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基于二叉树的故障诊断信息录入技术 被引量:5

Recording Technology of Fault Diagnosis Information Based on Bintree
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摘要 提出了一种基于二叉树的故障诊断信息录入技术。建立了故障树与二叉树的转换原则,并且在此基础上按照顶结点—子结点—兄弟结点的顺序,将故障信息依次按照规则录入数据库,以便实现故障信息的更新。通过实例验证了该项技术的可行性和高效率。该技术解决了以往在基于故障树的故障诊断过程中故障信息录入数据库时出现的效率低和繁琐的问题。 A recording technology of fault diagnosis information based on Bintree is proposed.The principle of conversion between Bintree and fault tree is established first.Based on it,the fault information is recorded in the database according to the sequence of topnode-subnode-brothernode,then the fault information is refreshed.The feasibility and efficiency of this technology are verified by instance.This technology solves the problems of inefficiency and tediousness in recording fault information in database.
出处 《无线电工程》 2012年第11期55-57,64,共4页 Radio Engineering
关键词 二叉树 故障树 故障诊断 数据库 Bintree fault tree fault diagnosis database
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  • 1Wang Y R, Zhang Z Q, Cui J. The architecture and circuital implementation scheme of a new cell neural network for analogsignal processing [J]. Journal of Universal Computer Science, 2007, 13(9): 1344-1353. 被引量:1
  • 2Luo H, Wang Y R, Cui J. A SVDD approach of fuzzy classification for analog circuit fault diagnosis with FWT aspreprocessor [J]. Expert Systems with Applications, 2011, 38(3) :10554-10561. 被引量:1
  • 3Aminian M, Aminian F. A modular fault-diagnostic system for analog electronic circuits using neural networks withwavelet transform as a preprocessor [J]. IEEE Transactions on Instrumentation and Measurement, 2007, 56 (5) :1546- 1554. 被引量:1
  • 4Seyyed M S J, Mohammadi K. Evolutionary derivation of optimal test sets for neural network based analog and mixedsignal circuits fault diagnosis approach [J]. Microelectronics Reliability, 2009, 49(2): 199-208. 被引量:1
  • 5Cui J, Wang Y R. A novel approach of analog circuit fault diagnosis using support vector machines classifier [J]. Measurement, 2011, 44(1): 281-289. 被引量:1
  • 6Lin C F, Wang S D. Fuzzy support vector machines [J]. IEEE Transactions on neural networks, 2002, 13 (2) : 464- 471. 被引量:1
  • 7Suykens J A K, Vandewalle J. Least squares support vector machine classifiers [J]. Neural Processing Letters, 1999, 9 (3) : 293-300. 被引量:1
  • 8Dietterich T G, Bakiri G. Solving multiclass learning problems via error-correcting output codes [J]. Journal of Artificial Intelligence Research, 1994, 2(1): 263-286. 被引量:1
  • 9Allwein E L, Schapire R E, Singer Y. Reducing multiclass to binary: a unifying approach for margin classifiers [J]. Journal of Machine Learning Research, 2001, 1:113-141. 被引量:1
  • 10Escalera S, Pujol O, Radeva P. On the decoding process in ternary error-correcting output codes [J]. IEEE Transactionson Pattern Analysis and Machine Intelligence, 2010, 32 (1) : 120-134. 被引量:1

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