高灵敏度电晕放电辐射信号探测方案

为了实现复杂电磁环境下电晕放电辐射信号的探测,从信号特征入手,通过对电晕电流的计算和模拟实验,揭示了电晕放电的时、频域特征。在分析自然环境下噪声频率分布规律的基础上,设计了窄频段探测技术,通过设计特定频段的定向天线、增加高频宽带低噪声放大器、应用数字处理终端等方式,搭建了高灵敏度的微弱信号探测系统,成功探测到自然环境中600m外的电晕放电辐射信号。实验结果充分证明了电晕放电辐射信号的远距离探测的可行性,为电晕放电目标探测提供了重要的技术手段。     

近岸4种鱼的声散射特征提取及融合实验研究*

为了有效地提取表征鱼类间差异的声散射特征参数,该文通过绳系法实验研究了近岸4种经济鱼类的声散射信号特征提取及融合方法。首先,通过自研双频鱼探仪采集花鲈、许氏平鲉、黑鲷和斑石鲷的个体鱼声散射信号;然后,分别测定200 kHz和450 kHz换能器下鱼体的目标强度,同时提取鱼声散射信号的时频域统计特征;最后,将降维后的时频特征与频差特征融合组成新的特征向量。该文通过实验验证了该方法的有效性,基于组合特征的支持向量机识别准确率达93%。结果表明,鱼的频率响应特性和鱼声散射信号的时频域统计特征能一定程度上反映鱼的固有属性,有效地增加判别依据能显著提高以上4种鱼类的识别准确率。     

超高速撞击声发射信号在载人航天器加筋结构的传播特性实验研究

为研究超高速撞击声发射信号经过载人航天器加筋结构后的传播规律,分别在平板结构和加筋结构上模拟高速撞击实验,利用传感器阵列采集高速撞击产生的声发射信号。结合小波和傅里叶分析方法从板波模态、频域以及时域三方面分析加筋结构对声发射信号传播特性的影响,并研究成坑和穿孔损伤模式下声发射信号的传播规律。结果表明:加筋板中的信号高频部分比平板中高频部分能量少,筋体对信号高频部分有滤波效果。加筋结构受高速撞击产生穿孔损伤时,S0模态声波的能量增多。研究成果可为载人航天器结构的高速撞击感知与定位技术提供有利参考。      

Leak Detection of Gas Pipelines Based on Characteristics of Acoustic Leakage and Interfering Signals

When acoustic method is used in leak detection for natural gas pipelines, the external interferences including operation of compressor and valve, pipeline knocking, etc., should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms. In this paper, the technologies of extracting characteristics of acoustic signals were summarized. The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain, frequency-domain and time-frequency domain were extracted. The main characteristics of time-domain are mean value, root mean square value, kurtosis, skewness and correlation function, etc. The features in frequency domain were obtained by frequency spectrum analysis and power spectrum density, while time-frequency analysis was accomplished by short time Fourier transform. The results show that the external interferences can be removed effectively by the characteristics of time domain, frequency domain and time-frequency domain. It can be drawn that the acoustic leak detection method can be applied to natural gas pipelines and the characteristics can help reduce false alarms and missing alarms.     

水下目标多模态深度学习分类识别研究

水下目标的分类识别对于水声探测具有重要意义。提出一种水下目标多模态深度学习分类识别方法。针对水声信号的一维时域模态和二维频域模态特征建立一种多模态特征融合的深度学习结构,结合长短时记忆网络和卷积神经网络的优点,对一维时域信号和二维频谱信号分别进行并行处理,对输出进行典型相关分析,形成特征融合表示,并利用相邻帧的相关性进行参数优化。利用实测水声信号对算法进行了验证。结果表明：提出的算法对于水下目标识别的精度有显著的提高。     

水声JANUS信号的分数低阶时频谱迁移学习识别方法

非合作第三方水下标准协议信号识别在水声通信信号识别中具有重要研究意义。针对浅海水声JANUS信号的特征提取因易受脉冲噪声和多径效应等复杂水声环境影响而导致识别率低下的问题,提出一种分数低阶时频谱和ResNet18 （Residual Network 18）相结合的迁移学习识别方法。首先,选取JANUS固定前导作为识别对象,设计分数低阶傅里叶同步压缩变换（FLOFSST）,以分数低阶操作抑制脉冲噪声,以时频重排特性增强时频集中性。其次,将基于ImageNet的ResNet18预训练模型微调,迁移至JANUS信号和常见水声信号时频图集。仿真表明所提算法在信噪比为-10 dB时JANUS信号的识别率为96.15%,能够有效抑制脉冲噪声并减小多径效应影响,比传统算法识别性能好。海试中JANUS信号识别率达90.00%,证明算法识别准确率和网络的泛化性较高。      

Toward a model for lexical access based on acoustic landmarks and distinctive features

This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of "articulator-bound" features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from neighboring segments.     

