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High-precision displacement sensor in advanced manufacturing: Principle and application

MEASUREMENT 2025年 242卷

作者： Zhou, Yufang Liu, Junfeng Li, Huang Li, Zelong Li, Saichen Lai, Tao Natl Univ Def Technol Coll Intelligence Sci & Technol Lab Sci & Technol Integrated Logist Support Changsha 410073 Peoples R China Hunan Key Lab Ultraprecis Machining Technol Changsha 410073 Peoples R China

Ultraprecision machining extensively utilizes high-precision displacement sensors due to their exceptional stability, sensitivity, and accuracy. Such sensors can directly measure displacement but are typically components of precision measurement systems, such as atomic force microscopes, profilometers, or coordinate measuring machines. Currently, as displacement sensors are moving towards the direction of high precision, large range, and universal applicability, the market has seen a large variety of new displacement sensor products. However, there is a dearth of comprehensive and systematic reviews of their application specifically in the field of ultraprecision inspection. This review discusses existing research on typical contact and noncontact displacement sensors in high-precision machine tools. First, it reviews and classifies the displacement sensors. Then, it introduces the principles, characteristics, and applications of these types of sensors, along with the technical indicators of their corresponding commercial sensors, and discusses the latest advances in related technologies. Moreover, it also presents a comprehensive summary and comparative study of various high-precision displacement sensors from the perspectives of measurement range, accuracy, resolution, and applicability. Finally, it discusses the technical obstruction and development trends of high-precision displacement sensors.

关键词： Displacement sensor High precision Contact measurement Optical measurement Surface profile

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Liquid-level sensor based on flat-shaped plastic optical fiber assisted by a long-period grating 14

Liquid-level sensor based on flat-shaped plastic optical fib...

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advanced sensor systems and applications xIV 2024

作者： Bao, Haiyang Zheng, Jie Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun130033 China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and Engineering Jilin University Changchun130012 China

ISBN: (纸本)9781510682146

A corrugated surface long-period grating (LPG) was imprinted on a flat-shaped plastic optical fiber (POF) as a liquid-level sensor. The flat shape was processed on commercial POF by a simple heat-pressing method, and the LPG was fabricated by a mechanical die-press-print method. The liquid-level sensing performance of the sensor with different structural parameters was evaluated. It was shown that the thinner flat-shaped POF assisted by an LPG exhibits better sensing performance. The LPG with deeper groove depth achieved higher sensitivity, and theoretical calculations were consistent with these results. The highest sensitivity of -0.2332dB/mm was obtained while the flat-shaped POF with a thickness of 500μm, on which was assisted by the LPG with a period of 300μm and a groove depth of 103μm. The results demonstrated that flattening the POF assisted an LPG could improve the liquid-level sensing performance. © 2024 SPIE.

关键词： Plastic optical fibers

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sensory Nervous System-Inspired Self-Classifying, Decoupled, Multifunctional sensor with Resistive-Capacitive Operation Using Silver Nanomaterials

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advanced FUNCTIONAL MATERIALS 2024年第40期34卷

作者： Yang, Yoonji Jung, Byung Ku Park, Taesung Ahn, Junhyuk Choi, Young Kyun Oh, Seongkeun Lee, Yong Min Choi, Hyung Jin Seo, Hanseok Oh, Soong Ju Korea Univ Dept Mat Sci & Engn 145 Anam Ro Seoul 02841 South Korea

Self-classification technology has remarkable potential for autonomously discerning various stimuli without any circuit or software assistance, enabling it to realize electronic skin. In conventional self-classification systems that rely on complex circuitry for operation, integrating the sensing and algorithm processing units inevitably leads to bulkiness in devices and bottlenecks in signal processing. In this study, the novel double-sided structure inspired by the human nervous system is newly designed for a self-classifying sensor (SCS) without the need for additional circuits. The sensor is layered with Ag nanocomposites that have been mechanically enhanced via interface engineering and surface treatment techniques. This structure enables the resistance-capacitance hybrid operation, facilitating the detection and distinguishment of changes in strain, pressure, and temperature within a single device, which mimics the human sensing recognition process. Moreover, the intensity of the applied stimuli is determined by analyzing the detected signal, and precise localization of the stimuli is achieved by arraying the sensors. With its self-classification capabilities, SCS opens promising avenues for applications in soft robotics and advanced multifunctional sensor platforms, providing a sensing system characterized by simplicity and efficiency. A self-classifying sensor (SCS) is designed with a novel double-sided structure and Ag nanomaterials, which does not require any external circuit computing. SCS successfully detects and distinguishes various signals of strain, pressure, and temperature as well as their location, and intensity by itself at the materials level through the resistance-capacitance hybrid operation. image

