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Compact TDLAS sensor System for ppm-Level CO Detection in Early Electrical Fires Using a Low-Power Laser Diode and Miniature Multipass Cell

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IEEE sensors JOURNAL 2025年第10期25卷 18163-18170页

作者： Wang, Gang Cui, Ruyue Di, Jin Wang, Yong Wang, Jiapeng Feng, Chaofan Chen, Yifan Wu, Hongpeng Dong, Lei Shanxi Univ Inst Laser Spect State Key Lab Quantum Opt Technol & Devices Taiyuan 030006 Peoples R China Shanxi Univ Collaborat Innovat Ctr Extreme Opt Taiyuan 030006 Peoples R China

A compact tunable diode laser absorption spectroscopy (TDLAS) gas sensor system for ppm-level carbon monoxide (CO) detection is demonstrated, featuring a miniature multipass cell (MPC) gas sensor module with an effective optical path length of similar to 4.8 m to take advantage of the directly proportional relationship between sensitivity and gas absorption path length, thereby improving the detection sensitivity. A low-power distributed feedback (DFB) laser with a power output of 2.8 mW was used as the excitation light source to further reduce power consumption, size, and weight of the TDLAS gas sensor system. The sensor performance was optimized and evaluated in terms of modulation depth, pressure, gas flow rate, signal linearity, accuracy, and stability. A minimum detection limit of 1.7 ppm was achieved with a 1-s integration time, further improved to 0.12 ppm with a 208-s integration time. Real-time measurements of CO concentration released during the combustion of cigarettes, heat-shrink tubing, and cable sheaths were performed to demonstrate the practicality and feasibility of the reported CO sensor system in early electrical fires.

关键词： Carbon monoxide (CO) detection gas sensor system miniature multipass cell (MPC) tunable diode laser absorption spectroscopy (TDLAS)

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Visibility control of phase fiber optic sensors in passive optical networks

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OPTICS AND LASER TECHNOLOGY 2025年 183卷

作者： Cubik, Jakub Kepak, Stanislav Nedoma, Jan Fajkus, Marcel Marques, Carlos VSB Tech Univ Ostrava Fac Elect Engn & Comp Sci Dept Telecommun 17 Listopadu 15 Ostrava 70833 Czech Republic VSB Tech Univ Ostrava Fac Elect Engn & Comp Sci Dept Phys 17 Listopadu 15 Ostrava 70833 Czech Republic Univ Aveiro Aveiro Inst Mat CICECO Phys Dept P-3810193 Aveiro Portugal

Integrating sensors into existing high-speed data networks delivers an intelligent hybrid network that is able to communicate and deliver a plethora of information about its surroundings. The use of existing fiber optic passive optical networks (PONs) is economically and technically advantageous in the future. Existing networks are often conveniently located, and the measured quantities maybe diagnostics of the network itself but, for example, monitoring of traffic, critical infrastructures, security, construction work, and others. These sensors can have unique features such as long-range interrogation, immunity to electromagnetic interference (EMI), high sensitivity, or, for example, distributed measurements, and their spatial resolution. The techniques of embedding a phase sensor into a PON are discussed in the article, and how the data and sensor part of the network will be affected and the balancing between the two. The measured quantity is the vibration acting on the interferometric fiber optic sensor (IFOS) and the visibility of its phase response (interference). In the case of a data network, it is the stability of the data transmission. Five different methods of sensor insertion have been investigated, simulated, and experimentally tested, showing functional and non-functional ways of integration. For the security of the network data part, the best configurations are those that influence visibility using asymmetric or WDM couplers. Changes in the difference in arm lengths are also a potentially promising method, but the coherent length of the source affects data security. These findings show how sensors can be operated on existing networks but also in what ways data services will be disrupted or completely disrupted.

