Naval Troop of 91918

Beijing, China

Naval Troop of 91918

Beijing, China

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Yang G.,Naval Troop of 91918 | Wu X.,Wuhan Naval University of Engineering | Xin D.,Naval Troop of 91918 | Li Q.,Naval Troop of 91918
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) | Year: 2013

For the reasons of low diagnosis accuracy and bad real-time capability of traditional fault diagnosis methods in handling diagnostic problems such as lots of data and various complex faults, a synthesized fault diagnosis reasoning strategy of fusing rough sets, neural network and evidence theory is presented by means of data fusion and meta-synthesis theory. Firstly, the diagnosis ability of the local diagnosis networks is advanced through parallel neural network structure; with the rough set theory, the complex neural networks are simplified by eliminating redundant properties, which overcomes networks' shortcomings of large scale and low-rate classification and the NN structure is determined. Secondly, an impersonal means obtaining basic reliability distribution of evidence theory is given. Finally, through taking full advantages of various redundant and complementary fault information, the accuracy and efficiency of the fault diagnosis are improved obviously by using combination rule of evidence theory. A given diagnostic example proves the method is feasible and available.


Yang G.,Naval Troop of 91918 | Wu X.,Wuhan Naval University of Engineering
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) | Year: 2011

For the reasons of low diagnosis accuracy of traditional diesel engine fault diagnosis methods in handling diagnostic problems such as lots of data and various complex faults, a diesel engine synthesized fault diagnosis technique fusing neural network and evidence theory is presented by means of data fusion theory. In this technique, the diagnosis ability of the local diagnosis networks is advanced through parallel neural network structure, and an impersonal means obtaining basic reliability distribution of evidence theory is given, and then the accuracy of the fault diagnosis is improved obviously by taking full advantages of various redundant and complementary fault information. Finally an example is applied for fault diagnosis of ship diesel engine, and diagnostic results indicate that the technique is available, which can improve the efficiency of diesel engine fault diagnosis system evidently.


Yang G.,Naval Troop of 91918 | Wu X.,Wuhan Naval University of Engineering | Xin D.,Naval Troop of 91918 | Li D.,Naval Troop of 91918
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) | Year: 2011

Through essence analysis of multi-sensor information fusion system and hall for workshop of Meta-synthetic Engineering (HWME), a universal HWME system configuration based on multi-sensor information fusion is put forward. Integrating analysis and research to fault diagnosis framework of complex system based on information fusion technique, and to the universal process of information fusion synthesis fault diagnosis, a fault diagnosis system configuration framework of HWME based on information fusion is constituted, which runs through the whole process of synthetic fault diagnosis. By this method, a new approach to multi-sensor information fusion synthesis fault diagnosis is sought.

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