DEVELOPING THE COMBINED KALMAN-EMD ALGORITHM TO PROCESS BLASTING SHOCKWAVE SIGNALS PROPAGATING IN A WATER MEDIUM

In experiments deploying underwater blast sensors, measured data is always disturbed, expressed as analog peaks in the obtained signal form. Except for pressure peak pmax, other parameters of an underwater explosion such as positive impulse I+, positive phase duration τ+, negative impulse I- and negative phase duration τ- are difficult or almost impossible to extract from this signal type. This article studies developing an algorithm called Kalman-EMD with the combination of Kalman filter and empirical mode decomposition for processing this signal type. The algorithm is applied in 6 data sets measuring the shockwave pressure of underwater explosions by PCB W138A05 sensors with the same condition that 184 grams of A-IX-2 explosive is detonated underwater. The results show that noise in signals is significantly eliminated. For the blasting parameters of processed signals, which can be compared with theory such as I+ and τ+, although it witnesses a small trade-off when errors of I+ enhance from about 3% to 6%, errors of τ+ are significantly decreased from about over 30% to only about 3%. Especially other pieces of information such as I- and τ- can be extracted from the processed signal so this trade-off can be acceptable. Hence, this algorithm can be applied to denoise and extract parameters from shockwave pressure signals of underwater explosions.