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作 者:谢林 Xie Lin
出 处:《起重运输机械》2024年第23期81-86,共6页Hoisting and Conveying Machinery
摘 要:文中研究了一种新的起重机设备启动装置故障检测方法,显著提高了故障检测的精度和效率。详细分析了现有检测方法,并指出其不足之处;继而提出了一种基于采样数据和贝叶斯网络的新方法,详细阐述了数据采集、预处理、故障树构建、故障检测与概率求解的过程,并通过实验验证了该方法的有效性。结果表明:该方法不仅能准确检测故障,还能有效识别故障类型,为起重机的安全运行提供可靠保障。In this paper,a new fault detection method for the starting device of crane is studied,which can significantly improve the accuracy and efficiency of failure detection.The existing detection methods are analyzed in detail,and their shortcomings are pointed out.Then a new method based on sampling data and Bayesian network is proposed,and the process of data acquisition,preprocessing,fault tree construction,fault detection and probability solution is expounded in detail,and the effectiveness of this method is verified by experiments.The results show that this method can not only accurately detect failures,but also effectively identify failure types,providing reliable guarantee for the safe operation of cranes.
关 键 词:起重机 启动装置 故障检测 采样数据 贝叶斯网络 故障树
分 类 号:TH165.3[机械工程—机械制造及自动化]
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