Raman Distributed Temperature Sensor Research Articles

Derived Sequences Decoding Approach for Long-Range Distributed Temperature Sensors

A novel derived sequences decoding approach is proposed to solve the transient effect in the process of amplifying Golay codes pulse sequences by Erbium-doped fiber amplifier (EDFA) in long-range Raman distributed temperature sensors (RDTS). The derived sequences that maintain good cross-correlation with the attenuated sequences are used to decode without distortion to the greatest extent. Without adding the hardware equipment of the RDTS system, the attenuation of Golay codes is compensated in the process of decoding. The sidelobes of the time-domain correlation results can be reduced to less than 1% of the peak height. In addition, the return-to-zero (RZ) Golay codes output by the distributed feedback (DFB) laser is transmitted to the fiber to improve the signal-to-noise ratio (SNR). Finally, the maximum temperature resolution of ±2.5 °C is achieved at a 45 km-long single-mode fiber (SMF) when the spatial resolution (SR) is 5 m.

Experimental research on temperature field construction of nuclear waste barrel based on RDTS with improved spatial resolution

In this paper, a 3D temperature field construction method based on Raman Distributed Temperature Sensor (RDTS) with improved spatial resolution is proposed to monitor the side surface temperature of Nuclear Waste Barrel (NWB). This method includes two aspects: the spatial resolution enhancement of RDTS and the signal dimension conversion. Firstly, the spatial resolution improvement method combining Fully-Connected Neural Network (FCNN) and Total Variation Deconvolution (TVD) is used to improve the spatial resolution of RDTS from 1.6 m to 0.4 m. Then, the one-dimensional temperature signal is converted into 2D temperature field by matrix laying method. Finally, by establishing the coordinate system of the NWB, the 2D temperature field can be converted into a 3D one. The experimental results of the simulation device showed that when the circular thermal area with diameter of 0.4 m, 0.6 m and 0.8 m appeared on the side surface of NWB, the temperature accuracy of the temperature field image constructed by this method can reach 80.91 %, 72.09 % and 85.97 % respectively, and the shape was accurate. The method proposed in this paper can accurately present the surface temperature field of NWB and provide technical support for the safe operation of the nuclear waste disposal repository during its life cycle.

Raman distributed temperature sensor at fiber optic for oil wells - reliability analysis and accelerated life testing

Raman distributed temperature sensor at fiber optic for oil wells - reliability analysis and accelerated life testing

Enhanced Raman Distributed Temperature Sensor Based on Self-Constructed Fully Connected Neural Network

The performance of Raman Distributed Temperature Sensing (RDTS) is greatly limited by the effect of optical and other random noise on the backscattered Anti-Stokes signal. Therefore, it is necessary to study the signal denoising method of the system. Existing methods to improve system performance mainly include improving the system structure and using denoising methods like cumulative averaging, wavelet transform, etc., which still have room for improvement. In this paper, a Fully-Connected-RDTS model based on fully connected neural network is designed to reduce temperature errors and improve spatial positioning accuracy. Compared with traditional denoising algorithms, the maximum temperature error is reduced to 0.53 °C (±0.25 °C) using only 500 averages of the temperature data, which is better than 2.61 °C of 10,000 cumulative averages, and 2.25 °C of wavelet transforms. The predictions for the boundary of the temperature curve are highly consistent with the original data, and the error of spatial positioning accuracy is less than 1 m without blurring the spatial information like cumulative averaging and wavelet transform algorithms. Compared with the results of 10,000 cumulative averages, the detection response time is reduced from 8 s to 1-s while the noise is greatly filtered. The measurement performance of the RDTS system is greatly improved by the Fully-Connected-RDTS model without sacrificing spatial accuracy. And once the model is successfully trained, there is no need to change the parameters of the model, so it could be used for large-scale real-time detection.

Distributed temperature sensor combining centimeter resolution with hundreds of meters sensing range.

