Research on Narrowband Line Spectrum Noise Control Method Based on Nearest Neighbor Filter and BP Neural Network Feedback Mechanism

Thefilter-x least mean square(FxLMS)algorithm is widely used in active noise control(ANC)systems.However,because the algorithm is a feedback control algorithm based on the minimization of the error signal variance to update thefilter coefficients,it has a certain delay,usually has a slow convergence speed,and the system response time is long and easily affected by the learning rate leading to the lack of system stability,which often fails to achieve the desired control effect in practice.In this paper,we propose an active control algorithm with near-est-neighbor trap structure and neural network feedback mechanism to reduce the coefficient update time of the FxLMS algorithm and use the neural network feedback mechanism to realize the parameter update,which is called NNR-BPFxLMS algorithm.In the paper,the schematic diagram of the feedback control is given,and the performance of the algorithm is analyzed.Under various noise conditions,it is shown by simulation and experiment that the NNR-BPFxLMS algorithm has the following three advantages:in terms of performance,it has higher noise reduction under the same number of sampling points,i.e.,it has faster convergence speed,and by computer simulation and sound pipe experiment,for simple ideal line spectrum noise,compared with the convergence speed of NNR-BPFxLMS is improved by more than 95%compared with FxLMS algorithm,and the convergence speed of real noise is also improved by more than 70%.In terms of stability,NNR-BPFxLMS is insensitive to step size changes.In terms of tracking performance,its algorithm responds quickly to sudden changes in the noise spectrum and can cope with the complex control requirements of sudden changes in the noise spectrum.

Line spectrum detection algorithm based on the phase feature of target radiated noise

In order to improve the performance of line spectrum detection,according to the feature that the underwater target radiated noise containing stable line spectrum,the differences of the phase difference between line spectrum and background noise,a weighted line spectrum detection algorithm based on the phase variance is proposed in frequency domain.After phase difference alignment,the phase variance of line spectrum and the phase of background noise,respectively,are small and big in frequency domain,this method utilizes the weighted statistical algorithm to cumulate the frequency spectrum based on the phase variance,which can restrain the background noise disturbance,and enhance the signal to noise ratio（SNR）.The theory analysis and experimental results both verify that the proposed method can well enhance the energy of line spectrum,restrain the energy of background noise,and have better detection performance under lower SNR.

Statistics Modeling of Shallow Sea Ambient Noise and Its Applications in Low-frequency Line Spectrum Detection

The noise's statistical characteristics are very important for signal detection.In this paper,the ambient noise statistical characteristics are investigated by using the recorded noise data in sea trials first,and the results show that the generalized Gaussian distribution is a suitable model for the ambient noise modeling.Thereafter,the optimal detector based on maximum likelihood ratio can be deduced,and the asymptotic detector is also derived under weak signal assumption.The detector's performance is verified by using numerical simulation,and the results showthat the optimal and asymptotic detectors outperform the conventional correlation-integration system due to accuracy modeling of ambient noise.

Special algorithm of enhancing underwater targetradiated dynamic line spectrum

Performance of traditional adaptive line enhancer （ALE） in suppressing Gaussian noise is low and can get worse at low input signal-to-noise ratio（SNR）. For greatly overcoming these disadvantages, feature of fourth-order cumulant （FOC） different slices for quasi-stationary random process is analyzed, fourth order cumulant（FOC） different slice-based adaptive dynamic line enhancer is presented, and output SNR of the proposed enhancer is derived and bigger than that of the ALE via theoretical analysis. Simulation tests with the underwater moving target-radiated data have shown that the proposed enhancer outperforms the ALE in suppressing Gaussian noise and enhancing dynamic line spectrum feature.

The quantum Kirchhoff equation and quantum current and energy spectrum of a homogeneous mesoscopic dissipation transmission line

On the basis of quantization of charge, the loop equations of quantum circuits are investigated by using the Helsenberg motion equation for a mesoscopic dissipation transmission line. On the supposition that the system has a symmetry under translation in charge space, the quantum current and the quantum energy spectrum in the mesoscopic transmission llne are given by solving their eigenvalue equations. Results show that the quantum current and the quantum energy spectrum are not only related to the parameters of the transmission llne, but also dependent on the quantized character of the charge obviously.

