- A compressor blade crack detection method based on the multilevel information fusion of acoustic and vibration signals. In: Structural Health Monitoring. :
- Quantitative blade damage detection based on multisource domain and multistage joint transfer. In: Structural Health Monitoring, v. 23, n. 6 (Februar 2024). (2024):
- A two-level fusion model of vibro-acoustic signals for centrifugal fan blade crack detection. In: Structural Health Monitoring, v. 23, n. 6 (Februar 2024). (2024):
- Incremental learning BiLSTM based on dynamic proportional adjustment mechanism and experience replay for quantitative detection of blade crack propagation. In: Structural Health Monitoring, v. 23, n. 2 (Juli 2023). (2023):
- Blade crack detection based on domain adaptation and autoencoder of multidimensional vibro-acoustic feature fusion. In: Structural Health Monitoring, v. 22, n. 5 (Februar 2023). (2023):
- Two-level fusion of multi-sensor information for compressor blade crack detection based on self-attention mechanism. In: Structural Health Monitoring, v. 22, n. 3 (September 2022). (2022):
- Blade crack detection using variational model decomposition and time-delayed feedback nonlinear tri-stable stochastic resonance. In: Structural Health Monitoring, v. 22, n. 2 (Mai 2022). (2022):
- Fault feature recognition of centrifugal compressor with cracked blade based on SNR estimation and adaptive stochastic resonance. In: Structural Health Monitoring, v. 22, n. 1 (November 2019). (2019):
- Crack damage monitoring for compressor blades based on acoustic emission with novel feature and hybridized feature selection. In: Structural Health Monitoring, v. 21, n. 6 (März 2022). (2022):