Estimation for Wheelset Angle of Attack by Kalman Filter Using Quasi-static Single Wheelset Model of Railway Vehicle

2019 ◽  
Vol 2019.16 (0) ◽  
pp. C207
Author(s):  
Shoya Kuniyuki ◽  
Takatoshi Hondo ◽  
Mitsugi Suzuki
Keyword(s):  
Kalman Filter ◽  
Angle Of Attack ◽  
Railway Vehicle

Aircraft flow angles calibration via observed-based wind estimation

2019 ◽  
Vol 91 (7) ◽  
pp. 1033-1038
Author(s):  
Francesco Schettini ◽  
Gianpietro Di Rito ◽  
Eugenio Denti
Keyword(s):  
Kalman Filter ◽  
Reference Data ◽  
Angle Of Attack ◽  
High Accuracy ◽  
Data Systems ◽  
Content Type ◽  
Novel Approach ◽  
Reference Measurements ◽  
Long Endurance ◽  
Practical Implications

Purpose This paper aims to propose a novel approach, in which the reference data for the flow angles calibration are obtained by using measurements coming from an inertial navigation system and an air data sensor. Design/methodology/approach This is obtained by using the Kalman filter theory for the evaluation of the reference angle-of-attack and angle-of-sideslip. Findings The designed Kalman filter has been implemented in Matlab/Simulink and validated using flight data coming from two very different aircraft, the Piaggio Aerospace P1HH medium altitude long endurance unmanned aerial system and the Alenia-Aermacchi M346 Master™ transonic trainer. This paper illustrates some results where the filter satisfactory behaviour is verified by comparing the filter outputs with the data coming from high-accuracy nose-boom vanes. Practical implications The methodology aims to lower the calibration costs of the air data systems of an advanced aircraft. Originality/value The calibration of air-data systems for the evaluation of the flow angles is based on the availability of high-accuracy reference measurements of angle-of-attack and angle-of-sideslip. Typically, these are obtained by auxiliary sensors directly providing the reference angles (e.g. nose-boom vanes). The proposed methodology evaluates the reference angle-of-attack and angle-of-sideslip by analytically reconstructing them using calibrated airspeed measurements and inertial data.

scholarly journals New Measuring Methods of Wheelset Angle of Attack of Railway Vehicle on Curves.

1992 ◽  
Vol 58 (547) ◽  
pp. 780-787 ◽  
Author(s):  
Masayuki MIYAMOTO ◽  
Hiroshi FUJIMOTO ◽  
Tadaomi OKABE ◽  
Eisaku SATO
Keyword(s):  
Angle Of Attack ◽  
Railway Vehicle ◽  
Measuring Methods

scholarly journals New Measuring Methods for Wheelset Angle of Attack of Railway Vehicle on Curves

1994 ◽  
Vol 37 (2) ◽  
pp. 292-299
Author(s):  
Masayuki Miyamoto ◽  
Hiroshi Fujimoto ◽  
Tadaomi Okabe ◽  
Eisaku Sato
Keyword(s):  
Angle Of Attack ◽  
Railway Vehicle ◽  
Measuring Methods

To the Problem of Estimating the Angle of Attack of an Aircraft by the Kalman Filter

2018 ◽  
Vol 61 (2) ◽  
pp. 311-315
Author(s):  
A. A. Golovan ◽  
A. V. Sharonov
Keyword(s):  
Kalman Filter ◽  
Angle Of Attack

scholarly journals An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

2017 ◽  
Vol 232 (6) ◽  
pp. 1686-1702 ◽  
Author(s):  
Altan Onat ◽  
Petr Voltr ◽  
Michael Lata
Keyword(s):  
Kalman Filter ◽  
Condition Monitoring ◽  
Unscented Kalman Filter ◽  
Test Stand ◽  
Railway Vehicle ◽  
Wheel Wear ◽  
Railway Vehicles ◽  
Wheel Profile ◽  
Roller Configuration ◽  
And Performance

Monitoring the conditions of railway vehicle systems plays an important role in the maintenance of safety and performance of railway vehicles. Rolling radius is one of the properties that should be monitored continuously for the predictive maintenance of a railway vehicle since it changes with time due to wheel wear. In this study, a model-based condition monitoring methodology, which is based on an unscented Kalman filter, is proposed. The model includes the torsional dynamics of an independently rotating tram wheel with a traction motor and a contact model. The rolling radius is estimated by considering the traction effort of the motor and the angular velocity measurements. The proposed methodology is tested on a tram wheel test stand (roller rig), which has a wheel on roller configuration. First, a mathematical model is validated by the measurements taken from the test stand. Second, the unscented Kalman filter is applied as a parameter estimator. The results demonstrate that the proposed scheme is a promising option to be used in the predictive condition monitoring of the wheel profile for traction vehicles.

Condition Monitoring of a Suspension Device of a Railway Vehicle Using an Extended Kalman Filter

2019 ◽  
Vol 22 (12) ◽  
pp. 939-950
Author(s):  
Myeong-Joon Kim ◽  
Jae-Min Moon ◽  
Chul-Goo Kang ◽  
Jae-Hwan Kim ◽  
Nam-Jin Lee ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Condition Monitoring ◽  
Railway Vehicle
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