Phase-sensitive OTDR Research Articles

Performance enhancement of optical pulse coding phase-sensitive OTDR system with genetic-optimized code

Optical pulse coding (OPC) in phase-sensitive optical time-domain reflectometry (φ-OTDR) traditionally relies on standard coding sequences as probe pulse trains, which usually suffer the problem of distorted probe pulse caused by the gain saturation in erbium-doped fiber amplifier (EDFA). To improve the signal-to-noise ratio (SNR) and mitigate distortion caused by the EDFA gain saturation, a genetic-optimized code (Go-code) based OPC φ-OTDR (GOPC φ-OTDR) scheme is proposed in this paper. The unique Go-code sequence generated by the distributed genetic algorithm (DGA) is explored in the field of φ-OTDR for the first time, and the coding sequence was optimized to adapt to the vibration sensing requirements in φ-OTDR. Theoretical analyses focused on EDFA gain saturation effects and coding gain were conducted. The experiment of GOPC φ-OTDR demonstrated significant improvements compared with Golay φ-OTDR, achieving less distortion in decoding response and approximately 7.48 dB phase demodulation SNR enhancement within a 10-km sensing range. This research marks Go-code's pioneering exploration into φ-OTDR, demonstrating substantial advancements in optimization metrics, and opening avenues for exploring advanced OPC technologies.

Pulse Intensity Coding Phase-Sensitive OTDR With Mismatched Filtering

Pulse Intensity Coding Phase-Sensitive OTDR With Mismatched Filtering

Instability Compensation of Recording Interferometer in Phase-Sensitive OTDR.

In the paper, a new method of phase measurement error suppression in a phase-sensitive optical time domain reflectometer is proposed and experimentally proved. The main causes of phase measurement errors are identified and considered, such as the influence of the recording interferometer instabilities and laser wavelength instability, which can cause inaccuracies in phase unwrapping. The use of a Mach-Zender interferometer made by 3 × 3 fiber couplers is proposed and tested to provide insensitivity to the recording interferometer and laser source instabilities. It is shown that using all three available photodetectors of the interferometer, instead of just one pair, achieves significantly better accuracy in the phase unwrapping. A novel compensation scheme for accurate phase measurements in a phase-sensitive optical time domain reflectometer is proposed, and a comparison of the measurement signals with or without such compensation is shown and discussed. The proposed method, using three photodetectors, allows for very good compensation of the phase measurement errors arising from common-mode noise from the interferometer and laser source, providing a significant improvement in signal detection. In addition, the method allows the tracking of slow temperature changes in the monitored fiber/object, which is not obtainable when using a simple low-pass filter for phase unwrapping error reduction, as is customary in several systems of this kind.

Interference fading suppression with fault-tolerant Kalman filter in phase-sensitive OTDR

A multi-sensor information fusion algorithm based on fault-tolerant Kalman filter is proposed in phase-sensitive optical time-domain reflectometer (Φ-OTDR) system, for achieving fading-free distributed vibration sensing. Firstly, a fault-tolerant dual-core complementary array model is designed. The Rayleigh scattering signal denoising, and vibration existence judgment of localization points are carried out to obtain the differentiated frequency demodulation results of the sensing points of the dual-core fiber array. Then a fault-tolerant control strategy is used to determine the sensor weight coefficients and vibration judgment coefficients during data fusion processing, and array data fusion is carried out based on time series data using Kalman filter to realize error value identification and filling. The advantage of this method is the combination of redundant data in a complementary way to improve the system stability. The frequency response ranges from 10 Hz to 2400 Hz and the localization accuracy is 98.33%. The influence of key parameters on the frequency demodulation performance of fault-tolerant Kalman filter is discussed, and a standard deviation of 14.6 Hz and an average error of 7.6 Hz are obtained. The demodulation frequency data matrix obtained by the classical demodulation method has a demodulation error probability of 89.18%, which proves the widespread existence of demodulation errors in vibration signals. The fusion error of demodulation frequency is reduced to 0.25 Hz, the frequency demodulation accuracy reaches 100%, and the demodulation error caused by interference attenuation can be completely eliminated. This system based on fault-tolerant Kalman filter has the characteristics of simple multiplexing structure, interference fading resistance and stable demodulation performance.

Detection and Recognition of Voice Commands by a Distributed Acoustic Sensor Based on Phase-Sensitive OTDR in the Smart Home Concept.