关键词： Ag nanocomposite artificial sensory nervous system multifunctional sensor resistive-capacitive type sensor self-classification

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Multi-Modal AI for Enhanced Forest Fire Early Detection: Scalar and Image Fusion

Multi-Modal AI for Enhanced Forest Fire Early Detection: Sca...

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International conference on advanced systems and Emergent Technologies (ICASET)

作者： Azzabi, Tarek Jeridi, Mohamed Hechmi Mejri, Ikbel Ezzedine, Tahar Tunisian Naval Acad Lab LR DN02 19 Menzel Bourguiba 7050 Tunisia Tunisian Naval Acad Menzel Bourguiba 7050 Tunisia Natl Engn Sch Tunis ENIT SYSCOM LR ES21 99 Tunis Tunisia

ISBN: (纸本)9798350384901;9798350384895

Forest fires pose significant threats to both the environment and human safety, underscoring the critical importance of early detection methods. This article introduces a novel approach grounded in artificial intelligence to enhance the early detection of forest fires. The fusion of sensor technology and imagery holds substantial potential for augmenting prediction accuracy. sensors furnish crucial environmental data encompassing factors such as temperature, humidity, and wind speed, all pivotal in the ignition and propagation of forest fires. In contrast, imagery supplies visual evidence of fire or smoke presence, a particularly invaluable asset in densely forested regions where vegetation cover can obscure sensor-derived information. Employing machine learning algorithms proficient in the analysis and interpretation of this composite data, we achieve a heightened level of accuracy in forest fire detection and probability prediction. This methodology undergoes rigorous evaluation using historical forest fire datasets, demonstrating impressive effectiveness in detecting fires. The potential applications extend to the enhancement of early warning systems for forest fires, ultimately mitigating the loss of life and property attributable to these catastrophic events.

关键词： Forest Fires Scalar sensors Artificial intelligence Machine Learning Deep Learning rTPNN CNN Multi-sensor fusion Concentrations Smoke density

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High-Performance Pressure and Temperature Dual-Mode sensor Based on Thermoelectric Aerogels for Multimodal Intellectual Panel Application

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advanced MATERIALS TECHNOLOGIES 2025年第0期

作者： Jiang, Saihua Wang, Zubin Li, Shun Huang, Yubing Lan, Yang Li, Guohui South China Univ Technol Inst Safety Sci & Engn Sch Mech & Automot Engn Wushan Rd 381 Guangzhou 510641 Peoples R China South China Univ Technol Guangdong Prov Key Lab Tech & Equipment Macromol A Guangzhou 510641 Peoples R China Univ Catholique Louvain UCLouvain Inst Condensed Matter & NanoSci B-1348 Louvain la Neuve Louvain Belgium UCL Dept Chem Engn London WC1 E7JE England Minist Publ Secur Tianjin Fire Res Inst Tianjin 300381 Peoples R China

Developing sensors with multi-sensory detection capabilities will streamline integrated systems and simplify the integration process. Herein, dual-mode temperature and pressure sensors based on PEDOT: PSS/CNTs/CNF/Mxene (PCCM) is established. In terms of temperature sensing, the aerogel structure and introduction of Mxene provide ultra-low thermal conductivity, ensuring a stable temperature gradient. The addition of CNTs forms an excellent conductive network, significantly enhancing temperature sensing performance and achieving a maximum Seebeck coefficient of 28.2 mu V K-1, the introduction of Mxene ensures PCCM the output electrical signal has ultra-low noise and a high signal-to-noise ratio, allowing the detection of temperature differences as small as 0.05 K. Regarding pressure sensing, the sensitivity exhibited in the low-pressure range (0-4 kPa) is -11.44% kPa-1. Additionally, Mxene significantly increases the sensor's electrical conductivity, reducing electron scattering and obstacles, shortening the response and recovery times (120 ms) for pressure measurements, and combining with CNTs/CNF increasing the hardness of the PCCM sensor, thereby expanding the pressure measurement range (0-20 kPa). It also highlights its promising potential for skin-like sensing and human-computer interaction applications by developing a multimodal intellectual panel. This work provides a simple and scalable fabrication method to design high-performance multifunctional sensors for various applications, such as e-skin and robotics.

