Multi-Sensor Intelligent System for On-Line and Real-Time Moneitoring Tool Cutting State in FMS

The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sensor (AE) with motor current sensor was presented. The parallel communication between control system of machine tools, the monitoring intelligent system,and several decision-making systems for identifying tool cutting state was established It can auto - matically select the sensor way ,monitoring mode and identifying method in machining process- ing so as to build a successful and effective intelligent system for on -line and real-time moni- toring cutting tool states in FMS.

STRONGLY CONVERGENT INERTIAL FORWARD-BACKWARD-FORWARD ALGORITHM WITHOUT ON-LINE RULE FOR VARIATIONAL INEQUALITIES

This paper studies a strongly convergent inertial forward-backward-forward algorithm for the variational inequality problem in Hilbert spaces.In our convergence analysis,we do not assume the on-line rule of the inertial parameters and the iterates,which have been assumed by several authors whenever a strongly convergent algorithm with an inertial extrapolation step is proposed for a variational inequality problem.Consequently,our proof arguments are different from what is obtainable in the relevant literature.Finally,we give numerical tests to confirm the theoretical analysis and show that our proposed algorithm is superior to related ones in the literature.

NLDA non-linear regression model for preserving data privacy in wireless sensor networks

Recently,the application of Wireless Sensor Networks(WSNs)has been increasing rapidly.It requires privacy preserving data aggregation protocols to secure the data from compromises.Preserving privacy of the sensor data is a challenging task.This paper presents a non-linear regression-based data aggregation protocol for preserving privacy of the sensor data.The proposed protocol uses non-linear regression functions to represent the sensor data collected from the sensor nodes.Instead of sending the complete data to the cluster head,the sensor nodes only send the coefficients of the non-linear function.This will reduce the communication overhead of the network.The data aggregation is performed on the masked coefficients and the sink node is able to retrieve the approximated results over the aggregated data.The analysis of experiment results shows that the proposed protocol is able to minimize communication overhead,enhance data aggregation accuracy,and preserve data privacy.

Smart Gas Sensors:Recent Developments and Future Prospective

Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.

Force and impulse multi-sensor based on flexible gate dielectric field effect transistor

Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate response.However,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of time.Herein we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor application.We systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 nW.The sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on it.Moreover,there was almost no performance loss for the device as left in the air for two months.

An Artificial Intelligence‑Assisted Flexible and Wearable Mechanoluminescent Strain Sensor System

The complex wiring,bulky data collection devices,and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable devices.To tackle these challenges,this work develops an artificial intelligenceassisted,wireless,flexible,and wearable mechanoluminescent strain sensor system(AIFWMLS)by integration of deep learning neural network-based color data processing system(CDPS)with a sandwich-structured flexible mechanoluminescent sensor(SFLC)film.The SFLC film shows remarkable and robust mechanoluminescent performance with a simple structure for easy fabrication.The CDPS system can rapidly and accurately extract and interpret the color of the SFLC film to strain values with auto-correction of errors caused by the varying color temperature,which significantly improves the accuracy of the predicted strain.A smart glove mechanoluminescent sensor system demonstrates the great potential of the AIFWMLS system in human gesture recognition.Moreover,the versatile SFLC film can also serve as a encryption device.The integration of deep learning neural network-based artificial intelligence and SFLC film provides a promising strategy to break the“color to strain value”bottleneck that hinders the practical application of flexible colorimetric strain sensors,which could promote the development of wearable and flexible strain sensors from laboratory research to consumer markets.

