基于改进局域波法的柴油机振动信号分析

提出了一种基于奇异值分解降噪的柴油机振动信号局域波分解方法,首先对原始振动信号进行相空间重构和奇异值分解,然后根据分解的奇异值降噪,接着利用经验模式分解法提取降噪后振动信号的基本模式分量,最后作出时频曲线和边界谱曲线。对滤波前和滤波后的柴油机振动信号进行了局域波分析,分析结果表明,奇异值分解能够有效地提高信噪比,突出原始振动信号的特征,使得降噪后的振动信号分解出的基本模式分量和时频曲线以及边界谱曲线具有更明确的物理意义,有利于对柴油机进行精确诊断。     

斜风作用下风-车-桥非线性分析系统建立

为了从风作用方向的三维模拟和系统非线性2个角度实现风-车-桥系统的全三维高真实度模拟,首先建立斜风荷载处理方法,采用平均风分解理论对桥梁斜风进行分解,形成桥梁斜风荷载,把桥梁风作用方向模拟域由垂直于桥梁纵轴线的二维平面扩展到三维空间;采用矢量合成法则和线性插值方法,依据车辆位置函数确定桥上车辆任意位置和时刻的合成风速,并基于风洞试验获取车辆气动力系数,形成车辆斜风荷载。然后基于已建立的非线性分析系统,融合斜风荷载处理方法,构建斜风作用下的风-车-桥全三维非线性分析系统,并实现动态可视化。最后采用建立的分析系统,对系列风偏角工况下的桥梁空间动力响应和车辆安全进行分析和评价。结果表明：斜风作用下,桥上车辆事故指标值及桥梁位移响应随着风偏角增大总体上均呈现先减小后增大趋势,且极值均出现在非90°的锐角区;基于风向垂直于桥跨方向的假定所进行的桥梁设计和车辆安全性评价结果偏于不安全。     

小波神经网络在舰载雷达多路径效应检测中的应用

针对海面反射对舰用电子支援措施(ESM)产生的多路径效应,研究了多路径反射信号模型,采用删除构造小波网络的结构,探讨了运用小波网络对多路径效应进行检测的方法.     

港口吞吐量变动的内在特征研究

以上海港为例,采用经验模态分解的方法对港口吞吐量的变化特征进行探讨。结果表明港口货物吞吐量具有3～4个月、准6个月、准1年、准2年、准6年的显著变化周期。分析后认为港口吞吐量这些变化特征和波动周期与社会生产和消费具有季节性、国民经济发展规律和宏观调控、国际贸易经济波动等有关。最后,分析指出了模态分解结果对实际工作的指导意义。     

地震波信号降噪技术

针对地震波信号本身的复杂性,在接收和处理地震波信号的各个阶段都可能引入噪声的问题,提出了采用小波变换对地震波信号进行降噪的方法,小波变换降噪方法在去除掉高频噪声的同时保留了信号的高频成分,是一种比傅立叶变换更有效的降噪方法。对比了几种小波去噪的方法,从不同的性能指标中优化出针对地震波信号的环境特点最为有效的降噪方法,从而达到有效提取有用信号的目的。     

A new time-frequency analysis method based on single mode function decomposition for offshore wind turbines

The Hilbert-Huang transform (HHT) has been widely applied and recognised as a powerful time-frequency analysis method for nonlinear and non-stationary signals in numerous engineering fields. One of its major challenges is that the HHT is frequently subject to mode mixing in the processing of practical signals such as those of offshore wind turbines, as the frequencies of offshore wind turbines are typically close and contaminated by noise. To address this issue, this paper proposes a new time-frequency analysis method based on single mode function (SMF) decomposition to overcome the mode mixing problem in the structural health monitoring (SHM) of offshore wind turbines. In this approach, the structural vibration signal is first decomposed into a set of window components using complex exponential decomposition. A state-space model is introduced in the signal decomposition to improve the numerical stability of the decomposition, and then a novel window-alignment strategy, named energy gridding, is proposed and the signals are constructed in the corresponding gridding. Furthermore, energy recollection is implemented in each gridding, and the reassembling of these components yields an SMF that is comparable to the intrinsic mode function (IMF) of the HHT, but with a significant improvement in terms of mode mixing. Four case studies are conducted to evaluate the performance of the proposed method. The first case attempts to detect three different frequencies in a simulated time-invariant signal. The second case attempts to test a synthesised signal with segmental time-varying frequencies (each segment contains three different frequencies components). The analysis results in these two cases indicate that mode mixing can be reduced by the proposed method. Furthermore, a synthesised signal with slowly varying frequencies is used. These analysis results demonstrate the effective suppression of non-relevant frequency components using SMF decomposition. In the third case, the experimental data from vortex-induced vibration (VIV) experiments sponsored by the Norwegian Deepwater Programme (NDP) are used to evaluate the proposed SMF decomposition for vibration mode identification. In the final case, field data acquired from an offshore wind turbine foundation and offshore wind turbine are analysed. The mode identification results obtained using SMF decomposition are compared with those produced by the HHT. The comparison demonstrates superior performance of the proposed method in identifying the vibration modes of the VIV experimental and field data.     

