A Bionic Fish Cilia Median-Low Frequency Three-Dimensional Piezoresistive MEMS Vector Hydrophone

A bionic fish cilia median-low frequency three-dimensional MEMS vector hydrophone is reported in this paper. The piezoresistive reasonable position was obtained through finite element analysis by ANSYS and the structure was formed by MEMS processes including lithography, ion implantation, PECVD and etching,etc. The standing wave barrel results show that the lowest sensitivity of the hydrophone is-200 d B and reach up to-160 d B(in which the voltage amplification factor is 300). It has a good frequency response characteristics in 25 Hz ～ 1500 Hz band. Directivity tests displayed that the hydrophone has a good "8"-shaped directivity,in which the resolution is not less than 30 d B, and asymmetry of the maximum axial sensitivity value is less than 1.2 d B.

Pressure and velocity cross-spectrum of normal modes in low-frequency acoustic vector field of shallow water and its application

The pressure and horizontal particle velocity combined descriptions in the very low frequency acoustic field of shallow wa- ter integrated with the concept of effective depth of Pekeris wave- guide is proposed, especially the active component of the pressure and horizontal particle velocity cross-spectrum, also called ho- rizontal complex cross acoustic intensity, when only two normal modes are trapped in the waveguide. Both the approximate theo- retic analysis and the numerical results show that the sign of the horizontal complex cross acoustic intensity active component is independent of the range when vertically deployed receiving dual sensors are placed in appropriate depths, the sum of which is equal to the waveguide effective depth, so it can be used to tell whether the sound source is near the surface or underwater; while the range rate is expected to be measured by utilizing the sign distribution characteristic of the reactive component. The further robustness analysis of the depth classification algorithm shows that the existence of shear waves in semi infinite basement and the change of acoustic velocity profiles have few effects on the application of this method, and the seabed attenuation will limit the detection range, but the algorithm still has a good robustness in the valid detection range.

Application of frequency estimation algorithm based on a single vector sensor in underwater acoustic communication

A method of high resolution frequency estimation based on a single vector sensor using ESPRIT （Estimating Signal Parameters via Rotational Invariance Techniques） algorithm is proposed and applied to the underwater acoustic （UWA） communication system of frequency modulation. Higher resolution frequency estimation can be obtained by this algorithm using fewer snapshots comparing with the sound intensity frequency estimation. Results of simulation and lake experiment show that the proposed algorithm can improve the communication data rate and reduce the bandwidth of the system. Because higher signal-to-noise ratio （SNR） is demanded, range UWA communication at oresent. this algorithm can be used in high speed short

Photonic Vector Signal Generation by Frequency Sextupling for Radio Over Fiber Systems

To generate high-frequency radio frequency(RF) vector signals, a vector signal generation method by optical frequency sextupling using a dual-parallel modulator is proposed. The method modulates vector signal on +3 rd order optical sideband and local oscillator(LO) signal on-3 rd order sideband using the intermodulation process in the DPMZM. After suppressing of the optical carrier and other sidebands through proper adjustment for modulator biases and modulation index, a frequency sextupled millimeter-wave vector signal can be generated after photodetection. The frequency sextupling will lower the bandwidth of the modulator, the local oscillator and the driving circuits. In addition, the phase of generated signal is not distorted after detection, and the power fading after fiber transmission can be avoided. In the simulation, a 500-MSym/s QPSK signal at 60 GHz is generated by 10-GHz drive signal. After travelling over fiber with length of 20/30/40-km, receiver power penalty keeps below 2.5 dB.

Joint estimation of DOA, frequency, and polarization based on cumulants and UCA

A joint estimation algorithm of direction of arrival （DOA）, frequency, and polarization, based on fourth-order cumulants and uniform circular array （UCA） of trimmed vector sensors is presented for narrowband non-Gaussian signals. The proposed approach, which is suitable for applications in arbitrary Gaussian noise environments, gives a closed-form representation of the estimated parameters, without spectral peak searching. An efficient method is also provided for elimination of cyclic phase ambiguities. Simulations are presented to show the performance of the algorithm.

Instantaneous frequency and wave mode identification in a magnetosheath using few spatial points

Observational data such as those obtained from the magnetosheath in the downstream of Earth＇s bow shock have waveforms that differ from those of sinusoidal signals. In practice, they are not even aggregates of sinusoidal signals. Therefore, the frequency decomposition for the data requires technique that will account for the time-varying features of the data that will lead to deduction of physical meaning of the observations. The combination of empirical mode decompo- sition （EMD） and Hilbert transform has been used for extracting the various contributing oscillatory modes （EMDs） and the instantaneous frequency determination （Hilbert transform） of every physically meaningful mode called intrinsic mode func- tion （IMF）. The resulting instantaneous frequencies are used to determine instantaneous wave vectors. The combination of the instantaneous frequencies and wave vectors is useful in the identification of wave modes based on the characteristics of the waves. The results show that EMD-Hilbert can be more reliable than simple Hilbert transform alone.

