一种基于新型间歇混沌振子的舰船线谱检测方法

为了实现低信噪比下未知频率的舰船辐射线谱的检测,对常规型间歇混沌振子列检测方法进行了改进,提出了一种基于适应步长型间歇混沌振子的信号检测方法.该方法可以只用一个Duffing振子,通过设定一组能够覆盖待测信号所在频段的求解步长序列,实现对未知频率、具有任意初相位的微弱周期信号的搜索检测.为进一步提高系统的弱信号检测性能,分析了Holmes型Duffing方程在不同频率内置策动力下对弱信号灵敏度的差异.综合理论分析和仿真研究结果给出了Duffing振子在内置策动力角频率为0.4 rad/s时对弱信号检测性能最佳,并据此对所采用的Duffing振子进行了优化;仿真结果表明,改进后的Duffing振子的弱信号检测性能提高了12 dB.最后将此方法应用于一组含有舰船辐射线谱的实船数据,结果表明此方法可以实现低信噪比下的未知频率微弱线谱检测.     

利用阵发混沌现象测定未知信号参数

利用Duffing方程对频率的极端敏感性产生阵发混沌现象,研究了一种利用该现象定量检测未知的微弱周期信号的各项参数的新方法,通过理论分析和实例仿真证明了该方法的可行性,并针对仿真结果提出了改进措施,提高了检测精度.     

Duffing振子微弱信号检测盲区消除及检测统计量构造

针对Duffing振子进行同频微弱信号检测时存在的检测盲区, 提出了一种策动力移相法予以消除. 结合微弱信号特性对检测盲区表达式进行分析, 得出了策动力与待测信号的“相差”位于检测盲区时的角度范围, 通过使策动力相位产生相移量π后实现对同频信号的检测, 实验证明了方法的可行性. 为了克服定性分析的不足和有效区分振子系统信号检测过程中出现的不同状态, 构造了一个基于类Halmiton系统的检测统计量, 并设计了基于该统计量的任意频率信号检测方法步骤, 方法的核心是以检测统计量出现极大值处所在的连续两个频点作为待测信号的频率范围. 在不同检测过程的仿真实验基础上, 给出了混沌、间歇混沌和大周期的检测统计量数值范围, 进而利用该数值范围作为判据实现了对任意频率信号的检测. 实验结果表明, 该方法不仅为系统状态提供了定量的判据准则, 而且提高了信号检测性能, 进一步完善了现有利用Duffing振子进行微弱信号检测的方法.     

光声池中微弱光声信号检测

大气中的污染源气体含量很少, 用光声光谱对其进行监测得到的光声信号极其微弱. 本文首先分析微弱信号产生机理, 在分析Holmes Duffing方程的基础上, 提出了适合光声池微弱信号检测的变尺度差分方法. 该方法通过对信号进行尺度变换, 再做差分来检测微弱信号. 理论分析和实验表明, 变尺度差分方法能很好地抑制系统相空间的共模噪声, 而且能很好地凸显混沌状态临界值. 变尺度差分方法测出的信号相对误差都小于5%, 说明其可以用于较高频率、 相位和频率都未知的微弱光声信号幅值检测. 关键词： 光声光谱 微弱信号 幅值 Duffing     

基于扩展型Duffing振子的局部放电信号检测方法研究

目前, 小波阈值去噪法、数字滤波法、傅里叶频域变换法等常用的微弱信号检测方法所能达到的最低检测信噪比为-10 dB, 而双向环形耦合Duffing振子能达到的最低检测信噪比为-20 dB. 但是, 现场检测时常常会出现更低信噪比的放电脉冲信号, 因此现有检测方法就很难满足信号检测的实际需求. 为了有效解决该难题, 研究了一种扩展型Duffing振子的微弱脉冲信号检测的新方法. 该方法的主要思想是使用广义时间尺度变换, 将Duffing振子模型变换为扩展型Duffing振子模型, 有效扩展了微弱信号的频率检测范围. 仿真结果表明, 扩展型Duffing振子不仅具有良好的噪声免疫特性, 而且能有效检测到信噪比低至-40 dB的局部放电微弱脉冲信号, 进一步扩展了现有Duffing振子微弱信号检测方法的检测范围和应用领域.     

