C. A. Kitio Kwuimy

Performance of a piezoelectric energy harvester driven by air flow

A turbulent wind source for possible energy harvesting is considered. To increase the amplitude of vibration, we apply a magnetopiezoelastic oscillator having a double well Duffing potential. The output voltage response of the system for different level of wind excitations is analyzed. The energy harvesting appeared to be the most efficient for the conditions close to the stochastic resonance region where the potential barrier was overcame.

Analysis of tristable energy harvesting system having fractional order viscoelastic material

A particular attention is devoted to analyze the dynamics of a strongly nonlinear energy harvester having fractional order viscoelastic flexible material. The strong nonlinearity is obtained from the magnetic interaction between the end free of the flexible material and three equally spaced magnets. Periodic responses are computed using the KrylovBogoliubov averaging method, and the effects of fractional order damping on the output electric energy are analyzed. It is obtained that the harvested energy is enhanced for small order of the fractional derivative. Considering the order and strength of the fractional viscoelastic property as control parameter, the complexity of the system response is investigated through the Melnikov criteria for horseshoes chaos, which allows us to derive the mathematical expression of the boundary between intra-well motion and bifurcations appearance domain. We observe that the order and strength of the fractional viscoelastic property can be effectively used to control chaos in the system. The results are confirmed by the smooth and fractal shape of the basin of attraction as the order of derivative decreases. The bifurcation diagrams and the corresponding Lyapunov exponents are plotted to get insight into the nonlinear response of the system.

Melnikov’s criteria, parametric control of chaos, and stationary chaos occurrence in systems with asymmetric potential subjected to multiscale type excitation

We consider the problems of chaos and parametric control in nonlinear systems under an asymmetric potential subjected to a multiscale type excitation. The lower bound line for horseshoes chaos is analyzed using the Melnikovs criterion for a transition to permanent or transient nonperiodic motions, complement by the fractal or regular shape of the basin of attraction. Numerical simulations based on the basins of attraction, bifurcation diagrams, Poincaré sections, Lyapunov exponents, and phase portraits are used to show how stationary dissipative chaos occurs in the system. Our attention is focussed on the effects of the asymmetric potential term and the driven frequency. It is shown that the threshold amplitude ∣γ(c)∣ of the excitation decreases for small values of the driven frequency ω and increases for large values of ω. This threshold value decreases with the asymmetric parameter α and becomes constant for sufficiently large values of α. γ(c) has its maximum value for asymmetric load in comparison with the symmetric load. Finally, we apply the Melnikov theorem to the controlled system to explore the gain control parameter dependencies.

Diagnostics of a Nonlinear Pendulum Using Computational Intelligence

A novel method has been presented in this paper for the diagnostics of nonlinear systems using the features of the nonlinear response and capabilities of computational intelligence. Four features of the phase plane portrait have been extracted and used to characterize the nonlinear response of a nonlinear pendulum. An artificial neural network has been created and trained using the numerical data for the estimation of parameters of a defective nonlinear pendulum setup. The results show that, with appropriately selected features of the nonlinear response, the parameters of the nonlinear system can be estimated with an acceptable accuracy.Copyright

Sequential Recurrence Analysis of Experimental Time Series of a Rotor Response with Bearing Outer Race Faults

Rolling elements bearings are one of the most common components used in expensive, high precision and critical machines such as gas turbines, rolling mills and gyroscopes. They can be subjected to various defects which could lead to catastrophic results. This includes inner and outer race defects and hence it is of interest to analyze the system response under such defects. A better understanding of the system performance under such defects can be beneficial when performing system diagnostics and system design. In this paper we are focused on the outer race defect and perform a comparative nonlinear time series analysis of a healthy system and a defective system. We consider various levels of outer race defects. The analysis is based on the recurrence properties of the system in its reconstructed state space. After determining the appropriate time lags through the average mutual information technique and the corresponding embedding dimensions through the false neighbor technique, we perform a sequential analysis of the system by subdividing the time series into bins and investigating the system response through recurrence quantification analysis parameters along with the entropy. This contributes to the enhancement of the science of diagnostics of outer race defects by analyzing the signature of various recurrence quantification analysis parameters as the system goes from a healthy state to a severely defective state.