Frequency domain polarization weighted ESPRIT method for bearing angle

The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.

Combined spatial frequency spectroscopy analysis with visible resonance Raman for optical biopsy of human brain metastases of lung cancers

The purpose of this study is to examine optical spatial frequency spectroscopy analysis(SFSA)combined with visible resonance Raman(VRR)spectroscopic method,for thefirst time,to discriminate human brain metastases of lung cancers adenocarcinoma(ADC)and squamous cell carcinoma(SCC)from normal tissues.A total of 31 label-free micrographic images of three type of brain tissues were obtained using a confocal micro-Raman spectroscopic system.VRR spectra of the corresponding samples were synchronously collected using excitation wavelength of 532 nm from the same sites of the tissues.Using SFSA method,the difference in the randomness of spatial frequency structures in the micrograph images was analyzed using Gaussian functionfitting.The standard deviations,calculated from the spatial frequencies of the micrograph images were then analyzed using support vector machine(SVM)classifier.The key VRR biomolecularfingerprints of carotenoids,tryptophan,amide II,lipids and proteins(methylene/methyl groups)were also analyzed using SVM classifier.All three types of brain tissues were identified with high accuracy in the two approaches with high correlation.The results show that SFSA–VRR can potentially be a dual-modal method to provide new criteria for identifying the three types of human brain tissues,which are on-site,real-time and label-free and may improve the accuracy of brain biopsy.

The Performance of Dual-Frequency Polarimetric Scatterometer in Sea Surface Wind Retrieval

The wind retrieval performance of HY-2 A scanning scatterometer operating at Ku-band in HH and VV polarizations has been well evaluated in the wind speed range of 0–25 m s^-1.In order to obtain more accurate ocean wind field,a potential extension of dual-frequency(C-band and Ku-band)polarimetric measurements is investigated for both low and very high wind speeds,from 5 to 45 m s^-1.Based on the geophysical model functions of C-band and Ku-band,the simulation results show that the polarimetric measurements of Ku-band can improve the wind vector retrieval over the entire scatterometer swath,especially in nadir area,with the wind direction root-mean-square error(RMSE)less than 12?in the wind speed range of 5–25 m s^-1.Furthermore,the results also show that C-band cross-polarization plays a very important role in improving the wind speed retrieval,with the wind speed retrieval accuracy better than 2 m s^-1 for all wind conditions(0–45 m s^-1).For extreme winds,the C-band HH backscatter coefficients modeled by CMOD5.N(H)and the ocean co-polarization ratio model at large incidence are used to retrieve sea surface wind vector.This result reveals that there is a big decrease of wind direction retrieval RMSE for extreme wind fields,and the retrieved result of C-band HH polarization is nearly the same as that of C-band VV polarization for low-to-high wind speed(5–25 m s^-1).Thus,to improve the wind retrieval for all wind conditions,the dual-frequency polarimetric scatterometer with C-band and Ku-band horizontal polarization in inner beam,and C-band horizontal and Ku-band vertical polarization in outer beam,can be used to measure ocean winds.This study will contribute to the wind retrieval with merged satellites data and the future spaceborne scatterometer.

Damage Detection Method Using Support Vector Machine and First Three Natural Frequencies for Shear Structures

A method is proposed for detecting damage to shear structures by using Support Vector Machine (SVM) and only the first three natural frequencies of the translational modes. This method is able to determine the damage location in any story of a shear building with only two vibration sensors;to obtain modal frequencies, one sensor on the ground detects an input and the other on the roof detects the output. Based on the shifts in the first three natural frequencies, damage location indicators are proposed, and used as new feature vectors for SVM. Simulations of five-story, nine-story and twenty-one-story shear structures and experiments on a five-story steel model were used to test the performance of the proposed method.

