Damage detection of offshore platforms using acoustic emission analysis
Guijie Liu1, Shirui Wang1, Yingchun Xie1
1School of Engineering & Key Laboratory of Ocean Engineering of Shandong Province, Ocean University of China, Qingdao 266100, China.
The Review of Scientific Instruments
|December 4, 2018
Summary
This study optimizes acoustic emission sensor placement for detecting structural damage in offshore platforms. The new layout improves damage detection efficiency and reduces sensor count by 80%.
Area of Science:
- Structural Health Monitoring
- Offshore Engineering
- Acoustic Emission Analysis
Background:
- KT-type jacket offshore platforms are critical infrastructure requiring robust structural integrity.
- Early detection of structural damage is essential to prevent catastrophic failures.
- Traditional monitoring methods may be insufficient for complex offshore environments.
Purpose of the Study:
- To develop an optimized acoustic emission (AE) sensor layout for detecting structural damage in KT-type jacket offshore platforms.
- To improve the efficiency and effectiveness of online damage monitoring systems.
- To reduce the number of sensors required for comprehensive monitoring.
Main Methods:
- Experimental investigation of AE signal transmission characteristics and attenuation laws.
- Determination of energy attenuation coefficient (α) and signal amplitude attenuation.
- Optimization of AE sensor layout based on energy attenuation data.
- Validation of the optimized layout through experimental source localization tests.
Main Results:
- Established the energy attenuation coefficient (α) and signal amplitude attenuation law for AE signals.
- Developed an optimized AE sensor layout significantly reducing sensor requirements.
- Achieved AE source localization with a positioning error of 8 mm or below.
- Demonstrated an 80% reduction in sensor count compared to theoretical layouts.
Conclusions:
- The optimized AE sensor layout enables efficient and effective online damage detection for KT-jacket offshore platforms.
- The proposed method significantly reduces the number of sensors needed, offering a cost-effective solution.
- This approach enhances structural health monitoring capabilities for offshore platforms.
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