Aldemir Ap Cavalini

Vibration Attenuation in Rotating Machines Using Smart Spring Mechanism

This paper proposes a semiactive vibration control technique dedicated to a rotating machine passing by its critical speed during the transient rotation, by using a Smart Spring Mechanism (SSM). SSM is a patented concept that, using an indirect piezoelectric (PZT) stack actuation, changes the stiffness characteristics of one or more rotating machine bearings to suppress high vibration amplitudes. A Genetic Algorithm (GA) optimization technique is used to determine the best design of the SSM parameters with respect to performance indexes associated with the control efficiency. Additionally, the concept of ecologically correct systems is incorporated to this work including the PZT stack energy consumption in the indexes considered for the optimization process. Simulation carried out on Finite Element Method (FEM) model suggested the feasibility of the SSM for vibration attenuation of rotors for different operating conditions and demonstrated the possibility of incorporating SSM devices to develop high-performance ecologic control systems.

Numerical and Experimental Modal Control of Flexible Rotor Using Electromagnetic Actuator

The present work is dedicated to active modal control applied to flexible rotors. The effectiveness of the corresponding techniques for controlling a flexible rotor is tested numerically and experimentally. Two different approaches are used to determine the appropriate controllers. The first uses the linear quadratic regulator and the second approach is the fuzzy modal control. This paper is focused on the electromagnetic actuator, which in this case is part of a hybrid bearing. Due to numerical reasons it was necessary to reduce the size of the model of the rotating system so that the design of the controllers and estimator could be performed. The role of the Kalman estimator in the present contribution is to estimate the modal states of the system and to determine the displacement of the rotor at the position of the hybrid bearing. Finally, numerical and experimental results demonstrate the success of the methodology conveyed.

Stochastic modeling of flexible rotors

Flexible rotors are characterized by inherent uncertainties affecting the parameters that influence the dynamic responses of the system. In this context, the handling of variability in rotor dynamics is a natural and necessary extension of the modeling capability of the existing techniques of deterministic analysis. Among the various methods used to model uncertainties, the stochastic finite element method has received major attention, as it is well adapted for applications involving complex engineering systems of industrial interest. In the present contribution, the stochastic finite element method applied to a flexible rotor system, with random parameters modeled as random fields is presented. The uncertainties are modeled as homogeneous Gaussian stochastic fields and are discretized according to the spectral method by using Karhunen-Loeve expansions. The modeling procedure is confined to the frequency and time domain analyses, in which the envelopes of frequency response functions, the Campbells diagram and the orbits of the stochastic flexible rotor system are generated. Also, Monte Carlo simulation method combined with the Latin Hypercube sampling is used as stochastic solver. After the presentation of the underlying theoretical formulations, numerical applications of moderate complexity are presented and discussed aiming at demonstrating the main features of the stochastic modeling procedure of flexible rotor systems.

Model updating of a rotating machine using the self-adaptive differential evolution algorithm

Despite the good accuracy of finite element (FE) models to represent the dynamic behaviour of mechanical systems, practical applications show significant discrepancies between analytical predictions and experimental results, which are mostly due to uncertainties on the geometry configuration, imprecise material parameters and vague boundary conditions. Thereby, different approaches have been proposed to solve the inverse problems associated with the updating of FE models. Among them, the techniques based on minimization processes have shown to be some of the most promising ones. In this paper, a self-adaptive heuristic optimization method, namely the self-adaptive differential evolution (SADE), is evaluated. Differently from the canonical differential evolution (DE) algorithm, the SADE strategy is able to update dynamically the required parameters such as population size, crossover parameter and perturbation rate. This is done by considering a defined convergence rate on the evolution process of the algorithm in order to reduce the number of evaluations of the objective function. For illustration purposes, the SADE strategy is applied to the solution of typical mathematical functions. Additionally, the strategy is equally used to update the FE model of a rotating machine composed by a horizontal flexible shaft, two rigid discs and two unsymmetrical bearings. For comparison purposes, the canonical DE is also used. The results indicate that the SADE algorithm is a recommended technique for dealing with this kind of inverse problem.

Impedance-based fault detection methodology for rotating machines

Visual examination, ultrasonic tests, and dye penetrant inspection are some examples of nondestructive techniques widely used for crack detection in rotors. These methods have proved to be costly, since satisfactory results rely on detailed and periodic inspections. Significant research effort has been directed in recent years to online monitoring techniques, that is, based on vibration signals measured during rotor operation. However, most of them are able to only detect deep cracks. The uniqueness of this article relies on the possibility of detection of incipient transverse cracks in rotating shafts using the so-called, electromechanical impedance method. This method has become a promising tool for structural health monitoring of systems due to its sensitivity to small local damage. Basically, the method monitors changes in the electric impedance of piezoelectric transducers, bonded to (or embedded into) the host structure, through specific mathematic functions, the so-called damage metrics, to detect damage. This is possible because the electrical impedance of the transducer is directly related to the mechanical impedance of the structure. In this context, successful experimental tests were performed in a horizontal rotor supported by roller bearings. Lead zirconate titanate (PZT) patches were bonded along the shaft of the rotor in which saw cuts approximating a breathing transverse crack were machined. The technique was validated under different rotating speeds and unbalance conditions.

