Aurora Condition Monitoring

Creation of logical data-subsets for analysis – Select portions of the database for analysis Algorithm definition for: Data Filtering – Rolling average etc. Derived Channels – Combine channels to create a new channel with meaning to the user Event Detection – Define logical and mathematical relationships between channels that relate to a region of interest User requested processing of data – Apply defined algorithms to the data (raw, filtered or derived) Automatic event detection and data processing – Rules can be set such that any new data is automatically processed using combinations of algorithms chained together Viewing measured, derived and event data – Multi-parameter plot allows up to 50 parameters to be plotted simultaneously Interactive viewing & cursor interrogation Event (Region-of-Interest) Amplitude Data Mining – Search the selected data-subset for specific regions of interest and for trending information

Aurora-CM is part of the Aurora Analysis system, an integrated analysis platform that provides all the tools and capabilities required for summary and detailed analysis of both time and frequency domain data from a single application window.

The Aurora-CM module is HGL Dynamics' main tool for analysing multipoint data collected from in-service engines to monitor their performance. Monitoring the performance of the installed engines is vital for scheduling maintenance in an effective and efficient manner and for determining operating characteristics which in turn can be used to improve the performance.

Instead of analysing the multipoint data from the ships by manually reviewing the raw data and inspecting it for occurrences of engine events, HGL Dynamics’ Aurora-CM System can perform specific analyses in a consistent and automated or manual manner with standard output formats. Reported results are produced that are based on validated techniques.

Automating the searching part of the analysis process enables the user to spend more time on the important tasks such as investigating and understanding the detected events rather than trawling through the data looking for the events.

The multi-function plot allows multiple parameters from multiple test vehicles from multiple tests to be simultaneously plotted on the same axes or on different axes. The flexible axes configuration allows the user to setup the chart area to suit their specific needs and to highlight the salient features in the data (different parameter types have different data ranges and hence to view both sets of data with some degree of accuracy requires different scaling factors). The plot configurations can be saved and reapplied so that complex configurations don’t have to be reset when restarting the application.