PSI - Issue 38

Denis Chojnacki et al. / Procedia Structural Integrity 38 (2022) 362–371 Author name / Structural Integrity Procedia 00 (2021) 000 – 000

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After calibration operations on our PG or on the field, some linear relations were established between this simplified instrumentation and a Fully-Instrumented car by comparison between 8h_VDV values and Fatigue values at WFT With a dedicated post-processing development we get the deliverables expected as: - The runs Labeling related to Road Quality - The speed Profile information on these runs in order to compare to professional drivers Although these methodologies are operational and patented (Chojnacki & Pons (2015)) they still require dedicated fleet and some funding for the external record system and to manage all runs to qualify. 4. Big Data opportunities With the democratization and miniaturization of microelectromechanical systems (MEMS), accurate and cheap accelerometers and / or gyroscopes sensors (from 1 up to 6 axis) become common in electronics systems, including automotive vehicles. Controlled suspension, loading gauge or pitch angle sensor to name a few need such MEMS to function. They measures continuously data histories of similar loading variables we used to assess in our previous expansive RLDA campaigns. With new sensors on vehicles equipped with controlled suspension, we have now the opportunity to access to these kind of parameters, see Fig. 12. a b

Fig. 12. (a) Vertical Accelerometers, (b) Coupled with controlled suspensions

R&D studies are in progress in order to take benefit with this valuable information. The difficulties for SDT are to define Edge computing algorithms inside the cars in order to produce useful information compliant with internal calculator constraints, see Fig. 13.

Fig. 13. Edge computing algorithm example to reduce the stored data on-board.