关键词： Mach-Zehnder interferometer (MZI) Fiber Optic sensor Visibility control Passive optical network (PON)

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A Review of Recent Advancements in sensor-Integrated Medical Tools

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ADVANCED SCIENCE 2024年第20期11卷 e2307427页

作者： Park, Jaeho Seo, Bokyung Jeong, Yongrok Park, Inkyu Korea Adv Inst Sci & Technol KAIST Dept Mech Engn Daejeon 34141 South Korea Korea Atom Energy Res Inst KAERI Radioisotope Res Div Daejeon 34057 South Korea

A medical tool is a general instrument intended for use in the prevention, diagnosis, and treatment of diseases in humans or other animals. Nowadays, sensors are widely employed in medical tools to analyze or quantify disease-related parameters for the diagnosis and monitoring of patients' diseases. Recent explosive advancements in sensor technologies have extended the integration and application of sensors in medical tools by providing more versatile in vivo sensing capabilities. These unique sensing capabilities, especially for medical tools for surgery or medical treatment, are getting more attention owing to the rapid growth of minimally invasive surgery. In this review, recent advancements in sensor-integrated medical tools are presented, and their necessity, use, and examples are comprehensively introduced. Specifically, medical tools often utilized for medical surgery or treatment, for example, medical needles, catheters, robotic surgery, sutures, endoscopes, and tubes, are covered, and in-depth discussions about the working mechanism used for each sensor-integrated medical tool are provided. In this review, recent advancements in sensor-integrated medical tools are presented, and their necessity, use, and examples are comprehensively introduced. Specifically, medical tools often utilized for medical surgery or treatment, for example, medical needles, catheters, robotic surgery, sutures, endoscopes, and tubes, are covered, and in-depth discussions about the working mechanism of each sensor-integrated medical tool are provided. image

关键词： in vivo sensing medical tools minimally invasive surgery patient monitoring sensor-integrated medical tools sensors

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Construction of a Novel Semiautomated Electrochemical sensor Array Platform and Its Application in Multiplexed Monitoring of Antibiotic Therapy

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ACS sensors 2024年第3期9卷 1349-1358页

作者： Wang, Heyu Liu, Jiang Peng, Zhengchun Wang, Qiqin Wei, Jun Li, Yingchun Harbin Inst Technol Sch Sci Shenzhen 518055 Peoples R China Harbin Inst Technol Shenzhen Key Lab Flexible Printed Elect Technol Shenzhen 518055 Peoples R China Shenzhen Univ Coll Optoelect Engn Shenzhen 518060 Peoples R China Jinan Univ Inst Pharmaceut Anal Coll Pharm Guangzhou 510632 Peoples R China

At present, traditional analytical methods suffer from issues such as complex operation, expensive equipment, and a lengthy testing time. Electrochemical sensors have shown great advantages and application potential as an alternative solution. In this study, we proposed a novel semiautomated electrochemical sensor array (SAESA) platform. The sensor array was fabricated using screen-printed technology with a tubular design where all electrodes were printed on the inner wall. The integration of the tubular sensor array with a pipet allows for a semiautomated process including sampling and rinsing, which simplifies operation and reduces overall time. Each working electrode in the tubular sensor array underwent distinct decoration to get specific sensing responses toward the target analytes in a mixture environment (e.g., blood samples). To demonstrate the applicability of the developed sensing platform for simultaneous multianalyte detection, we chose antibiotic treatment for inflammatory infection as a model scenario and continuously measured three biomarkers, namely, tigecycline (TGC), procalcitonin (PCT), and alanine aminotransferase (ALT). The detection limits were 0.3 mu M, 0.3 ng/L, and 2.76 U/L, respectively. The developed semiautomated electrochemical sensor array exhibits characteristics such as rapid and simple operation, portability, good selectivity, and excellent stability.

关键词： electrochemical sensor multiplex detection antibiotic therapy screen-printed technology therapeutic drug monitoring sensor array

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Smart embedded technologies and materials for enhanced pavement management

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AUTOMATION IN CONSTRUCTION 2024年 168卷

作者： Hossein, Atena Karbalaei Mohammad Golroo, Amir Akhoundzadeh, Medya Amirkabir Univ Technol Dept Civil & Environm Engn Tehran Iran

The integration of smart technologies is set to revolutionize pavement data collection and analysis, leading to more efficient decision-making in Pavement Management Systems (PMS). Smart pavements, featuring embedded sensors, offer continuous streams of high-quality real-time data, enhancing the PMS data analysis process. This paper provides a detailed examination of these embedded smart systems, discussing their technologies, applications, and potential impacts on pavement management. The study highlights the role of smart materials in pavement engineering, offering self-sensing, self-healing, and energy-harvesting capabilities. It investigates sensor technologies for monitoring pavement conditions, focusing on both on-surface and below-surface sensors for comprehensive data collection. Future research directions emphasize advanced data management systems, sensor durability enhancement, economic modeling, standardization efforts, energy-efficient technologies, and pilot programs for real-world testing. This research provides insights into smart pavement advancements and challenges, paving the way for improved road infrastructure efficiency and sustainability.

