Smart sensor system and method using a surface acoustic wave vapor sensor array and pattern recognition for selective trace organic vapor detection
First Claim
1. A method of identifying an unknown vapor as either belonging to a class or not, wherein the class comprises known vapors of interest, said method comprising the steps of:
- introducing a sample of an unknown vapor into at least one sensor coated with a vapor-sensitive coating,generating a weight vector corresponding to a N-space representation of the class;
generating a N-space representation of the unknown vapor and generating an unknown pattern vector based thereon; and
calculating the dot product of said unknown pattern vector and the weight vector to determine whether the unknown vapor is within said class, wherein the dot product producing a positive number is a member of the class in question while a negative number is not.
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Abstract
A method and a system using that method are provided which employ a patternecognition algorithm to improve sensitivity in detecting hazardous vapors. The algorithm enables the discrimination of vapors of interest from non-hazardous substances at higher concentrations in varying relative humidity. A weight vector is generated corresponding to a N-space representation of a class comprising known vapors of interest, and a N-space representation of the unknown vapor is used to generate an unknown pattern vector. By calculating the dot product of the unknown pattern vector and the weight vector a determination can be made as to whether the unknown vapor is within the class. The weight vector is generated by selecting a training set comprising a subset of the known vapors of interest and background vapors and generating an N-space representation of the training set so as to create an associated weight vector.
223 Citations
12 Claims
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1. A method of identifying an unknown vapor as either belonging to a class or not, wherein the class comprises known vapors of interest, said method comprising the steps of:
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introducing a sample of an unknown vapor into at least one sensor coated with a vapor-sensitive coating, generating a weight vector corresponding to a N-space representation of the class; generating a N-space representation of the unknown vapor and generating an unknown pattern vector based thereon; and calculating the dot product of said unknown pattern vector and the weight vector to determine whether the unknown vapor is within said class, wherein the dot product producing a positive number is a member of the class in question while a negative number is not. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A smart sensor system for determining whether an unknown vapor is within a known class of vapors, said system comprising:
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a sampling means for generating vapor samples; an array of sensors for generating vapor response data from said vapor samples; means for interpreting said response data as points in an N-dimensional feature space having N axes and defining unknown pattern vectors, each vector being associated with one of said points and extending from the origin of said axes to said point, where N is defined by the number of sensors in said sensor array; and means for calculating the dot product of said unknown pattern vector and a stored weighing vector associated with a N-space representation of the known class, and to determine if said vapor is within said class, said weight vector being defined by a discriminant function generated by a supervised learning technique. - View Dependent Claims (10, 11, 12)
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Specification