As one of the key parameters in biological and chemical reactions, glucose concentration objectively reflects the characteristics of reactions, so the real-time monitoring of glucose concentration is important in the field of biochemical. Meanwhile, the influence from temperature should be considered. The fiber sensors have been studied extensively for decades due to the advantages of small size, immunity to electromagnetic interference and high sensitivity, which are suitable for the application of biochemical sensing.
A long period fiber grating (LPFG) sensor induced by electric-arc discharge has been fabricated and demonstrated for simultaneous measurement of glucose concentration and temperature. The proposed sensor was fabricated by inscribing a sing mode fiber (SMF) with periodic electric-arc discharge technology. During the fabrication process, the electric-arc discharge technology was produced by a commercial fusion splicer, and the period of inscribed LPFG was determined by the movement of translation stages. A serials of periodic geometrical deformations would be formed in SMF after the fabrication, and the discharge intensity and discharge time can be adjusted though the fusion splicer settings screen. The core mode can be coupled into the cladding modes at certain wavelength when they satisfy the phase-matching conditions, and there will be several resonance dips in the transmission spectrum in LPFG. The resonance dips formed by the coupling between cladding modes and core mode have different sensitivity responses, so the simultaneous measurement for multi-parameter can be realized by monitoring the wavelength shifts of the resonance dips. Compared with the LPFG based on conventional SMF, the glucose concentration sensitivity has been obviously enhanced by etching the cladding with hydrofluoric acid solution. Based on the independent measured results, a dual-parameter measurement matrix has been built for signal demodulation. Because of the easy fabrication, low cost, small size and high sensitivity, the sensor is promising to be used for the biochemical sensing field where simultaneous measurement of glucose concentration and temperature is required.
Capsule quality inspection is important and necessary in the pharmaceutical industry. The popular methods often mis-detect capsule head defects. To solve this problem, we propose a high-quality visual defect inspection method for capsule heads. In detail, first, capsule head images are captured by high-speed cameras with ring illuminators. Then, radial symmetry transform (RST) is employed to locate region of interest (ROI). Next, the ROI image is enhanced by homomorphic filter and binarized by basic global thresholding. After that, six discriminative features of ROI are extracted, which are skeleton feature, binary density, number of connected boundaries, RST power, mean, and variance. Finally, these features are classified by support vector machine to inspect the quality of the capsule head. The experiment is carried out on a self-established capsule image database, Northeastern University Capsule Image Database Version 1.0. According to our experiment, the proposed method can detect ROI correctly for all of the capsule head images and inspection accuracy achieves a true positive rate of 100.00% and true negative rate of 100.00%.
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