基于改进增量LE的压缩机故障特征提取方法

提高离心压缩机故障特征提取精度对于后续故障诊断具有重要意义.针对传统增量LE算法处理精度差的问题,分析了参数t对传统增量LE算法特征提取精度的影响,提出了一种改进的增量LE算法.该方法将传统的增量LE算法与cam加权距离相结合,在新增样本点投影过程中通过cam加权距离选取邻域,采用热核形式计算新增样本的权值,由局部保持特性,通过新增样本的近邻来重构其低维嵌入.S-curve仿真数据以及离心压缩机故障数据分析表明:相比于传统的增量LE方法,改进的增量LE方法能有效提高新增故障样本特征提取的精度.     

基于一种流形学习新算法的转子故障数据集降维研究

针对旋转机械的转子故障诊断中原始特征多、难以有效提取振动信号非线性特性的问题,提出一种结合已知故障类别信息进行流形学习降维的新算法—监督邻域保持多项式嵌入(Supervised Neighborhood Preserving Polynomial Embedding,S-NPPE)。利用样本点的故障类别信息,改进转子故障特征数据集中样本点间的欧式距离,重新构造样本点邻接图,再对数据集进行非线性降维处理。先介绍流形学习降维理论,然后给出重构邻接图以及S-NPPE算法的基本步骤,结合转子试验台的不同状态下的振动信号,探讨其在转子故障数据集降维中的应用。     

改进邻域保持嵌入—独立元分析的间歇过程故障检测算法

针对间歇过程数据的非线性和高斯与非高斯混合分布特性导致故障检测效果不佳的问题,提出了基于多向差分邻域保持嵌入—加权差分独立元分析(MDNPE-WDICA)的间歇过程故障检测算法.首先采用Jarque-Bera检验方法(J-B test)将原始数据空间划分为高斯和非高斯子空间;然后,在高斯子空间,将差分策略与NPE算法结合提出MDNPE算法,对高斯空间数据进行维数约简,在保持其局部结构不变的同时处理非线性,并克服传统非线性处理方法由于引入核函数带来的计算复杂的问题;在非高斯子空间,将加权差分策略与IC A算法结合提出WDICA算法,在充分提取数据非高斯信息的同时解决其非线性,并有效利用数据的局部信息;最后,通过贝叶斯推断构建一个新的监测统计量,实现整个间歇过程数据的故障检测.通过青霉素生产过程仿真结果验证了所提算法的可行性和有效性.     

自适应邻域构造流形学习算法及故障降维诊断

针对流形学习算法中近邻构造问题,提出一种自适应邻域构造方法,该方法基于马氏距离计算样本间相似系数,由相似系数均值确定初始近邻数,根据样本高斯核概率密度估计调整近邻数,并将自适应邻域构造方法用于改进的主成分分析联合局部保持投景(principal component analysis-locality preserving projections,简称PCA-LPP)流形学习算法中。通过齿轮箱故障类型识别对其特征降维性能进行验证,结果表明,自适应邻域PCA-LPP方法比传统的k近邻方法及原始无处理的特征识别率都高,可以达到94.67%。     

基于半监督拉普拉斯特征映射的故障诊断

针对有标记故障样本不足和故障数据高维非线性的问题,提出了基于半监督拉普拉斯特征映射（LE）算法的故障诊断模型。该模型运用LE算法,直接从原始高维振动信号中提取低维流形特征,并将其输入到基于LE的半监督分类器,从而识别出机械设备的运行状态。与传统方法相比,该模型能明显提高滚动轴承和齿轮的故障识别性能。     

基于流形学习与一类支持向量机的滚动轴承早期故障识别方法

提出了一种基于流形学习与一类支持向量机的轴承早期故障识别方法。首先提取轴承信号的时域参数构成原始特征样本空间;然后采用基于拉普拉斯特征映射算法(Laplacian eigenmap,LE）的流形学习方法对特征样本进行特征压缩,提取出敏感的故障特征;最后采用一类支持向量机对各状态实现分类识别。利用实测的滚动轴承故障数据对算法进行了验证,并将LE方法与主成分分析（PCA）方法进行了比较,
结果证明该方法可行。     

