Concise method for high-precision vibration recovery of Φ-OTDR based on the GF-FastICA algorithm.

To efficiently restore the vibration signals of a phase-sensitive optical time domain reflectometer (Φ-OTDR), the GF-FastICA joint algorithm is proposed, which combines guided filtering with fast independent component analysis (FastICA). The marked region of vibration is precisely located by guided filtering. FastICA deals with the optimal phase mixing matrix of the marked region to separate the vibration signals from the noise-containing phase signals. The experimental results show that the GF-FastICA achieves a correlation coefficient of 0.998 for 5-Hz vibration signal recovery from a 14.3-km sensing fiber, verifying the potency of the algorithm. Compared with the traditional method and FastICA only, GF-FastICA improves the root mean square error (RMSE) metric by an order of magnitude, which is approaching an experience value of 10-3.

Highly efficient method for cutting position selection of an x-ray mono-capillary lens based on an improved SCA-CSA algorithm.

In order to efficiently select the optimal cutting position of x-ray mono-capillary lenses, an improved sine cosine algorithm-crow search algorithm (SCA-CSA) algorithm is proposed, which combines the sine cosine algorithm with the crow search algorithm, with further enhancements. The fabricated capillary profile is measured using an optical profiler; then the surface figure error for interest regions of the mono-capillary can be evaluated using the improved SCA-CSA algorithm. The experimental results indicate that the surface figure error in the final capillary cut region is about 0.138 µm, and the runtime is 2.284 s. When compared with the traditional metaheuristic algorithm, the particle swarm optimization algorithm, the improved SCA-CSA algorithm, enhances the surface figure error metric by two orders of magnitude. Furthermore, the standard deviation index of the surface figure error metric for 30 runs also improves by more than 10 orders of magnitude, demonstrating the superior performance and robustness of the algorithm. The proposed method provides significant support for the development of precise cuttings of mono-capillaries.

Highly discriminative and adaptive feature extraction method based on NMF-MFCC for event recognition of Φ-OTDR.

To enhance the capability of phase-sensitive optical time domain reflectometers (Φ-OTDR) to recognize disturbance events, an improved adaptive feature extraction method based on NMF-MFCC is proposed, which replaces the fixed filter bank used in the traditional method to extract the mel-frequency cepstral coefficient (MFCC) features by a spectral structure obtained from the Φ-OTDR signal spectrum using nonnegative matrix factorization (NMF). Three typical events on fences are set as recognition targets in our experiments, and the results show that the NMF-MFCC features have higher distinguishability, with the corresponding recognition accuracy reaching 98.47%, which is 7% higher than that using the traditional MFCC features.

High-sensitivity fiber optic Fabry-Perot ultrasonic sensor based on a grooved silicon diaphragm for partial discharge detection.

An extrinsic fiber optic Fabry-Perot interferometric (EFPI) ultrasonic sensor based on a grooved silicon diaphragm for partial discharge (PD) detection has been proposed. The size of the groove is determined by finite element simulation, which allows the resonant frequency of the sensor to meet the requirements of PD ultrasonic detection and improves the sensitivity of the sensor by 5.07 times compared with that based on a traditional circular diaphragm. The microelectro-mechanical system process is used to fabricate the diaphragm on a silicon-on-insulator wafer, and the prepared diaphragm has a grooved section with a diameter of 829.34 µm and a thickness of only 2.09 µm. At its resonant frequency of 61.5 kHz, the acoustic pressure sensitivity of the sensor is 172.42 mV/Pa. The ultrasonic signal detection capability of the sensor is verified in the PD experiment. Furthermore, the characteristics of the corona discharge are successfully manifested based on the ultrasonic waves detected by the EFPI sensor. It is demonstrated that the proposed sensor is suitable for PD detection due to its high sensitivity, simple production process, and good resistance to environmental interference.

High-efficient disturbance event recognition method of ϕ-OTDR utilizing region-segmentation differential phase signals.

We demonstrate a disturbance event recognition method based on region segmentation, which utilizes differential phase signals of a phase-sensitive optical time-domain reflectometer (ϕ-OTDR) to recognize disturbance events efficiently. The long-haul sensing fiber is divided into subsensing regions; whereas the phase signals at the two end points of the subsensing regions are subtracted, unwrapped, and differenced to represent the disturbance information. Feature extraction and classification are performed separately on the subsensing regions datasets. The experimental results indicate that the average recognition accuracy of the region-segmentation-based event recognition method is up to 92.9%. Compared to the method without region segmentation, this proposed method improves the average recognition accuracy by 8%; whereas the recognition time of three disturbance events on a 14.8-km sensing system is only 0.39 s. The proposed method provides significant support for the development of disturbance event recognition of the ϕ-OTDR sensor system.

Simultaneous measurement of magnetic field and temperature based on two anti-resonant modes in hollow core Bragg fiber.

A simple and compact magnetic field and temperature dual-parameter sensor is proposed, which is based on a sandwich structure consisting of a section of hollow core Bragg fiber (HCBF) filled with magnetic fluid (MF) and two sections of single-mode fiber (SMF). The corresponding relationship between the resonant dip with different periods in the transmission spectrum and specific anti-resonant (AR) mode in the HCBF is determined. The resonant dips based on different AR modes shift differently when the magnetic field intensity and temperature change. Then, the simultaneous measurement of the magnetic field intensity and temperature can be achieved by utilizing a cross matrix. The experimental results show that the maximum magnetic field sensitivity in the range of 0-12 mT is 86.43 pm/mT, and the maximum temperature sensitivity in the range of 20-60 ℃ is 17.8 pm/℃. The proposed sensor has the advantages of compact structure, easy fabrication and low cost, thus, it has great potential applications in the field of simultaneous sensing of magnetic field intensity and temperature in complex environments.

Magneto-refractive properties and measurement of an erbium-doped fiber.

The magneto-refractive properties of an erbium-doped fiber (EDF) are investigated by theoretically analyzing the change in mode characteristics with a magnetic field and experimentally measuring it based on a fiber-optic Mach-Zehnder interferometer (MZI). The numerical results indicate that the mode effective refractive index (RI) increases as the magnetic field increases, and the mode field intensity distribution tends to be more concentrated in the core region with an increasing magnetic field. The variation in the mode effective RI of the fundamental mode with the magnetic field is greater than that of the higher-order modes. A magneto-refractive measurement system based on a fiber-optic MZI is set up to analyze the magneto-refractive effect of the EDF. The changes in the mode effective RI measured with a direct-current (DC) magnetic field and with a 100 Hz alternating-current (AC) magnetic field are 4.838×10-6 and 4.245×10-6 RIU/mT, respectively. The experimental results are in reasonable agreement with the theoretical analysis. Furthermore, the error between the experimental and numerical results is discussed. The magneto-refractive properties of the EDF exhibit potential in all-fiber magnetic field or current sensing area.