The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jun. 10, 2003
Filed:
Jul. 13, 2000
Luis C. Rabelo, Eden Prairie, MN (US);
Mark Walker, Mission Viejo, CA (US);
Radoslaw R. Zakrewski, South Burlington, VT (US);
Simmonds Precision Products, Inc., Charlotte, NC (US);
Abstract
Liquid gauging apparatus using a time delay neural network for determining a quantity of liquid in a container that is not directly measurable by sensors is disclosed. The apparatus comprises a plurality of sensors and a processor. Each of the sensors are capable of measuring a respective parameter of the liquid and for producing a time varying sensor output signal representative of the respective parameter measured thereby. The processor is programmed to process the sensor output signals by a time delay neural network algorithm to determine a current quantity of the liquid in the container based on current and past parameter measurements of the sensor output signals. Also disclosed is a method of training a time delay neural network algorithm for computing a quantity of liquid in a container from current and past liquid parameter sensor measurements. The method comprises the steps of: establishing a dynamic model of liquid behavior in the container and parameter measurements of the liquid behavior sensed by a plurality of sensors; deriving from the dynamic model training data sets for a plurality of liquid quantity values, each data set comprising current and past liquid parameter sensor measurement values corresponding to a liquid quantity value of the plurality, and the corresponding liquid quantity value; and training the time delay neural network algorithm with the derived training data sets.