纺纱锭子动态特性的研究

用近代非线性动力学理论分析了纺纱锭子的动态特性。用数值方法得到转子系统在某些参数区域内的轴心轨迹图、Poincare映射图和分岔图等。讨论了系统各种形式的倍周期、拟周期和混沌运动。分析结果为定性地改善转子系统的稳定运行状态,提供了理论依据。     

锭子振动测试的数学模型研究

锭子在纱线卷绕时的振动问题不仅与锭子本身的振动有关,还与纱线卷绕时的纱线作用力有关,本文以纱线在高速卷绕时锭子的振动为研究对象。建立了锭子振动的力学模型,并以此为依据设计锭子振动测试装置。     

高速纺纱锭子两支撑孔加工专用夹具设计与分析

以纺纱锭子中结合件为研究对象,基于液相静压夹紧技术原理,设计了两支撑孔加工的伪液相静压夹具,包括自定心夹紧机构和自适应辅助夹紧机构,并利用有限元分析软件,采用正交分析法,对自定心夹紧机构中的自定心夹紧元件进行了变形分析与几何结构的优化设计。研究结果为提高纺纱锭子两支撑孔的位置加工精度和保障纺纱锭子高速运转时的动态性能提供了技术基础。     

独立分量分析在自动机振动信号处理中的应用

自动机工作中的冲击响应多处在低信噪比和被噪声干扰的复杂振动信号中,寻求一种能在多干扰、噪声强的复杂振动信号中去除干扰信号和噪声的方法,可以提高速射武器自动机故障诊断准确率。研究了独立分量分析(independent component analysis,简称ICA)的基本理论,采用基于改进粒子群的独立分量分析算法模拟生成了仿真信号,获得了比较理想的分离效果。经实际射击数据验证了该方法的可行性,这种基于改进粒子群的独立分量分析算法在自动机结构振动信号处理方面具有较好的效果。     

独立分量分析在声发射信号处理中的应用

介绍了独立分量分析的基本原理和以峭度为目标函数的独立分量提取算法的梯度算法,并通过实例说明了利用独立分量分析对声发射信号进行分析的方法,验证了独立分量分析技术在声发射信号分析方面的优越性和实用性,表明独立分量分析在声发射信号处理等领域有着巨大的应用潜力。     

五月柱圆管编织机锭子运动学分析及其轨迹优化

五月柱圆管编织机的不合理锭子运动轨迹是限制其稳定运行的主要因素。建立编织机锭子运动的数学模型并分析其运动特性,得出锭子在轨道承受急剧变化的载荷是引起其振动的主要原因。本研究拟采用组合曲线对单个锭子运动轨迹进行优化,发现采用修正梯形运动规律曲线轨迹和摆线运动修正等速运动规律曲线轨迹的锭子类跃度均小于采用‘∞’字形运动轨迹锭子的类跃度。以载荷波动量最小化为目标,推得轨迹为等圆相切曲线时锭子运动的类跃度最小。实验研究结果表明,采用等圆相切曲线轨迹的编织机振动及噪声得到有效降低。     

独立分量分析在混叠通信信号分离中的应用

本文采用FASTICA算法,实现对混叠通信信号的盲分离.仿真结果表明,本算法具有分离效果好,收敛速度快,无需动态参数的特点,基本实现了对混叠通信信号的实时盲分离.     

空间滤波和独立成分分析在速度测量中的应用

介绍一种利用空间滤波、独立成分分析处理两相流信号的方法,首先研究电容传感器的空间滤波效应,然后介绍独立成分分析的基本原理,并利用此方法对两相流信号进行处理;根据傅立叶变换确定传感器信号的带宽;根据带宽求出固体速度.最后给出对实际测量信号的处理结果.     

