基于分层模型的配电网故障定位优化算法

针对配电网故障定位实时性要求高及配电网中存在T接点的特点,提出了基于分层模型的配电网故障定位优化算法。该算法充分考虑配电网故障定位和分层模型的特点,采用分段定位原理,通过计算某一区间中间层顶点故障信息状态组合情况,以确定故障所属的更小区间,逐步压缩故障所属区间,实现故障的快速、准确定位。     

基于属性层次模型的柴油机故障证据融合方法

针对证据理论在覆盖率高的柴油机故障诊断中容易出现证据融合误差的问题,提出一种基于属性层次模型的证据融合方法.首先,通过余弦相似度改进目标层权重算法,得到反映目标层不同证据源差异的本质差异因子;然后,采用贝叶斯网络规则改进属性层权重算法,计算相关联的属性层证据源熵值权重;最后,通过故障层次关联特性和CWAA算子修正证据理论融合规则,将不同层次属性权重有效融合,减少系统复杂性引起的诊断误差.在R6105AZLD柴油机台架上的实验结果表明,引入所提方法后的诊断准确度和鲁棒性大幅提高.     

Conditional fault diagnosis of hierarchical hypercubes

The design of large dependable multiprocessor systems requires quick and precise mechanisms for detecting the faulty nodes. The system-level fault diagnosis is the process of identifying faulty processors in a system through testing. This paper shows that the largest connected component of the survival graph contains almost all remaining vertices in the hierarchical hypercube HHC _n when the number of faulty vertices is up to two or three times of the traditional connectivity. Based on this fault resiliency, we establish that the conditional diagnosability of HHC _n (n=2 ^m +m, m≥2) under the comparison model is 3m?2, which is about three times of the traditional diagnosability.     

BPSO优化算法在含DG配电网中的故障诊断研究

针对含分布式电源(distributed generation,DG)的配电网故障检测,传统的故障检测方法容易出现检测精度低、适用性差、容错力低等问题;为此,提出了一种改进的二进制粒子群算法(binary particle swarm optimization,BPSO)进行故障检测,该算法是在BPSO算法的基础上,重新对自适应度值进行定义确保种群寻找到最为准确的最优解,解决BPSO算法容易陷入"早熟"的情况;通过IEEE33节点进行仿真分析,实验结果表明:采用改进的BPSO算法可以有效对故障区段进行定位,验证了改进的BPSO算法的有效性和正确性;同时,当存在信息畸变时,改进的BPSO算法比一般算法具有更强的容错能力。     

改进的基于霍夫曼编码的故障诊断策略

针对电子系统的可测试性设计和故障诊断中测试排序问题,提出了一种改进的优选测试点和故障诊断树生成算法。在相关性矩阵模型的基础上,以平均测试代价最小和平均测试步骤最少为设计目标,采用基于霍夫曼编码的启发式函数优选测试点,提出了一步回溯的与或树启发式搜索算法生成诊断树,并给出了诊断策略优化方法的具体实现步骤。实例表明该方法可行,能以较小的平均测试代价和较少的平均测试步骤隔离系统的故障状态。     

分布式汽车轮胎故障诊断系统设计与实现

轮胎故障诊断系统能够保证轮胎工作在正常的胎压和温度范围内,可以明显提高汽车行驶的平缓性、安全性和舒适性.提出并实现了一种应用传感器技术、微电子技术、嵌入式技术、射频通信技术的分布式轮胎故障诊断系统设计方案、在描述系统组成、硬件结构和软件开发方法的基础上,重点阐述了如何解决系统设计中的低功耗设计和可靠性设计等关键技术.     

A distributed model predictive control (MPC) fault reconfiguration strategy for formation flying satellites

In this paper, an active distributed (also referred to as semi-decentralised) fault recovery control scheme is proposed that employs inaccurate and unreliable fault information into a model-predictive-control-based design. The objective is to compensate for the identified actuator faults that are subject to uncertainties and detection time delays, in the attitude control subsystems of formation flying satellites. The proposed distributed fault recovery scheme is developed through a two-level hierarchical framework. In the first level, or the agent level, the fault is recovered locally to maintain as much as possible the design specifications, feasibility, and tracking performance of all the agents. In the second level, or the formation level, the recovery is carried out by enhancing the entire team performance. The fault recovery performance of our proposed distributed (semi-decentralised) scheme is compared with two other alternative schemes, namely the centralised and the decentralised fault recovery schemes. It is shown that the distributed (semi-decentralised) fault recovery scheme satisfies the recovery design specifications and also imposes lower fault compensation control effort cost and communication bandwidth requirements as compared to the centralised scheme. Our proposed distributed (semi-decentralised) scheme also outperforms the achievable performance capabilities of the decentralised scheme. Simulation results corresponding to a network of four precision formation flight satellites are also provided to demonstrate and illustrate the advantages of our proposed distributed (semi-decentralised) fault recovery strategy.     

The customizable fault/error model for dependable distributed systems

Dependability is a qualitative term referring to a system's ability to meet its service requirements in the presence of faults. The types and number of faults covered by a system play a primary role in determining the level of dependability which that system can potentially provide. Given the variety and multiplicity of fault types, to simplify the design process, the system algorithm design often focuses on specific fault types, resulting in either over-optimistic (all fault permanent) or over-pessimistic (all faults malicious) dependable system designs.A more practical and realistic approach is to recognize that faults of varied severity levels and of differing occurrence probabilities may appear as combinations rather than the assumed single fault type occurrences. The ability to allow the user to select/customize a particular combination of fault types of varied severity characterizes the proposed customizable fault/error model (CFEM). The CFEM organizes diverse fault categories into a cohesive framework by classifying faults according to the effect they have on the required system services rather than by targeting the source of the fault condition. In this paper, we develop (a) the complete framework for the CFEM fault classification, (b) the voting functions applicable under the CFEM, and (c) the fundamental distributed services of consensus and convergence under the CFEM on which dependable distributed functionality can be supported.     

基于分布式全光纤传感器的电机故障诊断系统研究

构造了全光纤振动传感系统,可用于对发电机组,飞机发动机等大型电机设备的健康状况监测。全光纤振动传感系统由于传感臂是光纤,属于无源器件,不会受到电磁干扰,其检测到的信号完全是由电机振动产生,且监测的灵敏度极高。克服了传统的加速度传感器容易受到电磁干扰导致信号检测出错的缺点。用全光纤振动传感器对电机的振动进行实时的采集,基于LabVIEW平台对振动信号进行实时的频谱分析,很容易判断电机是否工作正常。该检测系统结构简单,振动检测灵敏度高,能够很好地应用于电机健康状况的监测。