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Development and implementation of an artificially intelligent search algorithm for sensor fault detection using neural networks

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dc.contributor.advisor Langari, Reza en_US
dc.contributor.advisor Culp, Charles H., III en_US
dc.creator Singh, Harkirat en_US
dc.date.accessioned 2004-09-30T01:42:45Z
dc.date.available 2004-09-30T01:42:45Z
dc.date.created 2003-05 en_US
dc.date.issued 2004-09-30T01:42:45Z
dc.identifier.uri http://hdl.handle.net/1969.1/116
dc.description.abstract This work is aimed towards the development of an artificially intelligent search algorithm used in conjunction with an Auto Associative Neural Network (AANN) to help locate and reconstruct faulty sensor inputs in control systems. The AANN can be trained to detect when sensors go faulty but the problem of locating the faulty sensor still remains. The search algorithm aids the AANN to help locate the faulty sensors and reconstruct their actual values. The algorithm uses domain specific heuristics based on the inherent behavior of the AANN to achieve its task. Common sensor errors such as drift, shift and random errors and the algorithms response to them have been studied. The issue of noise has also been investigated. These areas cover the first part of this work. The second part focuses on the development of a web interface that implements and displays the working of the algorithm. The interface allows any client on the World Wide Web to connect to the engineering software called MATLAB. The client can then simulate a drift, shift or random error using the graphical user interface and observe the response of the algorithm. en_US
dc.format.extent 1869594 bytes
dc.format.extent 119077 bytes
dc.format.medium electronic en_US
dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.language.iso en_US en_US
dc.publisher Texas A&M University en_US
dc.subject Artificial Intelligence en_US
dc.subject Search Algorithm en_US
dc.subject Sensor Faults en_US
dc.subject Neural Networks en_US
dc.title Development and implementation of an artificially intelligent search algorithm for sensor fault detection using neural networks en_US
dc.type Book en
dc.type Thesis en
thesis.degree.department Mechanical Engineering en_US
thesis.degree.discipline Mechanical Engineering en_US
thesis.degree.grantor Texas A&M University en_US
thesis.degree.name Master of Science en_US
thesis.degree.level Masters en_US
dc.contributor.committeeMember Ioerger, Tom en_US
dc.type.genre Electronic Thesis en_US
dc.type.material text en_US
dc.format.digitalOrigin born digital en_US

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