LabVIEW及其在测试技术中的应用

介绍了构建虚拟仪器的图形化编程语言——LabVIEW的功能特点、程序设计结构特色等,并通过信号仿真和信号时域分析两个实例简要说明其在测试技术中的应用。     

独立分量分析在直升机齿轮箱故障早期诊断中的应用

齿轮箱早期的故障信号往往十分微弱 ,信噪比低 ,这大大限制了已有诊断方法在早期诊断中的应用 ,因此如何获取真实的振动信号是提高齿轮箱早期故障诊断质量的关键 ,独立分量分析 (ICA)为此提供了一种新的思路。文中研究了ICA在齿轮箱故障早期诊断中的应用 ,首先分析了齿轮箱的混合振动信号模型 ,然后针对具体的轴承故障进行了实验 ,并使用快速ICA算法分离出轴承的振动信号 ,再将其功率谱与原始振动信号的谱相比较 ,结果表明ICA更易于实现故障的早期诊断 ;最后提出了进一步的研究建议。     

工业线阵CCD相机系统测试与噪声评估

为了快速评价工业线阵CCD相机质量,本文选择信噪比为评价因子,建立了测试系统,研究了基于相机输出图像测试相机噪声的方法。分析了线阵CCD相机的噪声,建立了一个基于固定模式和随机噪声的信噪比计算模型,并分析了相关双采样(CDS)过程对电源噪声的影响。设计了一套适于工业场所的相机快速信噪比测试系统,结合理论分析数据和实际测试图像数据,提出了仅通过输出的8bit图片计算各噪声参数的方案。最后,对测试系统引入的光源不均匀性噪声进行了讨论,并证明该实验平台光源符合工业标准EVM1288要求。实验结果表明:当相机模数(AD)转化设置为8.7dB时,输出信噪比可达44dB;若排除光源干扰,输出信噪比可达46dB。该方案简便快捷,满足工业现场对相机信噪比评估的要求。     

机床噪声及控制对策

从人-机-环境系统角度出发分析机床噪声的特点和危害,描述了机床噪声的频谱特点,从机械系统和切削加工工艺两方面提出了降低机床噪声的方法。     

指数加权主元分析法及其在故障诊断中的应用

在研究主元分析法(PCA)理论的基础上,提出指数加权主元分析(EWPCA)算法。这种算法通过不断更新相关矩阵来实时监视动态生产过程中的超时趋势和设定点改变等状态。实验结果表明,该方法可以较好地反映生产过程中的实时信息,并能有效检测出系统的异常状况,具有广阔的实际应用前景。     

一种改进的快速独立分量分析方法在信噪分离中的应用

通常在信号分析过程中,由于测试环境存在诸多的干扰因素,使得故障信号中存在大量的噪声信息,因此,在提取信号中的故障特征之前,需要对其进行信噪分离,以确保提取到有用信息。在研究传统独立分量分析方法的基础上,提出了改进的快速独立分量分析方法。试验表明,采用改进的快速独立分量分析方法不仅大大提高了信噪分离的效率,而且能有效地提取信号中的故障特征。     

封头无胎冷旋压机机架的有限元分析及优化设计

在对封头无胎冷旋压机机架进行受力分析的基础上,以分析软件ANSYS和建模软件SolidWorks为主要开发工具建立了在静态下的机架受力模型。基于组合机架的结构特点,分析并计算了机架上梁与预紧螺母之间的作用力。对旋压机机架施加载荷和约束,得到加载模型。经过有限元分析,计算了机身的强度和刚度,确定了危险点的位置,并对机架进行了拓扑优化分析。依据优化分析结果给出了具体的改进方案,得到了经优化后的机身结构,为旋压机整机的结构优化设计打下了良好基础。     

Constrained independent component analysis and its application to machine fault diagnosis

For machine fault diagnosis the signals from working machine are always numerous, even uncountable, but there contains only a little useful information. Hence how to find out the useful signal from numerous signals, including noises, that is, how to only extract the desired fault signal is very attractive. This paper shows that the constrained independent component analysis (cICA) can solely extract desired faulty signal using some prior mechanical information. The methods of creating reference of cICA for machine diagnostics are discussed, and the effectiveness of the method is successfully verified by simulations and experiments.     

