加热区金属组织变化与加热切削深度的关系

本文通过等离子弧加热切削中金属表面软化层金相组织分析，来研究在一定加热条件下的切削深度，并提出４５＃和９ＳｉＣｒ两种淬火钢在一定加热条件下的合适切削深度。     

Lyapunov definition and stability of regular or chaotic vibration modes in systems with several equilibrium positions

This paper deals with forced vibrations of two-DOF systems with more than one equilibrium positions. Such systems may be obtained by digitization of elastic post-buckling systems. A vibration mode, which is periodic at small force amplitudes and becomes chaotic as the force amplitudes are slowly increased, is selected. It is possible to formulate and solve the problem of stability of a periodic or chaotic vibration mode in a space with greater dimension using the classical Lyapunov stability definition and some calculating procedures. Instability of phase trajectories is used as a criterion of the chaotic behavior in dynamical systems. Trajectories with very close initial values are compared. Use of the Lyapunov stability definition shows mutual stability/instability of the trajectories. Calculations permit to observe an appearance and enlargement of the chaotic behavior regions. Specific results are obtained for the nonautonomous Duffing equation and pendulum system.     

空调系统噪声控制技术

介绍空调系统噪声控制的措施,具有较大的实用意义.     

散斑检测技术及其应用

综述了散斑计量中的主要检测技术。主题包括散斑照相技术、散斑干涉技术、电子散斑干涉技术、数字散斑相关技术和时间序列散斑检测技术。介绍了散斑计量在科学和工程研究中的一些重要应用。     

阻尼复合材料舵板减振降噪试验研究

介绍了阻尼复合材料舵板的模拟试验情况,对阻尼复合材料舵板和金属舵板进行了水下振动和振动声辐射特性的对比试验分析,结果显示,在100Hz到5kHz范围内,水下辐射噪声前者比后者平均降低约7dB,表明该阻尼复合材料用于舰船的某些典型振动构件具有广阔前景。     

粘弹材料阻尼性能的分析模拟和预测

讨论了阻尼材料动态性能表征的数学模拟分析方法及其性能预测,从分数导数模型出发分析了阻尼材料动态性能内在的一些基本规律,为阻尼材料的研究、开发和性能测试提出了一些指导性的建议。     

逐孔爆破技术在金堆城露天矿的应用

介绍了以降低爆破震动为主要目标的逐孔爆破技术在金堆城露天矿的应用。利用SHOT PLAN软件进行爆破网路优化设计,实现了单孔单网路的可靠起爆。6次爆破震动测试结果表明,与原排间微差起爆技术相比,采用逐孔爆破技术后,爆破质点峰值振速降低了22%～78%。逐孔爆破技术的应用,有效降低了震动危害,使凹陷露天采场边坡的稳定得到了有效控制,同时改善了爆破效果,提高了铲装效率。     

Structural Damage Detection Using Empirical Mode Decomposition: Experimental Investigation

This paper presents an experimental investigation on the applicability of the empirical mode decomposition (EMD) for identifying structural damage caused by a sudden change of structural stiffness. A three-story shear building model was constructed and installed on a shaking table with two springs horizontally connected to the first floor of the building to provide additional structural stiffness. Structural damage was simulated by suddenly releasing two pretensioned springs either simultaneously or successively. Various damage severities were produced using springs of different stiffness. A series of free vibration, random vibration, and earthquake simulation tests were performed on the building with sudden stiffness changes. Dynamic responses including floor accelerations and displacements, column strains, and spring releasing time instants were measured. The EMD was then applied to measured time histories to identify damage time instant and damage location for various test cases. The comparison of identified results with measured ones showed that damage time instants could be accurately detected in terms of damage spikes extracted directly from the measurement data by EMD. The damage location could be determined by the spatial distribution of the spikes along the building. The influence of damage severity, sampling frequency, and measured quantities on the performance of EMD for damage detection was also discussed.     

Vibration Control of Wind-Excited Tall Buildings Using Sliding Mode Fuzzy Control

A sliding mode fuzzy control (SMFC) is proposed to design a controller for the third-generation benchmark problem on wind-excited buildings. A distinctive feature in vibration control of large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure; however, they cannot be precisely measured, especially for the case of wind excitations. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feedback loop only. The general structure of the SMFC, proposed herein, is composed of a compensation part and a convergent part. The compensation part prevents the system from diverging, and the convergent part directs the system to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feedback loop and a feedforward loop. To realize the virtual feedforward loop for the wind-induced vibration control, a disturbance estimation filter is introduced. The structure of the filter is constructed based on an autoregressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For verification of the proposed algorithm, numerical simulation is carried out on the benchmark problem for wind-excited buildings. The results indicate that the present control algorithm is efficient for reducing the wind-induced vibration.     

Baseline Models for Bridge Performance Monitoring

A baseline model is essential for long-term structural performance monitoring and evaluation. This study represents the first effort in applying a neural network-based system identification technique to establish and update a baseline finite element model of an instrumented highway bridge based on the measurement of its traffic-induced vibrations. The neural network approach is particularly effective in dealing with measurement of a large-scale structure by a limited number of sensors. In this study, sensor systems were installed on two highway bridges and extensive vibration data were collected, based on which modal parameters including natural frequencies and mode shapes of the bridges were extracted using the frequency domain decomposition method as well as the conventional peak picking method. Then an innovative neural network is designed with the input being the modal parameters and the output being the structural parameters of a three-dimensional finite element model of the bridge such as the mass and stiffness elements. After extensively training and testing through finite element analysis, the neural network became capable to identify, with a high level of accuracy, the structural parameter values based on the measured modal parameters, and thus the finite element model of the bridge was successfully updated to a baseline. The neural network developed in this study can be used for future baseline updates as the bridge being monitored periodically over its lifetime.