Development of statistical methods for vibration analysis and consideration of mechanical environments: application to ground vehicles

Abstract

The operational use of wheeled land transport vehicles and their on-board systems exposes them to significant vibratory stresses, particularly during motion. These vibrations, stemming from irregular road surfaces, exhibit complex non-Gaussian behaviour. To accurately assess their impact on mechanical systems and design robust qualification tests, the AFNOR X50-144-3 Edition 2 standard provides a framework for analysing mechanical environments. This method involves classifying measured data by stationarity and deriving statistical distributions to model vibratory effects. This study introduces key innovations to this methodology. A novel classification technique is proposed, leveraging spectral content similarity to enhance data segmentation. Additionally, new a priori statistical models are developed to extrapolate short-duration measurements into long-term system lifespan profiles. The effectiveness of these advancements is demonstrated through their application to real-world measurement data and synthetically generated signals with controlled spectral properties. This work represents a step forward in vibration analysis, offering improved accuracy for mechanical environment assessments in land vehicle engineering.