RESUMO

Nitrogen plays a key role in crop yields. Hence, farmers may apply excessive N fertilizers to crop fields, inducing environmental pollution. Crop N monitoring methods have been developed to improve N fertilizer management, most of them based on leaf or canopy optical-property measurements. However, sensitivity to environmental interference remains an important drawback. Electrical impedance has been applied to determine the physiological and nutritional status of plant tissue, but no studies related to plant-N contents are reported. The objective of this article is to analyze how the electrical impedance response of plants is affected by their N status. Four sets of lettuce (Lactuca sativa L.) with a different N-source concentrations per set were used. Total nitrogen and electrical impedance spectra (in a 1 to 100 kHz frequency range) were measured five times per set, three times every other day. Minimum phase angles of impedance spectra were detected and analyzed, together with the frequency value in which they occurred, and their magnitude at that frequency. High and positive correlation was observed between plant N content and frequency values at minimum phase angle with no significant variations detected between days of measurement. These results suggest that electrical impedance can be sensitive to plant N status.

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RESUMO

A New Adaptive Self-Tuning Fourier Coefficients Algorithm for Periodic Torque Ripple Minimization in Permanent Magnet Synchronous Motors (PMSM) Torque ripple occurs in Permanent Magnet Synchronous Motors (PMSMs) due to the non-sinusoidal flux density distribution around the air-gap and variable magnetic reluctance of the air-gap due to the stator slots distribution. These torque ripples change periodically with rotor position and are apparent as speed variations, which degrade the PMSM drive performance, particularly at low speeds, because of low inertial filtering. In this paper, a new self-tuning algorithm is developed for determining the Fourier Series Controller coefficients with the aim of reducing the torque ripple in a PMSM, thus allowing for a smoother operation. This algorithm adjusts the controller parameters based on the component's harmonic distortion in time domain of the compensation signal. Experimental evaluation is performed on a DSP-controlled PMSM evaluation platform. Test results obtained validate the effectiveness of the proposed self-tuning algorithm, with the Fourier series expansion scheme, in reducing the torque ripple.

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RESUMO

Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0-100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA) platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible.

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RESUMO

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.

RESUMO

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA).

RESUMO

Natural oleoresins rich in lycopene were obtained from two varieties of tomato (Zedona and Gironda) and their nutraceutical potential (antioxidant and antimutagenic capacity) was evaluated. Both oleoresins had a high content of lycopene, 58.33+/-1.67 mg/g (Zedona) and 63.97+/-0.80 mg/g (Gironda). The antioxidant activity (AA) of the oleoresins by beta-carotene method were 56.4-74.5% (Zedona) and 51-72.8% (Gironda), while when using the free radical stable 2,2-diphenyl-picryl-hydrazyl (DPPH) method, the antiradical activity (ARA) was determined to be 18.2-32.7% (Zedona) and 16.6-26.7% (Gironda) for the concentrations tested that of 200-400 microM equivalents of lycopene. The antimutagenic activity of the oleoresins was tested against aflatoxin B1 (AFB1) using the microsuspension assay, both varieties had a very high antimutagenic potential against AFB1 (60-66%).These results suggest the NCRT can be taken advantage to obtaining rich oleoresin in lycopene with a nutraceutical value.

Assuntos