In recent years, attention to the realization of a distributed fiber-optic microphone for the detection and recognition of the human voice has increased, whereby the most popular schemes are based on φ-OTDR. Many issues related to the selection of optimal system parameters and the recognition of registered signals, however, are still unresolved. In this research, we conducted theoretical studies of these issues based on the φ-OTDR mathematical model and verified them with experiments. We designed an algorithm for fiber sensor signal processing, applied a testing kit, and designed a method for the quantitative evaluation of our obtained results. We also proposed a new setup model for lab tests of φ-OTDR single coordinate sensors, which allows for the quick variation of their parameters. As a result, it was possible to define requirements for the best quality of speech recognition; estimation using the percentage of recognized words yielded a value of 96.3%, and estimation with Levenshtein distance provided a value of 15.

Integrated Fading Suppression for Phase-Sensitive OTDR: An Algorithm Set

Integrated Fading Suppression for Phase-Sensitive OTDR: An Algorithm Set

Enhancement of dynamic strain range based on phase-sensitive OTDR with time-delay double probe pulses

Enhancement of dynamic strain range based on phase-sensitive OTDR with time-delay double probe pulses

Polyphase Unimodular Coding in Phase-Sensitive OTDR for Low Crosstalk

Polyphase Unimodular Coding in Phase-Sensitive OTDR for Low Crosstalk

Ultralow-Frequency Vibration Sensing in Phase-Sensitive OTDR Using Multiscale VMD

Ultralow-Frequency Vibration Sensing in Phase-Sensitive OTDR Using Multiscale VMD

Acceleration of the frequency-shift demodulation in phase-sensitive OTDR

Abstract The frequency-shift demodulation is a primary demodulation method in phase-sensitive optical time domain reflectometry (Φ-OTDR) with intrinsic resistance to interference fading. So far, the least mean squares (LMS) estimation method has the optimal demodulation accuracy and robustness. However, it takes much processing time due to the step-by-step sliding operation. In this work, we propose a fast LMS estimation method based on cross-correlation calculation to accelerate the demodulation while maintaining accuracy. Experiments are performed along a 9 km sensing fiber with a 4 m spatial resolution. The performance of the fast LMS, LMS, and cross-correlation methods are compared by using the same parameters. Compared with the LMS method, the fast LMS achieves a 12-time improvement in processing speed while remaining the same demodulation accuracy. Although the proposed fast LMS method takes slightly more time than the cross-correlation method (1.6 times), it improves the demodulation accuracy ∼6 dB for the vibration signal and ∼2.1 dB for the overall demodulation accuracy.

Open-Set Event Recognition Model Using 1-D RL-CNN With OpenMax Algorithm for Distributed Optical Fiber Vibration Sensing System

Distributed optical fiber vibration sensing system (DVS) base on phase-sensitive OTDR is widely used for its simple structure and high sensitivity. Signal recognition is crucial for DVS because it can help to classify the different types of vibration events. Deep learning provides accurate event classification and can automatically extract features according to sample distribution. However, almost all current methods focus on closed set recognition, which misclassifies unknown events into known categories thus reduces the recognition accuracy of sensing system. In this paper, we propose a novel open set event recognition model based on one-dimension residual learning convolution neural network (1-D RL-CNN) with OpenMax algorithm for DVS, which is capable of processing the signals of known and unknown categories. The experimental results show that the proposed recognition model improves the classification accuracy greatly compared with conventional 1-D CNN signal classification method. The overall open-set classification accuracy of 1-D RL-CNN with OpenMax is 91.19%, which is improved of 18.47% and 7.57% compared with 1-D CNN with SoftMax and 1-D CNN with OpenMax.

Coded phase-sensitive OTDR with delayed polarization multiplexing for a WFBG array.

Polarization fading degrades the performance of phase-sensitive optical time-domain reflectometry (φ-OTDR) seriously and has to be suppressed. A novel scheme is proposed in this paper to combat polarization fading, which features a quite simple transceiver structure by exploiting both polarization diversity through delayed polarization multiplexing and the aperiodic autocorrelation of pseudorandom binary sequence. The components of Jones matrix of a sensing fiber are then shown at those four peaks of aperiodic autocorrelation and can be obtained directly without complicated computation to give a polarization independent phase variation due to vibration. Moreover, the scheme does not require stringent match between the delayed time and the spacing between sensors. The proposed scheme is demonstrated through experiment on a weak fiber Bragg grating (WFBG) array, which shows a high crosstalk rejection ratio among sensors of more than 50 dB and a high dynamic range of more than 30 dB.

