Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

A Multifunctional Anti-Proton Electrolyte for High-Rate and Super-Stable Aqueous Zn-Vanadium Oxide Battery

Large volumetric expansion of cathode hosts and sluggish transport kinetics in the cathode–electrolyte interface,as well as dendrite growth and hydrogen evolution at Zn anode side are considered as the system problems that cause the electrochemical failure of aqueous Zn-vanadium oxide battery.In this work,a multifunctional anti-proton electrolyte was proposed to synchronously solve all those issues.Theoretical and experimental studies confirm that PEG 400 additive can regulate the Zn^(2+) solvation structure and inhibit the ionization of free water molecules of the electrolyte.Then,smaller lattice expansion of vanadium oxide hosts and less associated by-product formation can be realized by using such electrolyte.Besides,such electrolyte is also beneficial to guide the uniform Zn deposition and suppress the side reaction of hydrogen evolution.Owing to the integrated synergetic modifica-tion,a high-rate and ultrastable aqueous Zn-V_(2)O_(3)/C battery can be constructed,which can remain a specific capacity of 222.8 m Ah g^(-1)after 6000 cycles at 5 A g^(-1),and 121.8 m Ah g^(-1) even after 18,000 cycles at 20 A g^(-1),respectively.Such“all-in-one”solution based on the electrolyte design provides a new strategy for developing high-performance aqueous Zn-ion battery.

An All‑In‑One Multifunctional Touch Sensor with Carbon‑Based Gradient Resistance Elements

Human–machine interactions using deep-learning methods are important in the research of virtual reality,augmented reality,and metaverse.Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes,signal crosstalk,propagation delay,and demanding configuration requirements.Here,an all-inone multipoint touch sensor(AIOM touch sensor)with only two electrodes is reported.The AIOM touch sensor is efficiently constructed by gradient resistance elements,which can highly adapt to diverse application-dependent configurations.Combined with deep learning method,the AIOM touch sensor can be utilized to recognize,learn,and memorize human–machine interactions.A biometric verification system is built based on the AIOM touch sensor,which achieves a high identification accuracy of over 98%and offers a promising hybrid cyber security against password leaking.Diversiform human–machine interactions,including freely playing piano music and programmatically controlling a drone,demonstrate the high stability,rapid response time,and excellent spatiotemporally dynamic resolution of the AIOM touch sensor,which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.

Conformal Human–Machine Integration Using Highly Bending‑Insensitive,Unpixelated,and Waterproof Epidermal Electronics Toward Metaverse

Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals,which is critical to the breakthrough development of metaverse.Interactive electronics face common dilemmas,which realize highprecision and stable touch detection but are rigid,bulky,and thick or achieve high flexibility to wear but lose precision.Here,we construct highly bending-insensitive,unpixelated,and waterproof epidermal interfaces(BUW epidermal interfaces)and demonstrate their interactive applications of conformal human–machine integration.The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection,high flexibility,rapid response time,excellent stability,and versatile“cut-and-paste”character.Regardless of whether being flat or bent,the BUW epidermal interface can be conformally attached to the human skin for real-time,comfortable,and unrestrained interactions.This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics,which offers a new technology route and may further broaden human–machine interactions toward metaverse.

Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm

Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.

A machine learning-assisted multifunctional tactile sensor for smart prosthetics

The absence of tactile perception limits the dexterity of a prosthetic hand and its acceptance by amputees.Recreating the sensing properties of the skin using a flexible tactile sensor could have profound implications for prosthetics,whereas existing tactile sensors often have limited functionality with cross-interference.In this study,we propose a machine-learning-assisted multifunctional tactile sensor for smart prosthetics,providing a human-like tactile sensing approach for amputations.This flexible sensor is based on a poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)-melamine sponge,which enables the detection of force and temperature with low cross-coupling owing to two separate sensing mechanisms:the open-circuit voltage of the sensor as a force-insensitive intrinsic variable to measure the absolute temperature and the resistance as a temperature-insensitive extrinsic variable to measure force.Furthermore,by analyzing the unsteady heat conduction and characterizing it using real-time thermal imaging,we demonstrated that the process of open-circuit voltage variation resulting from the unsteady heat conduction is closely correlated with the heatconducting capabilities of materials,which can be utilized to discriminate between substances.Assisted by the decision tree algorithm,the device is endowed with thermal conductivity sensing ability,which allows it to identify 10 types of substances with an accuracy of 94.7%.Furthermore,an individual wearing an advanced myoelectric prosthesis equipped with the above sensor can sense pressure,temperature,and recognize different materials.We demonstrated that our multifunctional tactile sensor provides a new strategy to help amputees feel force,temperature and identify the material of objects without the aid of vision.

