Search Results (17)

With the large-scale application and high-quality development demands of optical fiber cables, higher requirements have been placed on the corresponding measurement technologies. In recent years, optical fiber testing has played a crucial role in evaluating cable performance, as well as in the deployment, operation, maintenance, fault repair, and upgrade of optical networks. The Optical Time-Domain Reflectometer (OTDR) is a fiber fault diagnostic tool recommended by standards such as the International Telecommunication Union and the International Electrotechnical Commission. It is used to certify the performance of new fiber links and monitor the status of existing ones, detecting and locating fault events with advantages including simple operation, rapid response, and cost-effectiveness. First, this paper introduces the working principle and system architecture of OTDR, along with a brief discussion of its performance evaluation metrics. Next, a comprehensive review of improved OTDR technologies and systems is provided, categorizing different performance enhancement methods, including the enhanced measurement distance with simple structure and low cost in 2024, and the high spatial resolution measurement of optical fiber reflection events and non-reflection events in 2025. Finally, the development trends and future research directions of OTDR are outlined, aiming to achieve the development of low-cost, high-performance OTDR systems. Full article

Digital subcarrier multiplexing (DSCM) systems offer flexibility and software configurability, making them promising for point-to-multipoint (P2MP) communications. Meanwhile, DSCM systems exhibit enhanced communication damage tolerance and capabilities for damage monitoring and compensation. These capabilities include tolerance to equalized enhanced phase noise (EEPN) and high-speed Polarization State (SOP) tracking. The subcarrier intervals in DSCM systems naturally allow the insertion of pilot or training sequences. This facilitates enhanced communication functionality and integrated sensing capabilities. This review article summarizes the principles and schemes of integrated communication and sensing in DSCM systems. It analyzes performance in communication enhancement and sensing integration. Finally, it discusses unresolved technical challenges and future technological prospects. Full article

Since the advent of GPT, large language models (LLMs) have brought about revolutionary advancements in all walks of life. As a superior natural language processing (NLP) technology, LLMs have consistently achieved state-of-the-art performance in numerous areas. However, LLMs are considered to be general-purpose models for NLP tasks, which may encounter challenges when applied to complex tasks in specialized fields such as optical networks. In this study, we propose a framework of LLM-empowered optical networks, facilitating intelligent control of the physical layer and efficient interaction with the application layer through an LLM-driven agent (AI-Agent) deployed in the control layer. The AI-Agent can leverage external tools and extract domain knowledge from a comprehensive resource library specifically established for optical networks. This is achieved through user input and well-crafted prompts, enabling the generation of control instructions and result representations for autonomous operation and maintenance in optical networks. To improve LLM’s capability in professional fields and stimulate its potential on complex tasks, the details of performing prompt engineering, establishing domain knowledge library, and implementing complex tasks are illustrated in this study. Moreover, the proposed framework is verified on two typical tasks: network alarm analysis and network performance optimization. The good response accuracies and semantic similarities of 2400 test situations exhibit the great potential of LLM in optical networks. Full article

Electric pylons are crucial components of power infrastructure, requiring accurate detection and identification for effective monitoring of transmission lines. This paper proposes an innovative model, the EP-YOLOv8 network, which incorporates new modules: the DSLSK-SPPF and EMS-Head. The DSLSK-SPPF module is designed to capture the surrounding features of electric pylons more effectively, enhancing the model’s adaptability to the complex shapes of these structures. The EMS-Head module enhances the model’s ability to capture fine details of electric pylons while maintaining a lightweight design. The EP-YOLOv8 network optimizes traditional YOLOv8n parameters, demonstrating a significant improvement in electric pylon detection accuracy with an average mAP@0.5 value of 95.5%. The effective detection of electric pylons by the EP-YOLOv8 demonstrates its ability to overcome the inefficiencies inherent in existing optical satellite image-based models, particularly those related to the unique characteristics of electric pylons. This improvement will significantly aid in monitoring the operational status and layout of power infrastructure, providing crucial insights for infrastructure management and maintenance. Full article

