基于免疫抗体生成算法的电力变压器故障诊断

提出了一种基于人工免疫的抗体生成算法,并将其应用于电力变压器的故障诊断。抗体生成算法仿生生物免疫系统中抗体对抗原的识别与记忆的机理,先对训练样本进行免疫学习和记忆,提取表征样本的有效特征,形成表征样本特征的记忆抗体集,再用最邻近分类法对测试样本进行分类识别。UCI的Iris数据集和电力变压器故障数据的仿真分析结果表明,抗体生成算法能够进行有效的分类,并具有很高的准确率。     

一种开关磁阻电动机功率变换器故障诊断方法

针对现有开关磁阻电动机功率变换器故障诊断方法存在可靠性不高等问题,提出了一种新型的功率管故障诊断方法。该方法以不对称半桥型功率变换器主电路为研究对象,以常见的功率管开路和短路2种故障情况为诊断对象,通过比较母线电流估算值和实测值来判断故障,结合故障相绕组电流实现故障相的识别,必要时通过中断测试来确定故障点。选取电动机空载、低速度和高速度运行等较难实现故障诊断的工况进行了试验分析,结果表明,该方法均能完成故障类型的定性及故障点的准确定位。     

Adaptive variational models for image decomposition

Image decomposition refers to the splitting of an image into two or more components.In this paper,a clean image is separated into two parts:one is the cartoon component,consisting only of geometric structure,and the other is the oscillatory component,consisting of texture.Three parts for noisy image are considered:cartoon,texture,and noise.To better decompose an image,we propose two new variational models.In our models,two adaptive regularization terms are introduced.The two regularization terms are determined by an adaptive function which can discriminate the cartoon and texture of an image automatically.Experimental results illustrate the efectiveness of the proposed models for image decomposition.     

Fractional partial differential equation denoising models for texture image

In this paper,a set of fractional partial differential equations based on fractional total variation and fractional steepest descent approach are proposed to address the problem of traditional drawbacks of PM and ROF multi-scale denoising for texture image.By extending Green,Gauss,Stokes and Euler-Lagrange formulas to fractional field,we can find that the integer formulas are just their special case of fractional ones.In order to improve the denoising capability,we proposed 4 fractional partial differential equation based multiscale denoising models,and then discussed their stabilities and convergence rate.Theoretic deduction and experimental evaluation demonstrate the stability and astringency of fractional steepest descent approach,and fractional nonlinearly multi-scale denoising capability and best value of parameters are discussed also.The experiments results prove that the ability for preserving high-frequency edge and complex texture information of the proposed denoising models are obviously superior to traditional integral based algorithms,especially for texture detail rich images.     

基于BondGraph模型的定性故障诊断方法

研究一种基于键合图（Bond Graph）模型的定性故障诊断方法。根据Bond Graph模型元件中有关参数和变量的特定因果关系,推导出当某观测参量发生变化时,系统内所有可能产生故障的部位,并在此基础上预测每个故障的将来状态,通过与系统实际观测特征比较,在可能产生故障的集合中准确定位故障源。通过实例仿真验证,该方法是便捷有效的。     

非平稳时序循环平稳趋势提取与机械故障诊断

在简单介绍非平稳时序模型周期趋势项提取方法的基础上，提出了机械故障诊断和分析方法，该方法利用旋转机械出现故障以后所呈现的循环平稳特性，使用循环平稳分析方法剔除非平稳时间序列模型中的趋势项，然后建立平稳时序模型，用该模型进行机械故障诊断分析。并运用仿真和实例对方法的正确性进行了验证。     

滚珠丝杠的智能化研究进展

数控机床进给系统的智能化的状态检测、故障诊断以及自修复的能力可以提高数控机床工作的稳定性和可靠性,减少数控机床加工过程中出现的问题。滚珠丝杠是数控机床进给系统的重要组成部分,其精度与性能直接影响着数控机床的加工质量,滚珠丝杠的智能化发展也对数控机床的智能化发展有着非常重要的作用。综述了滚珠丝杠智能化的研究现状,分析了滚珠丝杠的动态测量和静态测量区别及优缺点;概述了基于数学模型和基于人工智能两个方面的故障诊断技术在滚珠丝杠中的应用;阐述了滚珠丝杠弹流润滑的机制以及通过润滑剂添加剂进行自修复的方法,阐明了滚珠丝杠的状态检测与故障诊断技术及自修复技术所存在的问题,展望了滚珠丝杠智能化的发展方向。     

Mooring system diagnosis and structural reliability control for position moored vessels

Early diagnosis and fault-tolerant control are essential for safe operation of floating platforms where mooring systems maintain vessel position and must withstand environmental loads. This paper considers two critical faults, line breakage and loss of a buoyancy element and employs vector statistical change detection for timely diagnosis of faults. Diagnosis design is scrutinised and a procedure is proposed based on specified false alarm probability and estimation of the distribution of the test statistics on which change detection is based. A structural reliability index is applied for monitoring the safety level of each mooring line and a set-point chasing algorithm accommodates the effects of line failure, as an integral part of the reliability-based set-point chasing control algorithm. The feasibility of the diagnosis and of the fault-tolerant control strategy is verified in model basin tests.     

PID和自适应算法在脉搏仿真器振动控制中的应用

以实现远程脉诊的脉象物理再现为切入点,设计了能够模拟人体脉象的脉搏振动器,并对振动信号的控制模块进行了设计,构建可还原真实脉象的脉搏再现系统,使在远处的医生能够身临其境地感受到患者的实际脉搏,从而进行诊断治疗。简单介绍了脉搏再现系统的硬件设计,主要包括基于DSP的脉搏信号发生器和模拟人体桡动脉寸、关、尺搏动的电磁振动器。运用自敏感的思路,通过粘贴在振动梁上的应变片敏感振动位移,作为振动控制的反馈量。基于理论分析,建立了基于音圈电机的脉搏振动原理样机,设计了PID控制算法和截断数据LMS算法,并对脉搏信号进行了开环和闭环实验,通过实验结果的对比和分析知,截断数据LMS算法对脉搏波的控制要优于PID算法。     

基于MultiBoost 的集成支持向量机分类方法及其应用

针对网络故障诊断中的模式识别问题, 提出一种基于多重提升(MultiBoost) 的优化支持向量机集成学习方法. 首先, 利用自适应的荷尔蒙调节遗传算法(HMGA), 对支持向量机基分类器进行建模参数优化; 然后, 通过构建MultiBoost 集成学习方法将多个基分类器集成, 建立以多分类器优化集成为核心的故障诊断系统. 实验结果表明, 所提出的方法在网络故障诊断中, 迭代次数少、建模时间短, 并且能够明显提高故障分类的准确率.