The application of multisensors fusion in Vehicle Transmission System Fault Diagnosis

Xiaobing Wu; Shuangzhe Liu; Dharmendra Sharma

doi:10.1109/ICNC.2007.709

The application of multisensors fusion in Vehicle Transmission System Fault Diagnosis

Xiaobing Wu, Shuangzhe Liu, Dharmendra Sharma

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

1 Citation (Scopus)

44 Downloads (Pure)

Abstract

Multi-sensors fusion technology is adopted for fault diagnosis of vehicle transmission system. By using hybrid pattern fusion based on artificial neural networks (ANN), the robustness of the diagnosing system is improved greatly. This hybrid fusion pattern avoids working with a great deal of original data from sensors, while it has the advantage of less information lost. At the same time, the diagnosis effect is improved by using feature-level and decision-level vibration data and original-level lube data

Original language	English
Title of host publication	Proceedings: 3rd International Conference on Natural Computation: ICNC 2007
Editors	J Lei
Place of Publication	China
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	728-731
Number of pages	4
ISBN (Print)	9780769528755
DOIs	https://doi.org/10.1109/ICNC.2007.709
Publication status	Published - 2007
Event	3rd International Conference on Natural Computation: ICNC 07 - Haikou, Haikou, China Duration: 28 Aug 2007 → 30 Aug 2007

Conference

Conference	3rd International Conference on Natural Computation
Country/Territory	China
City	Haikou
Period	28/08/07 → 30/08/07

Access to Document

10.1109/ICNC.2007.709

Conference ContributionFinal published version, 302 KB

Cite this

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title = "The application of multisensors fusion in Vehicle Transmission System Fault Diagnosis",

abstract = "Multi-sensors fusion technology is adopted for fault diagnosis of vehicle transmission system. By using hybrid pattern fusion based on artificial neural networks (ANN), the robustness of the diagnosing system is improved greatly. This hybrid fusion pattern avoids working with a great deal of original data from sensors, while it has the advantage of less information lost. At the same time, the diagnosis effect is improved by using feature-level and decision-level vibration data and original-level lube data",

author = "Xiaobing Wu and Shuangzhe Liu and Dharmendra Sharma",

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booktitle = "Proceedings: 3rd International Conference on Natural Computation: ICNC 2007",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "3rd International Conference on Natural Computation : ICNC 07 ; Conference date: 28-08-2007 Through 30-08-2007",

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Wu, X, Liu, S & Sharma, D 2007, The application of multisensors fusion in Vehicle Transmission System Fault Diagnosis. in J Lei (ed.), Proceedings: 3rd International Conference on Natural Computation: ICNC 2007 . IEEE, Institute of Electrical and Electronics Engineers, China, pp. 728-731, 3rd International Conference on Natural Computation, Haikou, China, 28/08/07. https://doi.org/10.1109/ICNC.2007.709

The application of multisensors fusion in Vehicle Transmission System Fault Diagnosis. / Wu, Xiaobing; Liu, Shuangzhe ; Sharma, Dharmendra.
Proceedings: 3rd International Conference on Natural Computation: ICNC 2007 . ed. / J Lei. China: IEEE, Institute of Electrical and Electronics Engineers, 2007. p. 728-731.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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