RESUMEN
Nowadays, early defect detection plays a significant role for the railway safety warning. However, the existing methods cannot satisfy the requirements of real-time and high-precision detection. Here, a high-precision, distributed and on-line method for detecting rail defect is proposed and demonstrated. When a train goes through defects, the instantaneous elastic waves will be excited by the wheel-rail interaction, which will further propagate along railway tracks bidirectionally. Through mounting the backscattering enhanced optical fiber on the railway as sensors, the fiber optic distributed acoustic sensing system can record the propagation trace precisely. Further, the acoustic propagation fitting method is applied onto the propagation data to detect and locate defects along the long-distance railway. Especially, the dual-frequency joint-processing algorithm is proposed to improve the location accuracy. The field test proves that multiple defects along the railway can be successfully identified and located with a standard deviation of 0.314m. To the best of our knowledge, this work is the first report of distributed rail defect detection, which will bring a breakthrough for high-precision structural damage detection in the infrastructures such as the railway, pipeline and tunnel.
RESUMEN
In order to suppress the noise of the coherent fiber distributed acoustic sensing (DAS) system, the spatio-temporal joint oversampling-downsampling technique is proposed. The spatial oversampling is used for artificially dense sampling, whose spacing is far less than the target spatial resolution. Then the spatial downsampling performed by the average of multiple differential sub-vectors is utilized to reduce the influence of noise vectors, which could completely eliminate the interfere fading without increasing any system complexity and introducing any crosstalk. Meanwhile, the temporal oversampling-downsampling is analyzed from the perspective of theory and simulation, demonstrating that the noise floor will decrease with the increase of downsampling coefficient. The temporal oversampling is carried out to expand the noise distribution bandwidth and ensure the correct quantization of the noise frequency. Then the temporal downsampling of differential phase reconstruction is utilized to recover the target bandwidth and reduce the out-of-band noise. The experimental results prove that the noise floor is inversely correlated with the spatiotemporal downsampling factors. The strain resolution of the DAS system with the proposed scheme can reach 2.58pε/âHz@100Hz-500Hz and 9.47pε/âHz@10Hz under the condition of DC-500Hz target bandwidth, as well as the probability of the large-noise sensing channels is greatly reduced from 44.32% to 0%. Moreover, the demodulated SNR of dynamic signal is improved by 20.8dB compared with the traditional method. Without any crosstalk, the noise floor is optimized 8dB lower than the averaging technique. Based on the proposed method, the high-performance DAS system has significant competitiveness in the applications with the demand of high-precision and high-sensitivity, such as passive-source seismic imaging and VSP exploration.
RESUMEN
A novel Rayleigh noise suppression method is proposed to improve temperature accuracy and resolution for Raman distributed fiber-optics sensors. The proposed temperature demodulation method can eliminate temperature measurement inaccuracy caused by Rayleigh noise. The experimental results indicate that the temperature accuracy is optimized from 6.2°C to 1.7°C at a sensing distance of 9.1 km by using the proposed method, and the temperature resolution leads to about 1.5°C improvement compared with the tradition demodulation method at a sensing distance of 10.0 km. The proposed method provides a robust and reliable high performance for long sensing ranges.
RESUMEN
We propose and experimentally demonstrate a novel auto-correction method for improving temperature stability in long-range Raman distributed fiber temperature sensors. The proposed method is based on multi-stage constant temperature control and dynamic gain calibration technology, which can suppress the unstable photoresponsivity and noise of a system. The experimental results indicate that the temperature stability is optimized from ±12.6°C to ±7.2°C at the sensing distance of 30 km for multimode fiber using this method.
RESUMEN
The field of tunnel fire detection requires a Raman distributed temperature sensor (RDTS) with high-accuracy and visual localization. A novel temperature demodulation method to improve the temperature measurement accuracy of the RDTS systems is presented. This method is based on the optical dynamic difference compensation algorithm, which can eliminate the optical power fluctuation. In addition, the visual localization technology is presented by using the longitudinal lining model (LLM) of a three-dimensional (3D) temperature display, which enhances the engineering application of RDTS in tunnel fire detection. Experimental results indicate that the temperature measurement accuracy is optimized from 7.0 °C to 1.9 °C at the sensing distance of 18.27 km by using the presented method. We provide a solution for temperature field monitoring as well as fire visual localization of the tunnel through RDTS systems.
RESUMEN
This paper considers a singular Kirchhoff equation with convection and a parameter. By defining new sub-supersolutions, we prove a new sub-supersolution theorem. Combining method of sub-supersolution with the comparison principle, for Kirchhoff equation with convection, we get the conclusion about positive solutions when nonlinear term is singular and sign-changing.