双树复小波包和ICA用于滚动轴承复合故障诊断

针对滚动轴承复合故障信号特征难以分离的问题,提出将双树复小波包变换和独立分量分析(independent component analysis,简称ICA)结合的方法应用到滚动轴承复合故障诊断中。首先,利用双树复小波包变换将复杂的、非平稳的复合故障信号分解为若干不同频带的分量;其次,引入ICA对各个分量所组成的混合信号进行盲源分离,从而尽可能消除频率混叠;最后,对从混合信号中分离出来的独立信号分量进行希尔伯特解调,即可实现对复合故障特征信息的分离和故障识别。试验结果表明,该方法可以有效地分离和提取轴承复合故障的特征频率,验证了方法的可行性和有效性。     

CEEMD与FastICA结合的故障特征提取方法

针对滚动轴承故障特征信息难以分离的问题,提出了互补式集成经验模态分解(Complementary Ensemble Empirical Mode Decomposition,CEEMD)与快速独立分量分析(Fast Independent Component Analysis,Fast ICA)结合的故障特征提取方法。首先将振动信号进行CEEMD分析,分解成不同尺度的固有模态分量(Intrinsic mode function,IMF);然后通过敏感度评估算法对分解信号进行重组,并利用Fast ICA对其进行降噪处理;最后对Fast ICA分离的信号进行Hilbert包络谱分析,获取故障特征信息。将此方法应用于滚动轴承振动信号故障分析,实验证明了所提方法的有效性。     

奇异值分解与LMD结合的滚动轴承故障诊断研究

针对滚动轴承故障信号具有的非线性和非平稳性,其故障特征难以提取的问题,提出一种奇异值分解(SVD)和局部均值分解(LMD)相结合的滚动轴承故障特征提取和诊断方法。首先,将轴承故障信号进行LMD分解得到若干PF分量;然后选取和原始信号相关度较大的PF分量,利用奇异值序列来构造其故障特征向量;最后,将得到的故障特征向量作为学习样本输入到支持向量机(SVM)中,对故障类型进行分类和识别。实验结果表明,LMD和SVD结合的故障特征提取方法,能有效提取滚动轴承不同状态下的故障特征,对不同故障状态做出准确分类。     

齿轮箱复合故障振动信号的形态分量分析

在改进形态分量分析系数阈值去噪方法的基础上,将其用于齿轮箱复合故障振动信号的分析。齿轮箱中的齿轮出现局部故障时,其振动信号中往往出现调幅调频成分;而滚动轴承出现局部故障时,其振动信号中往往出现周期性瞬态冲击成分。调幅调频成分的幅值变化相对缓慢,可看作信号中的光滑部分;而瞬态冲击成分的幅值变化较快,可看作信号中的细节部分,故可依据此形态差异实现二者的分离。采用形态分量分析方法将齿轮箱复合故障振动信号分解为包含滚动轴承局部故障信息的冲击分量、包含齿轮局部故障信息的谐振分量及残余分量,根据冲击分量和谐振分量的Hilbert包络解调谱分别诊断滚动轴承和齿轮的局部故障。对齿轮箱复合故障振动信号的分析结果表明,该方法可有效分离滚动轴承与齿轮的故障特征,且效果要优于经验模态分解(Empirical mode decomposition,EMD)方法。     

基于ITD-KICA盲分离降噪的滚动轴承故障特征提取

滚动轴承在实际工况下的故障信号和故障信息常常淹没于噪声中,传统的故障特征提取方法很难有效提取出轴承故障特征信息。因此,采用时间固有尺度分解(ITD)和核独立分量分析(KICA)相结合的信噪盲分离分析法降噪。对轴承信号进行ITD分解,根据相关系数将分解得到的PRC分量重组以及构建虚拟噪声通道,利用KICA解混实现故障信号与噪声信号分离,对信噪分离后的有效分量信号做包络谱的分析。通过仿真及轴承故障实验分析和对比表明,该方法能有效提取轴承的故障特征。     

