Extrapolation for Aeroengine Gas Path Faults with SVM Bases on Genetic Algorithm

Mining aeroengine operational data and developing fault diagnosis models for aeroengines are to avoid running aeroengines under undesired conditions.Because of the complexity of working environment and faults of aeroengines,it is unavoidable that the monitored parameters vary widely and possess larger noise levels.This paper reports the extrapolation of a diagnosis model for 20 gas path faults of a double-spool turbofan civil aeroengine.By applying support vector machine(SVM)algorithm together with genetic algorithm(GA),the fault diagnosis model is obtained from the training set that was based on the deviations of the monitored parameters superimposed with the noise level of 10%.The SVM model(C=24.7034;γ=179.835)was extrapolated for the samples whose noise levels were larger than 10%.The accuracies of extrapolation for samples with the noise levels of 20%and 30%are 97%and 94%,respectively.Compared with the models reported on the same faults,the extrapolation results of the GASVM model are accurate.

PERFORMANCE ANALYSIS OF MINIMAL PATH FAULT TOLERANT ROUTING IN NOC

Occurrence of faults in Network on Chip(NoC) is inevitable as the feature size is con-tinuously decreasing and processing elements are increasing in numbers.Faults can be revocable if it is transient.Transient fault may occur inside router,or in the core or in communication wires.Examples of transient faults are overflow of buffers in router,clock skew,cross talk,etc..Revocation of transient faults can be done by retransmission of faulty packets using oblivious or adaptive routing algorithms.Irrevocable faults causes non-functionality of segment and mainly occurs during fabrication process.NoC reliability increases with the efficient routing algorithms,which can handle the maximum faults without deadlock in network.As transient faults are temporary and can be easily revoked using re-transmission of packet,permanent faults require efficient routing to route the packet by bypassing the nonfunctional segments.Thus,our focus is on the analysis of adaptive minimal path fault tolerant routing to handle the permanent faults.Comparative analysis between partial adaptive fault tolerance routing West-First,North-Last,Negative-First,Odd Even,and Minimal path Fault Tolerant routing(MinFT) algorithms with the nodes and links failure is performed using NoC Interconnect RoutinG and Application Modeling simulator(NIRGAM) for the 2D Mesh topology.Result suggests that MinFT ensures data transmission under worst conditions as compared to other adaptive routing algorithms.

Gas Path Fault Tolerant Control of Aero-Engine Based on On-Board Model

A fault tolerant control method is proposed in this paper for a turbofan engine gas path degradation through the full flight envelope. A Quantum-behaved Particle Swarm Optimization(QPSO) algorithm is applied to obtain engine inputs adjustments, which contribute to construct off-line performance accommodation interpolation schedules. With a double closed-loop control system structure, command control is corrected based on real-time fault diagnostic results. Simulations indicate that fault tolerant control could reduce thrust and stall margin loss effectively in gas path faults.

A Cascading Fault Path Prediction Method for Integrated Energy Distribution Networks Based on the Improved OPA Model under Typhoon Disasters

In recent times,the impact of typhoon disasters on integrated energy active distribution networks(IEADNs)has received increasing attention,particularly,in terms of effective cascading fault path prediction and enhanced fault recovery performance.In this study,we propose a modified ORNL-PSerc-Alaska(OPA)model based on optimal power flow(OPF)calculation to forecast IEADN cascading fault paths.We first established the topology and operational model of the IEADNs,and the typical fault scenario was chosen according to the component fault probability and information entropy.The modified OPA model consisted of two layers:An upper-layer model to determine the cascading fault location and a lower-layer model to calculate the OPF by using Yalmip and CPLEX and provide the data to update the upper-layer model.The approach was validated via the modified IEEE 33-node distribution system and two real IEADNs.Simulation results showed that the fault trend forecasted by the novel OPA model corresponded well with the development and movement of the typhoon above the IEADN.The proposed model also increased the load recovery rate by>24%compared to the traditional OPA model.

A method of searching fault propagation paths in mechatronic systems based on MPPS model

In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).