Pipelines are structures with great relevance in different industrial sectors and are essential for the proper functioning of the logistics that support today’s society. Due to their characteristics, locations, and continuous operation, allied with the huge network of pipelines across the world, they require specialized labor, maintenance, and adequate sensing systems to access their proper operation and detect any damage they may suffer throughout their service life. In this work, a fiber Bragg grating (FBG)-based optical fiber accelerometer (OFA), which was designed and calibrated to operate through wavelength and optical power variations using different interrogation setups, was fixed together with a pair of FBG arrays along a 1020 carbon steel pipeline section with the objective of monitoring the pipeline natural frequency (f_{n_pipeline}) to indirectly evaluate the detection and evolution of corrosion when this structure was buried in sand. Here, corrosion was induced in a small area of the pipeline for 164 days, and the OFA was able to detect a maximum f_{n_pipeline} variation of 3.8 Hz in that period. On the other hand, the attached FBGs showed a limited performance once they could successfully operate when the pipeline was unburied, but presented operational limitations when the pipeline was buried in sand. This was due to the inability of the structure to vibrate long enough under these conditions and obtained data from these sensors were insufficient to obtain the f_{n_pipeline}. Full article

Linear feature networks are the roads, trails, pipelines, and seismic lines developed throughout many commercial boreal forests. These linear features, while providing access for industrial, recreational, silvicultural, and fire management operations, also have environmental implications which involve both the active and non-active portions of the network. Management of the existing linear feature networks across boreal forests would lead to the optimization of maintenance and construction costs as well as the minimization of the cumulative environmental effects of the anthropogenic linear footprint. Remote sensing data and predictive modelling are valuable support tools for the multi-level management of this network by providing accurate and detailed quantitative information aiming to assess linear feature conditions (e.g., deterioration and vegetation characteristic dynamics). However, the potential of remote sensing datasets to improve knowledge of fine-scale vegetation characteristic dynamics within forest roads has not been fully explored. This study investigated the use of high-spatial resolution (1 m), airborne LiDAR, terrain, climatic, and field survey data, aiming to provide information on vegetation characteristic dynamics within forest roads by (i) developing a predictive model for the characterization of the LiDAR-CHM vegetation cover dynamic (response metric) and (ii) investigating causal factors driving the vegetation cover dynamic using LiDAR (topography: slope, TWI, hillshade, and orientation), Sentinel-2 optical imagery (NDVI), climate databases (sunlight and wind speed), and field inventory (clearing width and years post-clearing). For these purposes, we evaluated and compared the performance of ordinary least squares (OLS) and machine learning (ML) regression approaches commonly used in ecological modelling—multiple linear regression (mlr), multivariate adaptive regression splines (mars), generalized additive model (gam), k-nearest neighbors (knn), gradient boosting machines (gbm), and random forests (rf). We validated our models’ results using an error metric—root mean square error (RMSE)—and a goodness-of-fit metric—coefficient of determination (R²). The predictions were tested using stratified cross-validation and were validated against an independent dataset. Our findings revealed that the rf model showed the most accurate results (cross-validation: R² = 0.69, RMSE = 18.69%, validation against an independent dataset: R² = 0.62, RMSE = 20.29%). The most informative factors were clearing width, which had the strongest negative effect, suggesting the underlying influence of disturbance legacies, and years post-clearing, which had a positive effect on the vegetation cover dynamic. Our long-term predictions suggest that a timeframe of no less than 20 years is expected for both wide- and narrow-width roads to exhibit ~50% and ~80% vegetation cover, respectively. This study has improved our understanding of fine-scale vegetation dynamics around forest roads, both qualitatively and quantitatively. The information from the predictive model is useful for both the short- and long-term management of the existing network. Furthermore, the study demonstrates that spatially explicit models using LiDAR data are reliable tools for assessing vegetation dynamics around forest roads. It provides avenues for further research and the potential to integrate this quantitative approach with other linear feature studies. An improved knowledge of vegetation dynamic patterns on linear features can help support sustainable forest management. Full article

The digital optical fiber repeater (DOFR) is an important infrastructure in the LTE networks, which solve the problem of poor regional signal quality. Various types of conventional measurement data from the LTE network cannot indicate whether a working DOFR is present in the cell. Currently, the detection of DOFRs relies solely on maintenance engineers for field detection. Manual detection methods are not timely or efficient, because of the large number and wide geographical distribution of DOFRs. Implementing automatic detection of DOFR can reduce the maintenance cost for mobile network operators. We treat the DOFR detection problem as a classification problem and employ a deep convolutional neural network (DCNN) to tackle it. The measurement report (MR) we used in this paper are tabular data, which is not an ideal input for DCNN. We propose a novel MR representation method that takes the overall MR data of a cell as a sample rather than a single record in the table, and represents the MR data as a pseudo-image matrix (PIM). The PIM will be used as the input for training DCNN, and the trained DCNN will be used to perform DOFR detection tasks. We conducted a series of experiments on real MR data, and the classification accuracy can achieve 93%. The proposed AI-based method can effectively detect the DOFR in a cell. Full article