High temperature friction and wear characteristics of various coating materials for steam valve spindle application

Various coatings such as chromium carbide (deposited by plasma spraying and detonation gun techniques), chromium oxide, chromium oxide+titania+silica, NiCrAlY, and Al₂O₃+NiAl, all deposited by plasma spraying; stelliting, and surface nitriding have been applied on X20CrMo V121 steel. This steel is used for high temperature applications such as steam turbine valve spindle. Friction and wear behavior of the surface coated and treated materials have been studied at an elevated temperature of 550°C while rubbing against graphite-filled stellited steel. These studies have been carried out on SRV Optimol reciprocating tribometer. Test parameters for tribological studies have been selected with a view to simulate operating conditions encountered in operation. Additionally, the structure, porosity, hardness, bond strength, and thermal cycling behaviour of these surface coated/treated materials have been characterised. Based on these laboratory investigations, chromium carbide coating deposited by plasma spraying technique has been identified as the most suitable coating for steam turbine valve spindle application. Process parameters have been established for deposition of chromium carbide coating by plasma spraying technique on actual valve spindles. The field results obtained are found to be commensurate with the laboratory findings.     

A study of wavelet analysis based error compensation for the angular measuring system of high-precision test turntables

An angular measuring system is the most important component of high-precision test turntables; its function and precision determine the turntable's function and precision. The angular measuring system's error was considered as a stationary signal in the past. An autocorrelation function and spectrum characteristics of the angular measuring system error are analyzed using the cyclostationary signal theory. The idea that the error in the angular measuring system is nonstationary is first put forward; theory is provided to reconstruct the angular measuring system's error signal using wavelet analysis. The error signal is reconstructed using one-dimensional Mallat's algorithm. The standard deviation between the reconstructed and the original signal is much less than the angular measuring system's accuracy. The reconstruction signal is used to compensate the system error instead of the original error signal; the angular measuring system accuracy is improved.     

Study on the design of control valve for U-shaped noise reduction cage and its fluid flow features and noise

In response to technical issues such as the ineffective noise reduction impact of balanced cage and single-seat control valves, the U-shaped noise reduction cage control valve is investigated and developed. In addition, its equal percentage flow properties and noise reduction impact are good, allowing it to effectively minimize the noise created by the change of fluid parameters of medium such as vapor, gas, and gas-liquid two-phase flow. The flow coefficient and flow properties were analyzed. The noise features of the medium air flow at small and large openings of 30% and 85% are simulated and analyzed, respectively. The pressure, velocity, and temperature of the inlet and outlet air, as well as the sound intensity maximum and sound power level maximum, are also analyzed with the opening curves. A small opening of 30% was selected, and the noise characteristics of cavitation generated by the medium water flow were simulated and analyzed. Together with the pressure and temperature change curves of the incoming water, the volume maxima and density minima of water are studied. The maximum sound intensity and sound power level of water are analyzed using the pressure and temperature curves of inlet water, as well as the cavitation coefficient and the degree of opening. The results of the trial for the pressure resistance of the valve body and the trial for the valve seat seal indicate that both the valve body strength and the valve seat seal meet the specifications. Comparing the noise trial results and simulation results reveals that the sound intensity and sound power level assessed by the trial and simulation are comparable, and the noise reduction impact of the control valve is positive.     

Detection of signal transients using independent component analysis and its application in gearbox condition monitoring

This paper addresses feature extraction of the higher-order statistics, which can effectively characterize the transients, using independent component analysis (ICA) for the one-dimensional measured vibration signal, and then proposes a novel automatic technique for detecting the transients in vibration signals with the low signal-to-noise ratio by ICA feature extraction. The basic principle of the ICA-based transient detection method is that the independent components (ICs) coefficients of the transients and the noise can be effectively distinguished by their different sparseness properties. Specifically, the proposed method mainly includes three steps: training the ICA basis features from the signal segments, denoising the sparse ICs coefficients using the shrinkage function deduced by the maximum a posteriori (MAP) estimation, and reconstructing the transient segments by the shrunken coefficients through the ICA basis functions. Experimental results through the simulated signal analysis and the vibration signal analysis show that the ICA-based method is very effective for transient detection outperforming the traditional methods and is valuable for gearbox condition monitoring and fault diagnosis.