Fault tree analysis of feeding control system for computer numerical control heavy-duty horizontal lathes with multiple common cause failure groups

The lathes are basic machine tools for manufacturing cylindrical parts. In recent years, the DLseries computer numerical control(CNC) heavy-duty horizontal lathes(HDHLs) have been widely used in the transportation, energy and aviation industries. High availability of the CNC heavy-duty lathes is demanded to guarantee the efficiency and benefit of these manufacturing industries. As one of the key subsystems of the HDHLs, the feeding control system is studied in this paper on reliability modeling and reliability analysis. The fault tree analysis(FTA) method is used for reliability modelling of the feeding control system. Considering the multiple common cause failure groups(CCFGs) existing in the system, a modified beta factor parametric model is introduced to model the common cause failure(CCF) in system. The reliability of feeding control system is then obtained and the effect of CCF on the reliability of the whole system is studied as well.     

Binary decision diagram quantitative analysis method based on fuzzy set theory

A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of the results. However, due to various types of uncertainties in reliability data, we cannot obtain precise failure probabilities. In order to accurately quantify the certainties and obtain much more reliable results, we use BDD method based on fuzzy set theory for reliability quantitative analysis. In this regard, we take W-axis feeding system of heavy-duty computer numerical control(CNC) machine as a project example and adopt fuzzy BDD quantitative analysis method to analyze its reliability. The analysis results(aided by computer calculation)illustrate the effectiveness of the method proposed in this paper.     

Numerical simulation to reliability analysis of fault-tolerant repairable system

In the traditional method for the reliability analysis of fault-tolerant system, the system structure is described by means of binary decision diagram (BDD) and Markov process, and then the reliability indexes are calculated. However, as the size of system augments, the size of state space will increase exponentially. Additionally, Markov approach requires that the failure and repair time of the components obey an exponential distribution. In this study, by combining dynamic fault tree (DFT) and numerical simulation based on the minimal sequence cut set (MSCS), a new method to evaluate reliability of fault-tolerant system with repairable components is proposed. The method presented does not depend on Markov model, so that it can effectively solve the problem of the state-space combination explosion. Moreover, it is suitable for systems whose failure and repair time obey an arbitrary distribution. Therefore, our method is more flexible than the traditional method. At last, an example is given to verify the method.     

民航运输航空器着陆阶段偏出跑道事件分析模型

为了克服故障树分析方法只能描述正常和故障两种状态的缺陷,利用故障树方法的逻辑分析优势,以及贝叶斯网络描述多态事件和计算概率的功能,建立了基于故障树和贝叶斯网络相融合的航空器着陆偏出跑道事件分析模型,提出了故障树与贝叶斯网络之间的转换算法求解该模型.根据1996—2010年中国民航着陆偏出跑道事件的数据,确定了着陆航空器偏出跑道的主要原因,并按重要程度进行了排序.研究结果表明:积水、反喷或减速板故障、复杂气象条件、驾驶术欠缺、前轮转弯卡阻、夜航或受灯光不利影响、对机组资源管理失效、积冰积雪是导致着陆偏出跑道的主要风险因素,其后验概率均大于0.3;应针对主要风险因素,制定针对性预防措施.      

TY180推土机工作装置液压系统常见故障及诊断

分析了TY180推土机工作装置液压系统的工作原理、组成结构及其典型故障,总结了常见故障的现象及其形成原因,提出了相应的排除措施;运用因果分析法、故障树分析法等故障诊断方法,绘制了推土铲刀不动或上升无力故障的鱼骨图和松土器油缸不动故障的故障树,明确了这2种故障的成因与相应结果之间的逻辑关系.实践证明:运用上述方法能够较快...     