Influence Analysis on the Floating Underwater Monitoring System Applicable for Very-Low-Frequency Acoustic Measurement

Ocean vector acoustic measurement is feasible affected by the hydrodynamic interference caused by the flow fluctuations and structural vibrations, especially in the very-low-frequency monitoring. Hence, a novel horizontal floating platform including a horizontal floating cable, vertical mooring cable and floating main body is proposed and described in this paper. It has the advantages of good maneuverability along with the current and multi-stage vibration isolation. The main application of this platform is to measure the ocean ambient noise coming from the wave fluctuation and the deterministic acoustic signals such as aquatic organisms, underwater targets and sailing vehicles. The influence of the current fluctuation on the attitude angle and flow induced vibration of cables and main body are analyzed with some previous sea test data. Moreover, the comparison between the vertical type platform used before and the horizontal type platform is also discussed. It is concluded that there is obvious relevance between the attitude angle and ocean current variation. Meanwhile, the abnormal influence on the main body is caused by the vibration transmission from the fluctuation of cables. There will be the influence on the accuracy of the acoustic measurement above 100 Hz, and the inherent vibration characteristic of the main body is the primary reason.

An Optimized Chinese Filtering Model Using Value Scale Extended Text Vector

With the development of Internet technology,the explosive growth of Internet information presentation has led to difficulty in filtering effective information.Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering,especially for Chinese texts.This paper selected the manually calibrated Douban movie website comment data for research.First,a text filtering model based on the BP neural network has been built;Second,based on the Term Frequency-Inverse Document Frequency(TF-IDF)vector space model and the doc2vec method,the text word frequency vector and the text semantic vector were obtained respectively,and the text word frequency vector was linearly reduced by the Principal Component Analysis(PCA)method.Third,the text word frequency vector after dimensionality reduction and the text semantic vector were combined,add the text value degree,and the text synthesis vector was constructed.Experiments show that the model combined with text word frequency vector degree after dimensionality reduction,text semantic vector,and text value has reached the highest accuracy of 84.67%.

基于频率响应与图像特征提取的动车组变压器绕组状态诊断方法研究

动车组变压器是保障高速铁路稳定运行的核心设备,频率响应法是目前检测变压器绕组状态的有效方法。为提升车载变压器绕组状态诊断的准确性,结合暂态信号与频率响应法提出基于频率响应与图像特征提取的动车组变压器绕组状态诊断方法。搭建试验车载变压器绕组故障模拟平台,获取不同故障类型和故障位置的频响曲线,利用类Gram矩阵结合幅频和相频曲线信息,再利用密度分层法转换为伪彩色图,提取对应的灰度共生矩阵和灰度差分矩阵特征值,根据鹈鹕优化支持向量机方法对绕组故障进行诊断。试验结果表明:车载变压器绕组故障发生时,伪彩色图能够反映出故障信息,有利于图像分析和特征提取,采用基于频率响应与图像特征提取的动车组变压器绕组状态诊断方法能够识别车载变压器绕组的典型故障类型和位置。

基于特征融合和B-SVM的鸟鸣声识别算法

为了实现在野外通过低成本嵌入式系统识别鸟类,提出了基于特征融合和B-SVM的鸟鸣声识别方法。对鸟鸣声信号提取梅尔频率倒谱系数、翻转梅尔频率倒谱系数、短时能量和短时过零率组成特征参数,通过线性判别算法对特征参数进行特征融合。利用黑寡妇算法通过测试集对支持向量机模型的核参数和损失值进行优化得到B-SVM模型。利用Xeno-canto鸟鸣声数据集对本文算法进行了测试,结果表明该方法的识别准确率为93.23%。算法维度参数的大小和融合特征维度的高低是影响算法识别效果的重要因素。在相同条件下,文中所提的基于特征融合和B-SVM模型的鸟鸣声识别算法相较于其他特征参数和模型,识别的准确率更高,为野外鸟类识别提供了参考。

低复杂度永磁同步电机三矢量固定开关频率模型预测电流控制策略

针对传统永磁同步电机(permanent magnet synchronous motor,PMSM)三矢量模型预测电流控制(three-vector model predictive current control,TV-MPCC)存在开关频率不固定和计算复杂的问题,提出一种固定开关频率TV-MPCC策略。利用前一周期的零电压矢量和参考电压矢量所在扇区来快速筛选所需最优电压矢量和次优电压矢量,避免了无效枚举计算,从而降低了开关频率和计算复杂度。引入系统d和q轴电流差参数,计算各电压矢量的作用时间,确保电压矢量作用时间恒大于零和开关频率固定。以三相两电平电压型逆变器驱动的表贴式PMSM为被控对象,通过仿真和实验对传统TV-MPCC策略和所提三矢量固定开关频率模型预测电流控制策略进行对比研究,仿真和实验结果表明,所提策略在保证系统稳态和动态性能的基础上,在固定和降低开关频率的同时,降低了计算复杂度。