改进局部保持投影算法及其在故障诊断中的应用

针对局部保持投影(LPP)的邻域参数设置主要依靠经验这一缺点,对LPP邻域参数的设置进行了改进设计,提出了改进局部保持投影算法(ILPP).相比于LPP,ILPP中引入了核密度估计,使得邻域参数会根据数据集的样本密度而自适应的变化,可以更好地对高维数据集的流形结构进行保持.将ILPP用于齿轮典型故障的诊断中,实验结果表明,ILPP可以对不同故障类型数据进行有效区分,实现了故障诊断精度的提高.     

改进局部保持投影算法及其在故障诊断中的应用

针对局部保持投影(LPP)的邻域参数设置主要依靠经验这一缺点,对LPP邻域参数的设置进行了改进设计,提出了改进局部保持投影算法(ILPP).相比于LPP,ILPP中引入了核密度估计,使得邻域参数会根据数据集的样本密度而自适应的变化,可以更好地对高维数据集的流形结构进行保持.将ILPP用于齿轮典型故障的诊断中,实验结果表明,ILPP可以对不同故障类型数据进行有效区分,实现了故障诊断精度的提高.     

基于等距映射与加权KNN的旋转机械故障诊断

针对旋转机械高维复杂故障特征数据难以快速准确辨识的问题,提出一种基于等距映射非线性流形学习与加权KNN(K-nearest neighbor)分类器相结合的旋转机械故障诊断方法.在由时域统计指标和内禀模态分量能量构造的原始特征空间中,首先利用等距映射非线性流形学习算法提取旋转机械故障状态变化的本质特征,随后将提取的低维本质特征输入给加权KNN进行旋转机械的故障模式辨识.通过对齿轮箱的实验数据分析表明,该方法不仅对高维复杂的非线性故障特征具有良好的降维性能,而且故障识别率较之传统方法也明显提高,能够有效识别出高维特征空间的非线性故障特征.     

基于正交局部保持映射的转子故障诊断方法

为了改善故障模式识别的分类性能,提出了一种基于正交局部保持映射算法的多流形特征提取方法。对于高维的非线性数据可以有效地提取低维流形特征向量,并且不会改变数据的内在属性。利用转子的振动信号构造一个高维多征兆矩阵,然后在应用正交局部保持映射将这个高维矩阵进行降维,提取低维特征向量矩阵,映射在可视空间里,从而可以有效地达到故障分类的效果,提高故障诊断的准确率。最后通过实验和数据降维仿真证明了正交局部保持映射算法的有效性和可行性。     

飞行时间质谱仪射频四极杆驱动器的研制

针对自制垂直引入式飞行时间质谱仪（orthogonal extraction time-of-flight mass spectrometer, O-TOFMS）的需要,运用直接数字频率合成 (direct digital frequency synthesis,DDS)技术,研制了射频四极杆的高压射频驱动电路装置。该驱动器频率可调范围为0.5~2 MHz,幅度最高达到1 000 Vp-p。该射频四极杆驱动器（radio frequency quadrupole driver,RFQ Driver）可用于分子离子反应器（molecule ion reactor,MIR）和RFQ驱动,其结构简洁、成本低、性能稳定可靠。     

