港口机械智能维护的决策支持方法

Decision Support Methods for Intelligent Maintenance in Port Machines

围绕集装箱自动化码头建设智能维护服务平台所需的关键技术,研究港口机械的维护决策支持方法,变被动服务为主动服务,实现智能维护理念。结合港机的机构功能,研究了支持维护模式选择的故障模式和后果分析方法;针对设备状态的不确定性,进行了基于不确定概率的故障树定量分析;为支持实现动态维护决策,研究了港机健康指标的灰色预测建模方法。研究结果和工程实践表明,所提出的决策支持方法能有效提高港口机械的可靠性,为管理者能及时了解设备的运行状态并做出维护决策提供有力的支持。

For developing an intelligent maintenance platform for automatic container terminals, some methods are studied to change passive service to active service and achieve intelligent maintenance. Based on machine mechanisms, potential failure mode and effects analysis is performed to decide maintenance modes. According to the uncertainty of port machine statuses, an improved fault tree quantitative analysis is proposed. Furthermore,a grey forecasting model for machine health indexes is developed to support the dynamic maintenance decision. Study results and engineering practices show that these decision support methods can effectively improve the reliability of port machinery. The methods also provide powerful support for management personnel to be aware of the operation status and make maintenance decisions.