We present a Raman distributed temperature sensor based on standard telecom single mode fibers and efficient polarization-independent superconducting nanowire single photon detectors. Our device shows 3 cm and 1.5 °C resolution on a 5 m fiber upon one minute integration. We show that spatial resolution is limited by the laser pulse width and not by the detection system. Moreover, for long fibers the minimum distance for a measurable temperature step change increases of around 4 cm per km length, because of chromatic dispersion at the Stokes and Anti-Stokes wavelengths. Temperature resolution is mainly affected by the drop in the laser repetition rate when long fibers are tested. On a 500 m fiber, a trade-off of 10 cm and 8 °C resolution is achieved with 3 minutes integration. Fiber-based distributed temperature sensing, combining centimetric spatial resolution with hundreds of meters sensing range, could pave the way for a new kind of applications, such as 2D and 3D temperature mapping of complex electronic devices, particles detectors, cryogenic and aerospace instrumentation.

Conductor Temperature Monitoring of High-Voltage Cables Based on Electromagnetic-Thermal Coupling Temperature Analysis

As a key state parameter of high-voltage cables, conductor temperature is an essential determinant of the current carrying capacity of cables, but in practice, this is difficult to measure directly during the operation of high-voltage cables. In this paper, the electromagnetic-thermal coupling analysis model of a 110 kV high-voltage cable is established using the finite element analysis software COMSOL. By analyzing the temperature distribution law of high-voltage cables under different load currents and ambient temperatures, the relationship between the change in the high-voltage cable surface temperature and the conductor temperature is deduced, which allows the monitoring of the high-voltage cable conductor temperature. Taking the 110 kV cable of the Yanzhong line in Shanxi Province as an example and using the electromagnetic-thermal coupling temperature field analysis method, the conductor temperature of the high-voltage cable can be measured using the data obtained from the cable surface temperature, which is measured by the self-developed Raman Distributed Temperature Sensor (RDTS) system with a maximum measurement error of about 2 °C. The method is easy to use and can achieve the accurate measurement of the conductor temperature without damaging the cable body.

Enhanced Raman Distributed Temperature Sensor Using a High Raman Gain Fiber

We have designed and fabricated a single-mode Raman gain fiber (RGF) and use it to experimentally demonstrate a Raman distributed temperature sensor (RDTS) for high-precision temperature measurement with low power consumption. We have performed simulation to analyze the impact of fluorine-doped inner cladding on the control of the acoustic field and suppression of stimulated Brillouin scattering (SBS), showing that the SBS threshold can be improved by 37dB at 6wt% fluorine-doping concentration. Taking advantage of high Raman gain, a maximum signal-to-noise ratio (SNR) improvement of 6dB has been realized by using RGF under the same pump power as by using single-mode fiber (SMF), and the temperature uncertainty at the fiber end is enhanced from 0.9°C to 0.5°C. To achieve comparable sensing accuracy as that of SMF-based RDTS, our RGF-based RDTS only consumes half of the power, showing good energy efficiency. The magnitude of SNR and temperature uncertainty enhancement is limited by the relatively large fiber attenuation, but it can be further improved through optimization of the fiber design with high fluorine-doping concentration and graded index structure.

Measurement accuracy enhancement with multi-event detection using the deep learning approach in Raman distributed temperature sensors.

In this work, we present a novel deep learning framework for multi-event detection with enhanced measurement accuracy from the measured data of a Raman Optical Time Domain Reflectometer (Raman-OTDR). We demonstrate the utility of a deep learning-based approach by comparing the results from three popular neural networks, i.e. vanilla recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU). Before feeding the experimentally obtained data to the neural network, we sanitize our data through a correlation filtering operation to suppress outlier noise spikes. Based on experiments with Raman-OTDR traces consisting of single temperature event, we show that the GRU is able to provide better performance compared to RNN and LSTM models. Specifically, a bidirectional-GRU (bi-GRU) architecture is found to outperform other architectures owing to its use of data from both previous as well as later time steps. Although this feature is similar to that used recently in one dimension convolutional neural network (1D-CNN), the bi-GRU is found to be more effective in providing enhanced measurement accuracy while maintaining good spatial resolution. We also propose and demonstrate a threshold-based algorithm for accurate and fast estimation of multiple events. We demonstrate a 4x improvement in the spatial resolution compared to post-processing using conventional total variational denoising (TVD) filters, while the temperature accuracy is maintained within ± 0.5 oC of the set temperature.