基于AIF和TT的滚动轴承复合故障诊断

针对滚动轴承复合故障模式下的微弱特征难以提取的问题,提出了基于自适应迭代滤波（adaptive iterative filtering,简称AIF）和改进的时时变换（time?time transform,简称TT）的滚动轴承复合故障诊断方法。首先,采用AIF将信号分解,得到一系列本征模态分量,并以最大相关峭度作为评价准则,筛选出其中的特征分量,实现滚动轴承复合故障振动信号的特征分离;其次,利用改进的时时变换方法对特征分量进行降噪,增强特征分量的冲击特征;最后,对降噪的特征分量进行包络谱分析,提取故障特征频率,实现滚动轴承故障模式的精确判别。仿真实验和故障诊断实例表明,该方法可以有效提取滚动轴承复合故障模式下的微弱特性信息。     

基于ICA和小波变换的滚动轴承故障诊断方法研究

提出了结合独立分量分析(ICA)和小波变换进行滚动轴承故障诊断的方法。在设计的系统平台上,首先对冲击脉冲信号进行预处理,使信号较好地满足独立分量分析的前提条件。然后,应用独立分量快速算法分离故障轴承的冲击脉冲信号,通过小波快速算法完成信号重构,实现滚动轴承故障的识别。实验结果表明,利用独立分量分析方法提取的故障状态特征向量与小波快速算法相结合可以有效、准确地识别滚动轴承的故障信号。     

基于SVD与改进EMD的滚动轴承故障诊断

针对经验模态分解(EMD)存在的模态混叠问题,提出一种奇异值分解(SVD)和改进经验模态分解相结合的信号分析新方法。该方法首先对故障信号进行SVD降噪,以消除随机干扰,再根据信号特征加入高频谐波信号并进行EMD进行分解,有效地减少模态混叠现象,最后对EMD分解得到的高频本征模态分量(IMF)进行代数运算得到故障冲击成分,经Hilbert包络分析,提取出故障特征信息。仿真信号分析了这种方法的实施过程,并将该方法成功运用于滚动轴承内圈和外圈故障的诊断中。实验结果证明:该方法能够有效地提取滚动轴承故障特征信息,实现故障诊断。     

基于全矢谱时间固有尺度分解和独立分量分析盲源分离降噪的滚动轴承故障特征提取

结合盲源分离技术和全矢谱技术的各自优势,提出一种同源双通道信噪盲源分离法。首先采用时间固有尺度分解（ITD）和独立分量分析（ICA）相结合的分析法降噪,对同源双通道的轴承信号进行ITD分解,根据相关系数准则将分解得到的PRC分量进行重组作为ICA输入矩阵,再采用FastICA解混,实现故障信号与噪声信号的分离;其次采用全矢谱技术对信噪分离降噪后的双通道有效分量信号进行全矢信息融合,做全矢谱分析。滚动轴承故障实验对比分析表明了该方法的有效性。     

LMD-ICA联合降噪方法在滚动轴承故障诊断中的应用

针对经典独立分量分析（ICA）只能应用于观测源数不少于信号源数的超定盲源分离问题,提出局部均值分解和ICA相结合的欠定盲源分离新方法。该方法将采集的单通道振动信号进行局部均值分解,基于互相关准则对分解的分量进行重组,构建虚拟噪声通道;将虚拟噪声通道与振动信号作为盲源分离的信号输入,采用基于负熵的FastICA算法实现信号源和噪声的分离,从而达到降噪目的。将该方法应用于滚动轴承故障信号,频谱分析结果表明,该方法处理后的信号中噪声得到一定程度滤除,频谱中毛刺更少,故障特征频率更加明显,有利于故障特征的提取,实验分析证明了该方法的有效性。     

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.     

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.     

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。     

同位素稀释质谱法测定贻贝中多氯联苯的国际比对研究(CCQM-P67)

A method developed to participate the pilot study of international comparison CCQM-P67 was introduced. Isotope dilution mass spectrometry (IDMS) was used in the detection of five PCB congeners in freeze-dried muscle tissue. Soxhlet Extraction is used for extraction of mussel, duplicate clean-up of GPS and SPE column were used, C-13 labeled PCB congeners were added as internal standard to avoid the error from sample preparation and diction. High resolution Mass spectrometer was used to give good result of detection.