Clustered Wireless Sensor Network in Precision Agriculture via Graph Theory

Food security and sustainable development is making a mandatory move in the entire human race.The attainment of this goal requires man to strive for a highly advanced state in thefield of agriculture so that he can produce crops with a minimum amount of water and fertilizer.Even though our agricultural methodol-ogies have undergone a series of metamorphoses in the process of a present smart-agricultural system,a long way is ahead to attain a system that is precise and accurate for the optimum yield and profitability.Towards such a futuristic method of cultivation,this paper proposes a novel method for monitoring the efficientflow of a small quantity of water through the conventional irrigation system in cultiva-tion using Clustered Wireless Sensor Networks(CWSN).The performance measure is simulated the creation of edge-fixed geodetic clusters using Mat lab’s Cup-carbon tool in order to evaluate the suggested irrigation process model’s performance.Thefindings of blocks 1 and 2 are assessed.Each signal takes just a little amount of energy to communicate,according to the performance.It is feasible to save energy while maintaining uninterrupted communication between nodes and cluster chiefs.However,the need for proper placement of a dynamic control station in WSN still exists for maintaining connectivity and for improving the lifetime fault tolerance of WSN.Based on the minimum edgefixed geodetic sets of the connected graph,this paper offers an innovative method for optimizing the placement of control stations.The edge-fixed geodetic cluster makes the network fast,efficient and reliable.Moreover,it also solves routing and congestion problems.

Key technologies of precision demolition blasting of ultra-long urban viaduct in complicated surroundings

The key technologies of precision blasting were put forward based on the characteristics of urban via- duct blasting demolition in complicated surroundings. Initial bending instability mechanics model of reinforcing steel bar frame of blasting fragmented pier and sequenced collapsed dynamic model were established for quanti- tative blasting design. Technologies of water pressure blasting were applied in multi-cell box girder fragmenta- tion. The detonating network of non-electric duplication crossover was adopted for the safety and reliability of ultra-long delay. The rationality of blasting scheme and parameters were validated by physical model test. Harm- ful effects were forecasted and controlled by integrated protective technologies. Specialization, cooperation, pre- cision, execution （SCPE） project management method was put forward for precision management. The key tech- nologies of precision demolition blasting can provide reference for similar proiects.

Parameter Method Data Processing for CPⅢ Precise Trigonometric Leveling Network

In view of the limitation of the difference method,the adjustment model of CPⅢprecise trigonometric leveling control network based on the parameter method was proposed in the present paper.The experiment results show that this model has a simple algorithm and high data utilization,avoids the negative influences caused by the correlation among the data acquired from the difference method and its accuracy is improved compared with the difference method.In addition,the strict weight of CPⅢprecise trigonometric leveling control network was also discussed in this paper.The results demonstrate that the ranging error of trigonometric leveling can be neglected when the vertical angle is less than 3 degrees.The accuracy of CPⅢprecise trigonometric leveling control network has not changed significantly before and after strict weight.

A Precise Calibration Method on Phase Center of Uplink Antenna Array Considering Its Actual Pointing

With regard to the inferior techniques and low accuracy of phase center calibration of an antenna array, this paper proposes a new calibration method considering the actual antenna pointing by introducing a precise engineering surveying technique to measure the real state of antennas. First, an industrial photogrammetric system is utilized to obtain the coordinates of points on antenna panels in different postures, and the actual pointing of the mechanical axis is obtained via least-squares fitting. Then, based on this, the coordinates of antenna rotation center are obtained by seeking the intersection of mechanical axes via using the matrix method. Finally, the mechanical axis in arbitrary postures is estimated based on the inverse-angle weighting interpolation method, and the reliable phase center is obtained by moving a fixed length from the projective center along the mechanical axis. An uplink antenna array including three ? 3 m antennas is taken as experimental object, and all photogrammetric coordinate systems are unified by the engineering control network, with each antenna phase center precisely calibrated via the proposed method. The results of electrical signal synthesis indicate that this method can effectively overcome the influence of gravity deformation and mechanical installation error, and enhance the synthetic signal magnitude of the uplink antenna array.