A time domain correction method for Doppler-distortion signal from acoustic moving source

Doppler effect widely exists in the signal from the moving acoustic source. In order to solve such problems as frequency shift and frequency band expansion, a time domain cor- rection method is presented in this paper. First, the discrete time vector for interpolation and the amplitude restoration formula is derived based on the moving relationship and the Morse acoustic theory, then the amplitude weights are corrected and the distortion signal is interpolated. Every point of the discrete signal is operated separately in time domain. Compared with the existing frequency domain methods, this method does not need to know the characteristic frequency beforehand and would not be influenced by the blending of the frequency band. Hence, this method can be employed to correct multiple frequency signals and it is also a simple and effective Doppler effect reduction method.     

Communicative pulsed signals of beluga whales in the reproductive gathering off Solovetskii Island in the White Sea

Results of the perceptive and acoustic analysis of communicative pulsed signals recorded in a reproductive gathering of beluga whales off Solovetskii Island in the white sea are presented. The mean signal duration varies from 0.04 to 1.52 s for various signal types, the pulse repetition rate on the average ranges from 13 to 1300 (possibly, 2700) impulses per second, and the mean peak frequency falls within 0.2 to 11.3 kHz. A high degree of similarity between the communicative pulsed signals produced by beluga whales from different populations is revealed.     

水声无源材料插入损失测量时反聚焦方法

提出了利用时间反转(时反)聚焦技术的水声无源材料插入损失测量方法。通过无试样及有试样情况下实现接收信号的时反聚焦,并对聚焦信号进行透射系数计算,获得试样的插入损失。由于时反原理可实现接收信号的空时聚焦,从而提高测量信混比,因此本方法适用于非自由场环境下材料声学参数的测量,尤其适用于低频条件下的声学参数测量。波导水池试验开展了对两块试样的测量,试样尺寸为1.1m×1.0m×5mm,测量频率范围为1—20kHz,通过测量值与理论值的对比验证了该方法的有效性。      

激光声信号的频谱特性

构建了激光声实验测量系统,利用脉冲激光聚焦击穿水介质产生声信号,由水听器将声信号转换成电信号并送入数字存储示波器。分析了激光声信号的时频域数学模型,实验研究了激光声信号的频域能量分布,以及激光器重复频率和激光声信号频谱特性的关系。结果表明:激光声信号能量主要集中在200 kHz内,其中100~200 kHz内的能量所占比例约50%。激光声信号的幅频响应极大值点可以受到激光器重复频率的控制。     

改进的梅尔倒谱系数在低空飞行器特征提取中的应用*

梅尔倒谱系数特征提取技术依据人耳的感知特性将声信号从线性频域转换到梅尔域,在语音识别中得到广泛应用。该文将梅尔倒谱系数技术用于小型低空飞行器的声信号特征提取中,并针对螺旋桨驱动类的小型低空飞行器具有稳定的强谐波特性,对梅尔倒谱系数特征提取中使用的梅尔滤波器进行改进,通过对此类谐波处的线性频谱与梅尔谱转换曲线的斜率进行投影替换,提高滤波器对该谐波处信号的感知敏感度。仿真结果表明,使用改进的梅尔倒谱系数特征提取方法对小型低空飞行器进行特征提取时,能够得到更低的等误识率,并且在低信噪比环境中,改进的梅尔倒谱系数特征提取方法具有更好的抗噪能力。     

盲重构频域阵列信号的压缩感知水声目标方位估计

针对复杂海洋环境条件下压缩感知水声目标方位估计性能下降的问题,利用盲源分离能够提高信噪比的优势,提出了一种盲重构频域阵列信号的压缩感知水声目标方位估计方法。首先将阵元域信号通过傅里叶变换方法得到多个子带阵列信号;然后对各个子带阵列信号进行复数域盲源分离得到子带解混矩阵和子带分离信号估计,并对子带分离信号进行属性分析和处理;再根据处理后的子带分离信号和子带解混矩阵重构子带阵列信号,对重构的子带阵列信号采用频域压缩感知方法进行空间谱估计,得到各个子带的空间谱;最后将各子带得到的空间谱进行求和,搜索求和后空间谱的峰值则可实现目标方位估计。模拟器数据和海上实测数据验证结果表明,同等条件下该方法的目标检测能力优于经典的最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)方法、频域压缩感知(Compressed Sensing,CS)方法、盲源分离(Blind Source Separation,BSS)与MVDR相结合的方法(BSS+MVDR方法),测向精度更高,明显提高了弱目标信号的空间谱能量,增强了声呐检测弱目标的能力。      

Low speed bearing fault diagnosis using acoustic emission sensors

In this paper, a new methodology for low speed bearing fault diagnosis is presented. This acoustic emission (AE) based technique starts with a heterodyne frequency reduction approach that samples AE signals at a rate comparable to vibration centered methodologies. Then, the sampled AE signal is time synchronously resampled to account for possible fluctuations in shaft speed and bearing slippage. The resampling approach is able to segment the AE signal according to shaft crossing times such that an even number of data points are available to compute a single spectral average which is used to extract features and evaluate numerous condition indicators (CIs) for bearing fault diagnosis. Unlike existing averaging based noise reduction approaches that require the computation of multiple averages for each bearing fault type, the presented approach computes only one average for all bearing fault types. The presented technique is validated using the AE signals of seeded fault steel bearings on a bearing test rig. The results in this paper have shown that the low sampled AE signals in combination with the presented approach can be utilized to effectively extract condition indicators to diagnose all four bearing fault types at multiple low shaft speeds below 10 Hz.     

