Recent Advances in Distributed Acoustic Sensing Based on Phase-Sensitive Optical Time Domain Reflectometry

Distributed acoustic sensing (DAS) using coherent Rayleigh backscattering in an optical fiber has become a ubiquitous technique for monitoring multiple dynamic events in real time. It has continued to constitute a steadily increasing share of the fiber-optic sensor market, thanks to its interesting applications in many safety, security, and integrity monitoring systems. In this contribution, an overview of the recent advances of research in DAS based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is provided. Some advanced techniques used to enhance the performance of ϕ-OTDR sensors for measuring backscattering intensity changes through reduction of measurement noise are presented, in addition to methods used to increase the dynamic measurement capacity of ϕ-OTDR schemes beyond conventional limits set by the sensing distance. Recent ϕ-OTDR configurations which significantly enhance the measurement spatial resolution, including those which decouple it from the probing pulse width, are also discussed. Finally, a review of recent advances in more precise quantitative measurement of an external impact based on frequency shift and phase demodulation methods using simple direct detection ϕ-OTDR schemes is given

Distributed Fiber Ultrasonic Sensor and Pattern Recognition Analytics

Ultrasound interrogation and structural health monitoring technologies have found a wide array of applications in the health care, aerospace, automobile, and energy sectors. To achieve high spatial resolution, large array electrical transducers have been used in these applications to harness sufficient data for both monitoring and diagnoses. Electronic-based sensors have been the standard technology for ultrasonic detection, which are often expensive and cumbersome for use in large scale deployments. Fiber optical sensors have advantageous characteristics of smaller cross-sectional area, humidity-resistance, immunity to electromagnetic interference, as well as compatibility with telemetry and telecommunications applications, which make them attractive alternatives for use as ultrasonic sensors. A unique trait of fiber sensors is its ability to perform distributed acoustic measurements to achieve high spatial resolution detection using a single fiber. Using ultrafast laser direct-writing techniques, nano-reflectors can be induced inside fiber cores to drastically improve the signal-to-noise ratio of distributed fiber sensors. This dissertation explores the applications of laser-fabricated nano-reflectors in optical fiber cores for both multi-point intrinsic Fabry–Perot (FP) interferometer sensors and a distributed phase-sensitive optical time-domain reflectometry (φ-OTDR) to be used in ultrasound detection. Multi-point intrinsic FP interferometer was based on swept-frequency interferometry with optoelectronic phase-locked loop that interrogated cascaded FP cavities to obtain ultrasound patterns. The ultrasound was demodulated through reassigned short time Fourier transform incorporating with maximum-energy ridges tracking. With tens of centimeters cavity length, this approach achieved 20kHz ultrasound detection that was finesse-insensitive, noise-free, high-sensitivity and multiplex-scalability. The use of φ-OTDR with enhanced Rayleigh backscattering compensated the deficiencies of low inherent signal-to-noise ratio (SNR). The dynamic strain between two adjacent nano-reflectors was extracted by using 3×3 coupler demodulation within Michelson interferometer. With an improvement of over 35 dB SNR, this was adequate for the recognition of the subtle differences in signals, such as footstep of human locomotion and abnormal acoustic echoes from pipeline corrosion. With the help of artificial intelligence in pattern recognition, high accuracy of events’ identification can be achieved in perimeter security and structural health monitoring, with further potential that can be harnessed using unsurprised learning

Unsupervised anomaly detection applied to F-OTDR

Distributed acoustic sensors (DASs) based on direct-detection Φ-OTDR use the light–matter interaction between light pulses and optical fiber to detect mechanical events in the fiber environment. The signals received in Φ-OTDR come from the coherent interference of the portion of the fiber illuminated by the light pulse. Its high sensitivity to minute phase changes in the fiber results in a severe reduction in the signal to noise ratio in the intensity trace that demands processing techniques be able to isolate events. For this purpose, this paper proposes a method based on Unsupervised Anomaly Detection techniques which make use of concepts from the field of deep learning and allow the removal of much of the noise from the Φ-OTDR signals. The fact that this method is unsupervised means that no human-labeled data are needed for training and only event-free data are used for this purpose. Moreover, this method has been implemented and its performance has been tested with real data showing promising results