Special Marking of 3D Networks＇ Points for the Monitoring of Modern Constructions

In order to monitor the deformations of modern constructions a local 3D network was usually being established at the surrounding area. The centering error, of both the instrument and targets, causes significant uncertainties in the determination of the x, y, z coordinates of the network＇s points. In order to assure precise centering for both the instrument and targets, not only for the accessible but also for the inaccessible network＇s points, a prototype way of marking is being implied. A special semi-permanent portable metallic stand （Photo 1） was manufactured for marking the accessible points. The stand provides forced instrument centering of the order of_＋0, lmm. It is light enough to carry, it accelerates and facilitates the centering and leveling of the instrument as well as it eliminates the time needed for the measurements. The applied laboratory checks in order to certify the suitability of its use and the provided accuracy are being described. For the inaccessible points special targets were used. The targets were put in permanent attachments （Photos 7-8）, which were also manufactured. Useful conclusions were drawn when these special accessories were used in to a 3D network, which was established for the monitoring of a new football stadium. Two measurement phases were carried out. The first one is with the stadium empty and the second one is when it was crowded （about 32000 people） during a significant football match.

基于物联网农业灌溉系统精准控制模型的研究

为进一步提升我国农业灌溉系统的综合作业效率,体现灌溉的先进性与科学性,提出以精准控制模型为切入点,以物联网技术为主体支撑平台,针对其作业系统展开设计与优化。通过引入物联网强大的系统性架构,规范与强化各网络节点的部署与协作关系,科学搭建用于实现精准灌溉控制的数学模型,同时导入合理的系统软件设计程序与硬件功能组件配置,形成完整集成式的农业智能灌溉系统。结果表明:基于物联网平台技术的精准控制模型应用后,整体的作业效率得到显著提升,系统精准度、系统响应率分别相对提高了6.25%和7.68%,动作延迟率相对降低了2.72%,灌溉节水效率提升至91.50%。物联网平台下的精准控制模型应用效果良好,设计理念正确,可为灌溉领域实施节能降耗提供参考。

半导体晶圆键合加压精确控制方法

晶圆键合质量受键合压力控制精度显著影响。对于本身有一定翘曲度的晶圆,容易在键合过程中产生非预期位移,造成键合工艺偏差,甚至碎片。因此,提出了一种基于模糊PID(比例-积分-微分)和RBF(Radial Basis Function)径向基函数神经网络算法的半导体晶圆键合压力控制方法。由于加入了模糊PID和深度学习算法控制,使得键合工艺过程响应更迅速,控制更精准,且安全性更高。采用铝样片进行加压试验,结果表明RBF神经网络模糊PID控制算法能够满足压力精度为±1%的控制需求。

基于高精度地图的智能网联技术师资培训探究——以《交通管理与控制》为例

在智能化、网联化的大环境下,随着相关政策落地和人才市场的需求,导致高校教师理论和实践技能遇到新的挑战,因此交通智能技术领域的教育教学改革也将成为必然的趋势。据此,文章首先简要介绍了基于高精度地图的智能网联技术的发展现状,随后围绕该新型技术对人才的需求探讨了该专业教学领域师资现状以及存在的问题,最后结合交通工程专业核心课程《交通管理与控制》对教师队伍的建设和培训给予了建议和意见,为更好地构建以高精度地图为基础的智能网联技术专业师资队伍提供借鉴。

上海市高程控制网复测关键技术研究

结合上海市高程控制网复测项目,就其关键技术及质量控制进行了实践和探讨。重点阐述了上海市高程控制网复测准备阶段的水准点调查、水准路线设计,外业施测阶段的几何水准测量、跨隧道水准测量、跨河水准测量、SHCORS高程属性测量,内业数据处理阶段的改正数计算、平差计算等关键技术。项目实现了全周期质量控制,通过各项精度指标证明其取得了良好的质量效果。最后就大型水准项目开展提出一些建议。

平陆运河工程施工控制网的建立

航道工程施工控制网是运河建设的重要课题。以平陆运河工程施工控制网的建立为例,根据枢纽建筑物施工放样的精度要求,确定平面控制网和高程控制网的等级。采用先进的测量仪器,快速完成控制网的外业数据采集,利用广西连续运行参考站(GXCORS)测量数据,集中统一处理全球导航卫星系统(GNSS)数据。高效率完成了施工控制网技术设计、外业数据采集、内业数据处理、精度分析、成果提供等全部生产过程。

