考虑摆振的裂纹转子运动及阵发性混沌

在考虑含裂纹转子盘的摆振运动的情况 ,建立了盘的运动方程并进行数值求解。在裂纹很小时 ,横向振动是与转速相同的同频振动 ,而盘的摆振包含多种倍频成分。当裂纹较大时 ,横向振动会出现阵发性混沌。当摆振的幅值随时间不断增大到一定极限时 ,横向振动的稳定的周期或拟周期运动被打破 ,出现阵发性混沌。同时还出现通过拟周期进入混沌的现象。当裂纹很深时 ,会出现多个新的共振区 ,在此区域振幅迅速发散。盘的偏心距U的增大 ,会抑制混沌 ,使混沌运动锁定到周期运动     

转子裂纹识别仿真研究中的小波时频分析方法

谐波共振是识别转子裂纹的重要依据，但由于转子裂纹的弱激励、非线性、非平称稳等特性，导致利用传统信号处理方法不能准确有效地获取系统的谐波共振特性，从而难于识别出裂纹；小波时频分析方法是处理非线性、非平稳信号的强有力工具，将小波时频分析方法引入到裂纹识别的仿真研究中，基于建立的裂纹转子动力学模型，分析了利用小波时频分析方法识别裂纹的可行性。偏心激励转子裂纹故障识别的仿真研究表明了该方法的有效性。     

SD振子的设计及非线性特性实验研究初探

具有光滑与不连续转迁特征的SD振子发现和提出以来, 引起了广泛关注. 基于双稳系统大位移特征的测量法困难, SD振子的实验研究还未见报道. 该文提出并设计了具有SD振子系统光滑特征的非线性实验装置, 用实验的方法揭示由几何关系产生的强非线性系统的非线性动力学行为. 设计的非线性实验装置基本振动参数均有良好的可调性和可测量性, 对SD振子在不同频率及幅值的简谐激励作用下的非线性动力学响应进行了实验研究. 为克服大位移测量难题, 研究采用高速摄像机采集振子振动视频信号并进行分析. 结果表明, SD振子系统在一定的参数条件下会产生周期振动、周期5振动及混沌运动等复杂非线性动力学现象, 在相同实验参数条件下进行了数值仿真, 仿真结果与实验结果一致.      

HE PRELIMINARY INVESTIGATION ON DESIGN AND EXPERIMENTAL RESEARCH OF NONLINEAR CHARACTERISTICS OF SD OSCILLATOR

具有光滑与不连续转迁特征的SD振子发现和提出以来,引起了广泛关注.基于双稳系统大位移特征的测量法困难,SD振子的实验研究还未见报道.该文提出并设计了具有SD振子系统光滑特征的非线性实验装置,用实验的方法揭示由几何关系产生的强非线性系统的非线性动力学行为.设计的非线性实验装置基本振动参数均有良好的可调性和可测量性,对SD振子在不同频率及幅值的简谐激励作用下的非线性动力学响应进行了实验研究.为克服大位移测量难题,研究采用高速摄像机采集振子振动视频信号并进行分析.结果表明,SD振子系统在一定的参数条件下会产生周期振动、周期5振动及混沌运动等复杂非线性动力学现象,在相同实验参数条件下进行了数值仿真,仿真结果与实验结果一致.     

用弱周期摄动抑制软弹簧Duffing振子的混沌

本文研究了用弱周期摄动抑制弹簧Ｄｕｆｆｉｎｇ振子中的混沌。基于广度Ｍｅｌｎｉｋｏｖ方法可知，寻原振动系统呈现混沌悸态时，可以分别民受迫力谐波共振的线性项参数 励、非一性项参数激励和外激励３种弱周期摄动使混沌得以抑制。     

受迫Duffing振子中混沌运动的控制

本文研究了受迫Ｄｕｆｆｉｎｇ振子发生混沌运动时的控制问题，通过周期激振力、自适应控制和连续反馈控制来抑制、控制其中的混沌运动，使系统从混沌运动状态转变变到规则运动状态。     

准周期激励非对称Duffing振子存在混沌的必要条件

分别研究了非对称Ｄｕｆｆｉｎｇ振子的准周期受近和参数激励振动，分析了相应未受摄动Ｈａｍｉｌｔｏｎ系统的全局结构，应用推广的Ｍｅｌｎｉｋｏｖ方法给出了混沌存在的必要条件，考虑了增激励对混沌阈值的影响。     

