NOISE REMOVAL IN MONITORING SENSORS OF CIVIL STRUCTURES USING BLIND SOURCE SEPARATION

Blind source separation (BSS) is known to be an efficient and powerful process to separate and estimate individual mutually independent signals acquired by various types of monitoring sensors. This paper proposes an algorithm to identify and reduce noise in monitoring sensor signals using blind source separation. This algorithm can be applied in any area of monitoring. It can identify noise without any kind of previous information of the signal analyzed. Initially, the algorithm makes the separation of the signals that were acquired by the sensors. These signals may have suffered influence from several noise sources. Different from the standard BSS, which requires at least two sources, this algorithm removes the noise from each signal separately applying the maximum signal-to-noise ratio and temporal predictability algorithms. The proposed algorithm also produces two outputs for each signal, the estimated original signal and the estimated noise. The results satisfy all the proposed objectives of this work. The proposed algorithm is a great solution for other types of applications, such as thermal profiling of wells.