Bioinspired Ultrasensitive Flexible Strain Sensors for Real‑Time Wireless Detection of Liquid Leakage

Liquid leakage of pipeline networks not only results in considerableresource wastage but also leads to environmental pollution and ecological imbalance.In response to this global issue, a bioinspired superhydrophobic thermoplastic polyurethane/carbon nanotubes/graphene nanosheets flexible strain sensor (TCGS) hasbeen developed using a combination of micro-extrusion compression molding andsurface modification for real-time wireless detection of liquid leakage. The TCGSutilizes the synergistic effects of Archimedean spiral crack arrays and micropores,which are inspired by the remarkable sensory capabilities of scorpions. This designachieves a sensitivity of 218.13 at a strain of 2%, which is an increase of 4300%. Additionally, it demonstrates exceptional durability bywithstanding over 5000 usage cycles. The robust superhydrophobicity of the TCGS significantly enhances sensitivity and stability indetecting small-scale liquid leakage, enabling precise monitoring of liquid leakage across a wide range of sizes, velocities, and compositionswhile issuing prompt alerts. This provides critical early warnings for both industrial pipelines and potential liquid leakage scenariosin everyday life. The development and utilization of bioinspired ultrasensitive flexible strain sensors offer an innovative and effectivesolution for the early wireless detection of liquid leakage.

Flexible Strain Sensors with Ultra‑High Sensitivity and Wide Range Enabled by Crack‑Modulated Electrical Pathways

This study presents a breakthrough in flexible strain sensor technology with the development of an ultrahigh sensitivity and wide-range sensor,addressing the critical challenge of reconciling sensitivity with measurement range.Inspired by the structure of bamboo slips,we introduce a novel approach that utilises liquid metal to modulate the electrical pathways within a cracked platinum fabric electrode.The resulting sensor demonstrates a gauge factor greater than 108 and a strain measurement capability exceeding 100%.The integration of patterned liquid metal enables customisable tuning of the sensor’s response,while the porous fabric structure ensures superior comfort and air permeability for the wearer.Our design not only optimises the sensor’s performance but also enhances the electrical stability that is essential for practical applications.Through systematic investigation,we reveal the intrinsic mechanisms governing the sensor’s response,offering valuable insights for the design of wearable strain sensors.The sensor’s exceptional performance across a spectrum of applications,from micro-strain to large-strain detection,highlights its potential for a wide range of real-world uses,demonstrating a significant advancement in the field of flexible electronics.

Bioinspired Passive Tactile Sensors Enabled by Reversible Polarization of Conjugated Polymers

Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced robots.Compared to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static stimuli.Here,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic stimuli.Specifically,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential differences.The controllable and reversible polarization process of the conjugated polymers is fully in situ characterized.Then,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference outputs.Compared with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior bio-friendliness.As demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning algorithms.This tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.

Design, Implementation and Simulation of Non-Intrusive Sensor for On-Line Condition Monitoring of MV Electrical Components

Non-intrusive measurement technology is of great interest for the electrical utilities in order to avoid an interruption in the normal operation of the supply network during diagnostics measurements and inspections. Inductively coupled electromagnetic sensing provides a possibility of non-intrusive measurements for online condition monitoring of the electrical components in a Medium Voltage (MV) distribution network. This is accomplished by employing Partial Discharge (PD) activity monitoring, one of the successful methods to assess the working condition of MV components but often requires specialized equipment for carrying out the measurements. In this paper, Rogowski coil sensor is presented as a robust solution for non-intrusive measurements of PD signals. A high frequency prototype of Rogowski coil is designed in the laboratory. Step-by-step approach of constructing the sensor system is presented and performance of its components (coil head, damping component, integrator and data acquisition system) is evaluated using practical and simulated environments. Alternative Transient Program-Electromagnetic Transient Program (ATP-EMTP) is used to analyze the designed model of the Rogowski coil. Real and simulated models of the coil are used to investigate the behavior of Rogowski coil sensor at its different stages of development from a transducer coil to a complete measuring device. Both models are compared to evaluate their accuracy for PD applications. Due to simple design, flexible hardware, and low cost of Rogowski coil, it can be considered as an efficient current measuring device for integrated monitoring applications where a large number of sensors are required to develop an automated online condition monitoring system for a distribution network.

