Computational intelligence based simultaneous determination of the spatial profile of the laser beam and vibrational-to-translational relaxation time by pulsed photoacoustics

This paper is concerned with the possibilities of computational intelligence application for simultaneous determination of the laser beam spatial profile and vibrational-to-translational relaxation time of the polyatomic molecules in gases by pulsed photoacoustics. Results regarding the application of neural computing and genetic optimization are presented through the use of feed forward multilayer perception networks and real-coded genetic algorithms. Feed forward multilayer perception networks are trained in an offline batch training regime to estimate simultaneously, and in real-time, laser beam spatial profile R(r) (profile shape class) and vibrational-to-translational relaxation time ?V?T from a given (theoretical) photoacoustic signals ?p(r,t). The proposed method significantly shortens the time required for the simultaneous determination of the laser beam spatial profile and relaxation time and has the advantage of accurately calculating the aforementioned quantities. Real coded genetic algorithms are used to calculate ?V?T by fitting the ?p(r,t) with the theoretical one. The previously developed methods determine the laser beam profile and relaxation time with sufficient precision, but the methods based on the application of artificial intelligence are more suitable for practical applications, such as the real-time in-situ measurements of atmospheric pollutants.