船用机械系统线谱展频技术研究

机械系统线谱噪声是重要的水声探测和识别特征,减振降噪技术主要针对其量级进行控制。针对线谱能量在频域集中的特征,提出一种展频运行策略,可在功能不变的同时将其能量在频域进行展宽,削弱其可供识别的频域特征。船用离心泵台架试验表明,提出的展频运行策略工程可行,随着频率分辨率的细化降低线谱峰值的效果可达7~15 dB。

基于随机森林的发电机定子线棒局部放电图谱特征识别方法

发电机定子线棒局部放电的在线监测和故障诊断对于电机故障预警、故障定位和指导机组检修有重要意义。目前存在部分不同类型局部放电相似度高,模式识别方法计算时间过长的问题,需要高精度和高效的识别方法,为此提出一种基于随机森林的定子线棒局部放电识别方法。制备了6种类型定子线棒,用特高频天线检测局部放电信号,基于相位分布局部放电(PRPD)图谱比对,提出参数幅值不对称度。基于随机森林方法识别缺陷类型,计算特征重要性,选择有效特征。最后,可视化特征相似度,与传统反向传播(BP)神经网络方法对比,验证有效性。结果表明:随机森林算法可以有效识别人工缺陷定子线棒局部放电,总体识别正确率达到93.33%。筛选半数特征后,随机森林比BP神经网络的准确率提高了10.83%,特征选择对随机森林的准确率影响很小,但识别效率大幅提高。随机森林在少量特征时识别准确率、计算时间都明显优于神经网络。幅值不对称度参数的重要性排在全部特征前1/3,具有推广价值。

燃煤锅炉温度场与高温腐蚀气氛场同步在线检测装置开发及应用

燃煤锅炉主燃区燃烧场的经济性、安全性和环保性对于智慧电厂建设具有重要意义。其中,水冷壁近壁面高温腐蚀H_(2)S和CO气体浓度的实时在线监测尤为重要。为实现燃煤锅炉主燃区温度场和高温腐蚀气氛场的同步测量,基于红外热成像原理,采用Optris-PI1M小型红外热成像仪,基于LabVIEW温度实时采集应用软件,在炉膛的观察口对主燃区温度场进行连续监测。以低成本1.5μm附近的通信波段激光器作为测量高温腐蚀气体H_(2)S和CO的激光光源,并结合波长调制光谱技术和频分复用技术,以实现H_(2)S和CO气体浓度的同步检测。线性度实验表明,其线性拟合相关系数为0.9995。将研制的同步检测仪器对某300 MW四角切圆燃煤锅炉的主燃区的温度场和气氛场进行了现场应用试验。现场测试结果表明,锅炉主燃区温度主要分布范围在1300~1400℃,最高温度达到了1500℃;同时得到了锅炉主燃区的H_(2)S和CO浓度分布,H_(2)S浓度在12~125 mg/m^(3)的范围内波动,而CO浓度主要分布在10%~20%之间,最高可达22%;炉内H_(2)S和CO的浓度呈正相关,氧气浓度保持在1%以下,由于厌氧燃烧会导致两种气体的含量增加,从而造成对水冷壁近壁面的高温腐蚀。

Methods for the Determination of Stable Isotopes of Carbon and Nitrogen Directly in Valine, Proline, Glutamine, and Glutamic Acid

Amino acids are very important compounds for the body and are involved in important functions that keep us healthy. Amino acids are essential components such as valine, proline, glutamine and glutamic acid. They can be synthesized either naturally or artificially. To examine the metabolism and regulate the synthesis process, compounds labeled with nitrogen or carbon isotopes need to be used. These isotopic compounds allow for more extensive research and enable studies that would otherwise be impossible. However, their use is dependent on the availability of simple, efficient methods for isotopic analysis. Currently, the determination of the atomic fraction of carbon and nitrogen isotopes is only possible through their conversion into molecular nitrogen or carbon monoxide or carbon dioxide. This leads to the loss of information about isotopic enrichment in specific centers of the molecule. This article explores a new direct approach to determining the atomic fraction of carbon and nitrogen isotopes in the isotope-modified or identical centers of these compounds. This method eliminates the transfer process and dilution due to nitrogen and carbon impurities. It is now possible to simultaneously determine the atomic fraction of nitrogen and carbon isotopes in the research substance. This method can be applied to amino acids, making it an effective tool for proposing new research methods. Several articles [1] [2] [3] have proposed similar methods for organic compounds and amino acids.

基于窄带频谱分析的电力线载波通信干扰过滤技术

电力线路载波通信受到背景噪声、脉冲噪声等方面干扰因素影响,导致通信信号质量下降,为此提出一种基于窄带频谱分析的通信干扰过滤技术。首先构建近似模型分析通信信号特征,利用马尔可夫链模拟信道上脉冲噪声状态。然后基于窄带频谱分析算法,在信号频谱周期图下,利用正交数据窗分离直接频谱,筛选估计方差以避免频谱泄漏事件的发生。利用傅里叶变换计算特征频谱,估计信号能量的集中特性,分析通信信号,平衡信号振幅和干扰抑制。最后通过时频峰值实施干扰滤波,有效保证电力线载波通信信号质量。经过实验数据分析证明,所提技术的载波干扰幅值最小值为1.1 dB,载波通信信号误码率平均值为1.9%,方法耗时平均值为3.8 s。