Novel Optical Fiber Gas Sensor for On-line Measurement of Methane

Based on analysis of near infrared spectral absorption of methane,absorption type optical fiber methane gas sensor with high sensitivity using DFB LD as a source is demonstrated. Light source modulation harmonic measurement is presented in this paper. In order to eliminate the noise, the ratio of the fundamental and second-harmonic signals is used. The mathematical model of gas concentration harmonic measurement is built up.The detection result of methane concentration is also shown. Experiments have proved a sensitivity of 28×10-6.

Design of Na-K Alloy Differential Pressure Sensor with On-line Monitoring Function

Because the melting point of the alkalis is very high and the metal activity is strong, the common pressure sensor can＇t be used to measure pressure of liquid metal. In this paper, a differential transformer differential pressure sensor for measuring liquid alkalis pressure is designed, the working principle and specific design plan of the sensor are introduced, the standard current signal （ 4 -20 mA） or digital communication RS485 can be output according to the needs, and the functions of remote monitoring and data optimization can be realized through the LAN interface.

A smart finger patch with coupled magnetoelastic and resistive bending sensors

In the era of Metaverse and virtual reality(VR)/augmented reality(AR),capturing finger motion and force interactions is crucial for immersive human-machine interfaces.This study introduces a flexible electronic skin for the index finger,addressing coupled perception of both state and process in dynamic tactile sensing.The device integrates resistive and giant magnetoelastic sensors,enabling detection of surface pressure and finger joint bending.This e-skin identifies three phases of finger action:bending state,dynamic normal force and tangential force(sweeping).The system comprises resistive carbon nanotubes(CNT)/polydimethylsiloxane(PDMS)films for bending sensing and magnetoelastic sensors(NdFeB particles,EcoFlex,and flexible coils)for pressure detection.The inward bending resistive sensor,based on self-assembled microstructures,exhibits directional specificity with a response time under 120 ms and bending sensitivity from 0°to 120°.The magnetoelastic sensors demonstrate specific responses to frequency and deformation magnitude,as well as sensitivity to surface roughness during sliding and material hardness.The system’s capability is demonstrated through tactile-based bread type and condition recognition,achieving 92%accuracy.This intelligent patch shows broad potential in enhancing interactions across various fields,from VR/AR interfaces and medical diagnostics to smart manufacturing and industrial automation.

Recent progress on artificial intelligence-enhanced multimodal sensors integrated devices and systems

Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,and improve the reliability and safety of the system.Artificial intelligence(AI),referring to the simulation of human intelligence in machines that are programmed to think and learn like humans,represents a pivotal frontier in modern scientific research.With the continuous development and promotion of AI technology in Sensor 4.0 age,multimodal sensor fusion is becoming more and more intelligent and automated,and is expected to go further in the future.With this context,this review article takes a comprehensive look at the recent progress on AI-enhanced multimodal sensors and their integrated devices and systems.Based on the concept and principle of sensor technologies and AI algorithms,the theoretical underpinnings,technological breakthroughs,and pragmatic applications of AI-enhanced multimodal sensors in various fields such as robotics,healthcare,and environmental monitoring are highlighted.Through a comparative study of the dual/tri-modal sensors with and without using AI technologies(especially machine learning and deep learning),AI-enhanced multimodal sensors highlight the potential of AI to improve sensor performance,data processing,and decision-making capabilities.Furthermore,the review analyzes the challenges and opportunities afforded by AI-enhanced multimodal sensors,and offers a prospective outlook on the forthcoming advancements.

