Leak location in gas pipelines using cross-time–frequency spectrum of leakage-induced acoustic vibrations

The correlation-based location methods are widely used in leak detection of the pipelines assuming that the acoustic speed has been known and constant. In practice, the acoustic speed is frequency-varying due to the dispersions of gas-leak-induced acoustic waves, and thus the assumption is not supported. In this work, a location scheme based on cross-time–frequency spectrum (CTFS) is intended for the gas-leak-induced acoustic waves with frequency-varying acoustic speed. In the scheme, the CTFS is obtained by the one-dimensional Fourier transform of the time domain convolution between the kernel function in correlation domain and the instantaneous cross-correlation of the two spatially separately collected acoustic signals on either sides of a leakage. Then, the time difference of arrival (TDOA) and the corresponding frequency information are extracted simultaneously when the CTFS reaches the maximum value. The resulting peak frequency is used to online determine the frequency-dependant acoustic speed in combination with the known dispersive curve of gas-leak-induced dominated mode. Finally, the gas leakage is located by the TDOA and the frequency-dependant acoustic speed of real-time determination instead of constant acoustic speed. Consequently, for the proposed scheme, the constant acoustic speed is no longer a prerequisite. The proposed scheme has been experimentally validated in leak detection of gas pipelines and results demonstrate that the average relative location errors are reduced by six times compared with the commonly used correlation-based location method.     

输气管道声波法泄漏检测技术的理论与实验研究

为探究输气管道声波法泄漏检测技术的基本原理和研究方法,建立了输气管道泄漏仿真模型和实验模型。首先,研究输气管道发生泄漏时声波产生机理,从而明确声波法泄漏检测技术的工作原理;其次根据声波法泄漏检测的原理建立Fluent仿真模型,通过CFD软件模拟输气管道泄漏得到流场和声场,得到声波信号特征;再次根据声波法泄漏检测的原理搭建实验管道,设计完成声波信号数据采集终端,并在仿真结果指导下完成输气管道泄漏检测实验,采集得到实验数据并进行分析,得到泄漏时声波信号特征并对仿真结果进行验证;最后对比多工况条件下的实验结果和仿真结果,分析不同工况条件对压力波动值的影响规律,从而总结输气管道声波法泄漏检测的仿真与实验研究方法,为声波法泄漏检测的实际工程应用提供理论基础。研究结果表明:输气管道泄漏产生的声波来源于泄漏时气体不稳定流动产生的偶极子声源和四极子声源;仿真模拟和实验研究的方法都可以完成声波法泄漏检测技术的研究,可以对声波法泄漏检测技术的推广和工程应用提供强大的理论支持和可行性保证。结论是:声波法泄漏检测技术可以很好的检测输气管道泄漏,是一种灵敏度高,检测时间短,值得推广的方法。     

基于小波包能量谱的分布式光纤燃气管道泄漏监测及实验分析

基于Mach-Zehnder/Sagnac混合干涉仪原理,利用分布式光纤对城市燃气管道进行泄漏监测模拟实验研究。对测量光纤长4 km和6 km时的干涉信号利用小波包能量谱提取法和绝对距离法相结合的方法诊断管道泄漏与否,再结合频谱图进行泄漏定位,最后对系统的虚警率(false alarm rate,FAR)进行了分析。结果表明,与传统直接通过频谱图识别零点频率的方法相比,虚警率降低了8.475%,能够更准确地识别燃气管道泄漏与否,从而提高系统监测及定位的可靠性。     

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。     

基于改进最小方差无失真响应角度谱算法的 气体泄漏定位方法*

针对噪声环境下微小气体泄漏难以准确定位的问题,提出了一种基于改进最小方差无失真响应角度谱算法的气体泄漏定位方法。该算法通过引入信噪比追踪加权的方式,提取受噪声影响较小且单个声源能量占优的时频支撑域,并通过Softplus激活函数自适应地调整不同频率分量对角度谱函数的贡献,增加泄漏声源占优的时频域权重;此外,引入基于时频稀疏性的分频带处理,使各子频带内存在一个主导声源能量占优,抑制低频段噪声能量的积累同时避免高频混叠现象。通过软件仿真计算以及实验验证算法的性能,结果表明改进最小方差无失真响应角度谱算法可以实现气体泄漏源的精准定位,定位结果的最大误差在3.5°以内。相比传统算法,该方法在低信噪比和低采样点数下有更高的稳定性、抗噪能力及准确率,可为气体泄漏定位的实际应用提供一定的参考价值。     

自来水铸铁管道泄漏声信号频率特征研究

针对基于声发射技术的自来水管网泄漏检测定位方法，研究因泄漏而形成的声信号频率分布及不同泄漏量对频率分布的影响。实际泄漏检测时，通常采用互相关法估计泄漏信号到达不同传感器间的时间延迟实现漏点定位，因此，借助互相关分析法研究了管道的不同口径及泄漏信号传播距离对泄漏信号频率分布的影响。同时，泄漏声信号的传播不可避免要经过管道间的接口，因此分析了两种管道接口对信号频率成分的影响。进而为设计合理的管道泄漏检测过程提供依据，并为泄漏声信号形成及多种因素对泄漏声信号特征产生影响的机制研究奠定基础。     

