An improved system for 3D individualized modeling of the artificial femoral head

Liu, Bin; Jia, Xianyong; Huang, Zhihuan; Li, Haojie

doi:10.1007/s00371-012-0767-z

Cited by 3 publications

(1 citation statement)

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“…Traditional methods such as 3 -criterion, Grubbs criterion, Chauvenet criterion, and Dixon criterion [19][20][21][22] are mainly utilizing simple statistics to identify gross errors, which do not consider time series features of data and often cannot obtain satisfactory results when there exist consecutive gross errors. Unlike them, AR model is based on mathematical modeling of a group of time series data assuming that each value of the series is dependent on a weighted sum of the "previous" values of the same series.…”

Section: Detecting and Correcting Gross Errors Based On Armentioning

confidence: 99%

A Novel Dynamic Measurement System for Evaluating the Braking Coordination of Articulated Vehicles

Chen

2016

Journal of Sensors

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The braking coordination between tractor and semitrailer is vital to the safety of articulated vehicles. Traditional evaluation about braking coordination is based on the pressure measurement along air braking pipeline, which needs to change original braking structure to install gauges and cannot directly reflect the final braking coordination of different wheels. To overcome these limitations, this paper proposes a novel dynamic measurement system for evaluating the braking coordination of articulated vehicles. During the brake test, all wheel velocities of the whole articulated vehicle are synchronously obtained through a specially designed distributed acquisition platform. To effectively eliminate gross errors and noises in wheel angular velocity data, a 3-order autoregressive (AR) model and an improved-thresholding wavelet filtering algorithm are developed. Further, a novel direct evaluation method about braking coordination is proposed according to the differences in angular velocity dropping time of all wheels. Finally, the overall system is assessed through real field tests. The results validate the feasibility and effectiveness of the proposed system.

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Section: Detecting and Correcting Gross Errors Based On Armentioning

confidence: 99%