Optical performance monitoring (OPM), particularly the optical power and optical signal-to-noise ratio (OSNR) of each wavelength channel, are of great importance and significance and need to be implemented to ensure stable and efficient operation/maintenance of wavelength division multiplexing (WDM) networks. However, the critical monitoring module of existing solutions generally are too expensive, operationally inconvenient and/or functionally limited to apply over WDM systems with numerous nodes. In this paper, a low-cost and high-efficiency OPM scheme based on differential phase shift keying (DPSK)-modulated digital optical labels is proposed and demonstrated. Each pilot tone is modulated by digital surveillance information and treated as an identity indicator and performance predictor that ties up to each wavelength channel and thereby can monitor the performance of all wavelength channels simultaneously by only one low-bandwidth photoelectric detector (PD) and by designed digital signal processing (DSP) algorithms. Simulation results showed that the maximum errors of channel power monitoring and OSNR estimation were both less than 1 dB after 20-span WDM transmission. In addition, offline experiments were also carried out and further verified the feasibility of our OPM scheme. This confirms that the optical label based OPM has lower cost and higher efficiency and thereby is of great potential for mass deployment in practical WDM systems. Full article

For many parasitic diseases, the microscopic examination of clinical samples such as urine and stool still serves as the diagnostic reference standard, primarily because microscopes are accessible and cost-effective. However, conventional microscopy is laborious, requires highly skilled personnel, and is highly subjective. Requirements for skilled operators, coupled with the cost and maintenance needs of the microscopes, which is hardly done in endemic countries, presents grossly limited access to the diagnosis of parasitic diseases in resource-limited settings. The urgent requirement for the management of tropical diseases such as schistosomiasis, which is now focused on elimination, has underscored the critical need for the creation of access to easy-to-use diagnosis for case detection, community mapping, and surveillance. In this paper, we present a low-cost automated digital microscope—the Schistoscope—which is capable of automatic focusing and scanning regions of interest in prepared microscope slides, and automatic detection of Schistosoma haematobium eggs in captured images. The device was developed using widely accessible distributed manufacturing methods and off-the-shelf components to enable local manufacturability and ease of maintenance. For proof of principle, we created a Schistosoma haematobium egg dataset of over 5000 images captured from spiked and clinical urine samples from field settings and demonstrated the automatic detection of Schistosoma haematobium eggs using a trained deep neural network model. The experiments and results presented in this paper collectively illustrate the robustness, stability, and optical performance of the device, making it suitable for use in the monitoring and evaluation of schistosomiasis control programs in endemic settings. Full article

The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is prone to failure due to high electrical stresses, and thus it is a critical aspect that needs to be monitored. The ageing process of the electrical insulation in high voltage equipment may accelerate due to the occurrence of partial discharge (PD) that may in turn lead to catastrophic failures if the related defects are left untreated at an initial stage. Therefore, there is a requirement to monitor the PD levels so that an unexpected breakdown of high-voltage equipment is avoided. There are several ways of detecting PD, such as acoustic detection, optical detection, chemical detection, and radiometric detection. This paper focuses on reviewing techniques based on radiometric detection of PD, and more specifically, using received signal strength (RSS) for the localization of faults. This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN). Full article

An electrical power grid, is an interconnected network for delivering electricity from producers to consumers. Electrical grids vary in size from covering a single building through national grids (which cover whole countries) to transnational grids (which can cross continents). As the rollout of smart meters continues worldwide, there are use-cases where common solutions fail and the network availability of certain meters is very low due to poor communication conditions. This paper proposes a data slicing model for large data files which have to travel securely and reliably throughout the Smart Grid. The manuscript addresses improvements for PRIME PLC network availability by using correct data slicing at the application level along a tuned transmission rate in accordance with the noise levels of the power grid. Successful communications, even at low rates, mean that no manual interaction from energy supplier operators is needed reducing the maintenance costs for both the energy companies as well as for the end user. Experiments on a low power electrical grid setup have been performed in order to evaluate availability improvements through the proposed method as well as the feasibility of remote firmware upgrades. The results have shown that the current approach has similar upgrade time results with a manual firmware upgrade performed through an optical probe. Moreover, the results show that the presented remote firmware upgrade method is reliable and practical. Full article

