Multiphase flow is a commonly seen transient and complex dynamic system in many industrial processes. The phase fraction and velocity are two of the most important parameters for flow monitoring and measurement. Due to the advantages of simplicity in sensor structure, low fabrication costs and fast response, conductance sensors have received broad attentions in horizontal, vertical and inclined multiphase pipe flow measurement. A conductance sensor measures the multiphase mixture conductivity between two electrodes in contact with the fluid to determine the phase fraction. Combined with cross-correlation technique, the velocity can also be acquired. This paper presents a review on the basic sensing principle, different types of conductance sensors and their applications in flow monitoring, flow pattern identification, phase fraction determination and velocity measurement of multiphase flow. Finally, based on the conclusion of the disadvantages, advantages and limitations of this technique, the insight into trends for future development are given.

In this paper, the implementation, characterization, calibration, and testing of a biaxial optical fiber accelerometer for vibration monitoring in three-phase induction motors is presented. The optical sensor uses fiber Bragg gratings to measure the displacement of an inertial mass relatively to a support base. The sensor characterization was measured through the impact hammer, allowing the determination of the natural frequencies in both sensitive directions, the values of 747.5 Hz and 757.5 Hz were estimated for the x-axis and the y-axis, respectively. For calibration, an electromagnetic exciter was used to introduce a controlled harmonic excitation at different frequencies, with this analysis, a high SNR was observed, on average over 30 dB for both sensitive directions, and a sensitivity of 100 pm × g ^-1 was obtained, up to one third of the natural frequency, in each direction. The tests were developed with the main aim of the analysis in induction motors based in vibration monitoring, the analysis can help to prevent wear in motors, increasing its efficiency, and lowering maintenance costs. The optical accelerometer measurements were compared with the ones from a capacitive sensor, during regular operation and with a broken rotor bar operating with 75% and 100% load. The performed tests with the optical sensor allowed to successfully analyze the frequency components, and its changes, for the regular and damage operation.

Due to its robustness and cost-effectiveness, the three-phase induction motor (TIM) has become the most widespread electric machine today. However, like any other equipment, it is vulnerable to a fault, and about 52% of these are related to bearings. This work presents the detection of flaws in the outer bearing’s raceway from the measurement of motor dynamic strain signals collected from sensors based on fiber Bragg grating (FBG). Three different degrees of severity were considered for faults in the outer bearing’s raceway. The tests were carried out on the motor operating under no-load conditions, with 47 different power supply frequencies. This work proposes a support vector machine (SVM) classifier to identify fault severity levels. Feature extraction was performed using two techniques: selecting the four highest peaks in the frequency spectrum and principal component analysis (PCA). The supervised SVM classifiers show that the dataset formed from the PCA presented a higher hit rate than the dataset constituted by the four highest peaks, with 99.82% and 92.73%, respectively. Based on the methodology presented in this work, it was possible to validate the use of FBG to detect bearing faults. Regardless of the degree of severity of the fault analyzed, the sensor detected its characteristic frequency. Based on the methodology presented in this work, it was possible to validate the use of FBG to detect bearing faults. Regardless of the degree of severity of the flaw analyzed, the sensor detected its characteristic frequency.

Capacitive sensors are found in numerous applications, and they are capable of sensing several parameters. Multiphase flows occur in many industrial processes that require proper monitoring to improve the efficiency and safety of plants and equipment. Detailed (high-resolution) flow information is required from dedicated flow experiments at a laboratory scale to develop and validate flow modelings. In both cases, capacitive flow sensors have been applied to have a varying degree of flow detailing, e.g., from simple capacitive probes up to capacitive flow imaging and tomography. This article reviews the different capacitive sensors applied to multiphase flow measurement and imaging. Operating principles, sensor geometries, and capacitive measuring circuits are presented and discussed along with advantages and disadvantages, focusing on flow applications and possible flow parameters yielded from sensors. Some new trends in capacitive flow sensors are also presented.

Traditional Raman distributed optical sensor (DTS) exhibits a low-pass characteristic that causes sharp temperature changes to be over smoothed. This behavior can be modeled as the convolution of the real temperature profile with the DTS impulse response. This paper presents a deconvolution algorithm developed to improve the spatial resolution of a Raman DTS system. The algorithm is based on a linear DTS model and total variation regularization. The main advantage is the ability to correctly reconstruct hot regions with dimensions down to 15 cm, which represents a resolution gain of up to six times when compared with the DTS spatial resolution of 1 m. We present simulations and experimental results demonstrating the efficacy of the proposed method.

Mechanical and electrical forces of a three-phase induction motor (TIM), in operation, can cause strain in the stator, which may lead to frustrating vibration problems. These problems may greatly reduce reliability and ultimately lead to increased maintenance cost. This paper shows the method to overcome this problem by carrying out the dynamic strain measurement analysis in a TIM running at no-load condition, using an optical fiber sensor. The dynamic strain induced by mechanical and electrical forces was measured by using fiber Bragg gratings (FBGs), installed inside the motor, in between two stator teeth. The electromagnetic immunity and reduced size of the FBGs render them suitable for this application. The frequency components of the strain in TIM were predicted using a model of the forces present in the air gap, considering static and dynamic rotor eccentricities. Two TIM motors, one of 2-poles and the other of 4-poles, and each equipped with two FBGs strain sensors, were used. The sensors were positioned between two stator teeth, separated by 120° from each other in the 2-pole motor and 90° in the 4-pole motor. The experimental analysis shows that the frequency components of the dynamic force spectrum presented by the two motors are the same as those predicted theoretically. Rotor eccentricity was achieved by attaching an unbalanced load to the rotor shaft. The amplitude of vibration at rotor rotational frequency increased when the unbalanced load on the rotor shaft increased. The measurement presented in this paper can be used to determine some TIM parameters, such as the effect of the motor power supply on its vibration signal. It can also be used as a potential maintenance tool for the continuous monitoring of the TIM with high sensitivity.