Dynamic Promotional Resource Allocation for Segment Specific and Spectrum Effect of Promotion for a Product Line Incorporating Repeat Purchase Behavior

Promotion is an essential element in the marketing mix. It is used by businesses to inform, influence and persuade customers to adopt the products and services they offer. Without promotion, business would be stagnant and lack substantial growth because the brands would have low visibility in the market. Moreover, today’s vast and assorted markets comprise of customers with different needs and varied behavior. So it is rarely possible for companies to satisfy all customers by treating them alike. Thus there arises a need to divide the market into segments having customers with similar traits/characteristics. After identifying appropriate market segments, firms can design differentiated promotional campaigns for each segment. At the same time there can be a mass market promotional campaign that reaches different segments with a fixed spectrum. Also since promotional effort resources are limited, one must use them judiciously. In this paper, we formulate mathematical programming problem under repeat purchase scenario, which optimally allocates mass promotional effort resources and differentiated promotional effort resources across the segments dynamically in order to maximize the overall sales obtained from multiple products of a product line under budgetary and minimum sales aspiration level constraint on each product under consideration in each segment. The planning horizon is divided into multi periods, the adoption pattern of each product in each segment is observed in every subinterval and accordingly promotional effort allocations are determined for the next period till we reach the end of planning period. The optimization model has been further extended to incorporate minimum aspiration level constraints on total sales for each product under consideration from all the segments taken together. The non linear programming problem so formulated is solved using differential evolution approach. A numerical example has been discussed to illustrate applicability of the model.

架空输电线路非平稳台风风场数值模拟与验证

为了实现架空输电线路非平稳台风风场模拟,考虑非平稳脉动风场的紊流强度和阵风因子特性及其影响,提出了一种架空输电线路非平稳台风风场的模拟方法。首先利用Spline插值方法生成时变平均风速,采用更新时变平均风速的谐波合成法模拟脉动风速,然后基于三向风谱功率密度函数,构建了台风风场的时变功率谱,计入风场空间上的相关性,获取了调制进化功率谱,并与模拟台风功率谱比较;最后以沿海500 kV架空输电线路为例,验证了台风模拟方法的合理性。研究结果表明:随着基本时距的增加,台风的非平稳因素所占比重越大;所提出的输电线路非平稳台风模拟方法合理有效。

利用近场法向声能流调控远场低频线谱噪声的自适应控制方法

针对水下结构远场低频辐射噪声的控制问题,提出了基于水下结构近场法向声能流的噪声自适应控制方法。该方法以结构近场的法向声能流作为控制物理量,利用有源控制系统自适应调节次级声源,抑制结构法向方向上的能量传播,实现远场低频辐射噪声控制。以圆柱壳为模型的试验结果表明,在1000~3000 Hz的频段内,相比于传统的以近场声压作为控制物理量的有源控制方法,能流法能够在保证总辐射声功率不升高的前提下,实现远场周向52.8%~76.3%区域内的噪声控制,且频率越低,降噪范围越广。

利用盲反卷积和混沌振子增强船舶辐射噪声解调线谱

针对经典解调方法中心频率、带宽选择困难和解调线谱受带外噪声干扰难以分辨等问题,提出采用盲反卷积和混沌振子方法抑制带外噪声,增强船舶噪声解调线谱。该方法通过Duffing振子预检宽带船舶噪声低频弱周期信号,随后将相应频率作为最小噪声幅值比反卷积(MNAD)方法的先验参数,利用MNAD方法自适应搜索解调频带得到可清晰分辨的高信噪比解调线谱。仿真和实测数据分析表明,该方法较经典解调方法和其他盲反卷积方法,可获取更佳的中心频率和滤波带宽,所得解调线谱的窄带信噪比DF值最高。

基于单矢量水听器的水中目标高分辨线谱增强方法

微弱信号检测一直是被动声呐系统远程探测面临的技术挑战。为了解决水下微弱信号条件下,即低信噪比(SNR)情况下,目标线谱检测难点问题,本文基于单矢量水听器信号接收,提出一种水下目标声压振速频域解卷积联合(CPVD)处理方法,可以实现线谱增强以及提高频域分辨率。采用单矢量水听器接收,保证声呐系统体积小,同时利用其具有指向性这一特点,可以抑制噪声,提高信号增益。在此基础上,通过CPVD算法对水中微弱信号进行线谱增强,实现有效检测。本文提出的方法克服了一些增强算法以及功率谱分析算法需要一定的先验知识以及频域线谱分辨率较低的缺点,从仿真分析和海试数据处理结果可以看出:本文所提出的基于单矢量水听器的水下目标线谱增强算法在低SNR条件下提高频率分辨率方面具有优势,为被动声呐系统微弱信号下的线谱检测提供有效算法。

