In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning.

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

Fiber Bragg grating temperature sensors in a 6.5-MW generator exciter bridge and the development and simulation of its thermal model.

This work reports the thermal modeling and characterization of a thyristor. The thyristor is used in a 6.5-MW generator excitation bridge. Temperature measurements are performed using fiber Bragg grating (FBG) sensors. These sensors have the benefits of being totally passive and immune to electromagnetic interference and also multiplexed in a single fiber. The thyristor thermal model consists of a second order equivalent electric circuit, and its power losses lead to an increase in temperature, while the losses are calculated on the basis of the excitation current in the generator. Six multiplexed FBGs are used to measure temperature and are embedded to avoid the effect of the strain sensitivity. The presented results show a relationship between field current and temperature oscillation and prove that this current can be used to determine the thermal model of a thyristor. The thermal model simulation presents an error of 1.5 °C, while the FBG used allows for the determination of the thermal behavior and the field current dependence. Since the temperature is a function of the field current, the corresponding simulation can be used to estimate the temperature in the thyristors.

Force monitoring in a maxilla model and dentition using optical fiber Bragg gratings.

The aim of this work is to show the possibility of using fiber optic sensors to instrument inside parts of an artificial maxilla and measure internal tension transmitted by the orthodontic and orthopedic appliances to the dentition and the adjacent bone. Bragg gratings written in a standard optical fiber were used to monitor the maxillary teeth and a multiplexed fiber was used to monitor the surface of the maxillary bone, transversally to the longest axis of the teeth. A Universal Test Machine was used to evaluate the sensitivity of the sensor to the vertical and lateral forces applied on the teeth. A wavelength shift of approximately 0.30 nm was detected when applying loads ranging from 0 to 20 N. By applying forces using the standard orthodontic appliances installed on the dentition it was possible to detect a range of forces between 0.025 N to 0.035 N during the activation of the arch wire and extra-oral forces. The use of the internal sensors in an artificial model made possible the monitoring of the resulting forces on the internal parts of the teeth and at the position where the strain takes place within the maxilla. The sensors detected that the orthodontic forces were not transmitted to the surface of the maxilla. This information is important to elucidate and to correlate undesirable effects as tooth root absorption and local pain during the orthodontic treatment.