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Erik Molino Minero Re

Erik Molino Minero Re

Contributions to the identification of impulsive signals generated by impacts.

Ph.D. Thesis title:

Contributions to the identification of impulsive signals generated by impacts.

Author:

Erik Molino Minero Re

Director:

Antonio Manuel, Mariano Lopez, Alfonso Carlosenya

Reading Date:

31/05/2010

Abstract:

 

In this thesis, the processing of impulsive signals generated by impacts between rigid bodies is investigated. One of the problems found when working with impacts is that their analysis is generally limited to indirect measurements: because collisions do not develop directly on the sensor, or it is not possible to install the sensor on the colliding bodies. This means that between the sensor and the point of impact there is a propagation medium that distorts the measured signal.
The main effort of this thesis focuses on the problem of how to compensate or to reduce the effects of such distortion. To do this, the following points have been investigated and developed:

  1. The study of the mechanical impact theory and the development of a mathematical model of the impact process between two rigid bodies. Through this study, the characteristics of the mpulsive signals generated by collisions are investigated.
  2. Definition of an experimental methodology for generating repeatable impacts and for determining the parameters of the mathematical model. The methodology is based on the design and implementation of an experimental prototype for generating controlled impacts between a test object and a sensorized impactor. To perform the experiments, a set of different test objects have been selected, cylinders made form aluminum, steel, bronze and brass in different sizes. Through a careful study and calculation of the experimental parameters, the validity of the mathematical model has been verified.
  3. Study of the indirect measurement problem, and proposal of a signal processing method, based on artificial neural networks, to determine an inverse filter in order to estimate the impacting signal (the impact force as a function of the time). This methodology adapts the training process to the characteristics of the impulsive signals that are generated during a collision, and that have been identified through the study and modeling of the impact process. The training uses real signals, which come from experimental impacts generated at different impacting velocities, and signals generated by a mathematical model of the impacting force.
  4. Proposal for a methodology to estimate the type of material and mass of test objects that collide. The problem found in this analysis is that  both, the objects and their responses, have similar characteristics. With the method proposed in this thesis, it is possible to identify correctly the characteristics of one of the objects. The procedure considers the extraction of parametersfrom the vibrating signals of the objects, and then uses a neural network to classify those parameters.
  5. Evaluation process of the proposed methods. To determine the validity of the processing methods described above, first, the selection of the most appropriate sensors to acquire these signals has been analyzed (this signals have a very short duration and very large bandwidth). Secondly, a measurement and acquisition system for impulsive signals has been implemented. The experimental results show the validity of the proposed methods. In the case of the model, its validity has been verified with data from different test objects, made from different materials. Also, the proposed method used to deal with the distortion due to the indirect measurement has been tested with experimental data, from impacts with different test objects, and the results show that it operates properly. Likewise, the proposed method to identify the type of material and mass of the test objects has generated satisfactory results.