PATHS AND CYCLES EMBEDDING ON FAULTY ENHANCED HYPERCUBE NETWORKS

Let Qn,k （n 〉 3, 1 〈 k ≤ n - 1） be an n-dimensional enhanced hypercube which is an attractive variant of the hypercube and can be obtained by adding some complementary edges, fv and fe be the numbers of faulty vertices and faulty edges, respectively. In this paper, we give three main results. First, a fault-free path P[u, v] of length at least 2n - 2fv - 1 （respectively, 2n - 2fv - 2） can be embedded on Qn,k with fv ＋ f≤ n- 1 when dQn,k （u, v） is odd （respectively, dQ,~,k （u, v） is even）. Secondly, an Q,,k is （n - 2） edgefault-free hyper Hamiltonianaceable when n （ 3） and k have the same parity. Lastly, a fault-free cycle of length at least 2n - 2fv can be embedded on Qn,k with f~ 〈 n - 1 and fv＋f≤2n-4.

Hybrid Fault Diagnosis and Isolation for Component and Sensor of APU in a Distributed Control System

This paper addresses the gas path component and sensor fault diagnosis and isolation(FDI) for the auxiliary power unit(APU). A nonlinear dynamic model and a distributed state estimator are combined for the distributed control system. The distributed extended Kalman filter(DEKF)is served as a state estimator,which is utilized to estimate the gas path components’ flow capacity. The DEKF includes one main filter and five sub-filter groups related to five sensors of APU and each sub-filter yields local state flow capacity. The main filter collects and fuses the local state information,and then the state estimations are feedback to the sub-filters. The packet loss model is introduced in the DEKF algorithm in the APU distributed control architecture. FDI strategy with a performance index named weight sum of squared residuals(WSSR) is designed and used to identify the APU sensor fault by removing one sub-filter each time. The very sensor fault occurs as its performance index WSSR is different from the remaining sub-filter combinations. And the estimated value of the soft redundancy replaces the fault sensor measurement to isolate the fault measurement. It is worth noting that the proposed approach serves for not only the sensor failure but also the hybrid fault issue of APU gas path components and sensors. The simulation and comparison are systematically carried out by using the APU test data,and the superiority of the proposed methodology is verified.

基于chirplet path tracing-VMD的变转速信号故障特征提取

针对变分模态分解方法在提取故障特征时处理非平稳信号能力不足的情况,提出基于线调频小波路径追踪(chirplet path tracing)的自适应改进变分模态分解(variational mode decomposition,VMD)方法。该方法首先利用线调频小波路径追踪算法由非平稳信号得到估计转速变化曲线;其次对目标信号进行等角度重采样,通过转速变化曲线将信号从时域转化为角域;再次采用奇异值分解确定角域信号的降噪阶次,当该阶次自适应变分模态分解的分量个数后,对重采样信号进行变分模态分解处理;最后对分解后的各信号分量进行Hilbert包络谱分析,从而提取故障特征。通过对齿轮箱轴承故障进行仿真和实验验证,表明该方法能有效提取变转速信号的故障特征。

Probabilistic Selection of QoS Paths for Improving Survivability in MPLS Networks

Many applications do not fit well with the traditional best effort packet delivery policy of the Internet. These include applications such as Internet telephony and video conferencing which require voice and bulky graphical images transfer. Therefore, the policies of assigning traffic to various service classes and providing service as per the service level agreement of the user with the network provider came into existence. Multi-protocol Label Switching is the backbone of fast switching technology that helps the network service providers to implement these policies. It provides Quality of service oriented reserved paths from the source to the destination for the user’s traffic. Selection of these paths is a cumbersome task, especially when the traffic forecast is totally unknown. Furthermore, nodes and link failures in the Internet worsen the situation. This paper addresses the issue of selecting Label Switched Paths (LSPs) for various traffic demands in the network so that the resultant network has the characteristics like high failure resistance, low LSP demand blocking probability, low impact from the node or link failure, load balancing and low over-all resource utilization. By extensive simulations, the proposed cost function has been compared with the various cost functions mentioned in the literature and it was found to score over them in major aspects.

