The transient suppression for piezoelectric ceramic emission transducer

A transient suppression method for piezoelectric ceramic transducer is presented. By adding some special pedestal pulses to the original transmitted signal, the transient effects in the output of the transducer can be just precisely transmission by use of a narrowband transducer. canceled, thereby achieving the broadband The experimental results show that the transient responses of the sinusoid pulses and coded signals are suppressed successfully and the acoustic waveforms radiated into the surrounding water are improved significantly.     

An identification method to estimate surface shortwave fluxes on temperature and thickness observations of sea ice in CHINARE 2006

In this paper, a parameter identification method to determine surface shortwave fluxes using temperature and thickness measurements of sea ice in CHINARE 2006 is presented. Adopting a new standard for the calculation of the thermodynamic properties of seawater named TEOS‐10, the surface shortwave fluxes are calculated by the temperature and thickness observations that were measured at Nella Fjord around Zhongshan Station, Antarctica. New simulations for temperature profiles in a different measurement period are performed by three parameterization schemes including the present method, Zillman and Shine. All numerical results are compared with in situ measurements. Results show that better simulations of the surface shortwave radiations and temperature distributions are possible with the identification method than Zillman and Shine. Therefore this method is valid, and the obtained shortwave radiation function can be applied in sea ice modeling. Copyright © 2015 John Wiley & Sons, Ltd.     

Simulating the dynamic behavior of planetary gearbox based on improved Hanning function

Planetary gearboxes are widely used in industrial machines. They usually work in harsh environments giving rise to damages and high maintenance costs. Condition monitoring is a key action allowing one to detect the presence of such damage ensuring healthy running conditions. The knowledge of the dynamic behavior of such a gearbox can be achieved using modeling tools as a primary step before conditioning the monitoring subject. In addition, modeling a gear set can help in the stage of design in order to optimize physical and geometric parameters of the system. Therefore, in this work, a two-dimensional lumped parameter model is adopted to build all vibration sources. The time-varying mesh stiffness is approximated as a square wave form. A novel mathematical formulation is proposed to model the amplitude modulation phenomenon due to the rotational motion of the planets around the center of the gearbox. Finally, the overall vibration signal is concluded as a summation of all vibration components influenced by the modulation function.     

基于S变换的地震信号降噪方法研究

S变换在分析非平稳信号时能有效地反映出频率随时间的变化,但由于其窗函数是固定不变的,在实际中应用受到了限制.从基本理论出发,推导出一种改进的S变换形式,并对合成信号分别进行傅立叶变换、s变换和改进的S变换,通过对比发现:改进的s变换方法能够更好地分辨非平稳信号的频率特性,比S变换具有更高的分辨率.最后应用改进的s变换方法对地震背景噪声数据进行了去噪处理,取得了较好的结果.     

基于一维离散小波变换的心电信号降噪研究

针对心电信号中含有噪声的现象,为了准确提取反映心电信号的特征信息,该文提出了应用一维离散小波变换实现对心电信号的降噪处理方法.研究结果表明,该方法能够有效地去除心电信号中的噪声,从而为进一步实现心电信号特征信息的提取提供了有效的参考价值.     

《信号与系统》课程教学改革探讨

《信号与系统》是高等院校电子、通信类专业开设的一门重要的专业基础课.在教学改革中,应优化教学内容、改革教学方法、完善考核措施,尤其是加强实践教学,培养学生的实际工程能力.只有通过教改实践,才能调动学生学习的积极性,提高教学质量.     

叶绿体信号通过诱导抗氧化酶和花青素参与拟南芥环境胁迫响应

本文研究了渗透胁迫和冷胁迫对于叶绿体信号缺失突变体gun1、gun5和abi4的影响.实验结果表明,叶绿体信号缺失突变体对胁迫的抵抗力下降,表现在植株含水量降低,电导率和丙二醛含量升高.并且发现叶绿体信号缺失突变体中抗氧化酶如POD、SOD、APX活性明显下降,活性氧(超氧离子)积累明显加重,此外叶绿体信号缺失突变体不能诱导植物体内花青素的合成.本文初步探讨了叶绿体信号与植物体内活性氧和花青素合成途径的关系,表明叶绿体信号可以通过诱导抗氧化酶和花青素从而抵抗环境胁迫.     

基于旋转阀控制脉冲重构的钻井液QPSK信号解码及误码率分析

钻井液压力正交相移键控(QPSK)调制具有高密度携带及传输井下信息特点,其信号的解调与解码关系到所携带信息的正确恢复。通过建立信号的相位解调及旋转阀转速控制脉冲重构的数学模型,研究解调系统固有干扰及信号噪声对脉冲重构的影响;根据重构脉冲的幅度判别研究信号解码的可行性;通过建立重构脉冲的信噪比数学模型,对误码率进行理论分析。结果表明,解调系统固有干扰与信号噪声均对脉冲重构产生影响,且固有干扰影响较大;脉冲重构时,相邻码元编码产生的脉冲电平差值较小,使得误码阈值降低,上述影响更易引起误码。误码率的理论计算结果与仿真分析结果基本一致,可以将误码率分析模型用于钻井液压力QPSK信号传输效果的可靠性评估。     

Roller bearing acoustic signature extraction by wavelet packet transform,applications in fault detection and size estimation

Continuous online monitoring of rotating machines is necessary to assess real-time health conditions so as to enable early detection of operation problems and thus reduce the possibility of downtime. Rolling element bearings are crucial parts of many machines and there has been an increasing demand to find effective and reliable health monitoring technique and advanced signal processing to detect and diagnose the size and location of incipient defects. Condition monitoring of rolling element bearings, comprises four main stages which are, statistical analysis, fault diagnostics, defect size calculation, and prognostics. In this paper the effect of defect size, operating speed, and loading conditions on statistical parameters of acoustic emission (AE) signals, using design of experiment method (DOE), have been investigated to select the most sensitive parameters for diagnosing incipient faults and defect growth on rolling element bearings. A modified and effective signal processing algorithm is designed to diagnose localized defects on rolling element bearings components under different operating speeds, loadings, and defect sizes. The algorithm is based on optimizing the ratio of Kurtosis and Shannon entropy to obtain the optimal band pass filter utilizing wavelet packet transform (WPT) and envelope detection. Results show the superiority of the developed algorithm and its effectiveness in extracting bearing characteristic frequencies from the raw acoustic emission signals masked by background noise under different operating conditions. To experimentally measure the defect size on rolling element bearings using acoustic emission technique, the proposed method along with spectrum of squared Hilbert transform are performed under different rotating speeds, loading conditions, and defect sizes to measure the time difference between the double AE impulses. Measurement results show the power of the proposed method for experimentally measuring size of different fault shapes using acoustic emission signals.     

Low frequency acoustic signals associated with rock falls,thunderstorms, and wind turbulences in field environment

This paper characterized the observed low frequency acoustic signals generated by rock falls, thunderstorm, and wind turbulence in large rocky landslide. A digital infrasonic recording system was deployed on site to capture real-time low frequency acoustic signals associated with rock falls. An advanced non-stationary signal analysis method, i.e. Empirical Mode Decomposition (EMD), was applied to get insight to the characteristics of the low frequency acoustic signals induced by the hazards. Joint time–frequency distribution spectra technique was used to detect distinctive features of the events. The study shows that the low frequency acoustic signals can be excited by rock falls, thunderstorm and wind turbulence in the field environment, but the signal varies in both time domain and frequency domain with different patterns depending on the physical processes. The results demonstrated that the EMD-based signal processing technique is capable of extracting distinctive features to differentiate acoustic signals in real environment.