NARX neural network model for strong resolution improvement in a distributed temperature sensor.

This paper proposes an approach to process the response of a distributed temperature sensor using a nonlinear autoregressive with external input neural network. The developed model is composed of three steps: extraction of characteristics, regression, and reconstruction of the signal. Such an approach is robust because it does not require knowledge of the characteristics of the signal; it has a reduction of data to be processed, resulting in a low processing time, besides the simultaneous improvement of spatial resolution and temperature. We obtain total correction of the temperature resolution and spatial resolution of 5 cm of the sensor.

Design and characterization of a curvature sensor using fused polymer optical fibers.

This Letter demonstrates the application of polymer optical fibers (POFs) damaged by the fiber fuse effect to curvature sensing and dynamic angular monitoring. The curvature sensing performance using the fused-POF is compared to POF without the fuse effect. Both POFs are submitted to angles of up to 90 deg in flexion/extension cycles with angular velocities ranging from 0.48 rad/s to 5.61 rad/s. The fused POF is found to show higher performance with respect to sensitivity, correlation coefficient with linear regression, and hysteresis. For instance, at the angular velocity of 0.48 rad/s, the fused POF shows >3 times higher sensitivity and significantly lower hysteresis than those of the non-fused POF. In addition, the fused POFs have lower cross-sensitivity and hysteresis variations on the tests with different angular velocities. These results indicate that the fused POFs are potential candidates to develop curvature sensors with various advantages over non-fused POFs, for applications such as gait analysis and wearable robotics.

Polymer-optical-fiber-based sensor system for simultaneous measurement of angle and temperature.

This paper presents a polymer-optical-fiber (POF)-based sensor system for simultaneous measurement of angle and temperature. The main contribution is obtaining a sensor with higher temperature sensitivity and lower hysteresis on the angle measurements. The annealing was made on the fibers under the conditions of low relative humidity and under water, and a third set of samples without any heat treatment was applied for comparison with the annealed ones. Results of temperature and angle characterization show that the fibers annealed under water presented higher temperature sensitivity and lower errors when compared with the fibers annealed with low humidity or the fibers without annealing. Furthermore, the fibers annealed under water also presented lower hysteresis on the angle characterization. For these reasons, such fibers were employed for the temperature and angle measurements, which results in a sensor system capable of simultaneously measuring the angle and temperature with root-mean-squared error of 0.82°C for temperature and 2.20° for angle, which is further reduced to 1.20° after the application of a dynamic compensation technique for POF curvature sensors.