The optical fiber acoustic sensing system is suitable for long-distance monitoring of the acoustic signals generated by the external disturbances. According to the continuity of sensing units, quasi-distributed and distributed optical fiber acoustic sensing technologies are differentiated to meet different application requirements. On the one hand, the recent progress of Fabry-Perot interferometer (FPI) focusing on the diaphragm material, and the research hotspots in the field of the continuous Fiber Bragg grating (FBG) array are firstly reviewed. On the other hand, Mach-Zehnder interferometry (MZI), Michelson interferometry (MI), and Sagnac interferometry (SI) have rapidly developed in the aspect of the demodulation algorithm optimization with the purpose of the sensing performance improvement. Moreover, the current primary research works of the phase-sensitive optical time-domain reflectometer ( $\varphi $ -OTDR) are the signal-to-noise ratio improvement and the mixed optical structure design. Finally, this paper presents an overview of the recent advances of optical fiber acoustic sensing system in the application domains of military defense, structural health monitoring, petroleum exploration, and development.

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A Comprehensive Study of Optical Fiber Acoustic Sensing

Most geotextiles consist of polymers of polyolefin, polyester or polyamide family, which involve environmental problems related to soil pollution. Geotextiles can be used for at least one of the following functions: Separation, reinforcement, filtration, drainage, stabilization, barrier, and erosion protection. Due to the characteristics of high strength, low cost, and easy to use, geotextiles are widely used in geotechnical engineering such as soft foundation reinforcement, slope protection, and drainage system. This paper reviews composition and function of geotextiles in geotechnical engineering. In addition, based on literatures including the most recent data, the discussion turns to recent development of geotextiles, with emphasis on green geotextiles, intelligent geotextiles, and high-performance geotextiles. The present situation of these new geotextiles and their application in geotechnical engineering are reviewed.

Review of Application and Innovation of Geotextiles in Geotechnical Engineering.

In electrical engineering, partial discharge (PD) measurement is frequently employed to detect insulation defects and judge insulation conditions of high-voltage electrical apparatus. However, it is easily corrupted by white noises in the field. In this article, a joint algorithm is proposed, in which the wavelet threshold and total variation (TV) denoising methods are combined by the convex optimization theory to denoise ultrahigh frequency (UHF) PD signals corrupted by white noises. Since the two respective methods are incorporated into the joint algorithm, it is with high potential to reduce oscillation error introduced by the wavelet threshold method and eliminate stair error introduced by the TV denoising method. In order to validate the effect of the proposed algorithm, a numerical simulation is carried out to compare it with several existing methods. Indicators of their performance are computed, and the results verify that the proposed algorithm outperforms all the other methods.

A Denoising Algorithm for Partial Discharge Measurement Based on the Combination of Wavelet Threshold and Total Variation Theory

Diagnostic and condition monitoring of power transformers are key actions to guarantee their safe operation. The subsequent benefits include reduced service interruptions and economic losses associated with their unavailability. Conventional test methods developed for the condition assessment of power transformers have certain limitations. To overcome such problems, fiber optic-based sensors for monitoring the condition of transformers have been developed. Flawlessly built-up fiber optic-based sensors provide online and offline assessment of various parameters like temperature, moisture, partial discharges, gas analyses, vibration, winding deformation, and oil levels, which are based on different sensing principles. In this paper a variety and assessment of different fiber optic-based diagnostic techniques for monitoring power transformers are discussed. It includes significant tutorial elements as well as some analyses.

Review of Fiber Optic Diagnostic Techniques for Power Transformers

Timely detection of the incipient fault of a power transformer is of utmost importance to prevent potential malfunctioning. Monitoring the condition of the transformer insulation oil is the essential step as it contains most of the transformer’s health diagnostic information. Thus, the temperature of the oil is considered the most crucial parameter that has to be monitored continuously in real-time. Distributed optical fiber sensors for temperature monitoring has various advantages over traditional methods. In this study, an optical fiber-based distributed temperature measurement of insulation oil of a fully energized 100 kVA commercial distribution transformer is demonstrated. Two types of techniques were deployed to monitor the temperature of the transformer inside and outside of the tank using a distributed Optical Frequency Domain Reflectometry (OFDR) and a quasi-distributed Fiber Bragg Grating (FBG) sensor array respectively. The insulation oil temperature was monitored with different load conditions in a distributed fashion and compared with the conventional method of single point thermocouple and infrared thermal imaging. The test results show very good agreement between the conventional methods and proposed distributed fiber temperature sensors.

Real-Time Optical Fiber-Based Distributed Temperature Monitoring of Insulation Oil-Immersed Commercial Distribution Power Transformer

Denoising is a key step in diagnosis and evaluation of partial discharge (PD) signals in power transformers. In this paper, a new PD signal denoising algorithm is presented, which is based on the combination of dual-tree complex wavelet transform (DTCWT) and adaptive singular value decomposition (ASVD). This new algorithm, which is introduced as adaptive DTCWT (ADTCWT), was evaluated through simulations and experimental tests. ADTCWT was employed in denoising from PD signals based on the selection of best singular values in each DTCWT level decomposition, corresponding to PD signal and noise. The superior performance of the ADTCWT algorithm was demonstrated using various indices in comparison with those of DTCWT and ASVD methods in noise reduction, besides preserving time of arrival of PD signals and PD localization.

A New Partial Discharge Signal Denoising Algorithm Based on Adaptive Dual-Tree Complex Wavelet Transform

This paper presented a new sensor to detect and localize partial discharge (PD) in power transformers based on a fiber Bragg grating (FBG). The fundamental characteristics of the proposed sensor, as a PD detector, were temperature compensation and direction independence. The proposed high-resolution PD detector operated based on the FBG wavelength shift. It is necessary to evaluate the physical parameters of the sensor to achieve the best results. Therefore, in this paper, the detected signal strength was investigated for different angles and temperatures. A Teflon hollow mandrel and two FBGs attached to the inner and outer surfaces of the hollow mandrel were chosen as the inner transformer PD detector. The changes in the sensor output were less than 0.4 mV and 0.5 mV for direction variations and a temperature variation of 14 °C (degrees Celsius), respectively. Consequently, the proposed sensor could be successfully employed for the detection of a transformer PD signal.

https://www.mdpi.com/1424-8220/19/23/5285/pdf

High-Resolution FBG-Based Fiber-Optic Sensor with Temperature Compensation for PD Monitoring.

This paper proposes and investigates a partial discharge (PD) detector based on fiber Bragg grating (FBG) sensor and a mandrel to detect and localize PD in power transformers. An identification of PD in the early stages is important, so using high-resolution sensor is considerable. A Teflon hollow mandrel with attached FBG is chosen as the inner transformer PD detector. The design of the sensor in terms of materials, dimensions, and the shape is chosen; it receives signal strength according to the obtained distance and angle. Standard deviation of angle data is <0.4  mV and as the distance increases, the received signal strength decreases exponentially and oscillatory. Simulation results verify the performance of the proposed sensor in the detection of the transformer PD signals. The proposed sensor is experimentally tested. It succeeded in detecting PD, and can simultaneously detect four frequencies of acoustic signal in the range of 14 to 350 kHz, which is superior to similar sensors.

Mohsen Ghorat

Papers

A New Partial Discharge Signal Denoising Algorithm Based on Adaptive Dual-Tree Complex Wavelet Transform

High-Resolution FBG-Based Fiber-Optic Sensor with Temperature Compensation for PD Monitoring.

Partial discharge acoustic emission detector using mandrel-connected fiber Bragg grating sensor