基于故障树的船舶电站可靠性、维修性研究

应用可靠性工程中的故障树分析法解决船舶大型复杂电气控制系统普遍存在的维修、管理难的问题,具有很强的使用价值．将故障树分析法应用于船舶电站自动控制系统,创建了船舶电站自动控制系统的故障树,编写出用户程序,完成对船舶电站自动控制系统故障树的定性、定量分析,编写出实用树、故障查找流程图等船舶电站自动控制系统维修、保养指南．     

基于故障树模型的高速公路机电系统性能评价

采用故障树分析法,以故障率（顶上事件的发生概率）为表征指标,可建立高速公路机电系统使用性能分析模型．提出基于故障树的高速公路机电系统性能评价方法,给出高速公路养护需重点检测的关键环节。这种方法亦可推广应用于高速公路机电系统运营期使用性能的评价当中,为系统养护中故障点的追溯提供具体可行的方案,从而大大减少系统养护诊断的工作量,提高监控系统的养护效率及针对性。     

汽车故障诊断专家系统的设计与实现

针对目前汽车故障的复杂多样以及无法实时诊断的情况,提出了基于规则的汽车故障诊断专家系统。该系统运用汽车故障诊断专家的知识填充知识库,运用人工智能的理论,以产生式规则作为知识的表示形式,采用基于故障树的分析方法,运用正向推理,达到对汽车基本故障诊断的目的,实现对汽车实时故障的诊断。     

基于Sugeno模糊模型的CNC机床故障诊断方法

通过将Sugeno模糊模型用于数控机床故障诊断系统的方式,实现了对各个诊断专家诊断结果的模糊综合,消除了诊断专家诊断结论的随意性,保证诊断结论的准确.利用此方法基于诊断专家系统技术可以实现对数控机床的自动诊断,诊断结果准确可靠.     

基于动态贝叶斯网络的列控中心可靠性及可用性评估

为解决共因失效、动态失效及恢复机制等问题,本文基于动态贝叶斯网络对联锁车站和中继站列控中心可靠性及可用性进行评估.在分析列控中心系统结构的基础上构建系统动态故障树,并将动态故障树转化为动态贝叶斯网络,实现结构学习和参数学习.通过动态贝叶斯网络正向推理得到两种类型列控中心可靠度和可用度并进行比较分析.通过动态贝叶斯网络反向推理得到列控中心系统薄弱环节.研究系统敏感性因素并讨论恢复机制对系统可靠性及可用性的影响.结果表明：考虑共因失效的联锁车站和中继站列控中心的稳态可用度分别为0.999 960和0.999 977;电源及驱动采集单元为系统薄弱环节,需要重点关注.该方法能有效提高列控中心智能维修维护水平.     

Bayesian Network Based Approach for Diagnosis of Modified Sequencing Batch Reactor

Wastewater treatment is a complicated dynamic process affected by microbial, chemical and physical factors. Faults are inevitable during the operation of modified sequencing batch reactors(MSBRs) because of the uncertainty of various factors. Abnormal MSBR results require fault diagnosis to determine the cause of failure and implement appropriate measures to adjust system operations. Bayesian network(BN) is a powerful knowledge representation tool that deals explicitly with uncertainty. A BN-based approach to diagnosing wastewater treatment systems based on MSBR is developed in this study. The network is constructed using the knowledge derived from literature and elicited from experts, and it is parametrized using independent data from a pilot test.A one-year pilot study is conducted to verify the diagnostic analysis. The proposed model is reasonable, and the diagnosis results are accurate. This approach can be applied with minimal modifications to other types of wastewater treatment plants.     