Frequency Stability Requirements in Quasi-Integer-Ratio Time-Expanded Phase-Sensitive OTDR

Time-expanded phase sensitive (TE-ϕ)OTDR is a recently reported technique for distributed fiber sensing that relies on the use of an electro-optic dual frequency comb (DFC) scheme. A distinctive feature of this approach is its ability to provide high spatial resolution (on the centimeter scale) with detection bandwidths orders of magnitude lower than those of conventional ϕOTDR systems. The stringent trade-off between resolution, range and sensing bandwidth that exists in TE-ϕOTDR has demonstrated to be substantially relaxed by implementing two frequency combs with quasi-integer-ratio repetition rates. However, employing very dissimilar line separations (with a ratio between them >100) is challenging due to the need of keeping the coherence over long sequences of interferograms, which eventually limits the attainable range. In this paper, we formulate the requirements for the frequency stability of the reference clock used in a quasi-integer-ratio DFC scheme. This analysis allows us to stablish the limits on the number of comb lines (i.e., on the number of available independent sensing points) for a particular reference clock. By using a rubidium atomic clock (with a relative frequency stability of ∼10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−13</sup> ), we demonstrate up to 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup> sensing points along 2 km of fiber with tens of Hz sensing bandwidth.

Classification of Acoustic Influences Registered with Phase-Sensitive OTDR Using Pattern Recognition Methods

This article is devoted to the development of a classification method based on an artificial neural network architecture to solve the problem of recognizing the sources of acoustic influences recorded by a phase-sensitive OTDR. At the initial stage of signal processing, we propose the use of a band-pass filter to collect data sets with an increased signal-to-noise ratio. When solving the classification problem, we study three widely used convolutional neural network architectures: AlexNet, ResNet50, and DenseNet169. As a result of computational experiments, it is shown that the AlexNet and DenseNet169 architectures can obtain accuracies above 90%. In addition, we propose a novel CNN architecture based on AlexNet, which obtains the best results; in particular, its accuracy is above 98%. The advantages of the proposed model include low power consumption (400 mW) and high speed (0.032 s per net evaluation). In further studies, in order to increase the accuracy, reliability, and data invariance, the use of new algorithms for the filtering and extraction of acoustic signals recorded by a phase-sensitive reflectometer will be considered.

Large Dynamic Range and Anti-Fading Phase-Sensitive OTDR Using 2-D Phase Unwrapping via Neural Network

Large Dynamic Range and Anti-Fading Phase-Sensitive OTDR Using 2-D Phase Unwrapping via Neural Network

Differentiating trace-to-trace noise effects using novel signal characteristics in phase-sensitive OTDR systems

Differentiating trace-to-trace noise effects using novel signal characteristics in phase-sensitive OTDR systems

Distributed vibration sensor with a lasing phase-sensitive OTDR.

The authors experimentally demonstrate the operation of a lasing phase-sensitive optical time-domain reflectometer (Φ-OTDR) based on random feedback from a sensing fiber. Here, the full output of the laser provides the sensing signal, in contrast to the small backscattered signal measured in a conventional OTDR. In this proof-of-principle demonstration, the laser operates as a distributed vibration sensor with signal-to-noise ratio of 23-dB and 1.37-m spatial resolution.

Advantages of using few-mode and multimode fibers in Phase Sensitive OTDR measurement system due to the modulation instability deferment

We discuss the possible advantages of using few-mode and multimode fibers in coherent optical time-domain reflectometry sensing systems. We show that the application of few-mode and multimode fibers decreases nonlinear effects and impedes modulation instability. In comparison to standard single-mode optical fiber, few-mode and multimode fibers may help to increase signal power at the receiver. We also show that few-mode fibers may potentially increase sensing distance.

Optical-pulse-coding phase-sensitive OTDR with mismatched filtering

Optical-pulse-coding phase-sensitive OTDR with mismatched filtering

Data Reduction in Phase-Sensitive OTDR with Ultra-Low Sampling Resolution and Undersampling Techniques.

Data storage is a problem that cannot be ignored in the long-term monitoring of a phase-sensitive optical time-domain reflectometry (Φ-OTDR) system. In this paper, we proposed a data-reduction approach for heterodyne Φ-OTDR using an ultra-low sampling resolution and undersampling techniques. The operation principles were demonstrated and experiments with different sensing configurations were carried out to verify the proposed method. The results showed that the vibration signal could be accurately reconstructed from the undersampled 1-bit data. A space saving ratio of 98.75% was achieved by converting 128 MB of data (corresponding to 268.44 ms of sensing time) to 1.6 MB. The proposed method led to a potentially new data-reduction approach for heterodyne Φ-OTDR, which also provided economical guidance for the selection of the data-acquisition device.