No abstract

In the present work, a neuronal dynamic response prediction system is shown to estimate the response of multiple systems remotely without sensors. For this, a set of Neural Networks and the response to the step of a stable system is used. Six basic characteristics of the dynamic response were extracted and used to calculate a Transfer Function equivalent to the dynamic model. A database with 1,500,000 data points was created to train the network system with the basic characteristics of the dynamic response and the Transfer Function that causes it. The contribution of this work lies in the use of Neural Network systems to estimate the behavior of any stable system, which has multiple advantages compared to typical linear regression techniques since, although the training process is offline, the estimation can perform in real time. The results show an average 2% MSE error for the set of networks. In addition, the system was tested with physical systems to observe the performance with practical examples, achieving a precise estimation of the output with an error of less than 1% for simulated systems and high performance in real signals with the typical noise associated due to the acquisition system.

The agglomeration of particles is a process that modifies the physical properties of a product originally manufactured as a powder. During milk powder agglomeration of fluidized bed, resulting agglomerates are sufficiently porous to improve the solubility of the final product but, at the same time, their rigidity decreases and agglomerates can be destroyed during packing. The porosity and rigidity properties depend on both the volume and shape characteristics of the agglomerates. This paper presents a three-dimensional reconstruction technique based on a laser displacement sensor (LDS) applied to characterize milk agglomerates. This technique allows three-dimensional scanning to estimate particle volume and extract shape parameters such as: sphericity, elongation and flatness ratio, shape factor and aspect ratio. This technique was implemented using a mechatronic device with two degrees of freedom. The device is composed of an angular positioning system to rotate the agglomerate and a linear positioning system to displace the LDS. Experimental result allows agglomerates classification according to shape parameters.

This paper presents a new algorithm for compensation of the time interval error (TIE), applying an unbiased p-step predictive FIR filter (with and without prediction) to the signal global positioning system (GPS) SynPaQ III with problems of holdover, using as reference a rubidium atomic clock. The TIE refers to errors resulting in system stability. The error holdover is a problem that at present does not possess solution and the systems that present this type of error produce lines of erroneous synchronization in the signal of the GPS. The results from this study show that it is possible to emulate an atomic clock using a GPS receiver.

A harmonically driven oscillatory fully developed laminar flow through a rectangular cross-sectioned duct is analytically and experimentally studied. Experimental data is gathered at low cost with a relatively easy to implement, non-commercial, do-it-yourself (DIY) particle image velocimetry (PIV) system, which is proposed here as a flexible pedagogic resource for use in physics/engineering fluid mechanics undergraduate or graduate level education. As a DIY system, its components can be generic and/or open source based, making it useful in developing countries as well. An analytical model was developed, solved, and compared to the experimental data while the key features of the oscillatory flow were recognised and reciprocally represented by theory and experiments. This validated the proposed system as a low-cost alternative to the commercially available systems and it also confirmed it as a viable pedagogical resource. Consequently, the activities described could be straightforwardly implemented into undergraduate/graduate fluid mechanics pedagogical contexts, such as lecture aids, course projects, and laboratory practices. The proposed DIY-PIV system constitutes a teaching with technology pedagogical resource on fluid mechanics physics/engineering education that is also able to function as a limited/auxiliary or even state of the art research tool, according to the budget and the objectives.