US 12,222,238 B2
Blast triangulation
Suthee Wiri, Albuquerque, NM (US); Charles E. Needham, Albuquerque, NM (US); and David J. Ortley, Albuquerque, NM (US)
Assigned to Applied Research Associates, Inc., Albuquerque, NM (US)
Filed by Applied Research Associates, Inc., Albuquerque, NM (US)
Filed on May 27, 2022, as Appl. No. 17/826,631.
Prior Publication US 2023/0408325 A1, Dec. 21, 2023
Int. Cl. G01H 3/12 (2006.01); G01S 5/20 (2006.01)
CPC G01H 3/12 (2013.01) [G01S 5/20 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for identifying and triangulating blast exposure data, the method comprising:
training a machine learning model based on a set of historical blast data corresponding to a plurality of types of blast sources;
receiving, from each of a plurality of blast sensors, the blast exposure data corresponding to a blast exposure, the blast exposure data comprising pressure trace data over time;
receiving location data associated with the plurality of blast sensors;
triangulating the blast exposure using the blast exposure data and the location data to locate a source of the blast exposure;
estimating a yield of the blast exposure from the blast exposure data;
identifying a blast signature of the blast exposure based on the yield from the blast exposure data;
performing a comparison of the blast signature with one or more predefined blast signature profiles;
identifying, using the machine learning model, the source of the blast exposure based on the comparison of the blast signature; and
notifying one or more operators of the blast exposure.