Decomposition analysis of decoupling freight transport from economic growth in China

Freight transport industry plays a significant role in boosting economic growth, while also creating many negative externalities for social welfare and the environment. Using data from 1997 to 2017, this study employs the complete decomposition technique to identify the driving forces of freight transport and explores its internal relations with economic growth in China. The decomposition analysis focuses on four factors that are responsible for freight transport: economic activity, industrial structure, transport intensity, and haulage distance. Then, the decoupling index is adopted to examine the decoupling relationship between freight transport and economic growth in China. The results showed that weak decoupling between freight transport and economic growth was the main state during the study period. A strong decoupling effect was identified in 1997–1998, 2012–2013, and 2014–2015, whereas no decoupling effect was observed in 1998–1999, 2008–2009, and 2011–2012. The transport intensity was the most important contributor to the decoupling progress, the industrial structure effect played a role in promoting the decoupling progress over half of the years during the research period, and the haulage distance effect facilitated the decoupling progress in more than one-third of the years examined.     

多塔斜拉桥加劲索涡激振动实测与时域解析模态分解

为研究多塔斜拉桥中塔加劲索涡激振动时域和频域特性,对多根加劲索开展了振动加速度测量和风速、风向观测,研究了加劲索振幅与风速和风向的关系,分析了加速度时程的时域和频域特征。采用解析模态分解法对加劲索涡激振动加速度时程进行了分解,分析了所得分量的时域和频谱特征。研究发现,在无雨和较低风速条件下,同侧并列加劲索仅迎风侧发生明显涡激振动,其峰值振动是以频率为6.25 Hz的第28阶模态主要参与为特征,为高阶多模态涡激振动,明显发振风速约为4~5 m·s^-1,风向接近垂直桥轴线,其面内振动明显大于面外。1^#加劲索面内涡激振动时程分解得到的3个相邻高阶频率时程分量显示,第28阶模态振动加速度随时间的变化,主导了加劲索振动加速度幅值的增大和减小。同时认为,解析模态分解法不仅能较好地分离含有多个密集频率分量的时域信号,且分解得到的分量不改变原信号分量的频率特征,分解分量再合成的信号与原信号时频特征完全一致。因而可采用解析模态分解法分解具有多个密集频率分量的柔性结构响应,能有助于工程结构风致响应的模态参数识别。     

VIV response of a flexible cylinder with varied coverage by buoyancy elements and helical strakes

Many significant engineering challenges have emerged as the petroleum industry has moved their field development and production activities into increasingly deeper water depths. The design of deepwater marine risers presents the combined challenges to minimize top tensioning requirements, mitigate any flow-induced vibrations, and if possible to increase the expected fatigue life of these slender structural members. As part of the design process to achieve these goals external buoyancy modules and strakes have been employed. To gain insight into the complex multi-mode response behavior a recent experimental study was performed and the analysis of selected data sets is presented. In the experiments a horizontal cylinder with a length to diameter ratio of 263 was fitted with a variety of strake and buoyancy element configurations. The models were towed at uniform speeds ranging from 0.4 to 2.0 m/s and fiber optic strain gages were used to measure both in-line and cross-flow strain response. The resulting time series information was processed utilizing the method of time domain decomposition formulated for strain data input and the introduction of modal assurance criterion to resolve the modal strain information that included frequency, mode shape, and critical damping ratio information. The pre-tensioned cylinder without appendages was used as a base case and the results were basically consistent with expectations. In the case of 0.8 m/s low-tension test, multiple closely spaced non-overlapping peaks were observed in both in-line and cross-flow directions and were identified as being of the same mode with mode shapes distorted away from purely sinusoidal behavior. The test data for the 100% coverage by helical stakes demonstrated the effectiveness of that suppression device over the range of current velocities investigated. The most interesting case was that of a staggered combination of helical strakes and buoyancy element whose total for each type of coverage was equal. This effective asymmetric VIV suppression approach is presented and discussed in detail.     

多级优化模型分解方法的探讨

在确定模型类型及影响模型分解因素的基础上，提出了多级优化模型分解原则，同时给 种实用模型分解方法。