitoring in non-traditional environments

Abstract

To date, the infrasound community has avoided deployments in noisy urban sites because interests have been in monitoring distant sources with low noise sites. As monitoring interests expand to include low-energy urban sources only detectable close to the source, case studies are needed to demonstrate the challenges and benefits of urban infrasound monitoring. This case study highlights one approach to overcoming urban challenges and identifies a signal's source in a complex acoustic field. One 38 m and one 120 m aperture infrasound arrays were deployed on building rooftops north of downtown Dallas, Texas. Structural signals in the recorded data were identified, and the backazimuth to the source determined with frequency-wavenumber analysis. Fourteen days of data were analyzed to produce 314 coherent continuous-wave packets, with 246 of these detections associated with a narrow range of backazimuth directions. Analyzing the backazimuths from the two arrays identified the Mockingbird Bridge as the probable source which was the verified with seismic measurement on the structure. Techniques described here overcame the constraints imposed by urban environments and provide a basis to monitor infrastructure and its conditions at local distances (0–100 km).

Remote Structural Infrasound: Case Studies of Real-Time Infrastructure System Monitoring

“…All of the data presented in the paper are postprocessed, although the ERDC is developing automated, near-realtime techniques to process structural signals at the array without experts-in-the-loop rather than requiring structural infrasound experts for analysis. The signals associated with a structural source are continuous-wave (CW) packets in the time domain with a spectral peak at the fundamental mode of the structure (Donn et al 1974;McKenna et al 2009a;McComas et al 2016McComas et al , 2018. The signal processing methods are designed to identify these features in the data and have been refined over years of study.…”

“…These results align well with the on-structure measurements and infrasound observations. Full details of this study are published in McComas et al (2016McComas et al ( , 2018, with greater detail on the development of automated signal processing techniques tailored for noisy urban deployments. Further research is being conducted to understand how the ambient noise fields vary with the type of urban buildup and meteorological conditions, which will be used to develop detection thresholds for infrasound signals in urban scenarios.…”

“…A real-world urban terrain model space was developed centered on the campus of SMU that realistically represented large-scale features of buildings and roadways in the space. The following discussion summarizes the model development and results, but Pace et al (2015) and McComas et al (2016McComas et al ( , 2018) provided a complete methodology documentation and archived the data used to produce the models presented here. The model urban terrain was developed using spectroscopic aerial imagery and 1-m light detection and ranging (LIDAR) data; the terrain features included buildings, bridges, paved areas, and an atmosphere (temperature only) [Fig.…”

Airborne Infrasound Makes a Splash

“…Chief among these are chemical and nuclear explosions (Pilger, Gaebler et al., 2021; Stevens et al., 2002), rocket launches (Pilger, Hupe et al., 2021) and supersonic aircraft (Le Pichon et al., 2002), which may create sounds that travel thousands of kilometers. More localized sources include wind turbines (Marcillo et al., 2015), dams (McKenna et al., 2021), bridges (Donn et al., 1974; Whitlow et al., 2019), and general urban activity (Bird et al., 2021; McComas et al., 2018).…”

Infrastructure Structural Health Monitoring via Infrasound

“…Signal Processing Considerations: Applying infrasound monitoring to infrastructure has introduced a set of challenges with signal processing including the move from impulsive signals (such as from an explosion) to packetized continuous wave signals such as those generated by infrastructure (Donn et al 1974;McKenna et al 2009aMcKenna et al , 2009cMcComas et al 2016McComas et al , 2018. While ERDC researchers continue to explore these challenges and develop new processing techniques specific to the challenges posed by infrastructure monitoring (McKenna et al 2009a(McKenna et al , 2009cMcComas et al 2016;McComas et al 2018).…”