含裂纹梁参数的谐响应识别

主要研究含裂纹梁在简谐激励作用下的动力特性,提出一种依据幅值变化对裂纹参数进行识别的新方法。首先,在振动过程中考虑裂纹的呼吸特性,以悬臂梁为例建立含裂纹梁的二维有限元模型,指出在一般激励频率下,其对应的幅值均是明显信号,可用来描述裂纹梁的动力特性。其次,当激励频率分别取无裂纹梁一阶频率的1/4和二阶频率的1/4时,幅值随裂纹参数的变化明显不同,可依据响应幅值的变化对裂纹参数进行识别。然后,利用曲面拟合技术绘出幅值变化曲面,对未知参数的裂纹进行识别,验证了该方法的有效性,并归纳出利用幅值变化对任意裂纹参数进行识别的基本步骤。最后,针对无裂纹梁频率计算可能存在误差的情况,分析识别方法的鲁棒性,结果显示即使最大误差为10%,该方法也能对裂纹参数进行准确识别。     

复合材料构件损伤类型识别的一种方法

复合材料构件在使用过程中会产生脱层、内部裂纹、裂缝等损伤，这些损伤会引起构件动态特性的变化。本文提出了通过测取构件的动态特性，结合波形分析和模式识别技术进行复合材料损伤检测和损伤类型识别的方法。在比较了飞机环境噪声信号和周期脉冲信号的优缺点的基础上，提出使用周期脉冲信号作为构件的激振信号，来进行构件动态特性的测量。本文的研究中制作了多种类型的损伤试件，进行了实验，已发现显著特征，能够对构件的多种类型损伤进行识别     

标准信号置换法控制Mathieu方程的混沌

用数值方法揭示了非线必ａｔｈｉｅｕ方程的一种特殊形式－在纵向简谐激励、非线笥阻尼和联接质量惯性力作用下的欧拉变曲问题的分岔现象和混沌行为，利用标准周期信号置换的混沌控制方法（即用标准周期信号置换混沌系统中的某个变量，使系统的混沌为为周期行为的方法），对这种混沌行为进行控制，得到受控后系统的稳定周期（包括低周期、高周期和准周期）振动的结果。     

An adaptive vibrational resonance method based on cascaded varying stable-state nonlinear systems and its application in rotating machine fault detection

A weak character signal with low frequency can be detected based on the mechanism of vibrational resonance (VR). The detection performance of VR is determined by the synergy of a weak low-frequency input signal, an injected high-frequency sinusoidal interference and the nonlinear system(s). In engineering applications, there are many weak fault signals with high character frequencies. These fault signals are usually submerged in strong background noise. To detect these weak signals, an adaptive detection method for a weak high-frequency fault signal is proposed in this paper. This method is based on the mechanics of VR and cascaded varying stable-state nonlinear systems (VSSNSs). Partial background noise with high frequency is regarded as a special type of high-frequency interference and an energy source that protrudes a weak fault signal. In this way, high-frequency background noise is utilized in a VSSNS. To improve the detection ability, manually generated high-frequency interference is injected into another VSSNS. The VSSNS can be transformed into a monostable state, bistable state or tristable state by tuning the system parameters. The proposed method is validated by a simulation signal and industrial applications. The results show the effectiveness of the proposed method to detect a weak high-frequency character signal in engineering problems.

     

Chaotic resonance in Izhikevich neural network motifs under electromagnetic induction

Nonlinear Dynamics - Chaotic resonance (CR) is the response of a nonlinear system to weak signals enhanced by internal or external chaotic activity (such as the signal derived from Lorenz system)....     

Experimental Observation of Chaotic Motion in a Rotor with Rubbing

This paper presents an application for chaotic motion identification in a measured signal obtained in an experiment. The method of state space reconstruction with delay co-ordinates with the dynamic evolution described by a map is used. Poincaré diagrams, correlation dimensions and Lyapunov exponents are obtained as tools for deciding about the existence of chaotic behaviour. The method is applied to measurements of the lateral displacement of a vertical rotor experiencing rubbing and in some signals chaos is observed. The work concludes that the possibility of chaotic motion is well determined with the observation of Poincaré diagrams and computation of Lyapunov exponents. Correlation dimensions computations, strongly influenced by noise, are not convenient tools for investigation of chaotic behaviour in signals generated by mechanical systems.     

A memristor-based chaotic oscillator for weak signal detection and its circuitry realization

Nonlinear Dynamics - A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics...     

