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Data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite revealed the break. The iceberg's separation was later confirmed by NASA's polar-orbiting Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which captures imagery in visible and infrared, researchers with the British Antarctic research group Project MIDAS reported in a blog post.
MODIS scientists had been using Sentinal-1 data to monitor the progress of the Larsen C crack, relying on the satellite's radar technology to capture images even during the dark of winter in the Southern Hemisphere, ESA representatives said in a statement.
Then, a photo of a massive crack in Larsen C was captured on Nov. 10, 2016, by researchers with NASA's Operation IceBridge, a survey of polar ice from the air. At that time, the rift measured approximately 70 miles (113 km) long and 300 feet (91 m) wide. IceBridge experts warned that if the crack extended far enough for an iceberg to separate from Larsen C, the iceberg would be approximately the size of the state of Delaware.
By Jan. 19, 2017, the crack had extended to 109 miles (175 km) in length and 1,500 feet (460 m) in width. This left the shelf's edge precariously connected to the mainland part by a frozen expanse measuring only 12.4 miles (20 km) long.
Abstract:The precision of current research on fault recognition of marine bearing remains to be improved. Therefore, a recognition method of crack-rubbing coupling fault of bearing under high water pressure based on polar symmetry mode decomposition is proposed in this article. The structure of marine bearing was analyzed, and the system was divided into several subsystems. Then, the nonlinearity relationship among the subsystems was confirmed. One subsystem was used to represent other subsystems, which was imported into the kinetic equation to obtain the equation after dimensionality reduction. According to the results of dimensionality reduction, the features of signal were measured from time domain, energy, and entropy. Meanwhile, the interior features of signal were extracted. Based on the feature extraction, the classifier of probabilistic neural network was introduced. The signal was recognized, and the recognition results were output via the training of signal sample data. Experimental results show that the method has better dimensionality reduction effect and high recognition precision. The method is practical.Keywords: polar symmetry mode decomposition; marine bearing; crack-rubbing coupling; fault recognition; bearing crack identification; probabilistic neural network classification; kinetic equations 2b1af7f3a8