Preliminary Diagnostics of Dynamic Systems From Time Series

The state space reconstruction technique was recognized by Edward N. Lorenz as “one of the most surprising developments in nonlinear dynamics” [1]. Nowadays, the technique is applied in various scientific areas for prediction, analysis and diagnostics. This paper aims to discuss the possibility of using the embedding dimension of a reconstructed state space of time series as a tool for preliminary diagnostics. After a short description and illustration of the method, the paper considers two case studies: a single degree of freedom (DOF) and a 2 DOF system. The results of the analysis help detect a class of structural defects, including defects connected to a coupling mechanism. There is clearly a huge potential of such an approach for diagnostics of complex machinery.Copyright

Recurrence and Joint Recurrence Analysis of Multiple Attractors Energy Harvesting System

The method of recurrence plots and joint recurrence plots are considered as tools for the nonlinear analysis of a dimensionless model of magnetoelastric piezoelectric energy harvester under wind flow excitation with low Reynolds number. The dynamics of the system is investigated by considering the bifurcation of the recurrence rate, the laminarity and the determinism and illustrations of system response are presented though the recurrence plots and phase diagrams. In order to enhance the efficiency of the system, a second degree of freedom is added to the mechanical part. The method of joint recurrence plot is used to analyze the global synchronization of the system. In this spirit, a feedback Master-Slave configuration is adopted to ensure optimal synchronized mechanical excursion and thus maximal electric voltage harvested in the electric load. Throughout the paper, attention is focussed on the effects of feedback coupling and mistuning parameter, as well as the relevance of the method of recurrence plots and joint recurrence plots in the analysis of such system. Specifically, it is shown that the joint recurrence plot synchronization parameter effectively detects domain of maximal output electric power as well as domain of out-of-phase motion leading to minimal output power.

Development of Recurrence Analysis for Fault Discrimination in Gears

Most of the current approaches in gear fault diagnostic analysis do not provide a clear indication for discrimination between various common faults. This is almost certainly because failure in gear systems is always accompanied with a complex dynamic response. The inherent nonlinearities in geared systems and additional nonlinearity due to faults conspire to make the diagnostics problem extremely complex. The main goal of this paper is to exploit the nonlinear response in an attempt to solve this challenging problem. We aim to demonstrate effective discrimination between four kinds of common defects in gears by utilizing the method of recurrence analysis. We consider a healthy system, a system with a single crack, a system with multiple cracks and a system with a missing tooth. Careful measurements are collected from an experimental set up which is a mock-up of a real industrial gear box system. We develop and apply recurrence plot analysis to this data. Our results show that recurrence analysis parameters such as recurrence rate, trapping time, entropy and maximal diagonal length can be very effective in successful discrimination of gear faults.Copyright

Recurrence Analysis of Experimental Time Series of a Rotor Response With Bearing Outer Race Faults

In this paper, the time series response of a rotor with bearing outer race faults is analyzed. The recurrence quantification analysis (RQA) parameters deduced from the recurrence plot (RP) of the system response are used to delve into characterization of the specific and overall behavior of the system. Attention is focused on the variation of the RQA parameters for healthy and defective states of the system. The results of this investigation are encouraging for further application of the method of RP in the diagnostics and analysis of bearing faults. In fact, it is shown that appropriate classification of the RQA can be effectively used to detect outer race faults and serve as a discriminant for fault severity.Copyright

Enhancing Energy Harvesting System Using Materials With Fractional Order Stiffness

A bistable mechanical system having fractional order restoring force is considered for possible energy harvesting. The effects of the fractional order stiffness α on the crossing well dynamics (large amplitude motion) and the output electrical power are analyzed. The harvested electric power appears to be efficient for deterministic and random excitation, for smallα (α � 2). High level noise intensity was found to reduce the output power in the region of resonance and surprisingly increases the outup in other region ofα. For larger enough amplitude of harmonic excitation this effect is realized in a stochastic resonance.