Limits of performance of chirped- pulse phase-sensitive OTDR

Distributed acoustic sensing is an emerging field of research which aims to develop methods capable of using a single optical fiber as a long, dense, and high-sensitivity sensor array. Currently, the most promising implementations measure the interference of Rayleigh backscattered light, obtained by probing the fiber with light from a source of high coherence. These methods are known as Phase-sensitive Optical Time-Domain Reflectometers (φOTDR), and are currently undergoing a period of active research and development, both academically and industrially. One of its variants, known as the Chirped-Pulse φOTDR (CP-φOTDR), was developed in 2016. This technique has proven to be remarkably sensitive to strain and temperature, with an attractively simple implementation. In this thesis, we delve into the intricacies of this technique, probing its fundamental limits and addressing current limitations. We discuss the implications of estimation on the performance statistics, the impact of different noise sources and the origin of cross-talk between independent measured positions. In doing so, we also propose methods to reach the current fundamental limitations, and overcome the upper bound of measurable perturbations. We then demonstrate new potential applications of the technique: in seismology, by exploiting the high spatial density of measurements for array signal processing; in the fast characterization of linear birefringence in standard single-mode fibers; and on the measurement of sound pressure waves, by using a special flat cable structure to embed the fiber under test. Finally, we summarize and comment on the aforementioned achievements, proposing some open lines of research that may originate from these results.Distributed acoustic sensing is an emerging field of research which aims to develop methods capable of using a single optical fiber as a long, dense, and highsensitivity sensor array. Currently, the most promising implementations measure the interference of Rayleigh backscattered light, obtained by probing the fiber with light from a source of high coherence. These methods are known as Phase-sensitive Optical Time-Domain Reflectometers (φOTDR), and are currently undergoing a period of active research and development, both academically and industrially. One of its variants, known as the Chirped- Pulse φOTDR (CP-φOTDR), was developed in 2016. This technique has proven to be remarkably sensitive to strain and temperature, with an attractively simple implementation. In this thesis, we delve into the intricacies of this technique, probing its fundamental limits and addressing current limitations. We discuss the implications of estimation on the performance statistics, the impact of different noise sources and the origin of cross-talk between independent measured positions. In doing so, we also propose methods to reach the current fundamental limitations, and overcome the upper bound of measurable perturbations. We then demonstrate new potential applications of the technique: in seismology, by exploiting the high spatial density of measurements for array signal processing; in the fast characterization of linear birefringence in standard single-mode fibers; and on the measurement of sound pressure waves, by using a special flat cable structure to embed the fiber under test. Finally, we summarize and comment on the aforementioned achievements, proposing some open lines of research that may originate from these results

Data-Driven Distributed Optical Vibration Sensors: A Review

Distributed optical vibration sensors (DOVS) have attracted much attention recently since it can be used to monitor mechanical vibrations or acoustic waves with long reach and high sensitivity. Phase-sensitive optical time domain reflectometry (Φ-OTDR) is one of the most commonly used DOVS schemes. For Φ-OTDR, the whole length of fiber under test (FUT) works as the sensing instrument and continuously generates sensing data during measurement. Researchers have made great efforts to try to extract external intrusions from the redundant data. High signal-to-noise ratio (SNR) is necessary in order to accurately locate and identify external intrusions in Φ-OTDR systems. Improvement in SNR is normally limited by the properties of light source, photodetector and FUT. But this limitation can also be overcome by post-processing of the received optical signals. In this context, detailed methodologies of SNR enhancement post-processing algorithms in Φ-OTDR systems have been described in this paper. Furthermore, after successfully locating the external vibrations, it is also important to identify the types of source of the vibrations. Pattern classification is a powerful tool in recognizing the intrusion types from the vibration signals in practical applications. Recent reports of Φ-OTDR systems employed with pattern classification algorithms are subsequently reviewed and discussed. This thorough review will provide a design pathway for improving the performance of Φ-OTDR while maintaining the cost of the system as no additional hardware is required

Quantitative detection of multi-frequency disturbance signal by ϕ-OTDR system

Recently, the combination of pattern recognition technology and distributed fiber sensing systems has become increasingly common, so whether the disturbance signal can be well recovered has become increasingly important. To verify the recovery and linear response of a distributed fiber optic sensing system to multi-frequency disturbance signals, a heterodyne coherent detection system for phase-sensitive optical time-domain reflectometry is developed. The output beat signal is extracted using the digital in-phase/quadrature demodulation algorithm. The signal can be precisely located on a 7 km length range, and the disturbance signal can be restored well through the phase information. Not only the superposition signal composed of the same signal but also that composed of different kinds of signals can be successfully restored. A fast Fourier transform algorithm is used to obtain the frequency information of the superimposed signal. Combined with the use of a finite impulse response filter, the superposed signal is decomposed according to its frequency components, which perfectly restores the two signals before they are superimposed. In addition, their amplitude is highly linear with the driving voltage of the piezoelectric transducer. The system can fully retain the details of each frequency component in the recovery of multi-frequency disturbance signals. More importantly, in field experiments, the disturbance behavior is well recovered, which has broad prospects in the application of perimeter security