从光电容积图中提取脉搏率、呼吸率和心率的新方法

光电容积描记图(PPG)是一种利用光学技术无创检测人体心血管脉搏波的方法。PPG信号来源于MIMIC数据库,它含有许多生理信息。本文提出了将集合经验模态分解(EEMD)、倒谱、快速傅里叶变化和过零点检测相结合的方法,从PPG中可靠地估算脉搏率(PR)、心率(HR)和呼吸频率(RR)。首先,将PPG信号通过EEMD分解为有限个固有模态函数(IMF)。因为EEMD有自适应滤波特性,所以估算不同的生理参数时,可以用不同的IMF分量来重构信号。其次,估算脉搏率时,舍去低频含有伪迹的IMF,再通过过零点检测可以得到瞬时脉搏率。然后,估算心率时,用1 Hz~1.67 Hz(60次/分钟~100次/分钟)的IMF来重构信号,再求倒谱,选取反映心脏活动的频带来得到心率。最后,估算呼吸率时,用0.05 Hz~0.75 Hz(3次/分钟~45次/分钟)的IMF来重构信号,然后对呼吸信号求快速傅里叶变化得到频谱图,寻找频谱图中的峰值得到呼吸率。对来自MIMIC数据库的53个成人PPG信号进行了仿真。仿真结果表明使用该综合信号处理方法提取的生理参数与实际生理参数一致,且该方法有运算量小,精确度高的优点(误差不超过1.17%)。     

UPLC-MS/MS测定二苯甲烷二异氰酸酯

建立了二苯甲烷二异氰酸酯（MDI）的超高效液相色谱-串联质谱（UPLC-MS/MS）联用的分析方法。实验用甲醇作衍生试剂,将二苯甲烷二异氰酸酯衍生成二苯甲烷二氨基甲酸甲酯（MDC）,通过测定二苯甲烷二氨基甲酸甲酯来确定二苯甲烷二异氰酸酯的含量。实验采用Waters Acquity BEH C18超高效液相色谱柱,甲醇-0.1%甲酸作为梯度洗脱液,二苯甲烷二氨基甲酸甲酯在1.5 min内与其他化合物进行完全分离,经四极杆质谱选择离子监测模式检测。线性范围为2~100 μg/L,检出限为1 μg/L,相关系数0.999 4。考察了水、甲酸、甲酸铵流动相体系,以及进样量大小对样品的分离效果,发现甲酸流动相体系的分离效果优于其他两种流动相体系,同时发现在进样量大时出现平头峰。并且在优化条件下,对实际样品中游离的二苯甲烷二异氰酸酯进行了测定。     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or sub-systems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

汽车ESC系统DIL/HIL仿真平台设计

全面准确地标定与测试是开发车辆电子稳定控制(electronic stability control,ESC)系统的关键环节。车辆控制过程是典型的强非线性系统,建立精确的车辆模型比较困难,驾驶员模型也很难准确模拟紧急工况下驾驶员的真实反应。在仿真系统中将难以精确建模的液压制动系统、ESC压力调节单元、转向及电子节气门装置采用真实硬件,并在试验平台中嵌入真实驾驶员,基于Matlab/Simulink/dSPACE环境和车辆动力学软件veDYNA,开发硬件在环(hardware-in-the-loop,HIL)和驾驶员在环(driver-in-the-loop,DIL)的仿真试验平台,并在此平台上对所设计的ESC系统进行仿真试验研究。试验结果表明,所设计的DIL/HIL仿真平台可以大幅提高ESC系统的开发效率和测试准确性。     

Effect of the molecular weight on deformation states of the polystyrene film by AFM single scanning

Nanobundles patterns can be formed on the surface of most thermoplastic polymers when the atomic force microscope (AFM)‐based nanomechanical machining method is employed to scratch their surfaces. Such patterns are reviewed as three‐dimensional sine‐wave structures. In the present study, the single‐line scratch test is used firstly to study different removal states of the polystyrene (PS) polymer with different molecular weights (MWs). Effects of the scratching direction and the scratching velocity on deformation of the PS film and the state of the removed materials are also investigated. Single‐wear box test is then employed to study the possibility of forming bundle structures on PS films with different MWs. The experimental results show that the state between the tip and the sample plays a key role in the nano machining process. If the contact radius between the AFM tip and the polymer surface is larger than the chain end‐to‐end distance, it is designated as the “cutting” state that means the area of both side ridges is less than the area of the groove and materials are removed. If the contact radius is less than the chain end‐to‐end distance, it is designated as the “plowing” state that means the area of both side ridges is larger than the area of the groove and no materials are removed at all. For the perfect bundles formation on the PS film, the plowing state is ideal condition for the larger MW polymers because of the chains’ entanglement. SCANNING 35:308‐315, 2013. © 2012 Wiley Periodicals, Inc.     