船模水动力噪声及孔腔激励载荷试验与计算对比分析

开展某远洋客船光体船模水下噪声测试及带孔腔船模的水动力激励载荷测试,并进行孔腔处稳态和瞬态流场计算,孔腔处脉动压力频谱计算曲线与试验曲线吻合较好。孔腔脉动压力线谱频率测试值与经验公式频率计算值对比良好,说明该公式在一定情况下适用于船体条形格栅孔腔线谱频率的预估。采用统计能量法分析法计算光体船模中高频流激噪声,将流体激励以频率-波数功率谱的形式施加,可大大减少流场计算工作量,适合于工程快速预估。在工程一般范围内,阻尼损耗因子取值可导致噪声结果相差5.5 dB,说明阻尼损耗因子的取值会较大影响计算结果,有必要形成材料损耗因子随频率变化的数据库,为船舶噪声快速计算提供支撑。

基于FPGA的光谱仪动态基线补偿系统设计

线阵型CMOS光电图像传感器具有灵敏度高、光谱响应范围大、功耗低、体积小等优点,被广泛应用于便携式光谱仪的开发中。为解决由CMOS图像传感器暗电流变大而造成的光谱仪基线漂移问题,设计一种基于FPGA的光谱仪动态基线补偿系统。系统利用传感器预留像素计算得到该帧图像的基线值并进行实时反馈,使用高性能运算放大器、差分放大器设计电压跟随电路、基线补偿电路和单端转差分电路对CMOS模拟信号进行处理并进行高速A/D转换,选用精密DAC芯片实时动态反馈基线补偿值。最终测试结果表明,随着积分时间的不断增加,该设计始终能使光谱数据保持一个较低的基线水平。系统电路设计灵活、光谱采集准确、基线控制效果良好,比较适合检测微弱光谱信号。

多线谱干扰下的盔内语音通信降噪算法研究

航天服头盔内语音通信系统工作时,受到来自航天服自身的风机、泵、通风气流所产生的噪声影响,通话质量下降严重。传统降噪方法能有效抑制宽带噪声,但对线谱干扰的抑制较弱。文章以此为出发点,开展了多线谱干扰下的语音降噪算法研究,设计了一种自适应线谱检测方法,可有效识别线谱,定位其所处频带,在抑制宽带噪声的同时,进一步抑制线谱干扰。文章结合盔内实录噪声数据对算法进行了验证,结果显示,相对于传统降噪方式,文中方法对多线谱干扰的抑制能力更强,语音客观语音质量评估得分提高约6%。

基于时-频注意力机制网络的水声目标线谱增强

为提高被动声纳对水下低噪声安静型目标的检测,研究者开始关注基于深度学习的线谱增强方法,其中,基于LSTM的线谱增强网络由于同时具有时域和频域的非线性处理能力,具有很强的灵活性,然而其性能还需要进一步提升。为此,该文提出了基于时-频注意力机制的网络模型(TFA-Net),通过在LSTM模型的基础上同时增加时域注意力机制和频域注意力机制,充分利用了目标信号在时域和频域的双重重要特征,提升了对LOFAR谱的线谱增强效果。TFA-Net中的时域注意力机制利用LSTM隐藏状态之间的关联性,增加了模型在时域的注意力,频率注意力机制通过将深度残差收缩网络中收缩子网络的全链接层设计为1维卷积层,增加了模型在频域的注意力。相比于LSTM,TFA-Net具有更高的系统信噪比增益:在输入信噪比为–3 dB的情况下,将系统信噪比增益由2.17 dB提升到12.56 dB;在输入信噪比为–11 dB的情况下,将系统信噪比增益由0.71 dB提升到10.6 dB。仿真和实测数据的实验结果表明,TFA-Net可以有效提升LOFAR谱的线谱增强效果,解决低信噪比下水下目标的检测问题。

频率−波数域处理的线谱目标增强检测

针对复杂水下环境中的弱线谱目标检测问题,提出了一种基于频率−波数域处理的增强检测方法。该方法利用线谱目标的时空相干特性,构建适配于均匀线列阵处理的频率−波数域二维联合滤波器,通过自适应迭代方式实现对线谱目标的二维增强;在此基础上,将频率−波数域的主瓣检测累积结果作为方位谱的输出,实现对线谱目标的方位高分辨。仿真结果表明,该方法对带宽内信噪比−35 dB线谱目标的处理增益可达21.3 dB,方位分辨率在0.3°内。利用海上实测数据进行验证,该方法对线谱目标的处理增益可达8 dB。与CBF、SSED等宽带处理方法相比,该方法具有更高的线谱目标处理增益;与ALE、STJD等线谱处理方法相比,该方法具有更低的旁瓣起伏和更高的目标方位分辨率。