关键词： aerogel dual-mode sensor high-performance sensing multimodal intellectual panel

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Development and Characterization of Tactile Capacitive sensor for Soft Robotics Application 12

Development and Characterization of Tactile Capacitive Senso...

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12th International conference on Control Mechatronics and Automation

作者： Srinivas, Gidugu Lakshmi Carinthia Univ Appl Sci ADMiRE Res Ctr Sch Engn & IT A-9500 Villach Austria

ISBN: (纸本)9798331517519;9798331517526

This paper details developing and characterizing a soft capacitive sensor patch designed for force measurement in soft robotics and orthosis applications. The 6x6 matrix sensor was fabricated using silicone, selected for its viscoelasticity and strain resistance, making it well-suited for human-interactive applications. The sensing mechanism is based on capacitance changes when force is applied and measured using a MUCA board. The system also incorporates an SHT30 sensor to monitor environmental conditions like temperature and humidity, ensuring the sensor's performance under varying conditions. Data from the capacitive sensor is processed via an Arduino Nano 33 IoT, with all measurements wirelessly transmitted and displayed in real-time using a custom dashboard on Arduino Cloud. The sensor can detect forces in the range of 1 to 4 N. Machine learning techniques, specifically linear regression, were used to characterize the sensor, yielding a highly accurate R-2 value of 0.9932. Capacitance and environmental data are automatically saved and processed using Python scripts, allowing for efficient data analysis. This capacitive sensor shows great promise in applications requiring precise force measurement and enhanced human-machine interaction. Potential future uses include wearable orthosis devices to improve human comfort and soft robotic systems designed to mimic natural movements. The ability to integrate this sensor into wearable technology highlights its potential in fields such as medical rehabilitation and prosthetics, offering improved interaction and adaptability in human-centered environments.

关键词： Capacitive sensor Force measurement Machine learning Orthosis applications Soft-robotics Tactile sensor array

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Sun-Powered Tactical Uniforms for Soliders in Military applications 10

Sun-Powered Tactical Uniforms for Soliders in Military Appli...

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10th International conference on advanced Computing and Communication systems, ICACCS 2024

作者： Anila, Chowdam Ashokkumar, N. Vittan, Eduru Joel Chowdary, Bheemaneni Uma Maheswara Subramani, Dhanya Sree Bala Balamanikandan, A. Electronics and Communication Engineering Andra Pradesh Tirupati517102 India

ISBN: (纸本)9798350384369

This endeavor presents an innovative Solar-Powered Tactical Uniform for Military use, incorporating Arduino technology along with an array of sensors and communication modules. The configuration includes an Arduino ATmega16a microcontroller, LCD display, a 70x70 solar panel, a 12V battery, a heart rate sensor, a temperature sensor, dual relays, a CPU fan, a Peltier module, a DHT11 humidity and temperature sensor, GPS, a GSM module, and push-button switches. The renewable energy captured by the solar panel is utilized to recharge the 12V battery, ensuring a constant power supply for the electronic components of the uniform. Real-time data on the LCD display is derived from the soldier's vital signs, which are monitored by the heart rate and temperature sensors. To improve soldier comfort, the Peltier module actively regulates temperature. During crucial scenarios, the system initiates the cooling process by activating the CPU fan and engages the GPS and GSM modules for both location tracking and communication purposes. Manual control is facilitated through push-button switches. This intelligent E-uniform seamlessly integrates energy-efficient features, health monitoring, and communication capabilities, showcasing its ability to improve soldier well-being and enhance situational awareness in field operations. © 2024 IEEE.

