Unknown bearing fault diagnosis under time-varying speed conditions and strong noise background

The bearing vibration signal shows strong non-stationary property under time-varying speed conditions. In addition, the weak bearing fault characteristic is often submerged in strong background noise. How to accurately extract the unknown fault characteristic from the non-stationary vibration signal is the primary problem of bearing fault diagnosis. Stochastic resonance has been proved to be an effective weak signal enhancement method. Therefore, an unknown bearing fault detection technology of speed variation is proposed, which breaks through the periodicity limitation of the classical stochastic resonance on the input signal. It enables stochastic resonance suitable for the enhancement of non-stationary fault signal. Firstly, the non-stationary vibration signal is processed by the computed order tracking to obtain the stationary signal in angular domain. To extract the potential feature information, the bearing imaginary fault order index is constructed from the angular domain order spectrum. Then, the resonance response at the imaginary fault order is obtained. Finally, the coherence resonance theory is introduced to judge the bearing fault pattern through the resonance factor index of response order spectrum. The proposed method overcomes the fuzzy mapping relationship between the signal symptom and the bearing fault caused by speed variation. The experimental data analysis results provide effective support for the proposed method.

     

人体平衡功能测试仪及定量指标研究

本文介绍了人体平衡功能测试仪的构造,工作原理及标定.同时应用概率统计原理对仪器测试数据和前庭功能试验的眼震时间进行相关分析。两种数据有良好的相关性,获得了人体平衡功能定量指标.     

Observer-based adaptive stabilization of the fractional-order chaotic MEMS resonator

Compared to the integer-order chaotic MEMS resonator, the fractional-order system can better model its hereditary properties and exhibit complex dynamical behavior. Following the increasing attention to adaptive stabilization in controller design, this paper deals with the observer-based adaptive stabilization issue of the fractional-order chaotic MEMS resonator with uncertain function, parameter perturbation, and unmeasurable states under electrostatic excitation. To compensate the uncertainty, a Chebyshev neural network is applied to approximate the uncertain function while its weight is tuned by a parametric update law. A fractional-order state observer is then constructed to gain unmeasured feedback information and a tracking differentiator based on a super-twisting algorithm is employed to avoid repeated derivative in the framework of backstepping. Based on the Lyapunov stability criterion and the frequency-distributed model of the fractional integrator, it is proved that the adaptive stabilization scheme not only guarantees the boundedness of all signals, but also suppresses chaotic motion of the system. The effectiveness of the proposed scheme for the fractional-order chaotic MEMS resonator is illustrated through simulation studies.     

Stability of equilibrium for an inverted two-link mathematical pendulum with critical tracking forces

We investigate nonlinear stability for equilibrium of a pendulum with viscoelastic components. The tracking force is chosen so that the matrix of the linearized part of the perturbed motion has two purely imaginary roots or one zero and one negative root. The other two roots are complex with negative real part. The boundary of the domain of stability is divided into “dangerous” and “safe” (in the sense of Bautin) zones. Translated from Prikladnaya Mekhanika, Vol. 35, No. 9, pp. 100–105, September, 1999.     

惯性平台稳定回路基于Backstepping的动态滑模控制(英文)

针对带不匹配不确定非线性干扰的惯性平台稳定回路跟踪控制问题,提出了基于backstepping的动态滑模控制方法。首先,建立了惯性平台稳定回路的等价模型,该模型由一个线性模型加上一个不确定的非线性函数组成。然后,基于backstepping方法设计了带渐近稳定滑模面的动态滑模控制器,解决了模型不匹配的问题,并提高了系统的鲁棒性。进而应用Lyapunov稳定性理论证明了所设计的控制器不仅能保证闭环系统的稳定性,而且可以通过选择适当的控制器参数来调整跟踪误差的收敛率。最后,仿真结果表明,基于backstepping的动态滑模控制方法与PID控制方法相比,提高了系统的跟踪精度,增强了鲁棒性。     

Optimal control and analysis of stabilometric tests with step disturbances of human sensory systems

