Method for assessing the durability of structures under stationary and non-stationary random loading using variational mode decomposition (VMD)
In the era of digital transformation, most devices are equipped with a variety of sensors, which provide information to be used in developing intelligent models for predicting the fatigue life. The development of digital models of real objects for fatigue life estimation faces the lack of algorithms for performing such an estimation. The problem arises in the adaptive and automatic analysis of signals from real sensors installed on the object and their subsequent processing to estimate the fatigue life of the object. We propose a new method for assessing the fatigue life of structures based on application of the adaptive method of variational mode decomposition to signals gained from sensors, including non-stationary ones. Variational mode decomposition involves decomposition of an initial complex random process into simpler random processes (modes) that are stationary and narrowband. An original method of summarizing damage resulted from the action of the modes obtained as a result of the decomposition is used. The developed method can be used as an algorithmic support for the generation of digital doubles of the residual lifetimes of natural products. The proposed method is compared with the «rainflow» method in the time domain. Different realizations of random stationary and non-stationary signals with different bandwidths are compared numerically. In addition, the traditional frequency methods of Dirlik and Benasciutti have been compared with the «rainflow» method. The analysis showed good results for the proposed method, i.e., the error was smaller compared to traditional frequency methods, especially for non-stationary processes.
Authors
- I. V. Gadolina (ORCID: https://orcid.org/0000-0002-0509-2202)
- K. A. Khoroshevskii
- E. A. Rumyanceva
- A. V. Erpalov
Institutions
- South Ural State University (RU)
- Mechanical Engineering Research Institute of the Russian Academy of Sciences (RU)
Publication Details
- Journal
- Industrial laboratory Diagnostics of materials
- Published
- 2024-09-23
- DOI
- https://doi.org/10.26896/1028-6861-2024-90-9-63-74
- Citations
- 2
- Primary Topic
- Material Properties and Failure Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 0.23