软件定义网络中操作成本优化的控制路径恢复

软件定义网络(software defined network,SDN)是一种新兴的网络范式,其解耦了控制平面和数据平面,实现了网络管理的灵活性。然而,控制平面的逻辑集中化带来了新的挑战,即在各种故障情况下确保较高的可用性。文章在带内控制平面的前提下,提出一种控制平面恢复方法,该方法重复利用旧的控制路径规则,并建立相应的数学模型;最终提出一种考虑复用控制规则的树形恢复算法,并证明当控制路径以最短路径树的形式部署时,算法的近似度为3。实验结果表明,该方法具有较高的有效性。

An Approach to the Fault Diagnosis and Testability in Analog Circuits at Module Level

In this paper, a module level fault diagnosis method is presented which considers multi-port device or subnetwork as the basic unit. The fault model in this method is quite similar to an actual condition,hence it has practical meaning. The equations of moedule level fault diagnosis are derived, and thetestability problem for module-fault diagnosis is discussed in general. The paper then gives severaltoplolgical conditions for module-fault testubility, which are applicable to a general nonreciprocal network by introducing a generalized independent path.

图书馆高质量发展的现状问题、成因诊断和实现路径

人们对图书馆的黏度正在降低,图书馆发展已出现了“结构问题”,解决“结构问题”对于图书馆的高质量发展至关重要。通过对图书馆发展现状问题及其成因的分析,提出了解决这些问题的策略。研究发现,当前图书馆发展中存在严重的“结构问题”。“结构问题”的产生源于数字阅读破坏了传统的安全框架、新安全框架中缺乏代表性服务、政府管理对图书馆的重视程度下降导致政策缺乏执行力、缺乏强有力的理论支撑以及图书馆“专业”角色的退场。重构纸质阅读文化、提升服务层次、活化政府管理、探索发展理论并回归专业路线等,是解决图书馆“结构问题”的重要举措。

小涵道比涡扇发动机机载气路故障诊断研究综述:边界条件与研究难点

机载气路故障诊断模块是航空发动机健康管理系统的重要组成部分,是推动视情维护发展的关键环节,对于降低发动机维护成本、提高战时出勤率意义重大。为此,聚焦小涵道比涡扇发动机机载气路故障诊断研究,梳理了基于模型的气路故障诊断方法和数据驱动的气路故障诊断方法的发展历程和国内外研究现状,并从机载化的角度阐述了算法的应用和改进思路;罗列了机载气路故障诊断方法的应用需求、问题边界和技术指标,简要提出了研究过程中容易陷入的误区;结合小涵道比涡扇发动机的特点,从数据仿真、运行工况、测量不确定性、故障特征淹没、虚警处置和实时性等角度,归纳总结了气路故障诊断方法在机载化过程中的六大研究难点,并结合现有文献分析了与各研究难点相对应的18种解决思路。对全文进行总结并从算法可解释性、指标快速验证、容错及带故障限时诊断等方面给出了建议与展望。

基于多尺度多路径集成网络的轴承故障诊断方法

针对卷积神经网络参数量大、层数深、泛化性能弱的问题,提出了一种基于多尺度多路径集成网络(Multi⁃scale Multi⁃path Convolutional Neural Network,MCS⁃CNN)的轴承故障诊断方法。首先,提出多尺度卷积块,利用深度卷积和逐点卷积来降低网络参数量、增加网络宽度,有效提取多尺度特征;其次,提出集成块,利用多路径的连接方式将低级和高级特征连接起来以增加网络深度,进而提高模型诊断精度;最后,在凯斯西储大学轴承数据集上进行验证。结果表明,在高噪声和跨负载场景下的故障诊断精度分别可达97.5%和98.25%,在混合场景下相较于现有的诊断方法精度提高了15百分点以上,有效表明了此方法的鲁棒性和泛化性。

基于路径延迟故障序列的硬件木马检测方法

针对基于侧信道信号的硬件木马检测普遍面临的两类问题,即需要黄金芯片和信号测量成本大,提出一种利用路径延迟故障序列的检测方法。基于时序冲突时电路路径产生延迟故障的先后顺序,间接利用路径延迟之间相对大小关系产生芯片检测ID;检测不依赖于黄金芯片,且在大范围的环境变化和工艺偏差下具有稳定性;故障序列在芯片设计阶段仿真获得,无需额外硬件开销。对ISCAS-89基准和AES-128电路实例验证了检测的有效性,其可成功检测插入的两种类型硬件木马。

