Applied Soft Computing, Journal Year: 2024, Volume and Issue: 167, P. 112442 - 112442
Published: Nov. 9, 2024
Language: Английский
Applied Soft Computing, Journal Year: 2024, Volume and Issue: 167, P. 112442 - 112442
Published: Nov. 9, 2024
Language: Английский
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Jan. 9, 2025
An improved concrete structure health monitoring method based on G-S-G is proposed, which fully combines an optimized Gray-Level Co-occurrence Matrix (GLCM) with Self-Organizing Map (SOM) neural network to achieve accurate and real-time monitoring. First of all, in order obtain a dynamic image the crack damage region interest (ROI) clear contrast obvious target, acquisition system optimization are used process damaged image. Moreover, realize location damage, identification research GLCM-SOM effectively eliminates interference honeycomb pothole damage. In indicators for status structure, characteristics probability distribution gray level co-occurrence matrix combined extract range index (PRI). On basis extracting index, verify reliability sensitive feature starting from two dimensions texture data expansion, through reverse model, accurately locating was selected. It follows that final indicators: entropy (ENT) PRI can be structural because their strong characterization ability sensitivity characteristics. This shows helpful high precision intelligent modern
Language: Английский
Citations
1Expert Systems with Applications, Journal Year: 2025, Volume and Issue: 283, P. 127862 - 127862
Published: April 30, 2025
Citations
0Information Sciences, Journal Year: 2025, Volume and Issue: unknown, P. 122116 - 122116
Published: March 1, 2025
Language: Английский
Citations
0Applied Soft Computing, Journal Year: 2024, Volume and Issue: 167, P. 112442 - 112442
Published: Nov. 9, 2024
Language: Английский
Citations
1