Marco Antonio Meggiolaro

Fatigue life and crack path predictions in generic 2D structural components

This paper proposes a reliable and cost-effective two-phase methodology to predict crack propagation life in generic two-dimensional (2D) structural components. First, the usually curved fatigue crack path and its stress-intensity factors are calculated at small crack increments in a specialized finite-element software, using automatic remeshing algorithms, special crack tip elements and appropriate crack increment criteria. Then, the computed stress-intensity factors are transferred to a powerful general-purpose fatigue-design program, which has been designed to predict both initiation and propagation fatigue lives by means of classical design methods. Particularly, its crack propagation module accepts any KI expression and any crack growth rate model, considering sequence effects such as overload-induced crack retardation to deal with 1D and 2D crack propagation under variable amplitude loading. Non-trivial application examples compare the numerical simulation results with those measured in physical experiments. � 2002 Elsevier Science Ltd. All rights reserved.

Activation of a mobile robot through a brain computer interface

This work presents the development of a brain computer interface as an alternative communication channel to be used in Robotics. It encompasses the implementation of an electroencephalograph (EEG), as well as the development of all computational methods and necessary techniques to identify mental activities. The developed brain computer interface (BCI) is applied to activate the movements of a 120lb mobile robot, associating four different mental activities to robot commands. The interface is based on EEG signal analyses, which extract features that can be classified as specific mental activities. First, a signal preprocessing is performed from the EEG data, filtering noise, using a spatial filter to increase the scalp signal resolution, and extracting relevant features. Then, different classifier models are proposed, evaluated and compared. At last, two implementations of the developed classifiers are proposed to improve the rate of successful commands to the mobile robot. In one of the implementations, a 91% average hit rate is obtained, with only 1.25% wrong commands after 400 attempts to control the mobile robot.

On the dominant role of crack closure on fatigue crack growth modeling

AbstractCrack closure is the most used mechanism to model thickness and load interaction effects on fatigue crack propagation. Butassuming it is the only mechanism is equivalent to suppose that the rate of fatigue crack growth da/dN is primarily dependent on K eff =K max K op , not on K. But this assumption would imply that the normal practice of using da/dN× K curves measuredunder plane-stress conditions (without considering crack closure) to predict the fatigue life of components working under plane-strain could lead to highly non-conservative errors, because the expected fatigue life of “thin” (plane-stress dominated) structurescould be much higher than the life of “thick” (plane-strain dominated) ones, when both work under the same stress intensity rangeand load ratio. However, crack closure cannot be used to explain the overload-induced retardation effects found in this work underplane-strain, where both crack arrest and delays were associated to anincrease in K eff . These results indicate that the dominantrole of crack closure in the modeling of fatigue crack growth should be reviewed.2003 Elsevier Ltd. All rights reserved.

An analytical method to eliminate the redundant parameters in robot calibration

Model based error compensation of a robotic manipulator, also known as robot calibration, requires the identification of its generalized errors. These errors are found from measured data and used to predict, and compensate for, the end-point errors as a function of configuration. However, the generalized error formulation introduces redundant parameters, often non-intuitive, that may compromise the robustness of the calibration. The existing numerical methods to eliminate such errors are formulated on a case-by-case basis. In this paper, the general analytical expressions and physical interpretation of the redundant parameters are developed for any serial link manipulator, expressed through its Denavit-Hartenberg parameters. These expressions are used to eliminate the redundant parameters from the error model of any manipulator prior to the identification process, allowing for systematic robot calibration with improved accuracy. Simulations are conducted to verify the theory presented in the paper.

Fatigue life prediction of complex 2D components under mixed-mode variable amplitude loading

Accurate residual fatigue life predictions under variable amplitude (VA) loading are essential to maximize the time between the required inspections in defect-tolerant structures. However, this is not a trivial task for real structural components, in which cracks may change direction as they grow due to mixed-mode loading. Such curved crack paths can be predicted using finite element (FE) techniques, but this approach is not computationally efficient to predict the residual life, because it would require timeconsuming remeshing of the entire structure after each rain-flow counted load event under VA loading. In this work, a two-phase methodology that is both precise and cost-effective is applied to solve this problem. First, the fatigue crack path and stress intensity factors KI and KII are calculated in a specialized (global) FE program using fixed crack increments, requiring only relatively few remeshing steps. Then, an analytical expression is fitted to the calculated KI(a) values, where a is the length along the crack path, and exported to a companion fatigue design program to predict the crack propagation life by the local approach, considering load interaction effects such as crack retardation or arrest after overloads. This two-phase methodology is experimentally validated by fatigue tests on compact tension specimens, modified with holes positioned to attract or to deflect the cracks.  2003 Elsevier Ltd. All rights reserved.

