As a crucial part in aeronautical structures, the lug joint plays a critical role in transmitting concentrated loads. Its failure is bound to bring catastrophic consequences. Hence, the fatigue performance of the lug needs to be investigated by test. Since the Acoustic Emission (AE) technology is an on-line monitoring method that can capture the crack initiation and propagation process in time, it is chosen to monitor the damage to improve the test quality. However, due to the random load spectrum, a large number of extremely complex, irregular and intense AE noise signals will be generated, hampering the functioning of traditional AE analysis methods based on feature extraction and parameter filtering, and thus unable to effectively identify the initiation of joint cracks. This paper proposes a novel AE identification method of fatigue cracks with random load spectrum, utilizing the distribution characteristics of the random load spectrum. By analyzing the differences of AE signals from different load spectrum blocks, we can find and locate the abnormal signals. Furthermore, location analysis and interference elimination analysis are adopted to ultimately determine the occurrence time and location of the cracks. The validity of this method has been verified by the fatigue test, providing reference for the related aeronautical structure tests with random load spectrum.
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