System, Device, and Method for Feature Generation, Selection, and Classification for Audio Detection of Anomalous Engine Operation

A computer based method for collecting and reducing data used to detect vehicle faults for processing, comprising the steps of:

• collecting raw data pertinent to a vehicle function with a sensor;
• converting the raw data into a bulk feature vector for at least one feature class;
• applying feature selection to reduce the bulk feature vector producing a reduced feature vector;
• and
• providing the reduced feature vector for an analysis to identify a vehicle fault,
• wherein the feature selection comprises feature ranking.

A device for detecting faults in a vehicle comprising:

• a sensor proximate to the vehicle configured to produce sensor data;
• a processor and a memory configured to store non-transitory instructions that, when executed by the processor, performs the steps of:
• receiving the sensor data;
• generating a bulk feature set from the sensor data;
• and
• selecting features from the bulk feature set to produce a reduced feature set;
• and
• providing the reduced feature set for a fault analysis for the vehicle,
• wherein the reduced feature set does not substantially compromise accuracy of the fault analysis in comparison with a fault analysis based upon the bulk feature set.

A system for fault detection and providing a fault analysis for a vehicle comprising:

• a sensor proximate to the vehicle configured to produce sensor data;
• a first processor and a memory configured to store non-transitory instructions that, when executed by the first processor, performs the step of receiving the sensor data from the sensor;
• and
• a second processor and a memory configured to store non-transitory instructions that, when executed by the second processor, performs the step of:
• receiving the sensor data from the first processor;
• performing a data transformation to generate a bulk feature set from the sensor data;
• and
• selecting a subset of features from the bulk feature set to produce a reduced feature set;
• wherein the reduced data set does not substantially compromise accuracy of the fault analysis accuracy in comparison with a fault analysis based upon the bulk feature set.