Several optimal control problems are considered for a human motion model in the case of stabilometric tests when the posture of a person changes under a step disturbance. Such a situation is observed in the case of a galvanic vestibular stimulation or a vibration stimulation of the proprioceptors of shin muscles. Stabilometric tests with visual step disturbance are widespread in Russia. A characteristic feature of center of pressure (COP) trajectories for these tests is the presence of swings and overshoots. The test results are compared with the solutions of optimal control problems devoted to the repositioning of an inverted pendulum by a coupling torque. A speed-of-response problem and an optimal stabilization problem with a quadratic quality criterion are considered. The solutions to these optimum problems are compared with the results of stabilometric tests, which allows one to state a hypothesis on the sources of the above effects.     

A Distal Model of Congenital Nystagmus as Nonlinear Adaptive Oscillations

Congenital nystagmus (CN) is an incurable pathological spontaneous oscillation of the eyes with an onset in the first few months of life. The pathophysiology of CN is mysterious. There is no consistent neurological abnormality, but the majority of patients have a wide range of unrelated congenital visual abnormalities affecting either the cornea, lens, retina or optic nerve. In this theoretical study, we show that these eye oscillations could develop as an adaptive response to maximize visual contrast with poor foveal function in the infant visuomotor system, at a time of peak neural plasticity. We argue that in a visual system with abnormally poor high spatial frequency sensitivity, image contrast is not only maintained by keeping the image on the fovea (or its remnant) but also by some degree of image motion. Using the calculus of variations, we show that the optimal trade-off between these conflicting goals is to generate oscillatory eye movements with increasing velocity waveforms, as seen in real CN. When we include a stochastic component to the start of each epoch (quick-phase inaccuracy) various observed waveforms (including pseudo-cycloid) emerge as optimal strategies. Using the delay embedding technique, we find a low fractional dimension as reported in real data. We further show that, if a velocity command-based pre-motor circuitry (neural integrator) is harnessed to generate these waveforms, the emergence of a null region is inevitable. We conclude that CN could emerge paradoxically as an ‘optimal’ adaptive response in the infant visual system during an early critical period. This can explain why CN does not emerge later in life and why CN is so refractory to treatment. It also implies that any therapeutic intervention would need to be very early in life.     

Valuation of the Extraocular Effective Elastance on the Base of Dynamical Model

This paper makes an attempt to answer the question for the effective (functional) value of extraocular elastance. Here, this question is connected with the problem of rhythmicity mechanism of nystagmus phenomena. A likely dynamical model of the nystagmus horizontal motion is proposed by application of the energy and moment of momentum conservation laws to the extraocular muscle. The model is investigated qualitatively and numerically on the base of existing experimental data in the literature. On the base of analysis of obtained results a hypothesis is formulated that the nystagmus horizontal motions present self-oscillations of the considered system.     

Large Eddy Simulation and Extended Dynamic Mode Decomposition of Flow-Flame Interaction in a Lean Premixed Low Swirl Stabilized Flame

In this paper, numerical studies are reported on the effect of flow-flame interaction at large and medium scales and its impact on flame stabilization in a lean premixed low swirl stabilized methane/air flame. The numerical simulations are based on a large eddy simulation (LES) approach with a three-scalar flamelet model with equations for mixture fraction and fuel mass fraction and the level-set G-equation to account respectively for stratification of the mixture, fuel leakage at the trailing edge of the flame, and tracking of the flame front. Distinct frequencies, associated with the flame stabilization process, are identified from point data of LES in the outer and inner shear layers of the burner induced flow field. To understand the effect of the spatial structures related to the observed flow frequencies, a dynamic mode decomposition (DMD) is performed. Based on the analysis of LES data, frequency specific coherent flow structures are extracted along with associated flame structures through an extended version of DMD. The inner shear layer generated vortices are associated with recurring frequency specific coherent structures of both flow and flame and contribute to the flame stabilization in the outer regions of the flow.     

