Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.     

Behaviors of concrete-filled steel tubular members subjected to combined loading

The present study is an investigation on the behaviors of concrete-filled thin-walled steel tubular members subjected to combined loading, such as compression and torsion, bending and torsion, compression, bending and torsion. ABAQUS software is used in this paper for the finite element analysis (FEA). A comparison of results calculated using this modeling shows generally good agreement with test results. The FEA modeling is then used to investigate the influence of important parameters that determine the ultimate strength of the composite members under combined loading, such as compression and torsion, bending and torsion, compression, bending and torsion. The parametric studies provide information for the development of formulae for calculating the ultimate strength of the composite members subjected to combined loading.     

一种新型的转炉炉底车

本文介绍了一种作业效率高、省时省力新型的转炉炉底车，其特点是转盘转动灵活，炉底车上项盘径向任意方向均能平稳倾斜一定角度，以保证炉底圆周所受项力均匀可靠，满足炉底安装要求。     

Evaluation of Laminated Circular Elastomeric Bearings

This paper evaluates the behavior and performance of laminated circular elastomeric bearings and compares them to those of square and rectangular bearings. The study included an experimental evaluation and a nationwide survey of state Department of Transportations on the use and performance of circular bearings and bearings in general in their states. The experimental investigation studied the bearings' behavior in compression, compression and rotation, and compression and shear. Results from this limited study showed that the three bearings have similar stress-strain behavior in compression and they are in agreement with the AASHTO LRFD guide stress–strain curves. In compression and rotation, the AASHTO LRFD substructure moments are slightly less than the measured values for circular bearings and rectangular bearings rotated about their strong axis for a compressive stress of 10.3?MPa (1.5?ksi) and slightly higher than those of rectangular bearings rotated about their weak axis. In compression and shear, the shear stiffness of circular and square bearings is in agreement with theoretical values within the range of design displacements. Results from the survey showed that many states are using circular bearings and more states would consider using them, however no maintenance or monitoring data were available on their short-term and long-term performance.     

GCr15轴承钢的热变形模拟试验研究

利用先进的Gleeble-2000热模拟试验机，对GCr15轴承钢某一轧制过程进行模拟试验，测定出GCr15轴承钢动态CCT曲线，并结合微观组织分析，制定合理的GCr15轴承钢轧后控制冷却工艺，以期达到提高GCr15轴承钢质量的最终目的。     

用高分子复合材料修复轧管机组大型构件

介绍采用高分子复合材料修复用于钢管生产的轧管机组大型构件的方法。重点介绍机架轴承座孔的修复工艺流程 ,修复定位 ,技术操作要点及修复效果。     

汽轮机轴承烧瓦与轴颈的渗巴氏合金现象

简述轴承工作性质，巴氏合金应用与相组成的基本情况。论述汽轮机转子在两个电厂长期运行后，由于轴颈发生的不正常摩擦损伤，在大修改造中由无损检查、机械加工揭示出轴颈存在严重的渗巴氏合金现象，低熔点金属Sn、Sb与Cu向转子材料晶界的深层渗入最终导致了3根大型在投转子的严重开裂与报废。图11表2     

离子束混合工艺对材料抗蚀性能的影响

本文介绍了离子束混合工艺方法。与直接注入相比较,离子束混合所使用的设备造价低1/4—1/2,而生产效率可提高1—2个数量级,因而使生产成本大幅度降低,这无疑对离子束工艺的实际应用将产生巨大的促进作用。 通过对轴承材料(GCr15和Cr4Mo4V)经Cr、N、Ta不同元素的混合处理后,在0.5M H_2SO_4和0.1M NaCl的缓冲溶液中的阳极极化曲线表明经混合处理后的两种材料试样,其抗蚀能力和抗点蚀能力均大大提高,这与直接注入的试样效果是一致的。 通过俄歇谱仪和透射电镜的分析结果表明混合是成功的,且在一定的条件下,形成非晶组织。 本文的结论是,无论是离子的直接注入还是离子束混合,对提高轴承材料的抗腐蚀性能都是有效的方法,特别是离子束混合技术具有更大的应用前景。     

Integrating neural network technology and noise analysis

The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check valves and bearings illustrate the usefulness of the methodology developed.     

Φ76mm自动轧管机组穿孔机顶杆小车的改进

通过校核Φ７６ｍｍ自动轧管机组穿孔机顶杆小车的轴承寿命，提出了顶杆小车的改进措施，如重新选配合适的轴承型号，修改有关装配尺寸等。改进后，顶杆小车的使用效果良好。