深度残差收缩网络的含噪微泄漏超声识别方法*

在利用声学信号进行泄漏检测时,复杂的背景噪声往往会淹没微弱的泄漏信号,导致误判率高。针对微小泄漏在含噪环境中识别困难的问题,提出了基于深度残差收缩网络（DRSN）的含噪微泄漏识别方法。在提出的方法中,添加不同强度高斯噪声,建立数据集,使用DRSN网络进行训练,验证DRSN对不同泄漏强度、不同噪声含量样本识别的有效性。实验结果表明：DRSN对于微弱泄漏可以达到较理想的识别率,即使在高度杂糅数据识别时仍能达到较理想的识别效果,而且噪声含量并不会对DRSN迭代次数产生明显的影响。将提出的方法与CNN识别方法对比,DRSN具有明显的优势。     

Improved passive acoustic band-limited energy detection for cetaceans

Acoustic detection of cetaceans is challenged by the variability of calls and the presence of variable background noise. One detection method is to start with frequency band-limited signal and noise estimates, and apply a likelihood ratio test (LRT). These detectors suffer from false alarms when broadband signals overlap the band of interest, triggering detection. Some detectors only consider previous samples, causing further false alarms. The authors propose a method of reducing false alarms by defining a guard band that is not expected to contain energy from the species of interest. A second LRT is performed by testing the ratio of the signal estimate in the signal band with the signal estimate of the guard band. This method is shown to reduce false alarms with a small reduction in detection performance. A detection method is also presented that can be optimized for high processing efficiency, while improving false-alarm rejection from signals that are longer in duration than the signal of interest. Performance is demonstrated on real cetacean recordings and ocean noise. The detection algorithm is implemented in PAMGUARD, an open source Java application designed for passive acoustic monitoring (PAM) of cetaceans.     

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。     

Hilbert-Huang变换分析THz脉冲信号的时频特性

提出一种基于Hilbert-Huang变换的THz时域光谱分析方法,将THz时域脉冲信号分解成有限数目的单分量信号之和,利用Hilbert变换求得瞬时频率来获得幅值的时频分布——Hilbert-Huang变换谱,实现了通过水蒸气的THz脉冲信号的时频分析,揭示了THz波与水蒸气相互作用的频谱时域分布特性,并与基于小波变换的时频图进行了对比分析。结果表明,该方法可以同时提高THz脉冲时频分布的时间分辨率和频率分辨率,具有局部化分析和自适应选择的特点,还能直观地表现出各频率成分之间的相对时间延迟。     

An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles

This paper proposes an adaptive filter-based method for detection and frequency estimation of whistle calls, such as the calls of birds and marine mammals, which are typically analyzed in the time-frequency domain using a spectrogram. The approach taken here is based on adaptive notch filtering, which is an established technique for frequency tracking. For application to automatic whistle processing, methods for detection and improved frequency tracking through frequency crossings as well as interfering transients are developed and coupled to the frequency tracker. Background noise estimation and compensation is accomplished using order statistics and pre-whitening. Using simulated signals as well as recorded calls of marine mammals and a human whistled speech utterance, it is shown that the proposed method can detect more simultaneous whistles than two competing spectrogram-based methods while not reporting any false alarms on the example datasets. In one example, it extracts complete 1.4 and 1.8 s bottlenose dolphin whistles successfully through frequency crossings. The method performs detection and estimates frequency tracks even at high sweep rates. The algorithm is also shown to be effective on human whistled utterances.     

Hilbert-Huang变换分析THz脉冲信号的时频特性

提出一种基于Hilbert-Huang变换的THz时域光谱分析方法,将THz时域脉冲信号分解成有限数目的单分量信号之和,利用Hilbert变换求得瞬时频率来获得幅值的时频分布Hilbert-Huang变换谱,实现了通过水蒸气的THz脉冲信号的时频分析,揭示了THz波与水蒸气相互作用的频谱时域分布特性,并与基于小波变换的时频图进行了对比分析。结果表明,该方法可以同时提高THz脉冲时频分布的时间分辨率和频率分辨率, 具有局部化分析和自适应选择的特点,还能直观地表现出各频率成分之间的相对时间延迟。     

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.     

固定干扰源存在下的管道泄漏检测和准确定位

为了解决固定位置的声/振动干扰源引起的管道泄漏声检测的虚警或者漏点定位错误问题,利用泄漏信号源和固定干扰源之间的独立性,通过盲卷源分离算法得到泄漏信号在一定代价函数下的最优估计,并将该估计作为输入信号从检测信号中自适应预测得到泄漏信号,这样就可以保留泄漏信号中的时延信息。对实际检测信号的处理表明,应用提出来的方法可以有效的去除检测信号中来自固定干扰源的噪声,同时不损失泄漏信号中的时延信息,可在固定干扰源存在时实现管道泄漏有效检测和准确定位。     