Combined control of fast attitude maneuver and stabilization for large complex spacecraft

In remote sensing or laser communication space missions, spacecraft need fast maneuver and fast stabilization in order to accomplish agile imaging and attitude tracking tasks. However, fast attitude maneuvers can easily cause elastic deformations and vibrations in flexible appendages of the spacecraft. This paper focuses on this problem and deals with the combined control of fast attitude maneuver and sta- bilization for large complex spacecraft. The mathematical model of complex spacecraft with flexible appendages and momentum bias actuators on board is presented. Based on the plant model and combined with the feedback controller, modal parameters of the closed-loop system are calculated, and a multiple mode input shaper utilizing the modal information is designed to suppress vibrations. Aiming at reducing vibrations excited by attitude maneuver, a quintic polynomial form rotation path planning is proposed with constraints on the actuators and the angular velocity taken into account. Attitude maneuver simulation results of the control systems with input shaper or path planning in loop are sepa- rately analyzed, and based on the analysis, a combined control strategy is presented with both path planning and input shaper in loop. Simulation results show that the combined control strategy satisfies the complex spacecraft＇s require- ment of fast maneuver and stabilization with the actuators＇ torque limitation satisfied at the same time.     

Robust dynamic surface control of nonlinear systems with prescribed performance

In this paper, a robust dynamic surface controller with prescribed performance for a class of nonlinear feedback systems is proposed. Utilizing the prescribed performance control (PPC), the prescribed steady state and transient performance for the tracking error of the original system can be ensured through the stabilization of a transformed system. The dynamic surface control procedure solves the mismatched uncertainties and the explosion of the complexity problem. The uncertainties can be eliminated by the constructed compensation signals of a low-pass filter. And it is proven in the performance analysis that the proposed controller is of low complexity and has improved system robustness. Simulation results verify the proposed approach.     

Intelligent tracking control of a DC motor driver using self-organizing TSK-type fuzzy neural networks

In this paper, a self-organizing Takagi–Sugeno–Kang (TSK) type fuzzy neural network (STFNN) is proposed. The self-organizing approach demonstrates the property of automatically generating and pruning the fuzzy rules of STFNN without the preliminary knowledge. The learning algorithms not only extract the fuzzy rule of STFNN but also adjust the parameters of STFNN. Then, an adaptive self-organizing TSK-type fuzzy network controller (ASTFNC) system which is composed of a neural controller and a robust compensator is proposed. The neural controller uses an STFNN to approximate an ideal controller, and the robust compensator is designed to eliminate the approximation error in the Lyapunov stability sense without occurring chattering phenomena. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived to speed up the convergence rates of the tracking error. Finally, the proposed ASTFNC system is applied to a DC motor driver on a field-programmable gate array chip for low-cost and high-performance industrial applications. The experimental results verify the system stabilization and favorable tracking performance, and no chattering phenomena can be achieved by the proposed ASTFNC scheme.     

Nonlinear adaptive task space control for a 2-DOF redundantly actuated parallel manipulator

A nonlinear adaptive (NA) controller in the task space is developed for the trajectory tracking of a 2-DOF redundantly actuated parallel manipulator. The dynamic model with nonlinear friction is established in the task space for the parallel manipulator, and the linear parameterization expression of the dynamic model is formulated. Based on the dynamic model, a new control law including adaptive dynamics compensation, adaptive friction compensation and error elimination items is designed. After defining a quadratic performance index, the parameter update law is derived with the gradient descent algorithm. The stability of the parallel manipulator system is proved by the Lyapunov theorem, and the convergence of the tracking error and the error rate is proved by the Barbalat’s lemma. The NA controller is implemented in the trajectory tracking experiments of an actual 2-DOF redundantly actuated parallel manipulator, and the experiment results are compared with the APD controller.     