涤棉混纺段彩纱的工艺优化及风格探讨

为探讨涤棉粗纱混纺段彩纱的纺纱工艺与成纱风格,以涤棉混纺粗纱为原料,采用三罗拉牵伸法,通过HFX-A6型多功能细纱机来制备涤棉段彩纱。研究工艺参数(捻度、分段时间和牵伸倍数)对段彩纱风格(外观、结构、强伸性能、条干均匀度和毛羽)的影响,并根据其外观风格建立了段彩纱的周期结构模型。试验结果表明,增大辅纱分段时间和牵伸倍数对纱线风格具有积极的影响,而增大捻度对纱线风格具有消极的影响。当纺纱工艺的捻度为90捻/m,基纱与辅纱分段时间均为1 s,两根粗纱的总牵伸分别为22.8倍和24.0倍时,段彩纱的综合性能最为优异。

雷达工作模式识别方法综述

雷达工作模式识别通过对信号的截获分析来辨识雷达功能和行为状态,是情报侦察、电子对抗领域的重要内容。该文从适应背景的不同,研究了基于知识驱动和数据驱动算法的发展历程,从统计分析、行为推理、传统机器学习和深度学习4个阶段总结了现有算法的基本思路、创新点和局限性,归纳了当前研究存在的难点与挑战。统计分析方法解决了信号背景清晰、简单调制类型下的识别问题。行为推理方法通过概率计算分析雷达模式的内在关联性,具备了常规模式识别的能力。传统机器学习从数据分布的角度提取深层规律,在人工配合下能够实现复杂条件下的模式识别。深度学习方法基本摆脱人工的干预,通过“端到端”的识别实现了自动化的处理。

三元正极材料前驱体多维洗涤系统的设计

为满足三元材料前驱体生产过程对洗涤日趋严格的要求,对研制的多功能一体机的洗涤方式和机理进行分析,得出多维洗涤是解决前驱体杂质含量高、洗涤废水量大的可靠工程方法。通过将洗涤过程中的正反向旋转、转速、升降等动作优化组合,形成多维运动场,并与前驱体特性有机融合,实现多维洗涤。洗涤后的前驱体,钠(Na)的质量分数为0.015%、硫(S)的质量分数为0.140%、磁性异物的质量分数不超过5.0×10^(-6)%,均优于国家标准,并减少了废水排放。

用于含能材料生产的多功能一体机的设计

针对现有含能材料间断操作生产效率低、安全性差的问题,结合传统过滤洗涤一体机的技术优势,通过设计选型、计算校核和自动化控制,研制出平底结构型式一体机,应用到含能材料过滤、清洗、驱酸工序。经物料模拟分析,存在浆料出料不彻底的情况,进一步对一体机进行优化改进,形成中心低位出料的锥底结构型式一体机。

多功能矿用开槽机的研制与应用

目前我国大部分煤矿还是以井工开采方式为主,随着采煤工作面的开采结束,需在采空区建立井下密闭进行隔离。市场上已经有用于井下密闭施工的矿用开槽机,但是此类设备功能较为单一,在没有密闭施工任务时经常处于闲置状态。针对以上情况,在现有矿用密闭开槽机的基础上增加其功能性,研制一种能够满足井下不同工作需求的多功能矿用开槽机,代替人工作业,提高作业效率,降低事故发生概率。

水利水电工程单轨拦污清污系统及多功能清污机设计与应用

水利水电工程中的进水口单轨拦污清污系统,由于其轨道中心位置固定不变,产生了启闭机或清污机功能单一的问题,针对该问题,从拦污系统和清污系统两个方面进行了系统性研究,应用偏心原理,设计了带偏心结构的液压清污耙斗,建立了其重心位置方程式并给定了吊点的位置范围,使液压耙斗在开耙和闭耙时产生不同方向的偏心矩并加以利用,设计了拦污栅及导栅的参考结构,介绍了进水口单轨拦污清污系统及清污机的组成,结合工作过程,说明了拦污栅垂直布置工程中清污机启闭拦污栅和清污的过程及实现方法。理论和3个典型加设清污机改造工程实践表明,偏心矩、导栅和水流的共同作用,可使单轨清污机实现不同工况下的吊点偏移,在拦污栅垂直布置的工程中实现多种功能,通过荷重传感器等的保护作用,限定斜拉角度在10°以内,可保证不同工况下的作业安全,对工程设计或改造具有良好的借鉴意义。

收膜整地多功能作业机的研究

研究和设计了一种收膜整地多功能作业机,介绍了机器的结构和工作过程及主要工作部件的设计原理,通过分析研究取得了最佳的结构和工作参数。试验结果表明机器采用起膜铲、拾膜轮和推板机构相配合完成拾膜工艺过程并在起膜铲后配置旋耕和其它整地部件,结构紧凑,工艺原理新颖合理;机器适用于70cm的垄作农田双行作业,也适用于100cm的大垄单行作业,也可根据作业要求选择其中不同的功能。

基于多功能加工平台的微细电解加工工艺

利用多功能微细加工平台的微细电火花加工技术为微细电解加工在线制作微细电极,在低浓度钝化电解液、低加工电压和高频窄脉冲电流加工条件下,利用高速旋转工具电极和微电流密度下电解钝化作用,实现了微米级的微细电解加工.通过工艺实验,研究电压、电解液浓度和进给速度等参数对加工间隙的影响,优化工艺参数.在优化加工条件下,在厚为100μm的不锈钢薄片上微细电解钻削出65μm的微小孔.针对成型电极在微细加工中暴露出的缺点,提出了利用旋转微细电极像微铣刀一样进行微细电解铣削新工艺,加工出高精度型孔和悬臂梁等微结构.

MVB协议分析装置设计及其实时性分析

介绍多功能车辆总线MVB协议分析装置的功能、软硬件设计方案及实现原理。分析影响MVB协议实时性的关键因子,试验和对比4种不同改进方案下设计的MVB协议分析装置的实时性能,采用状态机模式实现MVB网络数据实时底层解码;采用多重缓冲技术,在无需控制器参与的情况下实现高速USB控制时序,解决了MVB协议分析装置实时性不高的难题。该设备与国外同类产品相比,在实时性、可靠性、灵活性等方面都有明显提高。

多功能果园田间管理机设计与试验

针对现有果园机械化水平较低、缺少集成式设备问题,依据果园农艺要求设计了一种多功能果园田间管理机。该机器为自走履带式有级变速,装配有大块有机肥宽深开沟器、粉状与粒状无机肥开沟施肥回填一体装置等,以完成果园的开沟和施肥等多环节的机械作业。通过快换装置实现开沟和施肥等功能的简便拆卸更换,以保障多功能管理机作业的可操作性和可靠性。经过田间试验,测知管理机能够完成35cm宽、0~40cm深的开沟,施肥深度可达到35cm,作业速度为350~2 000m/h,机身高度90cm,长度270cm。由于机型矮小,转弯半径最小1.8m,行走灵活,因此既可用于现代宽行矮砧密植果园,又可用于传统乔化果园。

多功能清洗机的临床应用

目的:观察多功能清洗机的临床应用效果。方法:比较机洗和手洗外伤的创面清洗效果、清洗所耗时间及所用清洁液量。结果:机洗组清洗创面效果优于手洗组,所耗时间与清洁液量少于机洗组。结论:本多功能清洗机冲洗清创与手工冲洗比较有明显优势,是一种处理创伤的高效率器械。

基于LS-SVM的非线性多功能传感器信号重构方法研究

提出了基于最小二乘支持向量机(Least squares support vector machine,LS-SVM)的非线性多功能传感器信号重构方法.不同于通常采用的经验风险最小化重构方法,支持向量机(Support vector machine,SVM)是基于结构风险最小化准则的新型机器学习方法,适用于小样本标定数据情况,可有效抑制过拟合问题并改善泛化性能.在SVM基础上,LS-SVM将不等式约束转化为等式约束,极大地简化了二次规划问题的求解.研究中通过L-折交叉验证实现调整参数优化,在两种非线性情况下对多功能传感器的输入信号进行了重构,实验结果显示重构精度分别达到0.154%和1.146%,表明提出的LS-SVM重构方法具有高可靠性和稳定性,验证了方法的有效性.

多功能卧底机设计

针对目前煤矿巷道维护困难的现状,研制了一种多功能卧底机,该机可快速更换卧底铲、截割滚筒、承重平台或破碎锤等工作装置,从而实现不同功能的切换。介绍了设备的组成及其工作原理,并对多功能卧底机主体及其工作装置进行了详细阐述。多功能卧底机研制成功及其推广可提高巷道维护的机械化作业程度、降低劳动强度、提高生产效率。

基于ARM的多功能数字化逆变电源

针对不同焊接方式的不同控制方法,设计了基于先进精简指令集处理器(ARM)控制的多功能数字化逆变电源.利用基于ARM和复杂可编程逻辑器件的人机交互系统,通过软件设计,在一台电源上实现了CO2气体保护焊、脉冲熔化极气体保护焊、手工焊条焊等多种焊接方式的转换与选择.采用小波分析仪采集焊接过程的电流电压信号,考察了多功能数字化逆变电源的工艺性能,结果表明所设计的电源可满足各种焊接工艺要求,实现了数字化逆变电源的多功能化,提高了数字化逆变电源的实用性.