Condition Monitoring of Diesel Engines

Reliability of emergency Diesel generator systems, or indeed any Diesel engines in a wide range of fields is critical. Traditional maintenance procedures for these engines follow time based or statistical based methods. Due to the wide variety of uses of Diesel engines it is not possible for these forms of maintenance to be as effective as condition based monitoring. Condition based monitoring holds many advantages over traditional maintenance methods. It allows for the earlier detection and diagnosis of a fault and allows for planned maintenance work avoiding costly and unexpected downtime. It also reduces the overall maintenance costs as parts need only be replaced when they are worn or faulty, not based on a time schedule.The ability to unobtrusively monitor the engines also has many advantages in- cluding reduced sensor cost and negating the need to tamper permanently with the engine. Acoustic monitoring has been identified as the most prominent and effective way in which to achieve this goal. As such, extensive experimentation was carried out on both large and small Diesel engines over a wide range of speeds, loads and faults and the data was then analysed. The data was first investigated statistically and then processed using Independent Component Analysis after the statistical re- sults were found to be poor.A program was written for the automatic comparison of the collected data and the results presented in this thesis show that ICA and acoustic emissions have the ability to aid in engine fault detection and diagnosis. The results have shown to be reliable, consistent and able to distinguish when the engine is healthy or faulty.

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