SNR enhancement of a Raman distributed temperature sensor using partial window-based non local means method

Raman scattering-based distributed sensor is nowadays the most mature and consolidated technology for distributed temperature sensing at long ranges. Even though the various applied methods in recent decades have made important improvements in performance of Raman sensors, they do not thoroughly exploit the high level of correlation and similitude existing in the acquired data. In the present, we exploit a 2D image processing method called non-local means (NLM) algorithm that takes full advantage of, compared to existing methods, highly redundant texture of the 1D data obtained from distributed Raman sensors. One of the main drawbacks of the original NLM filter in distributed sensors area is to establish complete squared similarity windows for denoising the boundary pixels, corresponding to the data placed at the last row of the data matrices, which constrains the best attainable SNR values. To overcome this issue, we introduce an unprecedented approach called partial window (PW) by which we utilize partial similarity windows for denoising the boundary pixels. The PW-based NLM (PW-NLM) technique not only leads to higher levels of SNR compared with the original one, but also has no detrimental effects on the denoised data. The simulation results demonstrate the SNR improvement of 2.8 dB using the PW-based NLM filter over the original NLM filter corresponding to the 17 dB SNR boost compared with the unprocessed data.

Photovoltaic Panel Temperature Monitoring and Prediction by Raman Distributed Temperature Sensor With Fuzzy Temperature Difference Threshold Method

Solar cells can operate at a lower efficiency after a certain temperature, which is caused by a negative thermal coefficient. Therefore, the temperature prediction of photovoltaic (PV) modules is critical to accurately evaluate the efficiency of photovoltaic devices. We propose and experimentally demonstrate a Fuzzy Temperature Difference Threshold Method (FTDTM) based on Raman Distributed Temperature Sensor (RDTS) system for the detection and prediction of PV module temperature. The FTDTM consists of four steps, i.e., division of the universe, establishment of fuzzy relationships, definition of relationship matrix and calculation of predicted temperature. The experimental results show that the proposed RDTS can detect and accurately predict temperature trends by using the FTDTM. When the system window base of the FTDTM is set to 2, the average absolute error of the predicted temperature is 1.08 °C, and the fluctuation range of prediction error is ±3.7 °C. In addition, the experiment studied some factors affecting temperature distribution characteristics of PV modules, including solar radiation intensity, surface dust and inclination angle. We provide a solution for large-scale PV module temperature detection and early warning through RDTS systems with FTDTM.

R-DTS With Heat Transfer Functional Model for Perceiving the Surrounding Temperature

In the field of temperature safety monitoring, it is important to quickly locate the position of temperature anomalies and start to alarm. The multimode fiber (MMF) has a certain temperature hysteresis effect when detecting the surrounding temperature along the sensing fiber, it deteriorates the warning-time of Raman distributed temperature sensor (R-DTS). This paper proposed and experimentally demonstrated an R-DTS with heat transfer functional model to perceive the surrounding temperature in advance. The temperature hysteresis effect of MMF cable in different temperature conditions are studied experimentally. The experimental results show that the temperature change rate of MMF and the surrounding temperature difference maintains a linear relationship after fitting. And this fitting relationship is used to perceive the surrounding temperature anomalies along the MMF for R-DTS system. The experimental results indicate that the warning-time of R-DTS can optimize from 23.4 s to 1.3 s at the temperature condition with 60 °C. It proves that this analytical model of the heat transfer function model can quickly perceive the environment temperature anomalies to avoid the temperature hysteresis effect of MMF at the difference temperature conditions. The research content can be applied in the temperature safety monitoring with high requirements for early-warning time, such as fire monitoring, power cable safety monitoring, and gas pipeline leakage detection.