关键词： Smart pavements Smart materials sensor technologies Road infrastructure Self-sensing pavement Self-healing pavement Energy harvesting

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Gas sensors based on metal-organic frameworks:Challenges and opportunities

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Chinese Journal of Structural Chemistry 2024年第3期43卷 67-73页

作者： Xiaoyan Peng Xuanhao Wu Fan Yang Yefei Tian Mingming Zhang Hongye Yuan State Key Laboratory for Mechanical Behavior of Materials Shaanxi International Research Center for Soft MatterSchool of Materials Science and EngineeringXi'an Jiaotong UniversityXi'an710049PR China School of Materials Science and Engineering Changan UniversityNo.75 ChanganMiddle RoadXi'an710064PR China

The need for high-performance and cost-effective gas sensors in industrial and domestic settings has led to ad-vancements in gas sensors based on metal-organic frameworks(MOFs).However,challenges remain in the design and synthesis of MOFs with customized structure and affinity toward targeted gases and their integration onto miniaturized electronic *** deliberate design of MOFs with desired characteristics is hindered by limited understanding of the interactions between MOFs and ***,there is a lack of customization of relevant MOF-based sensors with salient sensing performance and their integration into sensor arrays to align with different application *** combination of machine learning or artificial intelligence(AI)with gas sensors also represents a promising avenue for future ***,we provide a mini-review of recent ac-complishments in MOF-based gas sensors,covering materials design and device *** challenges of miniaturization and building smart sensing systems with anomaly detection,self-calibration,and lifetime pre-diction are also discussed.

关键词： MOFs Gas sensors integration approach Sensing performance

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Progress in self-powered sensors—Moving toward artificial intelligent and neuromorphic system

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Nano Research 2023年第9期16卷 11801-11821页

作者： Feng Wen Chan Wang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore National University of Singapore Suzhou Research Institute(NUSRI) Suzhou 215123China NUS Graduate School-Integrative Sciences and Engineering Programme(ISEP) National University of SingaporeSingapore 119077Singapore

Wearable and flexible electronics are shaping our life with their unique advantages of light weight,good compliance,and desirable *** marching into the era of Internet of Things(IoT),numerous sensor nodes are distributed throughout networks to capture,process,and transmit diverse sensory information,which gives rise to the demand on self-powered sensors to reduce the power ***,the rapid development of artificial intelligence(AI)and fifth-generation(5G)technologies provides an opportunity to enable smart-decision making and instantaneous data transmission in IoT *** to continuously increased sensor and dataset number,conventional computing based on von Neumann architecture cannot meet the needs of brain-like high-efficient sensing and computing applications *** electronics,drawing inspiration from the human brain,provide an alternative approach for efficient and low-power-consumption information ***,this review presents the general technology roadmap of self-powered sensors with detail discussion on their diversified applications in healthcare,human machine interactions,smart homes,*** leveraging AI and virtual reality/augmented reality(VR/AR)techniques,the development of single sensors to intelligent integrated systems is reviewed in terms of step-by-step system integration and algorithm *** order to realize efficient sensing and computing,brain-inspired neuromorphic electronics are next briefly ***,it concludes and highlights both challenges and opportunities from the aspects of materials,minimization,integration,multimodal information fusion,and artificial sensory system.

关键词： wearable and flexible electronics self-powered sensors virtual reality/augmented reality(VR/AR)and artificial intelligence(AI)-enhanced system neuromorphic electronics

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Load and Vibration Optical Fiber sensor Based on Miniature FabryPerot Cavity Encapsulated by Micrometer Thickness of Silica Film

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IEEE sensors JOURNAL 2023年第12期23卷 12930-12935页

作者： Sun, Yi-Ran Wang, Yan-Nan Li, Jin Meng, Fanli Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Northwest A&F Univ Coll Mech & Elect Engn Yangling 712100 Shaanxi Peoples R China

In this article, an optical fiber sensor has been proposed to determine load and vibration signals based on the Fabry-Perot cavity. The load sensitivity has been experimentally demonstrated to be about 0.0148 nm/g. The vibration signal was measured by tracing the changes in frequency and amplitude intensity. Experimental results reveal that this sensor has the resonant frequency of 150 Hz, at which the signal-to-noise ratio is 35 dB. The operating frequency range for the proposed vibration sensor is 200-400 Hz, and the response sensitivity to vibration signals with different amplitudes is 0.0042 V/V.

