Normalization and source separation of acoustic emission signals for condition monitoring and fault detection of multi-cylinder diesel engines

A signal processing technique is presented in this paper to normalize and separate the source of non-linear acoustic emission (AE) signals of a multi-cylinder diesel engine for condition monitoring applications and fault detection. The normalization technique presented in the paper overcomes the long-existing non-linearity problem of AE sensors so that responses measured by different AE sensors can be quantitatively analysed and compared. A source separation algorithm is also developed in the paper to separate the mixture of the normalized AE signals produced by a multi-cylinder diesel engine by utilising the system parameters (i.e., wave attenuation constant and the arrival time delay) of AE wave propagation determined by a standard pencil lead break test on the engine cylinder head. It is shown that the source separation algorithm is able to separate the signal interference of adjacent cylinders from the monitored cylinder once the wave attenuation constant and the arrival time delay along the propagation path are known. The algorithm is particularly useful in the application of AE technique for condition monitoring of small-size diesel engines where signal interference from the neighbouring cylinders is strong. Crown Copyright (C) 2015 Published by Elsevier Ltd. All rights reserved.