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A unique new technology that reduces the cost and increases effectiveness of Leak Detection and Repair (LDAR) activity.
This platform is unique in that it accurately generates mass leak-rate data from equipment items that have the propensity to leak (fugitive emissions or FE). The analysis is quantitative in nature, and is a break with existing technology that is deployed for this purpose. It can be applied across a range of gasses – both methane and other VOC’s.
The platform uses an arrangement of IR sensors with image resolution technology to eliminate false positives. The assembly is mounted onto a UAV to increase survey productivity and stream the results to an algorithmic data processing center that uses dispersion models and pixel quantification to obtain an accurate mass leak rate. This is then made available to asset owners via a portal.
The platform has the ability to perform image preprocessing of identified fugitive gas emissions onboard the UAV, which confers a number of technical advantages. The integration of three high resolution sensors, including IR sensors operating in the 3.2 – 3.4μm range, allows for surveying at greater altitudes, and most importantly, leads to the effective elimination of false positives from images gathered, such as:
Image stabilization is performed on board so that the output is a reliable, high resolution and a stable colored image of the gas cloud in question.
The Pulse Vapor55 has a 6’ rotor span and is especially suited to surveying / grid flying. It contains photomapping, HD video, LiDAR and multi-spectral sensing capability.
Additionally this UAV can fly through 30kts winds gusting up to 40kts and maintain sufficient image stabilization to satisfy image quality requirements.
The craft will fly between -10 and 120°F making it ideally suited to remote location flying.
It is noteworthy that fixed and handheld versions of the platform equipment are currently in development and will be commercially ready in June 2017.
Once a 30hz image is generated for a fugitive gas emission as part of an asset under survey, the image is streamed back to a base station where it is subsequently uploaded to an image processing center. Metadata is also captured both from the UAV and also ground stations which provide indications of ambient temperature, wind speed, humidity etc.
The emissions image, together with the metadata, are fed into an algorithmic software platform. The software undertakes a pixel-based analysis of the image, and:
The image processing can be carried out in fractions of a minute, rather than hours or days associated with existing survey methods such as bagging tests or Method21.
The accuracy that has been obtained in field tests so far have revealed correlation of results against bagging tests to be within 15%.
Method21 (which in any event cannot directly measure mass leak rates) have been calculated to produce bagging test correlation accuracies at around 250%, so the algorithmic image processing has demonstrated superior results in both accuracy and productivity.
Once mass leak rates have been assigned to equipment items through a combination of visual identification (from UAV HD footage) and automated geo-reference tagging, the results are made available in a cloud based conditional access portal, along with video. This can then be geo-referenced by the asset owner to serve repair programs, or converted to XML and electronically uploaded to regulatory authorities via the portal. Most importantly, it allows for the report to be sorted by mass leak rate so the asset owner now has the ability to determine which leaks to repair first, and then re-survey and quantify exactly how much emissions reduction has taken place.
The EPA stated that 10% of fugitive emissions are economically viable to fix (i.e. because they produce most of the emissions) - this platform helps you to identify this 10% at a much lower cost than existing methods will allow.