In this paper, a new multiparametric optical fiber transducer is presented for simultaneous temperature and vibration sensing in hydroelectric high-power generators. The optical transducer holds three multiplexed fiber Bragg gratings (FBGs) as the sensing elements. In the transducer, each FBG can simultaneously measure temperature and vibration independent of the other FBGs. With a temperature characterization, it is possible to determine the thermal stability (1.5 °C) over the test duration and the thermal sensitivity of the packaged FBGs 10 pm/°C. Moreover, the vibration characterization tests rely on an impact hammer and a shaker. With the impact hammer test, the transducer package natural frequency of 565 Hz is determined. The shaker performed a frequency sweep over 5 Hz to 1 kHz, and the transducer mean vibration sensitivity is found to be 7.2 pm/g. Subsequently, the power plant installation is performed using six transducers. They are installed into six different windings slots to sense stator bars of a 370-MVA hydroelectric generator. With this instrumentation, 23 h of simultaneous vibration and temperature sensing is carried out. All the FBGs used to monitor vibration were able to monitor the frequency of mechanical vibration (2 Hz) and electromagnetic vibration (120 Hz) of the generator. During the power plant test, the machine was turned OFF due to a failure and all the FBGs were able to measure the temperature as well as vibration changes caused by the machine shutdown.

This article describes the development of a fiber Bragg grating (FBG) sensor encapsulated in carbon-fiber reinforced polymer to detect faults in rotating electrical machine bearings. The proposed sensor was based on the temperature and strain sensitivity of the FBG sensor and the robustness of carbon fiber as an encapsulation. The sensor was composed of three FBGs, one of which was packaged in a glass tube. The behavior characteristics of the developed sensor were evaluated in the calibration process. The experimental setup and measurement system were discussed and analyzed under dynamic conditions. The sensor was implemented in an induction motor operating at a controlled full load. The tests were performed with new and faulty bearings. The results, for the faulty bearing frequencies of 147.5, 296.6, and 439.0 Hz, were identified. These frequency components were generated by defects in the inner raceway. Comparing the amplitude spectrum between the signal of the new and faulty bearing, a variation of approximately 96% was found. The FBG reinforced sensor can identify bearing integrity in real-time and be a preventive maintenance tool for bearing monitoring.

Over the past decade, distributed acoustic sensing has been utilized for structural health monitoring in various applications, owing to its continuous measurement capability in both time and space and its ability to deliver extensive data on the conditions of large structures using just a single optical cable. This work aims to evaluate the performance of distributed acoustic sensing for monitoring a multilayer structure on a laboratory scale. The proposed structure comprises four layers: a medium-density fiberboard and three rigid polyurethane foam slabs. Three different damages were emulated in the structure: two in the first layer of rigid polyurethane foam and another in the medium-density fiberboard layer. The results include the detection of the mechanical wave, comparing the response with point sensors used for reference, and evaluating how the measured signal behaves in time and frequency in the face of different damages in the multilayer structure. The tests demonstrate that evaluating signals in both time and frequency domains presents different characteristics for each condition analyzed. The supervised support vector machine classifier was used to automate the classification of these damages, achieving an accuracy of 93%. The combination of distributed acoustic sensing with this learning algorithm creates the condition for developing a smart tool for monitoring multilayer structures.

This article presents two in vivo instrumentation techniques to study the different types of gait of horses performing athletics using fiber Bragg gratings (FBG). These techniques can be used as an auxiliary tool in the early diagnosis of injuries related to the horse’s locomotor system, mainly in the distal portion of the digit, one of the most common causes of retirement when they are athletes. Therefore, the first technique presented consists of the fixation of FBGs without encapsulation, directly on the dorsal wall of the hoof in each of the limbs. In the second technique presented, the FBG sensor is encapsulated in a prototype developed using a composite material reinforced with carbon fiber in a horseshoe shape. The second technique is associated with digital image processing (DIP) for better visualization of the deformation and compression forces that act upon the limbs. The first method showed sensitivity to detection of the digit compression against the ground, being able to identify walking patterns. The second technique, with the encapsulated sensor elements, also allows the capture of characteristic signals of gait, such as step walk, trot, and gallop under training conditions. Both, FBG sensor interrogation and DIP, analysis techniques have proven good performance and promising results for the clinical and biomechanical study and medical evaluations of horses even during dynamic training and competitions.

In the industry, production lines depend on small and medium-sized electrical machines, and for this reason, continuous monitoring of these machines is important to avoid unexpected interruptions. Excessive rise in temperature during electric motor operation is usually associated with several causes, including voltage unbalance and overload. This article presents the measurements taken using a Raman Distributed Temperature Sensing (RTDS) device with 1 m spatial resolution to identify induction motor (IM) faults. In this regard, an algorithm to improving spatial resolution through signal processing allows measuring lengths of up to 15 cm. Experimental tests showed that it was possible to identify the temperature increase in four slots with an improvement of 60%. In addition, it was possible to detect faults in conditions of unbalanced voltage through temperature measurements. The proposed method shows that the measurements acquired by the distributed sensors installed in the IM stator allow thermal mapping of the machine’s entire structure.