Reliability-Based Optimization Using Differential Evolution and Inverse Reliability Analysis for Engineering System Design

In this contribution, a new methodology based on a double-loop iteration process is proposed for the treatment of uncertainties in engineering system design. The inner optimization loop is used to find the solution associated with the highest probability value (inverse reliability analysis), and the outer loop is the regular optimization loop used to solve the considered reliability problem through differential evolution and multi-objective optimization differential evolution algorithms. The proposed methodology is applied to mathematical functions and to the design of classical engineering systems according to both mono- and multi-objective contexts. The obtained results are compared with those obtained by classical approaches and demonstrate that the proposed strategy represents an interesting alternative to reliability design of engineering systems.

Fuzzy Uncertainty Analysis of a Tilting-Pad Journal Bearing

This paper is dedicated to the analysis of uncertainties affecting the load capability of a 4-pad tilting-pad journal bearing, in which the load is applied between two pads (load on pad configuration; LOP). A well-known stochastic method has been extensively used to model uncertain parameters, the so-called Monte Carlo simulation. However, in the present contribution, the inherent uncertainties of the bearings’ parameters (i.e. the pad radius, the oil viscosity, and the radial clearance) are modeled by using a fuzzy logic based analysis. This alternative methodology seems to be more appropriate when the stochastic process that characterizes the uncertainties is unknown. The analysis procedure is confined to the load capability of the bearing, being generated by the envelopes of the pressure fields developed on each pad. The hydrodynamic supporting forces are determined by considering a nonlinear model, which is obtained from the solution of the Reynolds’ equation. The most significant results are associated to the changes in the dynamic behavior of the bearing because of the reaction forces that are modified according the uncertainties introduced in the system. Finally, it is worth mentioning that the uncertainty analysis in this case provides relevant information both for design and maintenance of tilting-pad hydrodynamic bearings.Copyright

Fuzzy Robust Design of Dynamic Vibration Absorbers

This paper is dedicated to the development of robust optimization and decision making techniques taking into account the uncertain parameters of linear and nonlinear dynamic vibration absorbers. In this case, novel approaches are proposed regarding different fuzzy logic optimization strategies. The uncertain parameters of the considered mechanical systems are treated as fuzzy variables. Consequently, the associated optimization problem is described as a fuzzy function that maps the fuzzy inputs. The proposed techniques are applied to the design of dynamic vibration absorbers. This numerical study illustrates the versatility and convenience of the proposed fuzzy logic optimization strategies.

ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO ENGINEERING SYSTEMS DESIGN

IN ENGINEERING SYSTEMS DESIGN, THEORETICAL DETERMINISTIC SOLUTIONS CAN BE HARDLY APPLIED DIRECTLY TO REAL-WORLD SCENARIOS. BASICALLY, THIS IS DUE TO MANUFACTURING LIMITATIONS AND ENVIRONMENTAL CONDITIONS UNDER WHICH THE REAL SYSTEM WILL OPERATE. THEREFORE, A SMALL VARIA-TION IN THE DESIGN VARIABLES VECTOR CAN RESULT IN A MEANINGFUL CHANGE ON THE THEORETICAL OPTIMAL DESIGN AS REPRESENTED BY THE MINIMIZATION OF THE CORRESPONDING VECTOR OF OBJECTIVE FUNCTIONS. IN THIS CONTEXT, IT IS IMPORTANT TO DEVELOP METHODOLOGIES THAT ARE ABLE TO PRODUCE SOLUTIONS (EVEN SUBOPTIMAL) THAT ARE LESS SENSITIVE TO PERTURBATIONS IN THE DESIGN VARIABLE VECTOR AND, CONSEQUENTLY, LEADING TO A ROBUST OPTIMAL DESIGN. IN THIS CONTRIBUTION, FIRST THE PROPOSED APPROACH IS TESTED ON VARIOUS MATHEMATICAL FUNCTIONS. THEN, THE METHODOLOGY IS APPLIED TO THE DESIGN OF TWO REPRESENTATIVE ENGINEERING SYSTEMS THROUGH MULTI-OBJECTIVE OPTIMIZATION USING THE FIREFLY COLONY ALGORITHM IN ASSOCIATION WITH THE EFFECTIVE MEAN CONCEPT IS PRESENTED. THE RESULTS OBTAINED DEMONSTRATE THAT THE DESIGN STRATEGY CONVEYED REPRESENTS AN INTERESTING ALTERNATIVE APPROACH TO OBTAIN ROBUST DESIGN FOR A NUMBER OF ENGINEERING APPLICATIONS.

Fault Detection in a Rotating Machine by Using the Electromechanical Impedance Method

Shaft crack detection is a very serious problem and machines that are suspected of having a crack should be carefully and continuously monitored. The importance attributed to this problem is addressed to the serious consequences when cracks are not early identified in rotating systems. Although there are no statistical studies that account for the exact dimension of the damage caused by cracks in rotating shafts, estimations reveal that approximately