In order to better monitor and identify PCCP pipeline wire broken and obtain wire broken signal characteristics, this paper adopts φ-OTDR system to monitor pipeline wire broken signal and use wavelet packet decomposition to study the energy distribution of wire broken signal in different frequency bands. Firstly, the wire broken signal is collected by φ-OTDR system, and secondly, the wavelet packet decomposition is performed on the wire broken signal collected by the system to obtain the energy distribution of the wire broken vibration signal in different frequency bands. The results show that at 10kHz sampling rate, the frequency band energy (FBE) distribution of the wire broken signal is characterized as follows: the energy of the broken wire signal is higher in the high frequency band (2500-3125Hz, 3437.5-3750Hz, 4375-4687.5Hz) and lower in the low frequency range, and this feature is obvious compared with the non-broken wire case. This method provides a new idea for identifying wire broken events.
Optical pulse coding technique can improve some performance such as sensing distance of Brillouin Optical Time-Domain Analyzers (BOTDA) with the compatibility of its conventional device, and it often apply the Field Programmable Gate Array (FPGA) technique on pulse generation. To meet the requirement of fast measurement and system integration of BOTDA, a FPGA-based pulse coding and decoding technique is proposed in this paper, which accelerates the decoding process by parallelization and pipelining. The technique is tested in a BOTDA system with 100km measuring distance, 250MHz sampling rate and 255-bit Simplex coding, and achieves a decoding delay of 72ns to realize real-time decoding. In the experiment, the technique has an effect on improving the performance of BOTDA on measurement speed, sensing distance and spatial resolution on long sensing distance, comparing with the same system without pulse coding.
KEYWORDS: Hough transforms, Feature extraction, RGB color model, Image processing, Signal detection, Contour extraction, Signal to noise ratio, Signal processing, Reflection, Passive sonar
The image processing method is used to extract the target trajectory and signal features. This paper improves the traditional image processing method Hough transform, uses the Canny operator to detect the contour, and improves the traditional Hough transform by decomposing the signal features and time iteration. It can extract irregular trajectory targets and extract signal frequency domain features. At the end of this paper, experimental data proves that the improved Hough transformation method can meet the stable extraction of irregular curve trajectories and cross trajectories, and can also perform feature localization and feature extraction on feature signals.
KEYWORDS: Denoising, Signal processing, Fiber optics, Signal to noise ratio, Reconstruction algorithms, Optimization (mathematics), Genetic algorithms, Feature extraction, Signal detection
In the practical application of φ-OTDR system, the accuracy of the system is affected by the existence of environmental noise and so on. In order to effectively reduce the noise composition of the measured signal and better obtain the signal characteristics, this paper proposes a noise reduction method GA-VMD which combines genetic algorithm (GA) and variational mode decomposition (VMD). The method firstly optimizes the decomposition layer number (K) and penalty factor (α) of VMD by GA, and then performs multiscale permutation entropy (MPE) randomness detection of the intrinsic mode function (IMF) obtained by decomposition, so as to achieve the purpose of noise reduction. Through the processing of the measured signal, it is shown that the GA-VMD method is better than the empirical mode decomposition (EMD) and the Complementary Ensemble Empirical Mode Decomposition (CEEMD) method in terms of signal-to-noise ratio and cross-correlation coefficient. It shows that the GA-VMD algorithm is better than the EMD and CEEMDAN algorithms, which verifies the effectiveness of the method.
The structural health monitoring of Prestressed Concrete Cylinder Pipes (PCCP) is still a difficult issue because the existing detection methods and pipeline protection methods require pipelines to stop running for detection and maintenance, and cannot monitor the running status of pipelines online in real time. As a result, it is impossible to prevent pipeline damage timely and effective and prevent third-party intrusion and damage. Aiming at problems such as PCCP pipeline leakage and pipe burst caused by the external third-party intrusion, pipeline aging, and other factors, this paper proposes a distributed fiber-optic acoustic sensing monitoring method based on the combination of fiber-optic back Rayleigh scattering and phase-sensitive optical time-domain reflectometry. When the pipeline is running normally, by collecting and demodulating the vibration, sound, positioning information and other data along the vibrating optical cable laid on the pipeline, the monitoring and rapid positioning of the pipeline intrusion damage and broken wire can be realized, to achieve the effect of real-time online monitoring of the structural health of the pipeline. The simulation test results show that the system can monitor the length of the pipeline up to 50km, the fault location accuracy is less than 5m, and the system has a single-point listening function, which can realize the secondary review of the fault point alarm information.