关键词： sensors Vibrations Optical fiber sensors Optical fibers Discharges (electric) Sensitivity sensor phenomena and characterization Fabry--Perot (F--P) interferometer load sensor optical fiber integration vibration detection

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sensor Fusion Method for Object Detection and Distance Estimation in Assisted Driving Applications

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sensors 2024年第24期24卷 7895页

作者： Favelli, Stefano Xie, Meng Tonoli, Andrea Politecn Torino Ctr Automot Res & Sustainable Mobil CARS PoliTO I-10129 Turin Italy Politecn Torino Dipartimento Ingn Meccan & Aerosp DIMEAS I-10129 Turin Italy

The fusion of multiple sensors' data in real-time is a crucial process for autonomous and assisted driving, where high-level controllers need classification of objects in the surroundings and estimation of relative positions. This paper presents an open-source framework to estimate the distance between a vehicle equipped with sensors and different road objects on its path using the fusion of data from cameras, radars, and LiDARs. The target application is an Advanced Driving Assistance System (ADAS) that benefits from the integration of the sensors' attributes to plan the vehicle's speed according to real-time road occupation and distance from obstacles. Based on geometrical projection, a low-level sensor fusion approach is proposed to map 3D point clouds into 2D camera images. The fusion information is used to estimate the distance of objects detected and labeled by a Yolov7 detector. The open-source pipeline implemented in ROS consists of a sensors' calibration method, a Yolov7 detector, 3D point cloud downsampling and clustering, and finally a 3D-to-2D transformation between the reference frames. The goal of the pipeline is to perform data association and estimate the distance of the identified road objects. The accuracy and performance are evaluated in real-world urban scenarios with commercial hardware. The pipeline running on an embedded Nvidia Jetson AGX achieves good accuracy on object identification and distance estimation, running at 5 Hz. The proposed framework introduces a flexible and resource-efficient method for data association from common automotive sensors and proves to be a promising solution for enabling effective environment perception ability for assisted driving.

关键词： ADAS environment perception object detection sensor fusion camera LiDAR ROS

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An LSTM-Assisted GNSS/INS integration System Using IMU Recomputed Error Information for Train Localization

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2024年第3期60卷 2658-2671页

作者： Chen, Yidi Jiang, Wei Wang, Jian Cai, Baigen Liu, Dan Ba, Xiaohui Yang, Yang Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Univ New South Wales Sch Mech & Mfg Engn Sydney NSW 2052 Australia

Global navigation satellite system (GNSS)/inertial navigation system (INS) integration is widely used for train positioning, but railways tunnels and mountains can interfere GNSS signals and will lead to performance degradation when the system is operated in the standalone INS mode. This article proposes a long short-term memory (LSTM)-assisted GNSS/INS integration system using recomputed inertial measurement unit (IMU) error to suppress the error divergence of an INS in the case of GNSS solution nonavailability. The IMU error recomputation method (RM) is first proposed, where the GNSS/INS-derived position, velocity, and attitude information is utilized when is GNSS available. The train's attitude computed using the GNSS dual-antenna moving baseline method is used as the heading constraint for GNSS/INS integration so as to provide accurate attitude information. The recomputed IMU sensor error is then used for model training, and the system switches to LSTM-assisted INS mode when GNSS solutions are unavailable. The system predicts the IMU sensor error using the train motion state, and corrects the IMU measurements to suppress the accumulating IMU sensor error. The proposed system was evaluated through a train experiment on the Shuozhou-Huanghua railway. The IMU-RM was evaluated on four time slots of varying lengths, and the proposed LSTM-assisted GNSS/INS integration system using IMU-RM was evaluated in two "difficult" GNSS signal areas of curved and straight railtrack segments, and were simulated. Results showed significant improvement in horizontal position accuracy compared to conventional methods, with suppression of INS sensor error divergence by 79% and 63% for curved and straight segments, respectively.

关键词： Global navigation satellite system sensors Navigation Measurement uncertainty sensor systems Gyroscopes Accelerometers Global navigation satellite system (GNSS)/inertial navigation system (INS) inertial measurement unit (IMU) error long short- term memory (LSTM) recomputed method train positioning

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