网箱养殖大黄鱼合成声信号特性研究

对所采集到网箱中人工养殖的两组不同年龄大黄鱼(Pseudosciaena crocea)产生的声信号进行定量分析和比较,运用分段指数振荡函数合成大黄鱼声信号,并利用振荡频率和衰减指数定量地描述了鱼声信号特性。结果显示,合成的大黄鱼声信号在时频域都显示出很好的拟合优度,13—15月鱼龄组的平均振荡频率和衰减指数均低于7—8月鱼龄组。结果表明函数的振荡频率和衰减指数与大黄鱼发声的物理过程及年龄特征存在一定的联系,为今后人工养殖大黄鱼中声学技术的相关应用提供一定的科学参考和基础。      

滚动轴承声信号特征提取和诊断试验研究

为解决振动检测方法不能有效识别低速旋转机械滚动轴承故障问题,利用声发射检测方法,建立了滚动轴承低速声发射信号采集试验装置,对模拟人工缺陷滚动轴承声发射信号进行了采集,进而对滚动轴承声发射信号进行总体平均经验模式分解,结合能量矩及相关系数法综合判断分解后各模态分量的真伪,据此提取出特征信号并做出其局部Hilbert边际谱,最后对滚动轴承各种故障模式进行诊断。试验结果表明该诊断方法能准确识别滚动轴承声发射信号故障频率,依据特征频率及幅值大小可对低速滚动轴承故障进行有效诊断。     

浅海非均匀水平阵宽带声场信号无源孔径扩展

大孔径水平阵对于浅海低频水声物理实验研究和应用至关重要,然而受实际情况制约,通常使用的水平基阵孔径十分有限,通过孔径扩展处理来扩展基阵孔径是一条重要途径。传统的无源孔径扩展方法是建立在均匀线阵、匀速相对运动和相干窄带连续信号的基础上的,难以适用于非均匀阵以及非连续宽带声源的情况。针对这些问题,提出了非均匀阵宽带声场信号的无源孔径扩展方法。使用静止布设在海底的非均匀水平短阵接收运动声源重复发射的宽带声信号,先开展均匀空间插值,然后在阵元域和波束域进行宽带扩展孔径处理。仿真和实验结果表明,在水深约70 m的浅海波导环境中,纵向间隔27.5 m的2个阵元接收20~200 Hz宽带声场,其空间插值结果与真值的相关系数大于0.99,说明宽带声场插值方法的合理性。在水平非均匀、纵向孔径250 m的短阵接收声场无法分析简正波频散特征的情况下,仿真和实验数据经过宽带无源孔径扩展处理得到孔径大于1 km的均匀线阵的声场,能高分辨区分各阶简正波,证明所提方法是有效的。      

Habitat-dependent ambient noise: consistent spectral profiles in two African forest types

Many animal species use acoustic signals to attract mates, to defend territories, or to convey information that may contribute to their fitness in other ways. However, the natural environment is usually filled with competing sounds. Therefore, if ambient noise conditions are relatively constant, acoustic interference can drive evolutionary changes in animal signals. Furthermore, masking noise may cause acoustic divergence between populations of the same species if noise conditions differ consistently among habitats. In this study, ambient noise was sampled in a replicate set of sites in two habitat types in Cameroon: contiguous rainforest and ecotone forest patches north of the rainforest. The noise characteristics of the two forest types show significant and consistent differences. Multiple samples taken at two rainforest sites in different seasons vary little and remain distinct from those in ecotone forest. The rainforest recordings show many distinctive frequency bands, with a general increase in amplitude from low to high frequencies. Ecotone forest only shows a distinctive high-frequency band at some parts of the day. Habitat-dependent abiotic and biotic sound sources and to some extent habitat-dependent sound transmission are the likely causes of these habitat-dependent noise spectra.     

基于听觉谱特征的变压器绕组状态检测研究

绕组松动是变压器常见故障之一,对变压器的安全运行产生巨大威胁.故对其进行精准的监测,对提高电力系统的安全稳定性具有十分重要的意义.基于声信号的变压器绕组松动检测,由于其具有无损检测和不需停运变压器等优点,成为近年来研究的热点.但声信号检测存在故障特征提前复杂和易受噪声干扰等缺陷,限制了其工程应用.该文提出了一种基于声信...     

涂层厚度与粘接质量的电磁声谐振无损检测

为了解决电磁超声(EMAT)涂层质量检测中接收信号信噪比较低的问题,将电磁声谐振技术(EMAR)应用于涂层质量检测,有效提高了超声接收信号的信噪比.在EMAR仿真中,通过变步长离散仿真得出了谐振与非谐振状态下的时域波形和频谱图,验证了利用电磁声谐振进行涂层质量检测的可行性.以电磁超声谐振驻波作为检测信号,实验中谐振信号...