The Brillouin Optical Time Domain Analyzer (BOTDA) is based on the Brillouin scattering effect which is sensitive to the temperature and strain of the fiber at the same time. It is widely used in the field of large-scale structural monitoring. With the continuous development of market demand, the dynamics of the original BOTDA equipment The response speed, sensing distance, spatial resolution, and measurement error can no longer meet the application of various scenarios. This puts forward higher requirements for the signal-to-noise ratio of the BOTDA system. The image denoising algorithm based on non-local mean filtering can be Make full use of the similarity between two-dimensional image signals. In this article, we proposed an adaptive image denoising algorithm to be applied to the BOTDA system, and got good results.
In order to improve the integration of the detection system for underwater acoustic, temperature and pressure in the ocean, a novel fiber-optic combined underwater acoustic, temperature and pressure sensor is proposed. The fiber-optic combined sensor consists of a FBG temperature sensor, a FBG pressure sensor and a Michelson interferometric fiberoptic hydrophone, which are connected by a single optical fiber. The optical signals from the FBG sensors and the fiberoptic hydrophone are completely independent and do not affect each other, so they can be detected and demodulated simultaneously. The fiber-optic combined acoustic temperature and pressure sensor can also be used in combined sensor arrays by time division multiplexing and wavelength division multiplexing. The fiber-optic combined sensor is designed and fabricated, and the performance of the sensor is tested experimentally. The experimental results show that the fiberoptic combined sensor system can measure the underwater temperature and pressure, underwater acoustic signal accurately.
The photodetection intensity noise to demodulated phase noise conversion process of fiber optic sensors using phase generated carrier (PGC) scheme is investigated through theoretical calculation and experimental verification. Several categories of intensity noise are calculated, according to their relation between intensity noise power spectral density and photodetection current. The results revealed that demodulated phase noise power level increases by several decibels over the relative intensity noise power level of detected light power signal. Phase noise power level could also fluctuate with demodulated phase signal. Increase of phase noise power level varies according to the noise type, as well as the fluctuation amplitude. For noises that intensity noise power level unrelated to detected light power, such as electronic noise of detector circuit, phase noise power level increases by about 3.7 dB and do not fluctuate with demodulated phase signal. For noises that intensity noise power level proportional to detected light power, such as signal-amplified spontaneous emission(ASE) beat noise of optical amplifiers, phase noise power level fluctuates with demodulated phase signal by about 5.7 decibels and averagely increases about 3.7 decibels over a 2π period of demodulated phase signal. For noises that intensity noise power level proportional to square of detected light power, such as light source relative intensity noise, phase noise power level fluctuates with demodulated phase signal by about 9.0 decibels and averagely increases about 4.8 decibels over a 2π period of demodulated phase signal. Verification experiments are demonstrated on electronic noise, ASE-signal beat noise and light source relative intensity noise separately.
A fiber-optic hydrogen sensor based on tunable diode laser spectroscopy is designed. The fiber-optic hydrogen sensor is composed of a fiber-optic Fabry-Perot interferometer, where one mirror is made of a hydrogen sensitive Pd thin film. By optimizing the structure parameters of the fiber-optic hydrogen sensor, a reflectance spectrum with the similar curve to a gas absorption spectrum is obtained. The reflectance spectrum of the fiber-optic hydrogen sensor is calculated at different hydrogen concentrations and the relation between the intensity minimums of the spectrum and the hydrogen concentrations is explored. The wavelength modulation spectroscopy is used to analyze the reflectance spectra, the relation between the second harmonic component and hydrogen concentrations is obtained, and the feasibility of the application of TDLAS on the fiber-optic hydrogen sensor is verified. This hydrogen sensing method has great potential in industrial application due to the advantages of high sensitivity, low cost, system’s simplicity.
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