Parameter-dependent Lyapunov functions for state-derivative feedback control in polytopic linear systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Less Conservative Control Design for Linear Systems with Polytopic Uncertainties via State-Derivative Feedback

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Experimental damage detection grammian matrix

Structural Health Monitoring (SHM) has diverse potential applications, and many groups work in the development of tools and techniques for monitoring structural performance. These systems use arrays of sensors and can be integrated with remote or local computers. There are several different approaches that can be used to obtain information about the existence, location and extension of faults by non destructive tests. In this paper an experimental technique is proposed for damage location based on an observability grammian matrix. The dynamic properties of the structure are identified through experimental data using the eigensystem realization algorithm (ERA). Experimental tests were carried out in a structure through varying the mass of some elements. Output signals were obtained using accelerometers.

Design of a control system using linear matrix inequalities for the active vibration control of a plate

The study of algorithms for active vibration control in smart structures is an area of interest, mainly due to the demand for better performance of mechanical systems, such as aircraft and aerospace structures. Smart structures, formed using actuators and sensors, can improve the dynamic performance with the application of several kinds of controllers. This article describes the application of a technique based on linear matrix inequalities (LMI) to design an active control system. The positioning of the actuators, the design of a robust state feedback controller and the design of an observer are all achieved using LMI. The following are considered in the controller design: limited actuator input, bounded output (energy) and robustness to parametric uncertainties. Active vibration control of a flat plate is chosen as an application example. The model is identified using experimental data by an eigensystem realization algorithm (ERA) and the placement of the two piezoelectric actuators and single sensor is determined using a finite element model (FEM) and an optimization procedure. A robust controller for active damping is designed using an LMI framework, and a reduced model with observation and control spillover effects is implemented using a computer. The simulation results demonstrate the efficacy of the approach, and show that the control system increases the damping in some of the modes.

Optimal placement of piezoelectric sensor/actuators for smart structures vibration control

Smart material technology has become an area of increasing interest for the development of lighter and stronger structures that are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains is a very important issue. For that purpose, smart material modeling, modal analysis methods, and control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Identification of Mechanical Systems through Kautz Filter

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On the performance of a dual-mode non-linear vibration energy harvesting device

The research trend for harvesting energy from the ambient vibration sources has moved from using a linear resonant generator to a non-linear generator in order to improve on the performance of a linear generator; for example, the relatively small bandwidth, intolerance to mistune and the suitability of the device for low-frequency applications. This article presents experimental results to illustrate the dynamic behaviour of a dual-mode non-linear energy-harvesting device operating in hardening and bi-stable modes under harmonic excitation. The device is able to change from one mode to another by altering the negative magnetic stiffness by adjusting the separation gap between the magnets and the iron core. Results for the device operating in both modes are presented. They show that there is a larger bandwidth for the device operating in the hardening mode compared to the equivalent linear device. However, the maximum power transfer theory is less applicable for the hardening mode due to occurrence of the maximum power at different frequencies, which depends on the non-linearity and the damping in the system. The results for the bi-stable mode show that the device is insensitive to a range of excitation frequencies depending upon the input level, damping and non-linearity.

A Comparison of the Effects of Nonlinear Damping on the Free Vibration of a Single-Degree-of-Freedom System

This article concerns the free vibration of a single-degree-of-freedom (SDOF) system with three types of nonlinear damping. One system considered is where the spring and the damper are connected to the mass so that they are orthogonal, and the vibration is in the direction of the spring. It is shown that, provided the displacement is small, this system behaves in a similar way to the conventional SDOF system with cubic damping, in which the spring and the damper are connected so they act in the same direction. For completeness, these systems are compared with a conventional SDOF system with quadratic damping. By transforming all the equations of motion of the systems so that the damping force is proportional to the product of a displacement dependent term and velocity, then all the systems can be directly compared. It is seen that the system with cubic damping is worse than that with quadratic damping for the attenuation of free vibration. [DOI: 10.1115/1.4005010]

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modeling and Experimental Aspects of Self-healing Bolted Joint through Shape Memory Alloy Actuators

Bolted joints are a form of mechanical coupling largely used in machinery due to their reliability and low cost. Failure of bolted joints can lead to catastrophic events, such as leaking, train derailments, aircraft crashes, etc. Most of these failures occur due to the reduction of the pre-load, induced by mechanical vibration or human errors in the assembly or maintenance process. This article investigates the application of shape memory alloy (SMA) washers as an actuator to increase the pre-load on loosened bolted joints. The application of SMA washer follows a structural health monitoring procedure to identify a damage (reduction in pre-load) occurrence. In this article, a thermo-mechanical model is presented to predict the final pre-load achieved using this kind of actuator, based on the heat input and SMA washer dimension. This model extends and improves on the previous model of Ghorashi and Inman [2004, "Shape Memory Alloy in Tension and Compression and its Application as Clamping Force Actuator in a Bolted Joint: Part 2 - Modeling," J. Intell. Mater. Syst. Struct., 15:589-600], by eliminating the pre-load term related to nut turning making the system more practical. This complete model is a powerful but complex tool to be used by designers. A novel modeling approach for self-healing bolted joints based on curve fitting of experimental data is presented. The article concludes with an experimental application that leads to a change in joint assembly to increase the system reliability, by removing the ceramic washer component. Further research topics are also suggested.

Vibration Attenuation in Rotating Machines Using Smart Spring Mechanism

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of Laser Fluorescence in the Monitoring of the Initial Stage of the De-/Remineralization Process: An in vitro and in situ Study

This study aimed to evaluate laser fluorescence (LF) for monitoring the initial stage of subsurface de- and remineralization (<150 mu m depth). Ninety-six sound blocks of bovine enamel, selected according to surface hardness (SH) and LF were used in two experimental studies, in vitro and in situ. In vitro, blocks were exposed to a demineralizing solution, then remineralized by pH cycling for 6 days. In situ, 10 volunteers wore acrylic palatal appliances, each containing 4 dental enamel blocks that were demineralized for 14 days by exposure to 20% sucrose solution. Following this treatment, blocks were submitted to remineralization for 1 week with fluoride dentifrice (1,100 mu g F/g). In both experiments, SH and LH were measured after demineralization and after remineralization. Further, enamel blocks were selected after the demineralization/remineralization steps for measurement of cross-sectional hardness and integrated loss of subsurface hardness (Delta KHN). SH and Delta KHN showed significant differences among the phases in each study. LF values for sound, demineralized and remineralized enamel were: 5.2 +/- 1.1, 8.1 +/- 1.2 and 5.6 +/- 0.8, respectively, in the in vitro study, and 5.3 +/- 0.3, 16.5 +/- 4.7 and 6.5 +/- 2.5, respectively, in the in situ study, values for demineralized enamel being significantly higher than for sound and remineralized enamel in both studies. However, LF was correlated with Delta KHN only in situ. LF was capable of monitoring de- and remineralization in early lesions in situ, when bacteria are presumably present in the caries lesion body, but is not correlated with mineral changes in bacteria-free systems. Copyright (C) 2009 S. Karger AG, Basel