An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures
Abstract
1. Introduction
2. Methodology
2.1. A Review of GMM
2.2. The Proposed iGMM
2.3. Data Normalization
2.4. Damage Indicator and Threshold
2.5. Implementation Procedure
3. Case Studies
3.1. Case Study Using Numerical Simulation
3.2. Case Study Using the Z24 Bridge Data
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Cumulative Statistic | Damage Detection Rate (%) | ||||
---|---|---|---|---|---|
Training | Test (Intact) | Test (Damage 1) | Test (Damage 2) | Test (Damage 3) | |
0.31 | 0.20 | 42.71 | 70.42 | 91.46 | |
0.24 | 0.20 | 81.88 | 93.96 | 100 | |
0.26 | 0.34 | 93.54 | 99.58 | 100 | |
0.27 | 0.34 | 96.04 | 100 | 100 |
Cumulative Statistic | Damage Detection Rate (%) | ||
---|---|---|---|
Training | Test (Intact State) | Test (Damaged State) | |
0.29 | 0.14 | 96.32 | |
0.29 | 0.00 | 98.92 |
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Pei, X.-Y.; Huang, H.-B.; Cao, P. An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures. Buildings 2025, 15, 359. https://doi.org/10.3390/buildings15030359
Pei X-Y, Huang H-B, Cao P. An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures. Buildings. 2025; 15(3):359. https://doi.org/10.3390/buildings15030359
Chicago/Turabian StylePei, Xue-Yang, Hai-Bin Huang, and Peng Cao. 2025. "An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures" Buildings 15, no. 3: 359. https://doi.org/10.3390/buildings15030359
APA StylePei, X.-Y., Huang, H.-B., & Cao, P. (2025). An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures. Buildings, 15(3), 359. https://doi.org/10.3390/buildings15030359