摘要
在无人机飞行过程中,存在大量的异常振动环境,需要对振动心境进行实时报警。利用传统模型进行异常振动信号采集,受到多信号属性纠缠的影响,降低了采集的准确性。提出基于多特征属性集成算法的无人机飞行异常振动信号采集方法。采集大量的无人机飞行异常信号,并计算上述异常信号之间的关联性。对上述信号进行连续小波变换,提取无人机飞行异常信号的特征,并对提取的特征向量进行归一化处理。建立多特征属性集成模型,实现无人机飞行异常振动信号的采集。实验结果表明,利用改进算法进行无人机飞行异常振动信号采集,能够极大的提高采集的准确性。
In the process of unmanned aerial vehicle （uav） flight, there are a large number of abnormal vibration environment, the need for real time alarm vibration state of mind. Using the traditional model of abnormal vibration signal acquisition, affected by multiple signal properties of entanglement, reduces the accuracy of the collection. Based on multiple attributes integration algorithm of unmanned aerial vehicle （uav） flight abnormal vibration signal acquisition method. Collecting a large number of unmanned aerial vehicle （uav） flight abnormal signal and calculating the correlation between the abnormal signal. To continuous wavelet transform of the signal, the characteristics of the unmanned aerial vehicle （uav） flight of anomaly signal, and the normalized processing to extract the feature vector. Multiple attributes integration model, realizes the unmanned aerial vehicle （uav） flight abnormal vibration signal acquisition. The experimental results show that the use of improved algorithm for unmanned aerial vehicle （uav） flight abnormal vibration signal acquisition, can greatly improve the accuracy of the collection.
出处
《科技通报》
北大核心
2014年第7期184-187,共4页
Bulletin of Science and Technology
关键词
无人机
异常振动信号
信号采集
abnormal vibration signals
signal acquisition
