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Vol. 109, Issue 10, October 2009, pp. 76-91

 

Bullet

 

Accurate Fluid Level Measurement in Dynamic Environment Using Ultrasonic Sensor and ν-SVM

 

1Jenny TERZIC, 2Romesh NAGARAJAH, 3Muhammad ALAMGIR

1Delphi Corporation, 86 Fairbank Road, Clayton South VIC 3169, Australia

Tel.: +(61) 418 139 277

2Swinburne University, Burwood Hwy, Hawthorn VIC 3122, Australia

Tel.: +(61) 3 9214 8530

3Delphi Corporation, 86 Fairbank Road, Clayton South VIC 3169, Australia

Tel.: +(61) 423 017 656

E-mail: edin.terzic@delphi.com, nragarajah@swin.edu.au, muhammad.alamgir@delphi.com

 

 

Received: 12 August 2009   /Accepted: 23 October 2009   /Published: 30 October 2009

 

Abstract: A fluid level measurement system based on a single Ultrasonic Sensor and Support Vector Machines (SVM) based signal processing and classification system has been developed to determine the fluid level in automotive fuel tanks. The novel approach based on the ν-SVM classification method uses the Radial Basis Function (RBF) to compensate for the measurement error induced by the sloshing effects in the tank caused by vehicle motion. A broad investigation on selected pre-processing filters, namely, Moving Mean, Moving Median, and Wavelet filter, has also been presented. Field drive trials were performed under normal driving conditions at various fuel volumes ranging from 5 L to 50 L to acquire sample data from the ultrasonic sensor for the training of SVM model. Further drive trials were conducted to obtain data to verify the SVM results. A comparison of the accuracy of the predicted fluid level obtained using SVM and the pre-processing filters is provided. It is demonstrated that the ν-SVM model using the RBF kernel function and the Moving Median filter has produced the most accurate outcome compared with the other signal filtration methods in terms of fluid level measurement.

 

Keywords: Intelligent level measurement, Liquid slosh, Radial basis function, Support vector machine

 

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