晶闸管和IGBT混合的三相电机两相变频控制策略

现有三相交直交变频电路中大多使用IGBT作为电力电子器件,为了进一步降低低压大容量变频器设备成本,减少IGBT的使用,提出了一种晶闸管和IGBT混合的三相电机两相变频电路结构及四开关八电压矢量直接转矩控制策略.首先分析了利用IGBT辅助晶闸管关断的三相电机两相变频电路结构,并分析了不同开关状态下的瞬时电路工作原理,给出三相四开关拓扑下的八电压矢量生成方法;其次提出四开关八矢量异步电机直接转矩控制策略,并给出扇区划分、电压矢量选择和电压矢量伏秒生成原理;最后通过仿真实验验证所提策略的正确性和可行性.仿真结果验证了上述电路结构和控制方法的有效性.

考虑频率耦合特性的D-PMSG复数域阻抗建模及其特征分析

阻抗分析法因其简单有效被广泛用于含电力电子变换器的互联系统稳定性研究。然而,采用传统方法对频域序阻抗建模时,需通过非线性变换(Park变换及其反变换)进行坐标系转换,这会导致不同周期分量的卷积运算及相应的频移,其过程较为烦琐。针对上述问题,基于复向量时域微分算子,提出了永磁直驱同步发电机(D-PMSG)等效阻抗建模方法。该方法在时域周期系统稳定运行轨迹的邻域内直接进行小信号线性化,并采用指数旋转因子灵活反映系统受扰后的时变特性,结合时域微分算子等效表征互联系统控制环节的动态特性,避免了频域阻抗建模时坐标系的反复变换,大幅降低了解析建模的复杂度。此外,所提方法能够更加清晰地阐释互联系统受到扰动时D-PMSG并网逆变器产生频率耦合现象的物理意义;同时,能够说明基频电压初始相位对耦合分量相频特性的影响。最后,利用仿真验证了所提算法的有效性。

基于声信号的离心泵故障诊断研究

各种原因使得工业现场设备状态监测的首选测量信号是声信号时,提出一种基于声信号的设备状态监测方法显得尤为必要。以某型离心泵为依据对象,对现场采集的声信号提取梅尔倒谱系数(MFCC)作为信号的初始特征,然后计算这些MFCC初始特征的散布熵(DE)值,并通过主成分分析法(PCA)对矩阵进行降维,从而构造特征矩阵。利用蝙蝠优化算法(BA)对支持向量机(SVM)的惩罚系数与核函数参数进行优化,对离心泵的多种故障工况开展诊断,并与多种诊断方法进行比较。实验结果表明,经过BA优化后的模型在诊断准确率上提高了21.7%;在该模型的基础上利用DE对MFCC提取的信号进行深度挖掘,使模型诊断的准确率提高2.05%。

高频链矩阵变换器直接功率反步控制策略

针对高频链矩阵变换器(HFLMC)电路前后级耦合导致系统动态性能和鲁棒性降低的问题,提出一种基于直接功率的非线性反步控制策略(BS-DPC)。首先,建立HFLMC非线性数学模型和有功、无功功率动态模型,分析双极性电流空间矢量调制策略;然后,在考虑系统不确定性情况下引入2个解耦控制分量,设计直流输出电流和无功功率反步控制器,实现电池不同工况下输出电流参考值的快速跟踪控制;最后,根据李雅普诺夫稳定性理论证明HFLMC闭环系统全局渐进稳定性,并对比传统PI直接功率控制和BS-DPC策略。仿真和实验结果表明,所提BS-DPC策略控制HFLMC提高了输出电流的动态性能和电网波动及直流滤波电感变化下的鲁棒性,响应时间减少了约78%,网侧THD降低了0.98%。

基于单矢量水听器时频声强法的非合作水声跳频信号多维参数估计

针对传统方法对水下非合作跳频信号的多维参数估计效果不佳的问题,提出一种基于单矢量水听器时频声强法的非合作水声跳频信号空时频参数估计方法。利用矢量水听器声压通道与振速通道的接收信号建立时频域的短时互谱分布,分析噪声与信号在时频域分布的差异,通过迭代去噪法与连通域方法,对噪声进行抑制并平滑每跳的能量分布;采用复声强法对短时互谱矩阵进行处理,得到清晰稳定的跳频信号空时频分布;提取空时频分布的脊线并利用Haar小波变换对脊线进行奇异点检测,估计出信号的多维参数。仿真和水池试验结果表明,当信噪比大于-5 dB时,所提方法得到的参数估计归一化均方根误差小于0.05。