摘要
为提高液压支架故障诊断技术水平,促进综采工作面智能化技术发展,在分析液压支架常见故障的基础上,将常见故障分为3个等级,设计了液压支架状态监测传感器布置方案,针对3个等级故障将传感器输出数据进行深度融合,即数据层融合、特征层融合和决策层融合,提出了一种基于多级数据融合技术的液压支架故障诊断方法。基于AMEsim软件平台建立了故障仿真模型,对该诊断方法进行了有效性验证。结果表明:该方法可实现液压支架故障的有效诊断,诊断结果可靠性高,实时性强,能够有效降低工作面设备故障的检修时间。
In order to improve the fault diagnosis technology of the hydraulic powered supports and to promote the intelligent technology development of the fully mechanized coal mining face,based on the analysis on the common failures of the hydraulic powered supports,the common failures were divided into three grades. A layout plan of the status monitoring and measuring sensors on the hydraulic powered supports were designed. According to the three grade failures,the output data of the sensors should have a deep fusion,including the date layer fusion,the feature layer fusion and the decision layer fusion and the fault diagnosis method of the hydraulic powered supports was provided based on the multilevel data fusion technology. And based on the AMESim software platform,the failure simulation model was established and the effective verification was conducted on the diagnosis method. The results showed that the diagnosis method could realize the effective diagnosis on the failure of the hydraulic powered supports,the diagnosis results could be high reliable,the real time would be high and the diagnosis results could effectively reduce the failure detection and repair time of the equipment applied in the coal mining face.
引文
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