Fault detection of aircraft system with random forest algorithm and similarity measure.
Research on fault detection algorithm was developed with the similarity measure and random forest algorithm. The organized algorithm was applied to unmanned aircraft vehicle (UAV) that was readied by us. Similarity measure was designed by the help of distance information, and its usefulness was also...
| Published in: | Scientific World Journal pp. 727359 - 727360 |
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| Main Authors: | , , |
| Format: | research Journal Article |
| Published: |
Wiley-Blackwell
2014
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103836137&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103836137 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103836137 103836137 NLM25057508 2012659316 10.1155/2014/727359 NLM25057508 PMC4098612 103836137 ppf: 727359 ppct: 1 formats: tig: atl: Fault detection of aircraft system with random forest algorithm and similarity measure. aug: au: Lee, Sanghyuk Park, Wookje Jung, Sikhang affil: Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China. sug: subj: Aircraft Algorithms Models, Theoretical ab: Research on fault detection algorithm was developed with the similarity measure and random forest algorithm. The organized algorithm was applied to unmanned aircraft vehicle (UAV) that was readied by us. Similarity measure was designed by the help of distance information, and its usefulness was also verified by proof. Fault decision was carried out by calculation of weighted similarity measure. Twelve available coefficients among healthy and faulty status data group were used to determine the decision. Similarity measure weighting was done and obtained through random forest algorithm (RFA); RF provides data priority. In order to get a fast response of decision, a limited number of coefficients was also considered. Relation of detection rate and amount of feature data were analyzed and illustrated. By repeated trial of similarity calculation, useful data amount was obtained. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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