基于浸入与不变原理的四旋翼姿态系统反步滑模控制

针对较大幅度外部不确定扰动下的四旋翼姿态稳定问题,设计了一种基于浸入与不变原理(ⅠⅠ)的自适应反步滑模控制器(ABSMC)。首先建立了未知大扰动下四旋翼姿态系统动力学模型,然后以横滚角子系统搭建为例,设计并应用了反步法和基于趋进率的滑模控制策略。在扰动估计误差流型设计中,融合了ⅠⅠ原理,即自适应率的选取实现了误差流型的不变和吸引,确保估计误差收敛到0。最后,对系统进行了稳定性分析和数字仿真。结果表明,在较大未知扰动情况下,融合ⅠⅠ原理方法后,经10 s所测跟踪误差平方的累加和仅为传统ABSMC方法的11.2%,控制精度大幅提高。     

Noise parameter identification for video tracking systems

The appearance of noises in output records is analyzed for the following movement video tracking systems: Qualisys Oqus, Vicon Bonita, and ARTTRACK2. The static and kinematic noise components are distinguished and their parameters are proposed to identify by comparing with model movements. The comparative evaluation of these systems shows their satisfactory quality in the registration of movements with a velocity up to 6 m/s and with impact interactions with a surrounding medium. The obtained noise samples are used to compare these video tracking systems.     

A finite element method study of Eulerian droplets impingement models

To compute droplet impingement on airfoils, an Eulerian model for air flows containing water droplets is proposed as an alternative to the traditional Lagrangian particle tracking approach. Appropriate boundary conditions are presented for the droplets equations, with a stability analysis of the solution near the airfoil surface. Several finite element formulations are proposed to solve the droplets equations, based on conservative and non‐conservative forms and using different stabilization terms. Numerical results on single and multi‐elements airfoils for droplets of mean volume diameter, as well as for a Langmuir distribution of diameters, are presented and validated against measured values. Copyright © 1999 John Wiley & Sons, Ltd.     

Visual hull method for tomographic PIV measurement of flow around moving objects

Tomographic particle image velocimetry (PIV) is a recently developed method to measure three components of velocity within a volumetric space. We present a visual hull technique that automates identification and masking of discrete objects within the measurement volume, and we apply existing tomographic PIV reconstruction software to measure the velocity surrounding the objects. The technique is demonstrated by considering flow around falling bodies of different shape with Reynolds number?~1,000. Acquired image sets are processed using separate routines to reconstruct both the volumetric mask around the object and the surrounding tracer particles. After particle reconstruction, the reconstructed object mask is used to remove any ghost particles that otherwise appear within the object volume. Velocity vectors corresponding with fluid motion can then be determined up to the boundary of the visual hull without being contaminated or affected by the neighboring object velocity. Although the visual hull method is not meant for precise tracking of objects, the reconstructed object volumes nevertheless can be used to estimate the object location and orientation at each time step.     

猎雷声纳基阵姿态稳定系统自适应反步法控制

针对带非线性摩擦力矩和负载扰动的高精度猎雷声纳基阵姿态稳定系统,提出了一种基于神经网络的自适应反步法控制方法。其中神经网络用于估计未知非线性摩擦力矩,进而设计反步法控制器和参数自适应律来对神经网络估计误差和负载扰动进行补偿。最后应用Lyapunov方法证明了所提出的自适应控制器能保证闭环系统的稳定性,并且可以通过选择适当的控制器参数来调整收敛率。仿真结果表明,基于神经网络的自适应反步法控制方法与PID控制相比,系统的动、静态性能指标及鲁棒性得到了全面的改善,与双闭环PID控制相比,跟踪精度提高了3倍多。     

基于动态神经元网络的激光陀螺输出误差模型

惯性敏感器误差补偿技术对提高武器装备的性能具有重要的意义,而误差补偿的关键在于误差模型的辨识。由于动态神经元网络是在前馈网络的节点引入前馈和反馈环节,理论上已证明其具有很强的动态逼近能力,可用来描述任意的非线性动态系统。根据惯性敏感器误差的动态特性,本探讨将动态神经元网络引入到激光陀螺误差建模中去,详细介绍了网络结构和对应的动态梯度算法。通过仿真算例说明,动态神经元网络在激光陀螺输出误差建模时具有一定的优点：网络收敛速度快、较好的跟踪性能、稳定性好。