摘要
液压系统作为造纸装备的重要动力与控制单元,其运行可靠性直接影响生产效率与产品质量。由于液压系统运行环境复杂、失效模式多样,传统的故障树分析和马尔可夫模型在处理不确定性与数据稀疏性方面存在局限。本文引入贝叶斯网络方法,对造纸装备液压系统开展可靠性建模与推理研究。首先,分析了液压系统的结构组成及常见失效机理,构建了液压泵、控制阀、液压缸、管路及过滤器等关键部件的贝叶斯网络模型。其次,基于历史运行数据与专家经验构建条件概率表,并通过贝叶斯推理实现故障诊断与概率更新。研究结果表明,该模型能够有效识别关键部件的可靠性贡献度,并在压力异常情况下准确推断泵和阀的失效概率。
As an important power and control unit of papermaking equipment,the operational reliability of the hydraulic system directly affects production efficiency and product quality.Due to the complex operating environment and diverse failure modes of hydraulic systems,traditional fault tree analysis and Markov models have limitations in dealing with uncertainty and data sparsity.This paper introduces the Bayesian network method to conduct reliability modeling and reasoning research on the hydraulic system of papermaking equipment.Firstly,the structural composition and common failure mechanisms of the hydraulic system were analyzed,and Bayesian network models of key components such as the hydraulic pump,control valve,hydraulic cylinder,pipeline and filter were constructed.Secondly,a conditional probability table is constructed based on historical operation data and expert experience,and fault diagnosis and probability update are achieved through Bayesian reasoning.The research results show that this model can effectively identify the reliability contribution of key components and accurately infer the failure probability of pumps and valves under abnormal pressure conditions.
作者
郝江
刘永豹
HAO Jiang;LIU Yongbao(Tongchuan Vocational and Technical College,Tongchuan 727000,China)
出处
《造纸科学与技术》
2025年第8期134-137,共4页
Paper Science And Technology
关键词
造纸装备
液压系统
可靠性分析
贝叶斯网络
故障诊断
papermaking equipment
hydraulic system
reliability analysis
bayesian network
fault diagnosis