Achieving fine absolute positioning accuracy in large powerful manipulators

High accuracy is generally unattainable in manipulators capable of producing high task forces due to such factors as high joint, actuator, and transmission friction and link elastic and geometric distortions. A method called base sensor control has been developed to compensate for nonlinear joint characteristics, such as high joint friction, to improve system repeatability. A method to identify and compensate for system geometric and elastic distortion positioning errors in large manipulators has also been proposed to improve absolute accuracy in systems with good repeatability using a wrist force/torque sensor. This technique is called geometric and elastic error compensation. Here, it is shown experimentally that the two techniques can be effectively combined to enable strong manipulators to achieve high absolute positioning accuracy while performing tasks requiring high forces.

Information based indoor environment robotic exploration and modeling using 2-D images and graphs

As the autonomy of personal service robotic systems increases so has their need to interact with their environment. The most basic interaction a robotic agent may have with its environment is to sense and navigate through it. For many applications it is not usually practical to provide robots in advance with valid geometric models of their environment. The robot will need to create these models by moving around and sensing the environment, while minimizing the complexity of the required sensing hardware. Here, an information-based iterative algorithm is proposed to plan the robots visual exploration strategy, enabling it to most efficiently build a graph model of its environment. The algorithm is based on determining the information present in sub-regions of a 2-D panoramic image of the environment from the robots current location using a single camera fixed on the mobile robot. Using a metric based on Shannons information theory, the algorithm determines potential locations of nodes from which to further image the environment. Using a feature tracking process, the algorithm helps navigate the robot to each new node, where the imaging process is repeated. A Mellin transform and tracking process is used to guide the robot back to a previous node. This imaging, evaluation, branching and retracing its steps continues until the robot has mapped the environment to a pre-specified level of detail. The set of nodes and the images taken at each node are combined into a graph to model the environment. By tracing its path from node to node, a service robot can navigate around its environment. This method is particularly well suited for flat-floored environments. Experimental results show the effectiveness of this algorithm.

Mental Tasks Classification for a Noninvasive BCI Application

Mapping brain activity patterns in external actions has been studied in recent decades and is the base of a brain-computer interface. This type of interface is extremely useful for people with disabilities, where one can control robotic systems that assist, or even replace, non functional body members. Part of the studies in this area focuses on noninvasive interfaces, in order to broaden the interface usage to a larger number of users without surgical risks. Thus, the purpose of this study is to assess the performance of different pattern recognition methods on the classification of mental activities present in electroencephalograph signals. Three different approaches were evaluated: Multi Layer Perceptron neural networks; an ensemble of adaptive neuro-fuzzy inference systems; and a hierarchical hybrid neuro-fuzzy model.

An Evaluation of Elber-Type Crack Retardation Models

In this work, a review of plasticity induced crack closure is presented, along with models proposed to quantify its effect on the subsequent crack growth rate. The stress state dependence of crack closure is discussed. Overloadinduced retardation effects on the crack growth rate are considered, based on the crack closure idea, and improvements to the traditional models are proposed to account for crack arrest and crack acceleration after compressive underloads. Using a general-purpose fatigue design program, the models and the proposed modifications are compared with experimental results from various load spectra, and with simulated histories illustrating their main features.

A rough terrain traction control technique for all-wheel-drive mobile robots

Traction control is a critical aspect of mobile robots that need to traverse rough terrain, avoiding excessive slip - which may cause the terrain to collapse locally and trap the robot wheels - and guaranteeing an adequate trajectory and speed control while reducing the power requirements. Traction control of all-wheel-drive robots in rough terrain was originally motivated by space exploration, such as in the case of the Mars Exploration Rovers. However, such technology is also needed in our planet, in particular in the Amazon region. This is the case of the Hybrid Environmental Robot (HER), a 4-wheel-drive mobile robot with independent suspensions, under development at CENPES/PETROBRAS. This robot is susceptible to changing terrain conditions, facing slippery soil and steep slopes. In this work, a new traction control scheme is proposed to allow HER to maintain a desired velocity while minimizing power requirements and slippage, considering motor saturation and avoiding flip-over dynamic instability. The proposed technique is based on a redundant computed torque control scheme, analytically optimized to minimize power requirements. Simulations are performed for rough terrain conditions with 2D-profile, considering the general case of different tire-terrain contact angles at each wheel. It is found that the control scheme is able to analytically predict in real time the ideal torques required by each independent wheel to maintain the desired speed, even on very rough terrain, minimizing when possible the power consumption. The method is applicable to the 3D case as long as the roll angle of the robot chassis does not vary too much compared to the robot pitch angle.