Normal operation model generation and anomaly detection for a common rail internal combustion engine

A method for detecting an anomaly in an operational condition of a fuel rail of a common rail internal combustion engine based on comparison with a normal operation model, the normal operation model comprising statistical attribute model data previously generated from binned engine model data of the common rail internal combustion engine operating under normal operational conditions, in which the binned engine model data has been generated by dividing fuel rail pressure data of engine model data obtained from the common rail internal combustion engine into a predetermined number of engine speed bins, the engine model data comprises fuel rail pressure model data indicative of a fuel rail pressure of the fuel rail and engine speed model data indicative of an engine speed of the engine, the predetermined number of engine speed bins are derived from the engine speed data during a sampling time period, and the binned engine model data is indicative of frequency of occurrence of fuel rail pressures within each bin, the method comprising:

• receiving, from an engine management system of the common rail internal combustion engine via a data interface, engine test data obtained periodically during operation of the common rail internal combustion engine, the engine test data comprising fuel rail pressure test data indicative of a fuel rail pressure of the fuel rail and engine speed test data indicative of an engine speed of the engine;
• storing the engine test data in a memory, the engine test data being accumulated over a detection time period;
• dividing, by a processor, the fuel rail pressure test data into a predetermined number of engine speed bins during the detection time period so as to generate binned engine test data indicative of frequency of occurrence of fuel rail pressures within each bin, in which the predetermined number of bins corresponds to the same number of bins as those used for the normal operation model;
• generating, by the processor for each bin of the predetermined number of bins, statistical attribute test data based on the binned engine data;
• comparing, by the processor for each bin, the statistical attribute test data with the statistical attribute model data of the normal operation model;
• and
• generating, by the processor, an alert based on if the comparison between the statistical attribute test data and the statistical attribute model data of the normal operation model over the detection time period meets a predetermined condition.

A model generating system for generating a normal operation model indicative of a normal operational condition of a fuel rail of a common rail internal combustion engine, the system comprising:

• a data interface configured to receive, from an engine management system of the common rail internal combustion engine, engine model data obtained periodically during operation of the common rail internal combustion engine, the engine model data comprising fuel rail pressure data indicative of a fuel rail pressure of the fuel rail and engine speed data indicative of an engine speed of the engine;
• a memory configured to store the engine model data, the engine model data being accumulated over a sampling time period;
• and
• a processor configured to:
• divide the fuel rail pressure data into a predetermined number of engine speed bins derived from the engine speed data during the sampling time period so as to generate binned engine model data indicative of frequency of occurrence of fuel rail pressures within each bin;
• generate, for each bin of the predetermined number of bins, statistical attribute model data based on the binned engine model data;
• and
• generate the normal operation model based on the statistical attribute model data for each bin when taken together,
• in which the memory is configured to store the normal operation model for comparison with engine test data accumulated over a detection time period for enabling detection of an anomaly in an operational condition of the fuel rail based on comparison between the engine test data accumulated over the detection time period and the statistical attribute model data of the normal operation model.

A detection system for detecting an anomaly in an operational condition of a fuel rail of a common rail internal combustion engine based on comparison with a normal operation model, the normal operation model comprising statistical attribute model data previously generated from binned engine model data of the common rail internal combustion engine operating under normal operational conditions, in which the binned engine model data has been generated by dividing fuel rail pressure data of engine model data obtained from the common rail internal combustion engine into a predetermined number of engine speed bins, the engine model data comprises fuel rail pressure model data indicative of a fuel rail pressure of the fuel rail and engine speed model data indicative of an engine speed of the engine, the predetermined number of engine speed bins are derived from the engine speed data during a sampling time period, and the binned engine model data is indicative of frequency of occurrence of fuel rail pressures within each bin, the detection system comprising:

• a data interface configured to receive, from an engine management system of the common rail internal combustion engine, engine test data obtained periodically during operation of the common rail internal combustion engine, the engine test data comprising fuel rail pressure test data indicative of a fuel rail pressure of the fuel rail and engine speed test data indicative of an engine speed of the engine;
• a memory configured to store the engine test data, the engine test data being accumulated over a detection time period;
• and
• a processor configured to:
• divide the fuel rail pressure test data into a predetermined number of engine speed bins during the detection time period so as to generate binned engine test data indicative of frequency of occurrence of fuel rail pressures within each bin, in which the predetermined number of bins corresponds to the same number of bins as those used for the normal operation model;
• generate, for each bin of the predetermined number of bins, statistical attribute test data based on the binned engine data;
• compare, for each bin, the statistical attribute test data with the statistical attribute model data of the normal operation model;
• and
• generate an alert based on if the comparison between the statistical attribute test data and the statistical attribute model data of the normal operation model over the detection time period meets a predetermined condition.