For coal mine production, the role of mechanical bearings is to provide basic support for the transportation of mining coal resources. For coal production, because of its large production capacity and intensive produc...For coal mine production, the role of mechanical bearings is to provide basic support for the transportation of mining coal resources. For coal production, because of its large production capacity and intensive production, mechanical bearings will wear under the influence of high strength and high load in coal transportation, which will lead to bearing failure in the long run, thus affecting the transportation efficiency of coal resources. In order to improve this situation, it is necessary to analyze the wear failure of coal mine mechanical bearings, and to formulate corresponding preventive measures accordingly. Based on this, this paper focuses on the analysis method of mechanical bearing wear failure, and puts forward corresponding preventive measures, in order to effectively improve the current situation of coal mine production.展开更多
故障树分析法(Fault Tree Analysis,FTA),是一种将系统失效形成的原因由总体至部分按树枝状逐级细化的分析方法,可以简化系统结构,降低可靠性及重要度的计算复杂程度。文中以共因失效系统(Common Cause Failure System,CCF)作为研究对象...故障树分析法(Fault Tree Analysis,FTA),是一种将系统失效形成的原因由总体至部分按树枝状逐级细化的分析方法,可以简化系统结构,降低可靠性及重要度的计算复杂程度。文中以共因失效系统(Common Cause Failure System,CCF)作为研究对象,基于FTA方法,给出了系统结构通过各种不同的逻辑门(与门、或门、非门等)转化为故障树的表示方法,并提出了基于故障树的系统可靠性和Birnbaum重要度的隐式替代算法,最后针对串联和并联案例分别进行了系统可靠性及Birnbaum重要度的计算,结果验证了基于故障树方法计算系统可靠性和重要度的可行性。展开更多
为了从复杂的轴承振动信号中提取微弱的故障信息,提出了一种基于局部均值分解(local mean decomposition,LMD)和奇异值差分谱的轴承故障诊断方法。首先通过LMD将非平稳的原始轴承故障信号分解为若干个PF(product function)分量,由于背...为了从复杂的轴承振动信号中提取微弱的故障信息,提出了一种基于局部均值分解(local mean decomposition,LMD)和奇异值差分谱的轴承故障诊断方法。首先通过LMD将非平稳的原始轴承故障信号分解为若干个PF(product function)分量,由于背景噪声的影响,难以从PF分量准确得到故障频率,对PF分量进行Hankel矩阵重构和奇异值分解,相应的得到奇异值差分谱,根据奇异值差分谱理论对某个PF分量进行消噪和重构,然后再求重构后PF分量的包络谱,便能准确地得到故障频率。仿真分析和滚动轴承内圈故障实例很好地验证了提出的改进方法的有效性。展开更多
文摘For coal mine production, the role of mechanical bearings is to provide basic support for the transportation of mining coal resources. For coal production, because of its large production capacity and intensive production, mechanical bearings will wear under the influence of high strength and high load in coal transportation, which will lead to bearing failure in the long run, thus affecting the transportation efficiency of coal resources. In order to improve this situation, it is necessary to analyze the wear failure of coal mine mechanical bearings, and to formulate corresponding preventive measures accordingly. Based on this, this paper focuses on the analysis method of mechanical bearing wear failure, and puts forward corresponding preventive measures, in order to effectively improve the current situation of coal mine production.
文摘故障树分析法(Fault Tree Analysis,FTA),是一种将系统失效形成的原因由总体至部分按树枝状逐级细化的分析方法,可以简化系统结构,降低可靠性及重要度的计算复杂程度。文中以共因失效系统(Common Cause Failure System,CCF)作为研究对象,基于FTA方法,给出了系统结构通过各种不同的逻辑门(与门、或门、非门等)转化为故障树的表示方法,并提出了基于故障树的系统可靠性和Birnbaum重要度的隐式替代算法,最后针对串联和并联案例分别进行了系统可靠性及Birnbaum重要度的计算,结果验证了基于故障树方法计算系统可靠性和重要度的可行性。
文摘为了从复杂的轴承振动信号中提取微弱的故障信息,提出了一种基于局部均值分解(local mean decomposition,LMD)和奇异值差分谱的轴承故障诊断方法。首先通过LMD将非平稳的原始轴承故障信号分解为若干个PF(product function)分量,由于背景噪声的影响,难以从PF分量准确得到故障频率,对PF分量进行Hankel矩阵重构和奇异值分解,相应的得到奇异值差分谱,根据奇异值差分谱理论对某个PF分量进行消噪和重构,然后再求重构后PF分量的包络谱,便能准确地得到故障频率。仿真分析和滚动轴承内圈故障实例很好地验证了提出的改进方法的有效性。