关键词： Liquid crystal displays

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advanced Autonomous Navigation Technologies for UAVs: Challenges and Opportunities 4

Advanced Autonomous Navigation Technologies for UAVs: Challe...

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4th International conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2024

作者： Senhaji-Mouhaddib, Issam Bouzakri, Samir Lagrat, Ismail Ibn Tofail University Ensa Lab Of Advanced Systems Engineering Kenitra Morocco

ISBN: (纸本)9798350309508

The utilization of Unmanned Aerial Vehicles (UAVs) has revolutionized numerous industries, with navigation being a crucial factor in ensuring their operational success. This literature review examines the subject of UAV navigation, discussing fundamental concepts, GPS-denied challenges, and cutting-edge technologies. The review commences with an explanation of the basic principles of UAV navigation, including the employment of IMUs, GPS, LiDAR, and Stereo Vision systems. A dedicated section then delves into the challenges posed by GPS-denied environments, emphasizing the importance of GPS in navigation and exploring alternative approaches. The subsequent sections investigate advanced navigation technologies, such as INS/IMU, Multi-sensor Fusion, and AI applications. These innovative research areas cover enhancements to sensors, the development of hybrid navigation systems, deep learning for sensor fusion, and other related topics. The conclusion emphasizes the transformative potential of emerging technologies, providing a roadmap for researchers and practitioners. The identified research directions aim to address current limitations and develop next-generation UAV navigation systems capable of precise navigation in complex and challenging environments. © 2024 IEEE.

关键词： Global positioning system

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Indoor Human Activity Perception Based on Infrared Thermopile Array sensor 19

Indoor Human Activity Perception Based on Infrared Thermopil...

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IEEE 19th conference on Industrial Electronics and applications (ICIEA)

作者： Zhang, Tong Yang, Bo Gu, Nanhao Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China

ISBN: (纸本)9798350360875;9798350360868

Human activity perception systems play a significant role in "SENSEable City", smart homes and medical care, etc. Thermopile infrared array sensor (TPAS) is a new type of sensor to detect human targets without privacy invasion. This paper focuses on the perception of static and dynamic human activities. A hardware platform is built based on TPAS MLx90640 with the output of 24x32 pixels, to collect the thermal data of human targets from both side view and top view. After temporal Gaussian filtering, background removal, motion information extraction and data enhancement, different improved convolution neural network structures and technologies are introduced for activity perception. The best model among these networks for static and dynamic activity perception is selected and trained, achieving perception accuracy of 97.5% for static activity and 94.6% for dynamic activity respectively. The experimental results have shown that the system we proposed could correctly perceive continuous human activity and meet the real-time requirement as well.

关键词： Infrared Thermopile Array sensor Human Activity Perception Improved Convolution Neural Network

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Leveraging AI-Driven Chatbots for Legal Literacy: advanced Computing and Communication Technologies for Legal Awareness

Leveraging AI-Driven Chatbots for Legal Literacy: Advanced C...

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2024 International conference on Artificial Intelligence and Quantum Computation-Based sensor applications, ICAIQSA 2024

作者： Trivedi, Chetan Kumar, Sunil Mohd, Imran Bhalla, Rajiv Ahmad Lone, Naseer Dogra, Disha University Institute of Legal Studies Chandigarh University Punjab India

ISBN: (纸本)9798331517953

In a democratic society, public legal awareness is crucial for empowering citizens with knowledge of their rights and obligations. However, the vast complexity and volume of legal information can make it difficult for non-experts to access and understand their legal standing. This paper explores the development and deployment of AI-driven chatbot systems aimed at enhancing public legal literacy. These systems leverage advanced computing techniques, including natural language processing (NLP) and machine learning (ML) algorithms, to process legal queries and deliver personalized legal information to users in real time. The architecture, scalability, and implementation challenges of deploying these chatbots across diverse communication platforms (e.g., web, mobile) are examined. Additionally, the paper addresses the potential of these systems to bridge the gap in legal knowledge for underserved populations and discusses the importance of real-time communication technologies for ensuring effective system performance. Finally, the paper explores future advancements to further integrate AI and communication technologies for widespread legal literacy. © 2024 IEEE.

关键词： Natural language processing systems

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