SRv6中基于故障信息的路径转移策略

针对解决在段路由网络中提供弹性保护以及段路由头中插入过多段标识等问题,提出一种基于故障信息的静态快速路径转移协议。设计快速故障检测机制,改进段路由头存储故障信息;提出路径对比筛选算法与映射段标识策略优化在段路由头中插入的段标识;提出拓扑路径对比策略,源节点判断自身是否存储当前网络拓扑下的转发路径,避免路径收敛计算过程。仿真结果表明,与对比协议相比,该协议在节点压缩率、控制开销和丢包率等网络性能方面均优于对比协议。

面向风电场线路运维的无人机智能巡检系统

风电场线路的运维是保障风电场安全、稳定运行的关键环节。针对现有无人机巡检系统续航能力差、智能化水平不足等问题,提出一种面向风电场线路运维的无人机智能巡检系统。首先,构建巡检系统的巡检设备层、通信层和应用服务层架构;其次,设计无人机避障路径,对故障进行识别,提高无人机巡检的自主飞行和智能化水平;最后,构建面向风电场线路运维的无人机智能巡检系统,主要包括无人机及其搭载设备、机巢以及通信方案的设计。

基于路径重积分特征提取的轴承故障诊断

滚动轴承振动信号呈现非线性和非平稳特征,为充分挖掘滚动轴承振动信号的有效信息,提高故障诊断准确率,提出基于振动信号路径重积分(path signature, PS)的滚动轴承故障信号特征提取方法。首先,对一维故障振动信号进行时延重构,构成有限维路径空间;其次,对路径进行多重迭代积分得到高阶路径积分特征作为故障振动信号初始特征,利用主成分分析(principal component analysis, PCA)对其进行降维得到能充分表征故障信号本征信息的特征;最后,将不同故障信号基于路径重积分的故障特征构成故障特征集,输入到支持向量机(support vector machine, SVM)完成故障的识别和分类。实验结果表明,该方法在公开数据集上的10种故障类型诊断准确率达99.33%,对比其他几种方法,所提方法能快速准确地识别滚动轴承不同故障类型。

全并联AT牵引供电系统雷击故障测距多路径行波算法研究

针对AT变压器和并联结构导致行波传播路径复杂,行波波头性质难以有效识别和行波色散现象,线路频变参数特性导致波速不稳定的问题,提出一种基于多路径行波测距方法。基于上下行电流行波传播的差异性,利用电流相似度识别故障区段。探讨全并联AT牵引网结构对行波传播特性的影响,并对电流、电压行波传播路径进行标定。基于多路径电流、电压行波极性分析,筛选出用于故障测距的多路径行波,以推导出消去波速的测距方程。仿真表明:所提测距方法可以有效识别波头性质,且计算故障距离基本与波速无关,不受牵引网区段长度、结构影响。

基于工况识别与自训练时空图卷积的航空发动机气路故障诊断

航空发动机气路故障模式和运行工况多样,且相互耦合作用,使得同一故障模式在不同运行工况下表现特征存在差异性,增加了气路故障诊断的难度。提出一种基于多层感知器(MLP)工况识别与自训练时空图卷积网络(ST-GCN)模型的航空发动机气路故障诊断方法,利用高度、马赫数、燃油流量及高低压转子转速构建MLP对运行工况进行识别。利用发动机各截面状态监测参数构建图邻接矩阵,构建自训练ST-GCN半监督模型对相应工况下的故障模式进行诊断,采用自适应粒子群优化算法(APSO)对模型超参数进行寻优。采用燃气轮机仿真程序(GSP)生成发动机在动态工况下的状态监测数据,对提出方法的有效性进行验证。结果表明,先进行工况识别,再开展故障诊断,相较于忽略工况直接进行诊断,能够获得更高的故障诊断准确率,达到98.93%。