Performances of Radiation-Hardened Single-Ended Raman Distributed Temperature Sensors Using Commercially Available Fibers

Among all the distributed optical fiber temperature sensors, the Raman-based one that is intrinsically unaffected by the evolution of applied strain on the sensitive fiber. The radiation vulnerability of a classical single-ended Raman distributed temperature sensor (RDTS), even using a radiation-resistant fiber, is strongly degraded, leading to unacceptable levels of measurement errors. Double-ended RDTSs (DE-RDTS) allow mitigating most of the measurement errors but could be more largely impacted by the radiation-induced attenuation (RIA) in terms of accessible sensing length. A radiation-hardened architecture of single-ended RDTS was developed to overcome this problem. Here, we investigate the radiation performances of such an RDTS by combining it with commercial fibers of different compositions. Its potential to monitor temperature in various harsh environments mixing temperature and radiation constraints is discussed.

High-accuracy distributed temperature measurement using difference sensitive-temperature compensation for Raman-based optical fiber sensing.

In the temperature monitoring field, the Raman Distributed Temperature Sensor (R-DTS) is required with a temperature accuracy better than 1 °C over a long distance. This paper proposes and experimentally demonstrates an R-DTS system based on the difference sensitive-temperature compensation to optimize the temperature accuracy with the enhanced temperature sensitivity of backscattered spontaneous Raman scattering. While operating in the experiment, the distributed temperature measurement and theory analysis use the dual-demodulation, self-demodulation and double-end configuration principles for R-DTS are demonstrated. The experimental results show that the temperature accuracy is 12.54 °C, 8.53 °C and 15.00 °C along the 10.8 km under the standard R-DTS systems, respectively. Further, we analyze and recalibrate the intensity of the Raman scattering signal in theory, and substitute the sensitive-temperature factor (M(L)) into the Raman scattering signal. Finally, a novel temperature demodulation method with difference sensitive-temperature compensation is applied to the dual-demodulation, self-demodulation, and double-end configuration R-DTS systems. After compensation, the temperature accuracy can be optimized to 0.38 °C, 0.36 °C and 0.56 °C at the same position. It proves that the proposed method can make the temperature accuracy better than 1 °C for these three demodulation systems.

Monolithic multicore fiber based multi-parameter measurement based on spatial-division-multiplex sensing mechanisms

A monolithic all-solid multicore fiber based smart sensing system has been proposed and demonstrated in this paper. This technology enables the monitoring of multiple parameters of interest simultaneously, by spatially multiplexing specific sensing mechanisms seamlessly through different cores. The Raman distributed temperature sensor (RDTS), polarization detection based vibration sensor (PVS) and fiber Bragg grating (FBG) sensor are successfully integrated via a 7-core fiber for vibration frequency and discriminated strain and temperature sensing. The experimental results show that the performance of PVS based vibration frequency sensing is unacted on the influence of ambient strain and temperature. In addition, the discriminated strain and temperature measurements have also been experimentally investigated. All the results demonstrated that the proposed scheme of spatially multiplexing FBG with RDTS and PVS can readily achieve simultaneous measurement of vibration and discriminated strain and temperature, which provides a promising way of multi-dimension diagnosis for structural health monitoring.

Fiber Optic Raman Distributed Temperature Sensor Based on an Ultrashort Pulse Mode-Locked Fiber Laser

The testing of an all-fiber erbium ultrashort pulsed laser in a distributed fiber temperature sensor as a source of probing pulses has been performed. Among the prospects of such an approach are an improved signal–noise ratio in the receiving system and a better spatial resolution of the temperature sensor. The experiments have revealed the factors that limit the effective length of the fiber temperature sensor, such as a high pulse repetition frequency and intrinsic laser noises. As a result of the performed work, the distributed fiber optical temperature sensor with a near-room-temperature resolution of ~1.5 K, an effective length of ~3 m, and a spatial resolution of ~10 cm has been developed.

