Research on Fault Diagnosis of Certain Armored Vehicle’ Gear-Box with IMF’s Energy Moment


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Aim at the non-stationary and time-variation characteristic of the gear-box fault signal, proposing a condition identify method for gear-box based on EMD and NN. Take the vibrating signal of case as the analysis object, firstly, deal the signal with EMD, extract the IMFs’ energy moment as eigenvector, through neural network based on L-M optimization algorithm to identify gear-box fault. The result of testing certain armored vehicle reveals that method can identify a variety of conditions of gear-box effectively, and provides a availability intelligence fault diagnosis method for gear-box.



Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan




C. F. Wang et al., "Research on Fault Diagnosis of Certain Armored Vehicle’ Gear-Box with IMF’s Energy Moment", Advanced Materials Research, Vols. 383-390, pp. 248-253, 2012

Online since:

November 2011




[1] Huang N E, Zheng Shen, Steven R Long, The Empirical Mode Decomposition and the Hilbert Spectrum for Non-linear and Non-Stationary Time Series Analysis[J]. Proceeding of Royal Society London, A, 1998, 454(12): 903-995.


[2] Yang Yu, Research on fault diagnosis methods for rotating machinery based on Empirical Mode Decomposition [D]. Hunan University, (2005).

[3] Zhong Binglin, Huang Ren, Mechanical Fault Diagnosis[M]. Beijing; China Machine Press, (2003).

[4] Yang Yong, The research and application of the EMD and fuzzy neural network in the fault diagnosis of the roller bearing[D]. Tai Yuan University of science and technology, (2008).

[5] Zhu Daqi, Shi Hui, The principle and application of Artificial Neuron Network[M]. Beijing: Science Press, (2006).