Fuel tank leakage detection based on acoustic emission

Abstract

The Plastic Fuel Tanks are widely used in the automotive industry besides steel tanks as they offer numerous advantages such as lower weight, higher corrosion resistance, better crash performance and lower total system costs. Tank manufacturing from plastics and composites has been adapted to mass production to meet the ever growing demand. The management of quality control (QC) systems for the factory environment poses challenges in the absence of relevant experience in the development and use of insitu non-destructive evaluation technologies. The problem currently faced by the automotive industry is that most techniques that meet accepted leak detection sensitivity requirements are operator-dependent. Mechanized leak detection techniques are characterized by high investment and operational costs. Hence, their implementation is not economically feasible as the related costs outweigh their benefits for automotive QC purposes. The proposed Leak Detection project was targeted at bringing a low cost leak detection system that is fast, accurate, traceable and automated for the mass production environment of the fuel tank production industry. The system eliminates the disadvantages associated with the manual-intensive and operator dependent techniques currently employed by the industry, through the use of Acoustic Emission. In this approach, hydrophones were used to listen to the sound induced by gas escaping from tanks under pressure. When pressurized gas leaks from a tank it creates an acoustic signal that can travel through the liquid medium. At the core of the system denoising techniques were designed and developed in order to obtain the highest possible signal to noise ratio (SNR) in the noisy industrial conditions. Experiments were carried out at different conditions including bubble size, distance from hydrophone to the bubble source. Furthermore, experiments were carried out at real industrial plant in order to validate the signal processing techniques and the hardware to detect the bubbles produced by leakage in the real scenario.