Aurelio Dominguez-Gonzalez

FPGA-based fused smart-sensor for tool-wear area quantitative estimation in CNC machine inserts.

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used.

FPGA-Based Vibration Analyzer for Continuous CNC Machinery Monitoring With Fused FFT-DWT Signal Processing

The industry of machine tools keeps a constant progress that responds to the most demanding market requirements, such as production-time decreasing and zero-defect manufacturing. As part of this progress, sensors and monitoring instruments have been integrated on machine tools, improving computer numerical control (CNC) and monitoring during the manufacturing process. The vibrations are one of the most significant variables to be monitored on machine tools since they directly affect the end piece finishing, tool life expectancy, general machine-tool condition, current consumption, etc. Time domain, fast Fourier transform (FFT), and discrete wavelet transform (DWT) are techniques often used for vibration analysis, because they are computationally efficient for online implementation; unfortunately, it is difficult to find an instrument for vibration analysis that allows individually applying the time, FFT, and DWT techniques, and their fusion. Moreover, the lack of instruments with characteristics such as open architecture, low cost, parallel processing, and continuous online monitoring is remarkable. The contribution of this work consists of developing a vibration-analysis instrument based on the time, FFT, DWT, and DWT-FFT fusion techniques. The instrument is implemented into a low-cost field-programmable gate array with proprietary hardware signal-processing cores in parallel for achieving real-time and continuous online analysis. Experimentation is done to show the proposed methodology efficiency and the developed-instrument versatility, focusing on industrial control applications for CNC machine tools.

Vibration Control on Smart Civil Structures: A Review

Smart civil structures are capable of partially compensating the undesirable effects due to external perturbations; they sense and react to the environment in a predictable and desirable form through the integration of several elements, such as sensors, actuators, signal processors, and power sources, working with control strategies. This article will focus on reviewing the main control techniques applied to suppress vibrations in civil structures using smart materials, remarking on the advantages and disadvantages of smart actuators and control strategies tendencies in smart civil structures.

Filling Process in Injection Mold: A Review

This article refers to the injection molding process, mainly about the different methods used to solve the thermal and flow problems. The filling step is the phase in injection mold process in which more proprieties can change; this is why this article refers only to the filling phase. The article is divided in three parts: rheology of the polymers, in which the types and properties of polymers are reviewed. The second part presents the principal laws that take part. In the final part, techniques to solve equations of flow and heat transfer are presented including FEM and its hybrid variants.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node.

Improvement of the Injection Mold Process by Using Vibration Through a Mold Accessory

Recently, different authors agree that the way to optimize the flow in polymer melt is by changing the viscosity. There are several chemical products that help the above-mentioned, but these products change the molecular properties of the polymer. Recent nonchemical approaches use vibration techniques in the manufacturing process. The problems of the aforementioned approaches reside in the necessity of major modifications to the injection machine or the development of a new machine. The novelty of this research is to provide a mechanical apparatus to modify the viscosity of melted polymers by inducing vibrations without sacrificing the polymer properties in the injected parts, and which do not imply major modifications to the machine or molds. The developed apparatus is a simple mold accessory that makes easy for the end user the retrofitting of existing injection machines and it reduces the manufacturing costs. The improvement on the injection efficiency is tested with high-density polyethylene, reaching an improvement of 30% when excited at frequencies around 3 Hz.

Fractal dimension-based approach for detection of multiple combined faults on induction motors

Induction motors, key elements for industry, are susceptible to one or more faults at the same time; yet, they can keep working without affecting the process, but increasing the production costs. For this reason, a monitoring system that can efficiently diagnose the induction motor condition, even under multiple combined faults, is a demanding task. In this work, a methodology and its implementation into a field programmable gate array for an online and real-time monitoring system of multiple combined faults are presented. First, the fractal dimension approach, using the Katz algorithm, is introduced as a measure of variation of 3-axis startup vibration signals for the induction motor condition, considering that these signals describe changes on its dynamic characteristics due to the different faults. Then, an artificial neural network determines in an automatic way the induction motor condition according to the fractal dimension values. The obtained results show a higher overall efficiency than previous works for detecting broken rotor bars, outer-race bearing defects, unbalance, and their combinations, as well as a healthy condition.

Optimization of Q-factor of AFM cantilevers using genetic algorithms

Micro cantilever beams have been intensively used in sensing applications including to scanning profiles and surfaces where there resolution and imaging speed are critical. Force resolution is related to the Q-factor. When the micro-cantilever operates in air with small separation gaps, the Q-factor is even more reduced due to the squeeze-film damping effect. Thus, the optimization of the configuration of an AFM micro-cantilever is presented in this work with the objective of improving its Q-factor. To accomplish this task, we propose the inclusion of holes as breathing chimneys in the initial design to reduce the squeeze-film damping effect. The evaluation of the Q-factor was carried out using finite element model, which is implemented to work together with the squeeze-film damping model. The methodology applied in the optimization process was genetic algorithms, which considers as constraints the maximum allowable stress, fundamental frequency and spring constant with respect to the initial design. The results show that the optimum design, which includes holes with an optimal location, increases the Q-factor almost five times compared to the initial design.

Practical hysteresis model for magnetorheological dampers

The magnetorheological dampers have been extensively studied given their benefits such as fail-safe manner, low power requirements, relative fast response, and large force capacity and robustness. To take advantage of this remarkable device, a good model is required to accurately and effectively predict the real-time damping force in magnetorheological damper in order to apply the appropriate control actions to improve the response of the structural system. In this article, a new practical model is proposed to better characterize the hysteresis phenomenon in magnetorheological dampers. The model considers the displacement, velocity, and acceleration excitations as well as the current excitation as input variables and includes a reduced number of constant parameters to be determined. Since the displacement, velocity, and acceleration variables can be obtained in real time from adequate sensors, it is easy and practical to predict the current excitation required to generate the specific hysteresis force. The hysteresis damping forces predicted by the proposed model are validated with those experimentally obtained for different current, amplitude, and frequency of excitation, and a very good correlation has been observed.

Directional morphological approaches from image processing applied to automatic tool selection in computer numerical control milling machine

Automatic tool selection in milling operation has become a very important step in the manufacturing and planning processes for 2.5D piece machining. The main contribution of this article is the development of a new method based on directional morphological approaches, applied to automatic tool selection in computer numerical control milling machines for machining a 2.5D of a geometry piece provided of three-dimensional model of computer-aided design or from an image taken with other devices. First, the image is preprocessed by applying several image processing techniques. Later, mathematical morphology as erosion or dilation to create structural element with the shape of the cutting tool is used. The method displaces a structural element throughout the entire image with the values of the lengths of the piece boundary and the cutting tool to select the correct cutting tool and tool path. Besides, with the same structural element, the zig and zig-zag contour trajectories are obtained in standard computer numerical control code. Results from these experiments show that the method makes it possible to obtain good performance in automatic tool selection when several types of pieces are processed.