Bridge cable wire breakage signal identification method and system based on long short-term memory network

The invention belongs to the technical field of bridge cable state monitoring, and particularly relates to a bridge cable broken wire signal identification method and system based on a long short-term memory network, signal feature extraction is carried out from multiple dimensions of time domain, frequency domain, time-frequency analysis and the like, and feature parameters with relatively high classification capability are selected; a comprehensive feature vector representing the acoustic emission signal is constructed; a broken wire signal identification model is constructed based on LSTM, and good performance is shown on a test set; compared with a traditional machine learning algorithm model, the constructed broken wire signal identification model can accurately identify most broken wire and non-broken wire signals, and shows good identification capability for broken wire signals. 本申请属于桥梁拉索状态监测技术领域，具体涉及一种基于长短期记忆网络的桥梁拉索断丝信号识别方法及系统，从时域、频域、时频分析等多维度进行信号特征提取，选取了分类能力较强的特征参数，构建了表征声发射信号的综合特征向量；基于LSTM构建断丝信号识别模型，在