Parameter Uncertainty in Statistical Energy Analysis

XIAO Yanping; SONG Haiyang; YE Xianhui

doi:10.21656/1000-0887.390216

Volume 40 Issue 4

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XIAO Yanping, SONG Haiyang, YE Xianhui. Parameter Uncertainty in Statistical Energy Analysis[J]. Applied Mathematics and Mechanics, 2019, 40(4): 443-451. doi: 10.21656/1000-0887.390216

Citation:

XIAO Yanping, SONG Haiyang, YE Xianhui. Parameter Uncertainty in Statistical Energy Analysis[J]. Applied Mathematics and Mechanics, 2019, 40(4): 443-451. doi: 10.21656/1000-0887.390216

Citation:

XIAO Yanping, SONG Haiyang, YE Xianhui. Parameter Uncertainty in Statistical Energy Analysis[J]. Applied Mathematics and Mechanics, 2019, 40(4): 443-451. doi: 10.21656/1000-0887.390216

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Parameter Uncertainty in Statistical Energy Analysis

doi: 10.21656/1000-0887.390216

¹Flight Technology College, Civil Aviation Flight University of China, Guanghan, Sichuan 618307, P.R.China;²State Key Laboratory of Science and Technology on Reactor System Design Technology(Nuclear Power Institute of China), Chengdu 610041, P.R.China

Funds: The National Natural Science Foundation of China（51606180；11872060）

Received Date: 2018-08-07
Rev Recd Date: 2018-10-25
Publish Date: 2019-04-01

Abstract

Abstract

The statistical energy analysis (SEA) is an effective method to calculate the vibration and noise, where the damping loss factor and the coupling loss factor have very small values and usually are difficult to accurately measure. Then large measurement errors result in significant deviation between the calculated value and the true value of the total energy. To tackle this problem, 4 kinds of different energy interval analysis methods: the interval matrix perturbation approach, the method based on the properties of interval variables, the affine arithmetic and the inverse affine matrix, were used to calculate the steadystate SEA subsystems, where the effects of measurement errors of the damping loss factor and the coupling loss factor on the calculation results were fully considered. Two numerical examples with different errors of loss factors were provided, and the total energy intervals based on different methods were compared. The work improves the existent SEA theory and proves the superiority of the inverse affine matrix over other methods.
- statistical energy analysis,
- measurement error,
- damping loss factor,
- interval analysis method

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References(13)

References

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