首页|基于混合故障字典的高速公路机电设备故障定位方法研究

基于混合故障字典的高速公路机电设备故障定位方法研究

Fault Location Method of Expressway Electromechanical Equipment Based on Hybrid Fault Dictionary

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针对传统的高速公路机电设备故障定位方法存在故障诊断时间较长,虚警率、误检率和漏检率难以达到用户要求的问题,提出基于混合故障字典的高速公路机电设备故障定位方法.通过多维度传感器无线射频识别技术建立高速公路机电设备器件故障射频波束信息模型,获取高速公路机电设备故障数据.建立两部字典,利用第一部故障字典估算高速公路机电设备故障信息数据与各种故障模式类型之间的中心距离,按照距离远近判断要估计的决策函数类型,根据预定的设计算法,运用第二部故障字典的决策机制精确定位高速公路机电设备故障.试验结果表明,基于混合故障字典的高速公路机电设备故障定位方法能够确保虚警率为0,误检率和漏检率低于1%,比传统检测时间缩短了 50%以上.
Due to the fact that the traditional fault location method of expressway electromechanical equipment has a long fault diagnosis time,and the false alarm rate,false detection rate and missed detection rate are dif-ficult to meet the requirements of users,a fault location method of expressway electromechanical equipment based on hybrid fault dictionary is proposed.Through the multi-dimensional sensor radio frequency identifica-tion technology,the radio frequency beam information model of expressway mechanical and electrical equip-ment device fault is established to obtain the expressway mechanical and electrical equipment fault data.Two dictionaries are established.The first fault dictionary is used to estimate the central distance between the ex-pressway electromechanical equipment fault information data and various fault mode types.The decision func-tion type to be estimated is judged according to the distance.Based on the predetermined design algorithm,the decision mechanism of the second fault dictionary is used to locate accurately the expressway electrome-chanical equipment fault.The experiment results show that the fault location method of the expressway electro-mechanical equipment based on the hybrid fault dictionary can ensure that the false alarm rate is 0,the false detection rate and missed detection rate are less than 1%,and the detection time is reduced by more than 50%compared with the traditional detection time.

hybrid fault dictionaryhighwayelectromechanical equipmentequipment faultfault diagnosis

张弛

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北京公科飞达交通工程发展有限公司,北京 100088

混合故障字典 高速公路 机电设备 设备故障 故障诊断

2024

大连交通大学学报
大连交通大学

大连交通大学学报

CSTPCD
影响因子:0.258
ISSN:1673-9590
年,卷(期):2024.45(1)
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