Artificial olfactory system and an application thereof

• US 9,651,529 B2
• Filed: 05/22/2014
• Issued: 05/16/2017
• Est. Priority Date: 07/01/2013
• Status: Active Grant

• Current Assignee: Universiti Putra Malaysia (Government of Malaysia)
• Original Assignee: Universiti Putra Malaysia (Government of Malaysia)
• Inventors: Hamidon, Mohd Nizar, Lotfivandvahed, Nasser
• Primary Examiner(s): Caputo, Lisa
• Assistant Examiner(s): Roy, Punam
• Application Number:
  US14/284,617
• Publication Number:
  US 20150000373A1
• Time in Patent Office: 1,090 Days
• CPC Class Codes: G01N 33/0001 by organoleptic means
• CPC Class Codes: G01N 33/0031 comprising two or more sensors, e.g. a sensor array
• CPC Class Codes: G01N 33/0034 comprising neural networks or related mathematical techniques

Abstract

The present invention relates to an artificial olfactory system (100), comprising of an inlet (101); a gas chamber (110) having a detector means, connected to a data acquisition system (104); a heater (112) and a plurality of fans (115); a humidity absorber (111); an outlet (102); a vacuum pump (103); characterized by the detector means having a plurality of sensors (121) in each of a plurality of clusters (120), wherein the plurality of sensors (121) in each of the plurality of clusters (120) comprises identical sensors capable of responding to a particular gas or vapor. The present invention also relates to a method for detecting a gas or a vapor from the artificial olfactory system (100), comprising the step of exposing the gas or vapor to the plurality of sensors (121) to produce a plurality of output signals from the plurality of sensors (121); transferring the plurality of output signals to the data acquisition system (104); extracting median data from the plurality of output signals; applying a principal component analysis (PCA), neural network, and least square regression analysis on the median data from all of the plurality of clusters (120).

Claims

1. A method for detecting a gas or a vapour, which comprises using an artificial olfactory system (100), comprising:

an inlet (101);

a gas chamber (110) having a detector means, connected to a data acquisition system (104);

a heater (112) and a plurality of fans (115) for controlling the temperature in the gas chamber (110);

a humidity absorber (111);

an outlet (102);

a vacuum pump (103) for eliminating remaining polluting gas or vapours;

wherein the detector means comprises a plurality of clusters (120) and each cluster comprises a plurality of identical sensors (121) capable of responding to a particular gas or vapour, said method comprising the steps of;

exposing the gas or vapour to the plurality of sensors (121) in the gas chamber (110), thereby producing a plurality of output signals from the plurality of sensors (121) in each of the plurality of clusters (120);

transferring the plurality of output signals to the data acquisition system (104);

extracting median data from the plurality of output signals from each of the plurality of clusters (120) by applying statistic median method;

applying a principal component analysis (PCA) on the median data from all of the plurality of clusters (120) for gas or vapour identification and feature reduction;

applying a neural network on the median data from all of the plurality of clusters (120) for evaluating the classification of the gas or vapour;

applying a least square regression analysis on the median data from all of the plurality of clusters (120) to estimate the concentration of the gas or vapour.

2. The method for detecting a gas or a vapour according to claim 1, wherein the neural network is a multi-layer perceptron (MLP) classifier.

3. A method for detecting a gas or a vapour according to claim 1, wherein the minimum number of identical sensors (121) in each cluster is three.