Stochastic Models to Mitigate Sparse Sensor Attacks in Continuous-Time Non-Linear Cyber-Physical Systems

Cyber-Physical Systems are very vulnerable to sparse sensor attacks.But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely.Therefore,in this paper,we propose a new non-linear generalized model to describe Cyber-Physical Systems.This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and randomeffects in the physical and computationalworlds.Besides,the digitalization stage in hardware devices is represented too.Attackers and most critical sparse sensor attacks are described through a stochastic process.The reconstruction and protectionmechanisms are based on aweighted stochasticmodel.Error probability in data samples is estimated through different indicators commonly employed in non-linear dynamics(such as the Fourier transform,first-return maps,or the probability density function).A decision algorithm calculates the final reconstructed value considering the previous error probability.An experimental validation based on simulation tools and real deployments is also carried out.Both,the new technology performance and scalability are studied.Results prove that the proposed solution protects Cyber-Physical Systems against up to 92%of attacks and perturbations,with a computational delay below 2.5 s.The proposed model shows a linear complexity,as recursive or iterative structures are not employed,just algebraic and probabilistic functions.In conclusion,the new model and reconstructionmechanism can protect successfully Cyber-Physical Systems against sparse sensor attacks,even in dense or pervasive deployments and scenarios.

Advancements in implantable temperature sensors:Materials,mechanisms,and biological applications

Implantable temperature sensors are revolutionizing physiological monitoring and playing a crucial role in diagnostics,therapeutics,and life sciences research.This review classifies the materials used in these sensors into three categories:metal-based,inorganic semiconductor,and organic semiconductor materials.Metal-based materials are widely used in medical and industrial applications due to their linearity,stability,and reliability.Inorganic semiconductors provide rapid response times and high miniaturization potential,making them promising for biomedical and environmental monitoring.Organic semiconductors offer high sensitivity and ease of processing,enabling the development of flexible and stretchable sensors.This review analyzes recent studies for each material type,covering design principles,performance characteristics,and applications,highlighting key advantages and challenges regarding miniaturization,sensitivity,response time,and biocompatibility.Furthermore,critical performance parameters of implantable temperature sensors based on different material types are summarized,providing valuable references for future sensor design and optimization.The future development of implantable temperature sensors is discussed,focusing on improving biocompatibility,long-term stability,and multifunctional integration.These advancements are expected to expand the application potential of implantable sensors in telemedicine and dynamic physiological monitoring.

Recent progress in flexible sensors based on 2D materials

With the rapid development of the internet of things(IoT)and wearable electronics,the role of flexible sensors is becoming increasingly irreplaceable,due to their ability to process and convert information acquisition.Two-dimensional(2D)materials have been widely welcomed by researchers as sensitive layers,which broadens the range and application of flexible sensors due to the advantages of their large specific surface area,tunable energy bands,controllable thickness at the atomic level,stable mechanical properties,and excellent optoelectronic properties.This review focuses on five different types of 2D materials for monitoring pressure,humidity,sound,gas,and so on,to realize the recognition and conversion of human body and environmental signals.Meanwhile,the main problems and possible solutions of flexible sensors based on 2D materials as sensitive layers are summarized.

Design strategies and insights of flexible infrared optoelectronic sensors

Infrared optoelectronic sensing is the core of many critical applications such as night vision,health and medication,military,space exploration,etc.Further including mechanical flexibility as a new dimension enables novel features of adaptability and conformability,promising for developing next-generation optoelectronic sensory applications toward reduced size,weight,price,power consumption,and enhanced performance(SWaP^(3)).However,in this emerging research frontier,challenges persist in simultaneously achieving high infrared response and good mechanical deformability in devices and integrated systems.Therefore,we perform a comprehensive review of the design strategies and insights of flexible infrared optoelectronic sensors,including the fundamentals of infrared photodetectors,selection of materials and device architectures,fabrication techniques and design strategies,and the discussion of architectural and functional integration towards applications in wearable optoelectronics and advanced image sensing.Finally,this article offers insights into future directions to practically realize the ultra-high performance and smart sensors enabled by infrared-sensitive materials,covering challenges in materials development and device micro-/nanofabrication.Benchmarks for scaling these techniques across fabrication,performance,and integration are presented,alongside perspectives on potential applications in medication and health,biomimetic vision,and neuromorphic sensory systems,etc.