基于二元决策图的系统可靠性模块分析方法

为了克服二元决策图方法分析故障树所存在的不足,提出了基于二元决策图的模块方法分析系统可靠性。采用线性时间算法将故障树分解成相互独立的子故障树,然后用二元决策图方法对子故障树进行分析,递归综合相互独立子故障树的求解结果,得出整个系统的可靠性。基于二元决策图的模块分析方法克服了故障树分析与二元决策图方法存在的不足,适用于大型、复杂系统的可靠性分析。     

基于Petri 网模型的铁路快捷货运产品可靠性评价

为准确评价及预测铁路快捷货运产品的可靠性,在全面分析铁路快捷货运产品可靠性影响因素的基础上,建立用于产品可靠性评价的故障树模型,并采用下行法求取故障树的最小割集;结合Petri 网建模方法与故障树基本理论,将产品故障树转化为 Petri 网仿真模型,并证明两者的等价性;利用Matlab 仿真软件进行基于关联矩阵的Petri 网模型求解,并以北京-上海间特快货物班列为例,得到该产品的可靠度及故障因素重要度排序.实证结果显示,应用Petri 网模型来求解产品可靠性评价问题,不仅能够有效提升求解过程的效率,而且准确易行.研究成果可以为提高铁路快捷货运产品可靠性和市场竞争力提供科学依据和必要支撑.     

基于贝叶斯网络组合模型的公交驻站时间预测

公交驻站时间是公交行程时间的主要组成部分,其预测精度直接影响智能公交系统中公交信息发布的准确性.为了提高公交驻站时间的预测精度,提出一种基于贝叶斯网络的组合预测模型,它由反向传播神经网络和径向基函数神经网络模型组成.首先利用两种神经网络模型预测公交驻站时间;然后利用改进后的等宽数据离散方法,将两种神经网络的预测结果和观测的驻站时间数据离散后用于贝叶斯网络学习;最后通过贝叶斯网络推理得到驻站时间组合预测结果.实例分析表明,贝叶斯网络组合模型驻站时间预测结果的误差指标均优于单一模型,证明其可有效提高单一模型的预测精度.     

普通机床的数控改造策略

本文以西门子802D数控系统为例,介绍数控机床改造时需要进行的准备、数控系统和伺服系统选择以及电气控制系统设计改造等内容。     

故障树分析在计算机联锁系统中的应用

应用故障树分析方法对计算机联锁系统进行了可靠性的分析,用故障树讨论了其故障的原因与影响的逻辑关系,并提出了进一步的改进措施及建议.     

Transformer Fault Analysis Based on Bayesian Networks and Importance Measures

Complex environment stresses bring many uncertainties to transformer fault. The Bayesian network(BN) can represent prior knowledge in the form of probability which makes it an effective tool to deal with the uncertain problems. This paper established a BN model for the transformer fault diagnosis with practical operation dataset and expert knowledge. Then importance measures are introduced to indentify the key attributes which affect the results of transformer diagnosis most. Moreover, a strategy was proposed to reduce the number of attribute in transformer fault detection and the resource cost was saved. At last, a diagnosis case of practical transformer was implemented to verify the effectiveness of this method.     

汽车零部件制造数控装备可靠性评估与故障分析

通过对大量生产现场数据的统计分析,应用故障频次主次图和故障比重比主次图等方法,对当前汽车零部件制造常用的一种国产数控机加装备进行全面可靠性评估。对数控装备的故障部件进行分类,找出了故障修复和可靠性改进的主要部件。     

一种三坐标数控铣床CNC系统软件的设计

本文介绍了一种基于PC386微型机的新型三坐标微机数控铣床CNC系统软件的设计方法。提出了系统软件的结构，着重介绍了插补算法、刀具补偿、尖角过渡仿真、实时加工和刀具轨迹显示，同时简要介绍了加工程序的解释与分析。     

宏程序在数控铣削加工中的应用

目前,随着数控技术的发展,数控机床已经成为我国在用机床的主流.在数控铣削中,对于非圆曲线、曲面、圆角、倒角的加工,当机床内存容量较小时,如何使加工程序变得简洁,对现实加工来说,有着很重要的实际意义.相对普通程序,由于宏程序编程可以使用类似计算机编程语言中的函数变量,使得程序编制更加容易和灵活.本文通过实例介绍数控铣削加工编程中运用宏程序来解决有规则的曲线、曲面铣削加工问题.