Aplicações De Métodos De Sensoriamento De Vibração Baseados Em Técnicas

Orientadores: Fabiano Fruett, Claudio FloridiaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Sensores à fibra óptica distribuídos têm sido empregados para monitorar vários parâmetros, tais como temperatura, vibração, tensão mecânica, campo magnético e corrente elétrica. Quando comparados a outras técnicas convencionais, tais sensores são vantajosos devido a suas pequenas dimensões, imunidade a interferências eletromagnéticas, alta adaptabilidade, robustez a ambientes nocivos, dentre outros. Sensores acústicos distribuídos em particular são interessantes devido a sua capacidade em serem usados em aplicações tais como monitoração de saúde de estruturas e vigilância de perímetros. Através da análise em frequência da estrutura, por exemplo uma aeronave, uma ponte, um edifício ou mesmo máquinas em uma fábrica, é possível avaliar sua condição e detectar danos e falhas em um estágio primário. Tais soluções podem cobrir ambas as aplicações de detecção de intrusão e monitoração estrutural com mínimas adaptações no sistema sensor. Desta forma, vibrações e distúrbios pequenas estruturas com resolução de dezenas de centímetros e em grandes estruturas ou perímetros com alguns metros de resolução espacial e centenas de quilômetros de alcance podem ser detectadas. Outra característica útil desta solução baseada em fibra óptica é a possibilidade de ser combinada com técnicas de processamento digital de sinais, permitindo a detecção e localização de perturbações rápidas, reconhecimento de padrões de intrusão em tempo real e multiplexação de dados de superfícies estruturais para aplicações SHM. O principal objetivo desta tese é fazer uso desses recursos para empregar técnicas de DAS como soluções de tecnologias- chave para várias aplicações. Neste trabalho, as técnicas de phase-OTDR foram estudadas e as principais contribuições da tese focaram em trazer soluções inovadoras e validações para aplicações de vigilância e vigilância. Este doutorado teve um período sanduíche nas instalações da RISE Acreo AB, Estocolmo, Suécia, onde experimentos foram realizados e foi parte da 42ª Chamada CISB/Saab/CNPqAbstract: Distributed optical fiber sensors have been increasingly employed for monitoring several parameters, such as temperature, vibration, strain, magnetic field and current. When compared to other conventional techniques, these sensors are advantageous due to their small dimensions, lightweight, immunity to electromagnetic interference, high adaptability, robustness to hazardous environments, less complex data multiplexing, the feasibility to be embedded into structures with minimum invasion, the capability to extract data with high resolution from long perimeters using a single optical fiber and detect multiple events along the fiber. In particular, distributed acoustic sensors (DAS) based on optical time domain reflectometry (OTDR), are of high interest, due to their capability to be used in applications such as structural health monitoring (SHM) and perimeter surveillance. Through the frequency analysis of a structure, for instance an aircraft, a bridge, a building or even machines in a workshop, it is possible to evaluate its condition and detect damages and failures at an early stage. Also, OTDR based solutions for vibration monitoring can be easily adapted with minimum setup modifications to detect intrusion in a perimeter, a useful tool for surveillance of military facilities, laboratories, power plants and homeland security. The same OTDR technique can be used as a non-destructive diagnostic tool to evaluate vibrations and disturbances on both small structures with some dozens of centimeters¿ resolution and in big structures or perimeters with some meters of spatial resolution and hundreds of kilometers of reach. Another useful feature of this optical fiber based solution is the possibility to be combined with high-performance digital signal processing techniques, enabling fast disturbance detection and location, real-time intrusion pattern recognition and fast data multiplexing of structure surfaces for SHM applications. The main goal of this thesis is to make use of these features to employ DAS techniques as key enabling technologies solutions for several applications. In this work, OTDR based techniques were studied and the thesis main contributions were focused on bringing innovative solutions and validations for SHM and surveillance applications. This PhD had a sandwich period at Acreo AB, Stockholm, Sweden, where experimental tests were performed and it was part of the 42ª CISB/Saab/CNPq CalDoutoradoEletrônica, Microeletrônica e OptoeletrônicaDoutora em Engenharia Elétrica202816/2015-0CAPESCNP