二维Duffing振子的大参数随机共振及微弱信号检测研究

研究了二维Duffing振子在绝热近似条件下的随机共振特性,针对大参数条件,提出二维Duffing振子的大参数随机共振,并探讨二维Duffing振子变尺度随机共振和参数调节随机共振的关联性,揭示大参数条件下Duffing振子随机共振检测特征信号的机理,扩展其在微弱信号检测领域中的应用.     

非谐射频阱中离子云系统的精确周期解

射频阱中离子云与检测场的相互作用由周期驱动的Duffing方程描述.本文报道了该方程的一个精确的周期解,它描述了阱参数和外场对离子云周期运动的影响.结果表明,在各参变量满足周期解条件时,离子的运动频率为外场频率的三分之一,运动振幅分别与外场频率、振幅以及阱频正相关,与离子阱的非谐参数反相关.     

脉冲激励下环形耦合Duffing振子间的瞬态同步突变现象

研究非周期信号激励下Duffing振子动力学行为变化特征时,发现处于倍周期分岔的环形耦合Duffing振子系统,在一定的参数条件下,脉冲信号能引起其中一个振子与其他振子运动轨迹间出现短暂失同步的现象即瞬态同步突变现象.利用这种现象可以快速检测出强噪声背景中的微弱脉冲信号,从而扩展了现有的Duffing振子对非周期信号的检测范围及应用领域. 关键词： 瞬态同步突变 微弱信号检测 脉冲信号 Duffing振子     

基于耦合Duffing振子的局部放电信号检测方法研究

以双向环形耦合Duffing振子系统为对象, 研究脉冲信号激励下耦合振子间动力学行为变化特征时, 发现其与单向环形耦合Duffing振子系统类似, 在一定的参数条件下, 脉冲信号能引起其中一个振子与其他振子运动轨迹间出现短暂失同步的现象即瞬态同步突变现象. 基于这种现象, 提出了一种微弱脉冲信号检测的新方法, 用于检测强噪声背景中的局部放电脉冲信号. 实验测试表明, 利用本文方法对不同放电电极的局部放电脉冲信号进行检测时, 在低信噪比条件下可取得良好的检测效果, 进而扩展了现有的Duffing振子对非周期信号的检测范围及应用领域. 关键词： 耦合Duffing 振子 微弱信号检测 瞬态同步突变 局部放电脉冲信号     

级联双稳Duffing系统的随机共振研究

研究了级联双稳Duffing系统的随机共振特性, 证明级联双稳Duffing系统变尺度系数、阻尼比和级数等参数的适当调节, 不仅可实现大参数信号的级联随机共振, 而且可优化单级双稳Duffing系统的随机共振特征, 即参数调节的级联双稳Duffing系统能实现比单级双稳Duffing系统更好的随机共振输出. 此外, 级联双稳Duffing系统对方波信号具有良好的滤波整形作用, 可用于实现含噪方波信号的波形恢复. 关键词： 级联双稳Duffing系统 随机共振 变尺度 参数调节     

Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator

The conventional Duffing oscillator weak signal detection method, which is based on a strong reference signal, has inherent deficiencies. To address these issues, the characteristics of the Duffing oscillator's phase trajectory in a smallscale periodic state are analyzed by introducing the theory of stopping oscillation system. Based on this approach, a novel Duffing oscillator weak wide-band signal detection method is proposed. In this novel method, the reference signal is discarded, and the to-be-detected signal is directly used as a driving force. By calculating the cosine function of a phase space angle, a single Duffing oscillator can be used for weak wide-band signal detection instead of an array of uncoupled Duffing oscillators. Simulation results indicate that, compared with the conventional Duffing oscillator detection method,this approach performs better in frequency detection intervals, and reduces the signal-to-noise ratio detection threshold,while improving the real-time performance of the system.     

Duffing振子微弱信号检测方法研究

在前期实验工作的基础上,从理论分析的角度,提出了利用Duffing振子从大周期态向混沌态的相变 作为判据的微弱周期信号检测方法,给出了检测原理,并论证了其可行性;从过渡带影响和检测概率两方面 将该方法与传统的检测方法进行了比较分析,并对两者的检测性能进行了仿真对比.分析和仿真结果都显示,相同条件下, Duffing振子从大周期态向混沌态的相变受过渡带影响更小,所提方法具有更好的检测性能. 实验数据还表明, Duffing振子检测微弱信号只能基于单向相变, 利用阵发混沌进行频差检测只适用于待测信号信噪比较高的情况. 关键词： Duffing 混沌 检测 过渡带     

Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBCLFM) signals require prior knowledge, are computationally complex, and exhibit poor performance at low signal-to-noise ratios(SNRs). To overcome these problems, a blind parameter estimation method based on a Duffing oscillator array is proposed. A new relationship formula among the state of the Duffing oscillator, the pseudo-random sequence of the PRBC-LFM signal, and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived, providing the theoretical basis for blind parameter estimation. Methods based on amplitude method, short-time Fourier transform method, and power spectrum entropy method are used to binarize the output of the Duffing oscillator array, and their performance is compared. The pseudo-random sequence is estimated using Duffing oscillator array synchronization, and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency. Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 d B.     

A new approach to detecting weak signal in strong noise based on chaos system control

In this paper, a chaos system and proportional differential control are both used to detect the frequency of an unknown signal. In traditional methods the useful signal is obtained through the Duffing equation or other chaotic oscillators. But these methods are too complex because of using a lot of chaos oscillators. In this paper a new method is presented that uses the R?ssler equation and proportional differential control to detect a weak signal frequency. Substituting the detected signal frequency into the R?ssler equation leads the R?ssler phase state to be considerably changed. The chaos state can be controlled through the proportional differential method. Through its phase diagram and spectrum analysis, the unknown frequency is obtained. The simulation results verify that the presented method is feasible and that the detection accuracy is higher than those of other methods.     

The application of Duffing oscillator in characteristic signal detection of early fault

This paper presents a study of application of Duffing oscillator for extracting the features of early mechanical failure signal. By analysis of global solutions and bifurcation set of Duffing equation, we conclude that the bifurcation threshold, which corresponds to the maximum orbit outside the homoclinic orbit of Duffing equation, can be used to detect weak signal, such as the characteristic signal of early machinery fault. Therefore, the Duffing oscillator is suitable to be a model for weak signal detection, although some relative aspects for practical uses should be considered carefully. In this paper, the strategies for testing whether the weak signal is exists and how to estimate its amplitude are discussed in detail. Moreover, an example is presented here to demonstrate the utility of this method by analyzing the early rub-impact signal appearing in a rotor. The results show that the method is effective for early detection of fault described by specific periodic-motion components such as rub-impact fault of rotor in aeroengine.     

Research on detection method of multi-frequency weak signal based on stochastic resonance and chaos characteristics of Duffing system

Weak signal detection has been widely used in many fields such as military and national economy. Aiming at the problem that the traditional stochastic resonance (SR) method can’t obtain the signal amplitude when detecting weak signals, the frequency and amplitude of the weak signal are obtained by combining the SR and chaos characteristics of the two-dimensional Duffing system. Firstly, the effects of two-dimensional Duffing system parameters a, b, k, noise intensity D on the Kramers rate and signal-to-noise ratio (SNR) are analyzed under the Gaussian white noise environment. The results show that the damping ratio K can hinder the SR effect of the system to some extent. Secondly, to solve the misjudgment of the state method of the weak signal amplitude in the detection, the Lyapunov exponent is used to assure the threshold's range, and the threshold of the chaotic critical state is found. Finally, the paper gives the processes of frequency and amplitude detection of multiple high-frequency signals, which realizes the effective detection of the frequency and amplitude of multiple high-frequency signals in a Gaussian white noise environment, and successfully applies the method to the accurate detection of boundary voltage amplitude in electrical impedance tomography.     

基于量子粒子群算法的自适应随机共振方法研究

为提升随机共振理论在微弱信号检测领域中的实用性,以随机共振系统参数为研究对象,提出了基于量子粒子群算法的自适应随机共振方法.首先将自适应随机共振问题转化为多参数并行寻优问题,然后分别在Langevin系统和Duffing振子系统下进行仿真实验.在Langevin系统中,将量子粒子群算法和描点法进行了寻优结果对比;在Duffing振子系统中,Duffing振子系统的寻优结果则直接与Langevin系统的寻优结果进行了对比.实验结果表明:在寻优结果和寻优效率上,基于量子粒子群算法的自适应随机共振方法要明显高于描点法;在相同条件下,Duffing振子系统的寻优结果要优于Langevin系统的寻优结果;在两种系统下,输入信号信噪比越低就越能体现出量子粒子群算法的优越性.最后还对随机共振系统参数的寻优结果进行了规律性总结.