作　　者： ;

机构地区： 广州大学机械与电气工程学院

出　　处： 《计算机仿真》 2019年第11期121-125,共5页

摘　　要： 针对目前机电设备运行状态无线监测存在运营时间长以及成本开销大的问题,提出高速公路机电设备运行状态无线监测方法。将图像可听化技术、数据归一化技术以及主成分分析方法相结合,获取较低维数的主特征向量。利用主特征向量描述系统运行状态,通过余弦相似度评估系统异常程度。基于此对异常程度进行了量化处理,动态调整监测周期,完成机电设备运行状态无线监测。通过具体实验数据,证明所提方法能够有效抑制噪声干扰,降低漏警率,提升整体的运行效率,降低了监测成本开销。 Aiming at the problems existing in the wireless monitoring of the running state of mechanical and electrical equipment at present, a wireless monitoring method of the running state of mechanical and electrical equipment on expressway is proposed. The main eigenvectors with lower dimensions are obtained by combining audibility, data normalization and principal component analysis. The main eigenvector is used to describe the running state of the system and the degree of anomaly is evaluated by cosine similarity. Based on this, the abnormal degree is quantified, the monitoring period is dynamically adjusted, and the wireless monitoring of the running state of mechanical and electrical equipment is completed. Through specific simulation data, it is proved that the proposed method can effectively suppress the noise interference, reduce the alarm leakage rate, improve the overall operating efficiency, and reduce the monitoring cost.

关 键 词： 高速公路 机电设备 运行状态 无线监测

领　　域： []