Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN

dc.creator	Zhou, Y.
dc.creator	Zheng, J.
dc.creator	Liu, Z.
dc.creator	Yang, C.
dc.creator	Peng, P.
dc.date.accessioned	2007-05-07T20:45:39Z
dc.date.available	2007-05-07T20:45:39Z
dc.date.issued	2006
dc.identifier.other	ESL-IC-06-11-166
dc.identifier.uri	https://hdl.handle.net/1969.1/5311
dc.description.abstract	At first the basic research about FDD is summarized, and a detection model based on ANN is initially set up. The paper presents experiments that simulate seven faults, including change flow rate of chilled water, cooling water and refrigerant, charge non-condense gas, shift temperature of cooling water and alter outside cold load. A set of characteristic parameters are defined in order to differentiate these faults and clarify the reasons. Finally, an FDD tool is programmed based on ANN with experimental results which form a training stylebook and test stylebook.	en
dc.format.extent	150838 bytes	en
dc.format.mimetype	application/pdf
dc.language.iso	en_US
dc.publisher	Energy Systems Laboratory (http://esl.tamu.edu)
dc.publisher	Texas A&M University (http://www.tamu.edu)
dc.subject	water cooling chiller of screw	en
dc.subject	fault diagnosis	en
dc.subject	artificial neural network	en
dc.title	Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN	en