Secure communication in wireless sensor networks based on chaos synchronization using adaptive sliding mode control

Due to resource constraints in wireless sensor networks and the presence of unwanted conditions in communication systems and transmission channels, the suggestion of a robust method which provides battery lifetime increment and relative security is of vital importance. This paper considers the secure communication in wireless sensor networks based on new robust adaptive finite time chaos synchronization approach in the presence of noise and uncertainty. For this purpose, the modified Chua oscillators are added to the base station and sensor nodes to generate the chaotic signals. Chaotic signals are impregnated with the noise and uncertainty. At first, we apply the modified independent component analysis to separate the noise from the chaotic signals. Then, using the adaptive finite-time sliding mode controller, a control law and an adaptive parameter-tuning method is proposed to achieve the finite-time chaos synchronization under the noisy conditions and parametric uncertainties. Synchronization between the base station and each of the sensor nodes is realized by multiplying a selection matrix by the specified chaotic signal which is broadcasted by the base station to the sensor nodes. Simulation results are presented to show the effectiveness and applicability of the proposed technique.     

微磁检测应力和塑性区的磁弹塑耦合理论

金属磁记忆微磁检测方法, 利用铁磁材料局部磁性状态的变化, 进行应力集中或塑性区域位置及程度的检测与评价. 面向微磁信号的定量理论分析可对其工程领域应用提供重要指导. 本文介绍铁磁材料微弱环境磁场下的磁弹塑性本构进展, 及其在微磁信号分析方面的应用. 力磁本构关系方面, 针对微磁检测弱磁化条件, 基于有效场理论构建了受弹塑性载荷铁磁材料的理想磁化本构的显式解析式, 并结合接近原理分析了恒定外加微弱磁场下应力-应变对材料磁化强度的影响. 检测信号分析方面, 基于弹性力学理论、静磁学理论和新建立的磁弹塑性本构关系, 建立并求解了微弱磁场下铁磁试件中弹性应力或塑性区诱导的表面磁信号的二维分析模型. 结合实验结果证实其在刻画弹塑性因素对微磁信号影响规律方面的能力, 并详细分析了微磁信号的特征量与局部弹性应力或塑性区的尺寸间的相关关系. 相比已有力磁本构关系, 本文建立的显式解析形式的理想磁化更加简洁, 有助于提升对力磁耦合效应的定量化理解和应用.      

An experimental digital communication scheme based on chaotic time-delay system

We develop an experimental system for secure communication with nonlinear mixing of information signal and chaotic signal of a time-delay system. The proposed scheme is based on programmable microcontrollers with digital transmission line. The scheme allows one to transmit and receive speech and musical signals in real time without noticeable distortion. A high quality of extraction of hidden information signal is achieved due to the use of digital elements in the scheme, which ensures identity of the parameters and high stability to noise. We study a possibility of hidden message extraction from a chaotic carrier by a third party in the case of mismatch of the receiver and transmitter parameters.     

HARMONIC COMPONENT EXTRACTION FROM A CHAOTIC SIGNAL BASED ON EMPIRICAL MODE DECOMPOSITION METHOD

A novel approach of signal extraction of a harmonic component from a chaotic signal generated by a Duffing oscillator was proposed. Based on empirical mode decomposition (EMD) and concept that any signal is composed of a series of the simple intrinsic modes, the harmonic components were extracted from the chaotic signals. Simulation results show the approach is satisfactory.     

Second-order coupled tristable stochastic resonance and its application in bearing fault detection under different noises

Bearing fault is the most likely to occur in mechanical fault, and stochastic resonance (SR), as a noise enhanced signal processing tool, can find mechanical faults as early as possible, so as to avoid larger problems. However, most of the existing research methods are based on the first-order Langevin equation. According to the previous studies of many scholars, the weak signal detection ability of the second-order system is better than that of the first-order system, and the coupled system also has better performance due to the addition of the control system. So, in order to detect the fault signal more easily, a second-order coupled tristable stochastic resonance system (SCTSR) based on the adaptive genetic algorithm (AGA) is proposed, it is an improvement on improving the first-order coupled tristable stochastic resonance system (FCTSR). First, based on the fourth-order Runge–Kutta algorithm (F-RK), the performances of monostable, bistable and tristable control systems to SCTSR are compared, it is verified that the monostable system has the best performance as SCTSR’s control system. Secondly, the equivalent potential function of SCTSR is derived, and the influences of each system parameters on it are researched. The output signal-to-noise ratio gain (SNRG) is chosen as a measure to verify that SCTSR’s performance is better than that of FCTSR, and the influences of parameters on SNRG are discussed. SCTSR and FCTSR are used to detect low-, high- and multi-frequency cosine signals combined with AGA. The simulation results are compared with the wavelet transform method, which proves the performance superiority of SR, and also prove that SCTSR is easier to detect weak signals and has a stronger de-noising ability. Finally, SCTSR and FCTSR are applied in bearing fault detection under Gaussian white noise and trichotomous noise. The results also prove that SCTSR can get larger peaks and SNRG, and it is easier to detect fault signals. This proves that SCTSR’s performance is superior that of other methods in bearing fault detection, and has better engineering application value.