Application of Genetic Algorithms to Identify Ultrasonic Echoes for Thickness Measurements

Thickness measurement is a crucial matter in many applications, such as pipeline inspection by means of ultrasound. In this regard, an automated system must rely on an algorithm able to identify properly the ultrasonic echoes originated from the pipe's walls, which can be disturbed by noise and other sources of ultrasonic reflections. This paper describes the application of genetic algorithms for processing and analysis of signals obtained from thickness measurement using ultrasonic transducers. The main application for this algorithm is the processing and analysis of ultrasound signals obtained from oil duct inspections using ultrasonic pipeline inspection gauges (PIGs). The objective of the proposed algorithm is to identify correctly the ultrasound echoes in order to obtain an accurate thickness measurement, allowing the identification of cracks and corrosions in pipeline inspections. The algorithm was applied to several signals obtained from laboratory experiments with different distances between the transducer and a test plate with known thickness. Its efficiency was measured in terms of error percentage and computational cost.