Skid measurement errors are unavoidable for each kind of skid testing device. The simple linear regression (SLR), used worldwide to harmonize friction measuring devices, does not consider that measurement errors affect both devices. For this reason, its use provides a biased estimate of the relationship between devices. The measurement error models (MEMs) regression method is proposed as a better method to harmonize any two skid testing devices. Regression according to both the SLR and MEM approaches have been performed with repeated measurements (from the same device) and between measurements obtained from two different skid testing devices. A comparison of the results is shown; MEM regression appears to be a more appropriate tool to harmonize friction measuring devices than SLR.
Measurement Error Models (MEMs) Regression Method to Harmonize Friction Values from Different Skid Testing Devices
EVANGELISTI, Azzurra
;D'APUZZO, Mauro;
2016-01-01
Abstract
Skid measurement errors are unavoidable for each kind of skid testing device. The simple linear regression (SLR), used worldwide to harmonize friction measuring devices, does not consider that measurement errors affect both devices. For this reason, its use provides a biased estimate of the relationship between devices. The measurement error models (MEMs) regression method is proposed as a better method to harmonize any two skid testing devices. Regression according to both the SLR and MEM approaches have been performed with repeated measurements (from the same device) and between measurements obtained from two different skid testing devices. A comparison of the results is shown; MEM regression appears to be a more appropriate tool to harmonize friction measuring devices than SLR.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
