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可变工况下回转支承寿命预测的动态结构自适应符号方法 - 丁鹏， 贾敏平， 王华， 2021
Source: journals.sagepub.com
Article summary:
1. A dynamic structure-adaptive symbolic approach (DSASA) is proposed to predict the remaining useful life (RUL) of rotating bearings under variable working conditions.
2. DSASA intuitively displays the internal model structure, considers historical samples, and dynamically adapts to the real-time degradation of service components.
3. Results show that DSASA has reliable generalization and significantly reduces prediction errors compared to the initial model before reconstruction by 82.5%, 45.5%, and 79.8%.
Article analysis:
The article provides a detailed overview of a new method for predicting the remaining useful life (RUL) of rotating bearings under variable working conditions using a dynamic structure-adaptive symbolic approach (DSASA). The authors provide evidence from experiments conducted on rotary bearings to demonstrate the efficacy of their proposed method in comparison with existing methods, which suggests that it is reliable and trustworthy.
However, there are some potential biases in the article that should be noted. For example, while the authors discuss existing methods such as statistical models and AI-supported data-driven techniques, they do not explore any counterarguments or alternative approaches that could be used for RUL prediction. Additionally, while they provide evidence from experiments conducted on rotary bearings, they do not mention any possible risks associated with using their proposed method or any other potential drawbacks that should be considered when using it in practice.
In conclusion, while this article provides an interesting overview of a new method for predicting RUL under variable working conditions, there are some potential biases and missing points of consideration that should be noted when assessing its trustworthiness and reliability.