Monitoring the propagation of mechanical discontinuity using data-driven causal discovery and supervised learning
Mechanical Systems and Signal Processing(2022)
Abstract
•Data-driven workflow successfully monitored the crack location, orientation, and length.•Monitoring of three stages of crack propagation has a median RMSE lower than 2.5 mm.•Numbers of zero-crossing is the strongest causal signatures of crack propagation.•Not all highly correlated features exhibit high causality to crack propagation.•Several high importance features for monitoring task exhibit low causality.
MoreTranslated text
Key words
Signal processing,Mechanical discontinuity,Monitoring,Causal inference,Feature engineering
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined