基于Device Net总线的造纸机传动系统设计

把现场总线Device Net应用到纸机控制系统中,通过硬件设计实现整个控制系统的PLC配线和与变频器的硬件连接,根据功能连接和总线通信的需要对变频器进行相关参数设置,并在此基础上对纸机控制系统的软件进行设计,实现纸机传动中加、减速等基本操作控制、速度链控制及负荷分配控制等功能。

基于Device Net的现场总线设备及其开发

Device Net是一种基于CAN总线技术的符合全球工业标准的开放型通信网络。可以连接底层低端工业设备,又可以连接像变频器、操作员终端等复杂设备。介绍了Device Net网络模型、技术特点、基于Device Net的总线设备对象模型以及节点开发的途径及一般步骤,建立了节点开发实例并介绍了其软、硬件设计流程。

Danfoss变频器在Device Net总线控制中的应用

介绍了通过Device Net总线通信方式控制变频器的优越性,并详细分析了Darffoss变频器连接Device Net网络的具体参数设置及数据交换方式。

Device Net在低压配电控制系统中的应用

本文回顾了 Device Net现场总线的发展概况 ,分析了该总线协议的主要内容。根据我国低压配电控制过程的特点 ,针对现有的具有 Device Net通信接口的低压电器产品 ,提出了实现基于 Device

无线Device Net控制系统在移载车中的应用

根据以往运输线设计理念和使用效果,设计人员综合客户和创新设计要求,将铅阳极板运输线的运输小车采用无线Device Net网络与PLC之间的通讯方式,一改传统的有线网络模式,避免了有线网络的诸多弊端,此方案设计新颖,通讯快速灵敏,维护简洁方便。

Danfoss FC200变频器与AB PLC的Device Net通讯的实现

本文介绍了曹妃甸海水淡化项目中Danfoss FC200变频器与AB PLC的Device Net现场总线通讯的参数设置和软件编程方法,Device Net网络是工业控制的底层网络,采用了数据网络通信的新技术,具有低成本,高效率和可靠性高的特点。

An Environment‑Tolerant Ion‑Conducting Double‑Network Composite Hydrogel for High‑Performance Flexible Electronic Devices

High-performance ion-conducting hydrogels(ICHs)are vital for developing flexible electronic devices.However,the robustness and ion-conducting behavior of ICHs deteriorate at extreme tempera-tures,hampering their use in soft electronics.To resolve these issues,a method involving freeze–thawing and ionizing radiation technology is reported herein for synthesizing a novel double-network(DN)ICH based on a poly(ionic liquid)/MXene/poly(vinyl alcohol)(PMP DN ICH)system.The well-designed ICH exhibits outstanding ionic conductivity(63.89 mS cm^(-1) at 25℃),excellent temperature resistance(-60–80℃),prolonged stability(30 d at ambient temperature),high oxidation resist-ance,remarkable antibacterial activity,decent mechanical performance,and adhesion.Additionally,the ICH performs effectively in a flexible wireless strain sensor,thermal sensor,all-solid-state supercapacitor,and single-electrode triboelectric nanogenerator,thereby highlighting its viability in constructing soft electronic devices.The highly integrated gel structure endows these flexible electronic devices with stable,reliable signal output performance.In particular,the all-solid-state supercapacitor containing the PMP DN ICH electrolyte exhibits a high areal specific capacitance of 253.38 mF cm^(-2)(current density,1 mA cm^(-2))and excellent environmental adaptability.This study paves the way for the design and fabrication of high-performance mul-tifunctional/flexible ICHs for wearable sensing,energy-storage,and energy-harvesting applications.

In Situ Atomic Reconstruction Engineering Modulating Graphene-Like MXene-Based Multifunctional Electromagnetic Devices Covering Multi-Spectrum

With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot topic.Exploring the multispectral response of materials is a challenging and meaningful scientific question.In this study,MXene/TiO_(2)hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction engineering.More importantly,MXene/TiO_(2)hybrids exhibit adjustable spectral responses in the GHz,infrared and visible spectrums,and several EM devices are constructed based on this.An antenna array provides excellent EM energy harvesting in multiple microwave bands,with|S11|up to−63.2 dB,and can be tuned by the degree of bending.An ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the stopband.An infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14μm.This work can provide new inspiration for the design and development of multifunctional,multi-spectrum EM devices.

BLS-identification:A device fingerprint classification mechanism based on broad learning for Internet of Things

The popularity of the Internet of Things(IoT)has enabled a large number of vulnerable devices to connect to the Internet,bringing huge security risks.As a network-level security authentication method,device fingerprint based on machine learning has attracted considerable attention because it can detect vulnerable devices in complex and heterogeneous access phases.However,flexible and diversified IoT devices with limited resources increase dif-ficulty of the device fingerprint authentication method executed in IoT,because it needs to retrain the model network to deal with incremental features or types.To address this problem,a device fingerprinting mechanism based on a Broad Learning System(BLS)is proposed in this paper.The mechanism firstly characterizes IoT devices by traffic analysis based on the identifiable differences of the traffic data of IoT devices,and extracts feature parameters of the traffic packets.A hierarchical hybrid sampling method is designed at the preprocessing phase to improve the imbalanced data distribution and reconstruct the fingerprint dataset.The complexity of the dataset is reduced using Principal Component Analysis(PCA)and the device type is identified by training weights using BLS.The experimental results show that the proposed method can achieve state-of-the-art accuracy and spend less training time than other existing methods.

The Machine Learning Ensemble for Analyzing Internet of Things Networks:Botnet Detection and Device Identification

The rapid proliferation of Internet of Things(IoT)technology has facilitated automation across various sectors.Nevertheless,this advancement has also resulted in a notable surge in cyberattacks,notably botnets.As a result,research on network analysis has become vital.Machine learning-based techniques for network analysis provide a more extensive and adaptable approach in comparison to traditional rule-based methods.In this paper,we propose a framework for analyzing communications between IoT devices using supervised learning and ensemble techniques and present experimental results that validate the efficacy of the proposed framework.The results indicate that using the proposed ensemble techniques improves accuracy by up to 1.7%compared to singlealgorithm approaches.These results also suggest that the proposed framework can flexibly adapt to general IoT network analysis scenarios.Unlike existing frameworks,which only exhibit high performance in specific situations,the proposed framework can serve as a fundamental approach for addressing a wide range of issues.

Unconventional room-temperature negative magnetoresistance effect in Au/n-Ge:Sb/Au devices

Non-magnetic semiconductor materials and their devices have attracted wide attention since they are usually prone to exhibit large positive magnetoresistance(MR)effect in a low static magnetic field environment at room temperature.However,how to obtain a large room-temperature negative MR effect in them remains to be studied.In this paper,by designing an Au/n-Ge:Sb/Au device with metal electrodes located on identical side,we observe an obvious room-temperature negative MR effect in a specific 50 T pulsed high magnetic field direction environment,but not in a static low magnetic field environment.Through the analysis of the experimental measurement of the Hall effect results and bipolar transport theory,we propose that this unconventional negative MR effect is mainly related to the charge accumulation on the surface of the device under the modulation of the stronger Lorentz force provided by the pulsed high magnetic field.This theoretical analytical model is further confirmed by regulating the geometry size of the device.Our work sheds light on the development of novel magnetic sensing,magnetic logic and other devices based on non-magnetic semiconductors operating in pulsed high magnetic field environment.

Liquid Metal Grid Patterned Thin Film Devices Toward Absorption‑Dominant and Strain‑Tunable Electromagnetic Interference Shielding

The demand of high-performance thin-film-shaped deformable electromagnetic interference(EMI)shielding devices is increasing for the next generation of wearable and miniaturized soft electronics.Although highly reflective conductive materials can effectively shield EMI,they prevent deformation of the devices owing to rigidity and generate secondary electromagnetic pollution simultaneously.Herein,soft and stretchable EMI shielding thin film devices with absorption-dominant EMI shielding behavior is presented.The devices consist of liquid metal(LM)layer and LM grid-patterned layer separated by a thin elastomeric film,fabricated by leveraging superior adhesion of aerosol-deposited LM on elastomer.The devices demonstrate high electromagnetic shielding effectiveness(SE)(SE_(T) of up to 75 dB)with low reflectance(SER of 1.5 dB at the resonant frequency)owing to EMI absorption induced by multiple internal reflection generated in the LM grid architectures.Remarkably,the excellent stretchability of the LM-based devices facilitates tunable EMI shielding abilities through grid space adjustment upon strain(resonant frequency shift from 81.3 to 71.3 GHz@33%strain)and is also capable of retaining shielding effectiveness even after multiple strain cycles.This newly explored device presents an advanced paradigm for powerful EMI shielding performance for next-generation smart electronics.

Quality of Service and Security on Cisco Network Devices, Coupled with the Development of a Mobile Application Prototype Software for Server Room Temperature Monitoring

In an era where digital technology is paramount, higher education institutions like the University of Zambia (UNZA) are employing advanced computer networks to enhance their operational capacity and offer cutting-edge services to their academic fraternity. Spanning across the Great East Road campus, UNZA has established one of the most extensive computer networks in Zambia, serving a burgeoning community of over 20,000 active users through a Metropolitan Area Network (MAN). However, as the digital landscape continues to evolve, it is besieged with burgeoning challenges that threaten the very fabric of network integrity—cyber security threats and the imperatives of maintaining high Quality of Service (QoS). In an effort to mitigate these threats and ensure network efficiency, the development of a mobile application to monitor temperatures in the server room was imperative. According to L. Wei, X. Zeng, and T. Shen, the use of wireless sensory networks to monitor the temperature of train switchgear contact points represents a cost-effective solution. The system is based on wireless communication technology and is detailed in their paper, “A wireless solution for train switchgear contact temperature monitoring and alarming system based on wireless communication technology”, published in the International Journal of Communications, Network and System Sciences, vol. 8, no. 4, pp. 79-87, 2015 [1]. Therefore, in this study, a mobile application technology was explored for monitoring of temperatures in the server room in order to aid Cisco device performance. Additionally, this paper also explores the hardening of Cisco device security and QoS which are the cornerstones of this study.

Miniature tunable Airy beam optical meta-device

Tunable Airy beams with controllable propagation trajectories have sparked interest in various fields,such as optical manipulation and laser fabrication.Existing research approaches encounter challenges related to insufficient compactness and integration feasibility,or they require enhanced tunability to enable real-time dynamic manipulation of the propagation trajectory.In this work,we present a novel method that utilizes a dual metasurface system to surpass these limitations,significantly enhancing the practical potential of the Airy beam.Our approach involves encoding a cubic phase profile and two off-axis Fresnel lens phase profiles across the two metasurfaces.The validity of the proposed strategy has been confirmed through simulation and experimental results.The proposed meta-device addresses the existing limitations and lays the foundation for broadening the applicability of Airy beams across diverse domains,encompassing light-sheet microscopy,laser fabrication,optical tweezers,etc.

Recent developments in selective laser processes for wearable devices

Recently,the increasing interest in wearable technology for personal healthcare and smart virtual/augmented reality applications has led to the development of facile fabrication methods.Lasers have long been used to develop original solutions to such challenging technological problems due to their remote,sterile,rapid,and site-selective processing of materials.In this review,recent developments in relevant laser processes are summarized under two separate categories.First,transformative approaches,such as for laser-induced graphene,are introduced.In addition to design optimization and the alteration of a native substrate,the latest advances under a transformative approach now enable more complex material compositions and multilayer device configurations through the simultaneous transformation of heterogeneous precursors,or the sequential addition of functional layers coupled with other electronic elements.In addition,the more conventional laser techniques,such as ablation,sintering,and synthesis,can still be used to enhance the functionality of an entire system through the expansion of applicable materials and the adoption of new mechanisms.Later,various wearable device components developed through the corresponding laser processes are discussed,with an emphasis on chemical/physical sensors and energy devices.In addition,special attention is given to applications that use multiple laser sources or processes,which lay the foundation for the all-laser fabrication of wearable devices.

A mixed-coordination electron trapping-enabled high-precision touch-sensitive screen for wearable devices

Touch-sensitive screens are crucial components of wearable devices.Materials such as reduced graphene oxide(rGO),carbon nanotubes(CNTs),and graphene offer promising solutions for flexible touch-sensitive screens.However,when stacked with flexible substrates to form multilayered capacitive touching sensors,these materials often suffer from substrate delamination in response to deformation;this is due to the materials having different Young’s modulus values.Delamination results in failure to offer accurate touch screen recognition.In this work,we demonstrate an induced charge-based mutual capacitive touching sensor capable of high-precision touch sensing.This is enabled by electron trapping and polarization effects related to mixed-coordinated bonding between copper nanoparticles and vertically grown graphene nanosheets.Here,we used an electron cyclotron resonance system to directly fabricate graphene-metal nanofilms(GMNFs)using carbon and copper,which are firmly adhered to flexible substrates.After being subjected to 3000 bending actions,we observed almost no change in touch sensitivity.The screen interaction system,which has a signal-to-noise ratio of 41.16 dB and resolution of 650 dpi,was tested using a handwritten Chinese character recognition trial and achieved an accuracy of 94.82%.Taken together,these results show the promise of touch-sensitive screens that use directly fabricated GMNFs for wearable devices.

Clinical efficacy and mechanism study of mid-frequency anti-snoring device in treating moderate obstructive sleep apnea-hypopnea syndrome

BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is primarily caused by airway obstruction due to narrowing and blockage in the nasal and nasopha-ryngeal,oropharyngeal,soft palate,and tongue base areas.The mid-frequency anti-snoring device is a new technology based on sublingual nerve stimulation.Its principle is to improve the degree of oropharyngeal airway stenosis in OSAHS patients under mid-frequency wave stimulation.Nevertheless,there is a lack of clinical application and imaging evidence.METHODS We selected 50 patients diagnosed with moderate OSAHS in our hospital between July 2022 and August 2023.They underwent a 4-wk treatment regimen involving the mid-frequency anti-snoring device during nighttime sleep.Following the treatment,we monitored and assessed the sleep apnea quality of life index and Epworth Sleepiness Scale scores.Additionally,we performed computed tomo-graphy scans of the oropharynx in the awake state,during snoring,and while using the mid-frequency anti-snoring device.Cross-sectional area measurements in different states were taken at the narrowest airway point in the soft palate posterior and retrolingual areas.RESULTS Compared to pretreatment measurements,patients exhibited a significant reduction in the apnea-hypopnea index,the percentage of time with oxygen saturation below 90%,snoring frequency,and the duration of the most prolonged apnea event.The lowest oxygen saturation showed a notable increase,and both sleep apnea quality of life index and Epworth Sleepiness Scale scores improved.Oropharyngeal computed tomography scans revealed that in OSAHS patients cross-sectional areas of the oropharyngeal airway in the soft palate posterior area and retrolingual area decreased during snoring compared to the awake state.Conversely,during mid-frequency anti-snoring device treatment,these areas increased compared to snoring.CONCLUSION The mid-frequency anti-snoring device demonstrates the potential to enhance various sleep parameters in patients with moderate OSAHS,thereby improving their quality of life and reducing daytime sleepiness.These therapeutic effects are attributed to the device’s ability to ameliorate the narrowing of the oropharynx in OSAHS patients.

Application value research of swallowing treatment device combined with swallowing rehabilitation training in the treatment of swallowing disorders after stroke

BACKGROUND Stroke is a common disabling disease,whether it is ischemic stroke or hemorrhagic stroke,both can result in neuronal damage,leading to various manifestations of neurological dysfunction.AIM To explore of the application value of swallowing treatment device combined with swallowing rehabilitation training in the treatment of swallowing disorders after stroke.METHODS This study selected 86 patients with swallowing disorders after stroke admitted to our rehabilitation department from February 2022 to December 2023 as research subjects.They were divided into a control group(n=43)and an observation group(n=43)according to the treatment.The control group received swallowing rehabilitation training,while the observation group received swallowing treatment device in addition to the training.Both groups underwent continuous intervention for two courses of treatment.RESULTS The total effective rate in the observation group(93.02%)was higher than that in the control group(76.74%)(P=0.035).After intervention,the oral transit time,swallowing response time,pharyngeal transit time,and laryngeal closure time decreased in both groups compared to before intervention.In the observation group,the oral transit time,swallowing response time,and pharyngeal transit time were shorter than those in the control group after intervention.However,the laryngeal closure time after intervention in the observation group was compared with that in the control group(P=0.142).After intervention,average amplitude value and duration of the genioglossus muscle group during empty swallowing and swallowing 5 mL of water are reduced compared to before intervention in both groups.After intervention,the scores of the chin-tuck swallowing exercise and the Standardized Swallowing Assessment are both reduced compared to pre-intervention levels in both groups.However,the observation group scores lower than the control group after intervention.Additionally,the Functional Oral Intake Scale scores of both groups are increased after intervention compared to pre-intervention levels,with the observation group scoring higher than the control group after intervention(P<0.001).The cumulative incidence of complications in the observation group is 9.30%,which is lower than the 27.91%in the control group(P=0.027).CONCLUSION The combination of swallowing therapy equipment with swallowing rehabilitation training can improve the muscle movement level of the genioglossus muscle group,enhance swallowing function,and prevent the occurrence of swallowing-related complications after stroke.

3D printing of high-precision and ferromagnetic functional devices

The development of projection-based stereolithography additive manufacturing techniques and magnetic photosensitive resins has provided a powerful approach to fabricate miniaturized magnetic functional devices with complex three-dimensional spatial structures.However,the present magnetic photosensitive resins face great challenges in the trade-off between high ferromagnetism and excellent printing quality.To address these challenges,we develop a novel NdFeB-Fe_(3)O_(4) magnetic photosensitive resin comprising 20 wt.%solid loading of magnetic particles,which can be used to fabricate high-precision and ferromagnetic functional devices via micro-continuous liquid interface production process.This resin combining ferromagnetic NdFeB microparticles and strongly absorbing Fe_(3)O_(4) nanoparticles is able to provide ferromagnetic capabilities and excellent printing quality simultaneously compared to both existing soft and hard magnetic photosensitive resins.The established penetration depth model reveals the effect of particle size,solid loading,and absorbance on the curing characteristics of magnetic photosensitive resin.A high-precision forming and ferromagnetic capability of the NdFeB-Fe_(3)O_(4) magnetic photosensitive resin are comprehensively demonstrated.It is found that the photosensitive resin(NdFeB:Fe_(3)O_(4)=1:1)can print samples with sub-40μm fine features,reduced by 87%compared to existing hard magnetic photosensitive resin,and exhibits significantly enhanced coercivity and remanence in comparison with existing soft magnetic photosensitive resins,showing by an increase of 24 times and 6 times,respectively.The reported NdFeB-Fe_(3)O_(4) magnetic photosensitive resin is anticipated to provide a new functional material for the design and manufacture of next-generation micro-robotics,electromagnetic sensor,and magneto-thermal devices.

Accurate threat hunting in industrial internet of things edge devices

Industrial Internet of Things(IIoT)systems depend on a growing number of edge devices such as sensors,controllers,and robots for data collection,transmission,storage,and processing.Any kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire IIoT.Moreover,they can allow malicious software installed on end nodes to penetrate the network.This paper presents a parallel ensemble model for threat hunting based on anomalies in the behavior of IIoT edge devices.The proposed model is flexible enough to use several state-of-the-art classifiers as the basic learner and efficiently classifies multi-class anomalies using the Multi-class AdaBoost and majority voting.Experimental evaluations using a dataset consisting of multi-source normal records and multi-class anomalies demonstrate that our model outperforms existing approaches in terms of accuracy,F1 score,recall,and precision.