Spatial and Temporal Resolution Optimization on Raman Distributed Temperature Sensor System for Quench Detection in a No-Insulated Coil

Quench detection and protection technologies are extremely important for high-temperature superconducting (HTS) magnet applications. In a previous work, we have verified the feasibility of using a Raman-based distributed temperature sensor (RmDTS) system to measure a no insulation (NI) HTS coil temperature changes in an overcurrent induced quench event. However, rough and slow temperature measurement is unsuitable for actual application on quench detection and protection. Therefore, we designed a new RmDTS system consisting of an RmDTS device whose temporal resolution is 15 ms and a thinner polyimide-coated optical fiber with a diameter of 150 μ m. Then, the optimized RmDTS system and an original one were, respectively, applied to detect the NI coil temperature during quenches. The comparative results show that the highest heat was generated on the 22nd turn of the NI coil, and the temperature response time of the original DTS system is 2 s slower than that of the optimized one. By using an optimization method, the spatial and temporal resolutions of the RmDTS system have been enhanced triple and 66 times than before.

Raman Distributed Temperature Sensor with Optical Dynamic Difference Compensation and Visual Localization Technology for Tunnel Fire Detection.

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.

Link optimized few-mode fiber Raman distributed temperature sensors.

A link optimized few-mode fiber-based Raman distributed temperature sensor is proposed to enhance the temperature resolution of the long-distance sensing system. Comprehensive theoretical analysis and experimental validation in contrast with the traditional single-mode fiber-based sensing link have been conducted to reveal the benefits provided by the optimization scheme. The temperature resolutions are about 3.8°C for the proposed fiber link at 20km distance, leading to about 6.2°C improvement compared with the single-mode fiber (SMF) link. The total measurement is completed within 80s over 20km with a spatial resolution of 3m.

Long-range Raman distributed temperature sensor with high spatial and temperature resolution using graded-index few-mode fiber.

We designed and fabricated a graded-index few-mode fiber (GI-FMF) with large effective mode area and low intermodal dispersion for Raman distributed temperature sensor (RDTS) to simultaneously achieve high spatial and temperature resolution over long distance. In experiment, we measured the spatial and temperature resolution of the RDTS using different types of fibers under different launch conditions based on a commercially available RDTS system. By using the GI-FMF under the overfilled launch condition, we achieved a 1 °C temperature resolution with a spatial resolution of 1.13 m at the distance of 25 km. The spatial resolution using the standard MMF degraded to 2.58 m with only a 0.3 °C higher temperature resolution in comparison. As a result, the GI-FMF under the few-mode operation condition can provide a desirable temperature resolution comparable with that of the MMF with a negligible degradation on spatial resolution. Moreover, the RDTS using the GI-FMF under the quasi-single mode operation condition achieved a temperature resolution of 4.7 °C at the distance of 25 km with a 2.2 °C improvement and no degradation on spatial resolution compared with that using the standard SMF.

A metrological comparison of Raman-distributed temperature sensors

Raman distributed temperature sensing techniques (Raman-DTS) are currently meeting a growing interest from the industry as they are a promising and cheap alternative to classical temperature measurements which require the deployment of many sensors. The reliability of the DTS measurements, as well as the traceability to the temperature standards, must be ensured throughout the entire period of use (typically over a few tens of years for nuclear waste repositories and hydraulic structures). LNE, in association with Andra and EDF has developed facilities dedicated to the metrological characterization of Raman DTS devices. A first benchmark performed on five devices from different manufacturers has been performed following experimental procedures which enable a relevant comparison of these instruments. This paper defines the proposed metrological features to be evaluated for each Raman DTS system, and presents a ranking method enabling to provide useful pieces of information to the final users for the selection of the most appropriate device to the requirements of their applications.