关键词: 事件, 光纤振动信号, 实验样本, 极限学习机（ELM）, 识别率

Abstract: Information extraction and recognition methods of optical fiber vibration signals have gradually become the focus of research. Visual analysis and comparison of the short-time zero crossing rate and energy of 5 kinds of optical fiber vibration signals, such as excavator digging, artificial digging, automobile walking, pedestrian walking and noise, are carried out, and a method for selecting experimental samples is proposed. A decision tree model of two classification and ELM algorithm are adopted, and according to the importance of the events, they are identified at four stages. At the same time, the influence of the parameters about ELM algorithm on the experimental results is analyzed. It is proved by experiments that the recognition rate of events is improved and the training time of model is shortened.

Key words: event, optical fiber vibration signal, experimental sample, Extreme Learning Machine（ELM）, recognition rate