Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications
A Support Vector Machine Approach
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Beschreibung
Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods.
Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ν-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels of accuracy required for fluid level measurement in dynamic environments.
Aimed toward graduate and postgraduate students, researchers, and engineers studying applications of artificial intelligence, readers will learn about a measurement system that is based on a single ultrasonic sensor which can achieve the high levels of accuracy required for fluid level measurement in dynamic environments.
Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods.
Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ν-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels of accuracy required for fluid level measurement in dynamic environments.
Aimed toward graduate and postgraduate students, researchers, and engineers studying applications of artificial intelligence, readers will learn about a measurement system that is based on a single ultrasonic sensor which can achieve the high levels of accuracy required for fluid level measurement in dynamic environments.
Covers the dynamic aspect (sloshing) of the fluid level measurement system in the vehicle and uses SVM as a method to improve accuracy of the system and recognize the sloshing pattern in the fuel tank with superior accuracy Discusses extensive experimental results based on practical application Includes many illustrations and examples Includes supplementary material: sn.pub/extras
Autor*in
Jenny Terzic
Themen in »Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications«
Accurate Fluid Level Measurement Dynamic Vehicular Applications Gas Tank Level Intelligent Sensors Neural Network SVM Support Vector Machine Approach Ultrasonic Fluid Quantity Measurement