Abstract
A new temperature compensation technique combining optimal baseline selection and the filter based on Adaptive Linear Neuron Network was developed to enhance the robustness and effectiveness of guided Lamb wave-based damage detection. This paper focuses on three main issues for practically implementing the proposed method: (a) Establishment of temperature compensation standard; (b) Parameters design of compensation filter; (c) Determination of temperature gradient of baseline signals. Experiments were conducted on two stiffened composite plates to demonstrate the feasibility of proposed method under a temperature range from -40°C to 80°C for compensating temperature effects. Results showed that a reasonable temperature step for providing good temperature compensation can be up to 20°C in a baseline dataset.
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