Rapid one-of-a-kind production

To shorten the product development cycle time and reduce the cost at the same time, which is very critical for the survival of those small and mid-sized one-of-a-kind production (SMOKP) companies, various computer communication, simulation and computer aided engineering and management techniques have been widely used in these SMOKP companies. However, according to our study, the applications of these advanced computer technologies in these SMOKP companies are lack of system integration and synergy, which result in communication errors, reworks, duplications and hence a longer product development lead time and a higher cost. To solve this problem, an inter/intranet based computer aided rapid product development system is presented in this paper. This system consists of a number of inter/intranet based computer models or subsystems for supporting rapid development of a one-of-a-kind product. It also employs a novel concurrent product development strategy called “prototype based incremental product development strategy” and an integrated product data structure called “product production structure”. Some industrial implementations of the proposed system, product development strategy and product data structure are also reported in the paper.     

复合ICA-SVM机械状态模式分类

提出了一种新颖的、基于独立分量分析(ICA)的复合神经网络，用于不同机械状态模式的特征提取。利用支持向量机(SVM)进行最终分类。与通常的基于经验风险最小化(ERM)原理的神经网络方法相比，基于结构风险最小化(SRM)原理的支持向量机分类方法具有更好的推广能力。而借助多个独立分量分析网络，隐藏于多通道振动观测信号中的不变特征得到有效提取，从而实现了支持向量机分类器在分类能力和推广性两者间的合理平衡。     

The efficacy of back propagation neural network with delta bar delta learning in predicting the wear of carbide inserts in face milling

Face milling is a process predominantly affected by dynamic variation of cutting forces, thermo-mechanical shocks and vibration leading to catastrophic tool failure along with gradual wear of the inserts. Keeping in view the industrial importance of this process, it is necessary to devise suitable methods to predict in advance the onset of tool failure without grossly impairing the machining set-up and the job. Hence, the applicability of back propagation neural network with delta bar delta learning rule for faster convergence has been studied with the above objective. The multi sensor based tool condition monitoring strategy shows that the learning rate adaptation scheme combined with the selection of suitable process parameters drastically reduces the training time of the artificial neural network without dispensing with the prediction accuracy.     

血清AFP、CA199、GGT、ALP联检肝癌早期诊断价值

目的:探讨甲胎蛋白(AFP)、糖类抗原199(CA199)、谷氨酰转肽酶(GGT)和碱性磷酸酶(ALP)单独或联合检测对原发性肝癌(PHC)的早期诊断价值。方法:本研究为回顾性研究,筛选2016年-2019年本院87例原发性肝癌(PHC)患者、105例慢性乙肝患者及104例健康志愿者,收集不同组首次入院和体检外周血检测数据和其他临床资料。比较各血清指标在组间差异性,分析了血清学指标与入组PHC临床分期和病理分型的相关性,进一步利用ROC曲线法分析血清指标单项与联合诊断的灵敏度、特异度。结果:AFP、CA199、GGT、ALP检测均值在PHC组均明显高于慢乙肝组和健康体检组。AFP阳性检测值与PHC临床分期(r=0.9536)和病理分型(r=0.525)呈正相关性。AFP诊断PHC灵敏度和特异性分别为60.87%和77.97%、精准度AUC为0.726。联合四项指标检测灵敏度、特异度和AUC分别为75.36%、65.64%、0.806。结论:AFP、CA199、GGT、ALP四项指标联合检测可提高原发性肝癌早期诊断的准确率,操作性强且易于推广。