基于频散特征的单水听器模式特征提取及距离深度估计研究

针对浅海环境中低频宽带水声脉冲信号, 研究基于频散特征结合时频分析的单水听器距离和深度估计方法. 以简正波理论为依据, 将单水听器上的接收信号表示成一系列传播模式之和的形式, 分析了经典波导环境下的频散现象, 采用自适应径向高斯核函数的时频分析方法来表征接收信号的频散特征. 为提高时频分辨率, 采用自适应径向高斯核函数的时频分布来提取频散关系曲线中传播模式的到达时间差, 利用模式的到达时间差估计声源的距离. 采用多模式联合匹配的方式, 通过二值掩模滤波的时频滤波方法, 提取所需的模式. 通过计算实际提取出的模式能量与预测的模式能量之间的误差, 建立代价函数, 并通过模式能量匹配的方式, 确定声源的深度. 通过对基于Pekeris波导模型的浅海环境进行仿真验证, 结果表明: 自适应径向高斯核函数的时频分析方法能够很好地反映信号本身的频散特征, 具有较高的时频分辨率, 克服了传统短时傅里叶变换时频表征的限制, 使得模式在时频域更加容易辨识和分离; 从测距效果来看, 不同模式组合下的距离估计结果不同, 采用在时频面上具有较高能量的模式, 可得到较为准确的距离估计; 选用高能量的模式所得的距离估计的相对误差小于2%. 在定深方面, 参与联合匹配的模式个数越多, 代价函数的峰值更加地尖锐, 同时具有低的伪峰, 深度估计的性能会进一步有所提升. 该工作对于研究低频水声脉冲信号的分离和提取具有重大意义. 关键词： 频散信道 时频分析 单水听器 定位     

Eigenvalue spectrum analysis for temporal signals of Kerr optical frequency combs based on nonlinear Fourier transform

Based on the nonlinear Schr?dinger equation(NLSE) with damping, detuning, and driving terms describing the evolution of signals in a Kerr microresonator, we apply periodic nonlinear Fourier transform(NFT) to the study of signals during the generation of the Kerr optical frequency combs(OFCs). We find that the signals in different states, including the Turing pattern, the chaos, the single soliton state, and the multi-solitons state, can be distinguished according to different distributions of the eigenvalue spectrum. Specially, the eigenvalue spectrum of the single soliton pulse is composed of a pair of conjugate symmetric discrete eigenvalues and the quasi-continuous eigenvalue spectrum with eye-like structure.Moreover, we have successfully demonstrated that the number of discrete eigenvalue pairs in the eigenvalue spectrum corresponds to the number of solitons formed in a round-trip time inside the Kerr microresonator. This work shows that some characteristics of the time-domain signal can be well reflected in the nonlinear domain.     

圆孔非线性声阻抗三维时域仿真与特性分析

为研究有限振幅声波作用下圆孔的非线性声学特性,提出了基于三维时域计算流体动力学(CFD)仿真的圆孔非线性声阻抗提取方法,通过求解层流方程来模拟声信号在圆孔及上下游的传播,以及采用横向周期性边界条件来考虑高穿孔率时圆孔之间相互作用的影响。研究了不同幅值声波作用下孔径、厚度和穿孔率对声阻抗的影响规律,通过对质点振速幅值、频率和板厚等组成的无量纲参量进行非线性回归分析,得到了圆孔非线性声阻抗的拟合公式,并将其转换为可考虑多频声波影响的时域模型。最后结合声阻抗时域模型和有限差分方法计算了直通穿孔管消声器在小振幅和有限振幅声波作用下的传递损失,通过与实验测量结果的比较,验证了拟合公式的准确性和实用性。     

Acoustic detection and classification of river boats

We present a robust algorithm to detect the arrival of a boat of a certain type when other background noises are present. It is done via the analysis of its acoustic signature against an existing database of recorded and processed acoustic signals. We characterize the signals by the distribution of their energies among blocks of wavelet packet coefficients. To derive the acoustic signature of the boat of interest, we use the Best Discriminant Basis method. The decision is made by combining the answers from the Linear Discriminant Analysis (LDA) classifier and from the Classification and Regression Trees (CART) that is also accompanied with an additional unit, called Aisles, that reduces false alarms rate. The proposed algorithm is a generic solution for process control that is based on a learning phase (training) followed by an automatic real time detection while minimizing the false alarms rate.     

闭合裂纹非共线混频超声检测试验研究

针对结构中微裂纹检测难题,发展了一种闭合裂纹非共线混频超声检测方法。在对非共线混频超声检测机理分析基础上,进行了结构中疲劳裂纹混频非线性超声检测实验。对有无裂纹试件中检测信号进行了滤波和时频分析,结果表明,可根据信号滤波后时域波形中是否存在明显的混频波包或时频分析中是否存在明显的和频分量,实现有无闭合裂纹的判识;通过移动激励探头的位置,控制两列入射声波在试件中的交汇位置,实现试件中不同深度位置的混频非线性检测。并根据测得的混频非线性系数沿试件深度方向上分布,实现了闭合裂纹沿深度方向上长度的测量。研究工作为结构中微裂纹定量评价做了有益探索。