Research Article
Tan ACC
Abstract
Acoustic emission (AE) technique has recently been extensively used in machine health monitoring and diagnosis of diesel engine. Although it offers many advantages for early detection of fault symptoms, it also comes with many challenging problems. Due to its operation in high frequency range (stress waves), from a few kHz to MHz, it poses a problem of massive data storage and transmission. Furthermore, the non-linearity of AE sensors is also another challenge as it does not provide any quantitative/comparative analysis if multiple sensors are used, such in multi-cylinder diesel engine. Hence, this short paper will present the work carried out in the author’s laboratory by introducing a simple and innovative data reduction process termed as Peak Hold down Sampling (PHDS) and a normalization approach for diagnosis of diesel engine.