Implementation of blind source separation for optical fiber sensing

Abstract

Blind source separation (BSS) is implemented for optical fiber sensing systems, such as the fiber Bragg grating (FBG) sensing system and the single-mode-multimode-single-mode fiber (SMS) sensing system. The FastICA, a kind of multichannel BSS algorithm, is used to get the strain and the temperature with two FBGs. For the SMS sensing, a single-channel blind source separation (SCBSS) algorithm is employed to simultaneously measure the vibration and the temperature variation with only one SMS sensor. The errors of both the FBG and the SMS optical fiber sensing system are very small with the BSS algorithm. The implementation of BSS for the optical fiber sensing makes the multiparameter measurements more easily with low cost and high accuracy and can also be applied for signal de-noising field.

Quantum Particle Swarm Optimization Extraction Algorithm Based on Quantum Chaos Encryption

“…where c is the depth of the potential well. Solve the wave function by substituting equation ( 21) into equation (20), as shown in the following equation:…”

“…Ahmad et al proposed an improved FastICA algorithm based on kurtosis contrast function to separate mixed EEG signals [19]. Li et al used the FastICA algorithm to process optical signals [20]. Labounek et al used the Group ICA method to estimate the stable EEG spatial distribution [21].…”