Engine state monitoring and fault diagnosis of large marine diesel engines

摘要

The reliable detection of engine malfunctions in order to predict and to plan maintenance intervals is of major importance in various fields of industry. For instance, occurring faults of marine diesel engines which are on the high seas for months may lead to expensive holding times. In this context, condition monitoring systems (CMS) should be able to assess engine health, to predict developing failures, i.e. engine state degradation, and to diagnose failure modes at a low price. In this article, two different thermodynamical model-based approaches to detect two common failure modes - increased blow-by and compression ratio failures - of large diesel engines given cylinder pressure traces with low sampling rate are discussed and compared. Special focus is put on estimation robustness and reliability by excluding the combustion phase and signal parts with high noise level. The proposed algorithms are validated with experimental data.