It is 21 years since the first passive optical network (PON) was standardized as an asynchronous transfer mode passive optical network (APON) with same optical distribution network scheme as we know in current networks. A lot of PON networks were standardized in the following years and became an important part of telecommunication. The general principles of these PON networks are described in many papers and books, but only a little information about used lasers is available. The aim of this tutorial is to describe lasers used in PON networks and principles of their operation. The paper describes the principles of single longitudinal mode (SLM), multi longitudinal mode (MLM), distributed-feedback (DFB), and Fabry–Pérot (FP) lasers. Furthermore, the lasers are compared by their usage in optical line termination (OLT) for passive optical networks. The second part of this tutorial deals with activation process of optical network unit. The described principle is the same for connection of a new customer or blackout scenario. The end unit is not able to communicate until reach the operational state; each state is defined with physical layer operation and administration and maintenance (PLOAM) messages sequence and their processing. Full article

A microfluidic sensor was studied for the photometric detection of active chlorine, total chlorine, and pH in swimming pool samples. The sensor consisted of a four-layer borosilicate glass chip, containing a microchannel network and a 2.2 mm path length, 1.7 mL optical cell. The chip was optimised to measure the bleaching of methyl orange and spectral changes in phenol red for quantitative chlorine (active and total) and pH measurements that were suited to swimming pool monitoring. Reagent consumption (60 mL per measurement) was minimised to allow for maintenance-free operation over a nominal summer season (3 months) with minimal waste. The chip was tested using samples from 12 domestic, public, and commercial swimming pools (indoor and outdoor), with results that compare favourably with commercial products (test strips and the N,N’-diethyl-p-phenylenediamine (DPD) method), precision pH electrodes, and iodometric titration. Full article

Nowadays, the space operations environment have to face with space safety problems because of the growing of space debris in resident of space objects (RSOs) that can cause a catastrophic collision. In order to prevent debris-related risks in operational orbit, ground-based passive optical telescope network were used as a primary equipment for space debris observation due to the lowest maintenance costs. Furthermore, in technical, a precise tracking (position and velocity) of space objects can be beneficial towards not only orbit determination but also estimation spacecraft collision probability especially, in Low-Earth Orbit regime. National Astronomical Research Institute of Thailand (NARIT) has long experience operate in an observatory to perform both passive & active optical instruments for astrophysics and space sciences missions. In this research, based on Thai National Space objects Observation (TNSO) project, we re-establish the basic understanding of satellite tracking, optical subsystem integration and demonstration a framework so as to enhance the capability of telescope servo control subsystem. We describe the specific solutions adopted for continuous tracking mode and the results obtained during the commissioning of an alt-azimuth mounting equipped with 0.7 meter optical aperture telescope. The observation system can be performed with negligible as continuous tracking error. This contribution will present some of the experimental results and plans for further measurement campaigns. Full article

Passive optical networks are currently the most promising solution for access networks. These networks rely on broadcast signal distribution in the downstream direction and unicast signal transmission in the upstream direction. The upstream direction is controlled by optical line termination (OLT). The broadcast transmission method increases security vulnerability because the attacker is able to connect his/her modified optical network unit (ONU) to the free port of the splitter (commonly in the basement). We present the concept for the activation process of ONUs based on physical unclonable function (PUF) for next-generation passive optical networks stage 2 (NG-PON2). The use of PUF increases security in the NG-PON2. Furthermore, the registration identifier (ID) is not stored in a nonvolatile memory, in comparison with the common solution defined by the International Telecommunication Union (ITU) recommendation G.989.3. An attacker cannot perform a reverse engineering attack to obtain the registration ID. For this reason, the attacker cannot clone an ONU. We proposed security improvements that involve authentication, encryption, integrity protection, and data origin verification methods in the NG-PON2. Our model uses the standard implementation of the transmission convergence layer of NG-PON2 with the new physical layer operations, administration, and maintenance (PLOAM) messages. The recommendation G.989.3 allows specifying own PLOAM messages since not all IDs are used in the current specification. Full article