Development of a distributed optical fiber sensor for geological applications

The purpose of the study was to develop a distributed optical fiber acoustic sensor for monitoring ground subsidence before collapse sinkholes form causing costly damage on infrastructure. Costs in excess of R1.3 billion have been incurred while dealing with sinkhole related measures in South Africa. Monitoring sinkholes and the presence of an early warning alert system can drastically reduce the impact, risk and cost caused by sudden ground collapse. A related goal was to construct a reliable collapse alert early warning system to facilitate disaster preparedness and avoid further damage from accidents. This was achieved by developing a spectroscopic shift monitoring algorithm which analysed changes in the subsurface vibration modes using ambient noise signals. For the first time to our knowledge, an optic fiber sensor with an early warning alarm, using ambient noise vibrations to detect and monitor sinkholes was developed at NMU. A polarisation-based, interferometric optical fiber seismic sensor was developed and compared to a commercial geophone. The fiber sensor exhibited superior performance in sensitivity, bandwidth, signal response and recovery times. The sensitivity of the optical fiber sensor was 0.47 rad/Pa surpassing the geophone sensitivity by 9.32%, and the bandwidth of 3.349kHz was 20 times greater for the optical fiber sensor. The fiber sensor was used to measure millisecond events as the impact duration of a bouncing ball was successfully obtained. It was used to detect sinkhole formation in the simulator model, designed. Ground collapse precursors were identified, and early warning alert was achieved using the spectral analysis algorithm, developed. The collapse precursor condition was identified as a functional combination of variations in the peak frequency, bandwidth and peak intensity. A distributed acoustic sensor was built to detect ambient noise induced subsurface signals. Vibrations were located along the 28km length of optical fiber with a relative error of 9.6%. The sensor demonstrated a frequency response range of 212.25Hz, an event distance precision of 224m with time resolution of 1.12µs, and a spatial resolution of 1km. The position of disturbance was measured within 300m of its actual point of 3.21km along the optical fiber. The results showed that distributed optical fiber sensing allows real-time monitoring of the subsurface over extended distances, using ambient noise signals.Thesis (PhD) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202

Development of a distributed optical fiber sensor for geological applications

The purpose of the study was to develop a distributed optical fiber acoustic sensor for monitoring ground subsidence before collapse sinkholes form causing costly damage on infrastructure. Costs in excess of R1.3 billion have been incurred while dealing with sinkhole related measures in South Africa. Monitoring sinkholes and the presence of an early warning alert system can drastically reduce the impact, risk and cost caused by sudden ground collapse. A related goal was to construct a reliable collapse alert early warning system to facilitate disaster preparedness and avoid further damage from accidents. This was achieved by developing a spectroscopic shift monitoring algorithm which analysed changes in the subsurface vibration modes using ambient noise signals. For the first time to our knowledge, an optic fiber sensor with an early warning alarm, using ambient noise vibrations to detect and monitor sinkholes was developed at NMU. A polarisation-based, interferometric optical fiber seismic sensor was developed and compared to a commercial geophone. The fiber sensor exhibited superior performance in sensitivity, bandwidth, signal response and recovery times. The sensitivity of the optical fiber sensor was 0.47 rad/Pa surpassing the geophone sensitivity by 9.32%, and the bandwidth of 3.349kHz was 20 times greater for the optical fiber sensor. The fiber sensor was used to measure millisecond events as the impact duration of a bouncing ball was successfully obtained. It was used to detect sinkhole formation in the simulator model, designed. Ground collapse precursors were identified, and early warning alert was achieved using the spectral analysis algorithm, developed. The collapse precursor condition was identified as a functional combination of variations in the peak frequency, bandwidth and peak intensity. A distributed acoustic sensor was built to detect ambient noise induced subsurface signals. Vibrations were located along the 28km length of optical fiber with a relative error of 9.6%. The sensor demonstrated a frequency response range of 212.25Hz, an event distance precision of 224m with time resolution of 1.12µs, and a spatial resolution of 1km. The position of disturbance was measured within 300m of its actual point of 3.21km along the optical fiber. The results showed that distributed optical fiber sensing allows real-time monitoring of the subsurface over extended distances, using ambient noise signals.Thesis (PhD) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202