Optimization techniques for damage detection of composite structure: A review

Majority of the aerospace components are made up of composite materials. The composite materials are prone to damage especially low velocity impacts which lead to loss of serviceability and safety. Composites mainly damaged due to impact. Composite structures are more vulnerable to impact damage and therefore its detection is the main objective of SHM methodology. SHM is the best way for the identification and classification of damage due to low velocity impact (LVI). The structural integrity of composite can be assessed by two major components which are a set of accelerometers and computational techniques. By using these methods damage can be detected but it requires more time. The time required for assessing the extent of damage can be optimized by improving the accuracy and efficiency of the computational techniques. The computational techniques help in the classification, prediction, and time optimization required for damage detection. The popular computational techniques used for optimization are the neural network, genetic algorithm, principal component analysis, swarm particle optimization respectively. The paper discusses the various methods for optimization required for damage detection in the composite structure. (c) 2021 Elsevier Ltd. All rights reserved. Second International Conference on Aspects of Materials Science and Engineering (ICAMSE 2021).

Automated summary

Composite materials used in aerospace are prone to damage, especially from low velocity impacts. Structural Health Monitoring (SHM) is essential for detecting and classifying damage caused by low velocity impacts. By using accelerometers and computational techniques, the extent of damage can be assessed with a focus on improving efficiency for damage detection.