Analysis of vehicle vibration sources for automatic differentiation between gas and diesel piston engines

Abstract

Vibration signatures sensed from distant vehicles using laser vibrometry systems provide valuable information that may be used to help identify key vehicle features such as engine type, engine speed, and number of cylinders. While developing algorithms to blindly extract the aforementioned features from a vehicle's vibration signature, it was shown that detection of engine speed and number of cylinders was more successful when utilizing a priori knowledge of the engine type (gas or diesel piston) and optimizing algorithms for each engine type. In practice, implementing different algorithms based on engine type first requires an algorithm to determine whether a vibration signature was produced by a gas piston or diesel piston engine. This paper provides a general overview of the observed differences between datasets from gas and diesel piston engines, and proceeds to detail the current method of differentiating between the two. To date, research has shown that basic signal processing techniques can be used to distinguish between gas and diesel vibration datasets with reasonable accuracy for piston engines of different configurations running at various speeds.