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Effective Data Processing is Critical to Project Success

Date: April 24, 2015 at 08:00
North American infrastructure challenges have been well documented.  In the United States alone 600,000 national bridges have an average age of 42 years with one in nine rated structurally deficient according to the American Society of Civil Engineers (ASCE).  Governments have underinvested in road and bridge infrastructure for decades and today’s funding falls significantly short of addressing the need.

One positive offset of constrained capital is the adaption of innovation – innovation in thinking and innovation in technology.

Ground Penetrating Radar (GPR) is an innovative technology that is increasingly utilized in infrastructure inspections across Canada and the US to provide condition data necessary for properly allocating constrained capital.  Data is used to show reinforcement bar corrosion in bridges, estimate asphalt and granular volumes over kilometres of highway and identify voids and delaminations in concrete.  This information is necessary for Quality Control in newly funded projects and determining priority of fund allocation in repair/rehabilitation projects.  These applications of GPR require advanced processing software and often sophisticated high-speed collection systems.

GPR processing and interpretation is a complex activity, where accuracy and quality hinge on a number of variables.  Antenna frequency and sample rate considerations are compulsory for project success, along with grid collection spacing and data processing experience.  Concrete with dense embedded features such as reinforcement bar and doweling requires imaging at optimal sample rates to ensure proper signal propagation.

To provide some insight into the processing activity, below are two examples of raw unprocessed GPR data profiles.  Each profile below is identical, with settings and filters adjusted to show potential void and other features on one and missing on the other.  Applying default software settings can risk not identifying important features.  Concrete and all other subsurface conditions vary considerably, and data filters such as Gain Type, Gain Setting, Background Subtraction and “Dewow” removal of low frequency signal can significantly impact interpretation and results.

Image 1

Red line identifies a feature visible in Image 1, below the reinforcement bar reflections, but invisible in Image 2.

Image 2

When field data is collected properly, processed and turned into insightful information, it becomes powerful for business decisions.  Governments and engineers are collecting more data than ever before in history and although asset management software is beginning  to help manage these volumes, poor data inputs still result in poor data outputs.  Qualifying service providers on the data input side of projects is critical for ensuring project decisions are based on a compilation of accurately collected and interpreted field data.

Contact us for more information about GPR data processing and infrastructure inspection techniques.