铁路工程长距离带状GNSS控制网高精度解算

铁路工程控制网三网合一,采用GNSS卫星导航定位基准站(CORS)方式建网是发展的趋势,但其长距离、带状布设的控制网要确保高精度且连续均匀,具有一定的难度。针对长距离带状控制网的特点,分析影响GNSS控制网解算的影响因素,引入IGS站点坐标的松弛约束,筛选出优化解算策略:融合多星座卫星观测数据,基于电离层约束模型求解宽巷模糊度,当控制网的基线长度小于100 km时,对流层延迟采用站间差分改正、电离层延迟采用差分或模型改正,并结合环境条件顾及其他负荷改正。实际铁路工程带状控制网解算测试表明,优化策略控制网处理精度相较于常规策略在Y和Z方向上提升2~5 mm。通过对复杂地形环境下长距离带状控制网的解算质量分析,进一步表明该策略可优化铁路工程长距离带状控制网高精度解算性能。

基于SO-BP神经网络的温室环境预测模型研究

由于温室环境中温湿度的调控过程存在滞后响应特性,预测温室环境变化趋势是构建温室精准控制系统中不可或缺的一部分。针对传统神经网络算法在温室预测方面精度不足等问题,提出一种基于蛇优化算法(snake optimizer,SO)优化BP神经网络的温室环境预测方法。试验结果表明,该方法预测15 min内温度的决定系数R^(2)为0.9564,比BP模型、HHO-BP模型分别提高14.87%、2.19%,平均绝对误差MAE、平均绝对百分比误差MAPE、均方根误差RMSE值分别为0.4813、2.2378、0.6729;预测15 min内湿度的R^(2)为0.9821,比BP模型、HHO-BP模型分别提高13.12%、2.37%,预测指标MAE、MAPE、RMSE值分别为1.7090、2.5842、2.2838。该模型的预测结果较理想,可用于温室温湿度预测。

基于精测网体系的震后高速铁路构筑物变形特征测量

受地震影响,震中范围内铁路坐标基准易遭到破坏,控制点存在不同程度的位移,轨道结构产生不同程度的破损。为解决大范围控制点连续破坏后难以快速恢复的问题,结合工程实例,提出一种震后铁路精测网体系的快速恢复方法,以稳定的CP0为约束,联合CPⅠ控制点进行兼容性分析,完成不同级别控制网坐标逐级动态更新,以最大程度地利用原有控制成果,为震后应急抢险提供位置基准。基于重建后不同级别的精测网控制成果,结合CPⅢ复测数据,获得轨道横向、纵向变形量值,对铁路线路的整体变形特征进行量化分析;采用洞内三维扫描等手段对隧道断面进行净空测量,完成衬砌等构筑物多方位空间变形特征的分段分析,并与轨道的整体变形趋势进行匹配分析,以查明地震对大梁隧道洞内外的破坏程度和形变特征,为轨道结构可利用性评估、工程复旧提供数据基准。

基于BP神经网络PID的节水灌溉施肥系统研究

中国的化肥使用率常年居世界首位,且农业用水利用率较低,依靠个人经验的方法不仅造成了肥料和水资源的浪费,而且使当地生态环境也受到污染。由于管路运输等原因,节水灌溉施肥系统具有模型的时变性、非线性与时滞性的特点,普通控制器很难对节水灌溉施肥系统的流量进行精准控制。针对上述问题,设计了一种基于BP神经网络PID的控制器,以期实现节水灌溉施肥系统对液体肥流量的精准控制;同时,与传统PID控制器进行对比,用MatLab软件进行仿真分析,得到阶跃响应曲线。研究结果表明:基于BP神经网络PID的控制器具有优异的控制效果,可以满足节水灌溉施肥系统精准控制的实际要求。

高速磁浮轨道(梁)安装测控平面控制网测量技术实验研究

首先提出高速磁浮轨道(梁)安装测控平面控制网的精度要求,然后建立了小范围的CFⅢ平面控制测量实验网,在实验网中分别进行了基于高精度智能型全站仪和激光跟踪仪的观测实验,并对观测数据进行了处理与分析,以验证用这2种仪器及其对应的测量方法建立高速磁浮轨道安装测控平面控制网的精度及其可行性。实验结果表明,利用激光跟踪仪进行高速磁浮轨道(梁)安装测控平面控制网测量是可行的,且能够满足平差后方向改正数≤±1.5″、距离改正数≤±1 mm、相邻点的相对点位中误差≤±0.5 mm的精度要求。

Correlation Composition Awareness Model with Pair Collaborative Localization for IoT Authentication and Localization

Secure authentication and accurate localization among Internet of Things(IoT)sensors are pivotal for the functionality and integrity of IoT networks.IoT authentication and localization are intricate and symbiotic,impacting both the security and operational functionality of IoT systems.Hence,accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges.To overcome these challenges,recent approaches have used encryption techniques with well-known key infrastructures.However,these methods are inefficient due to the increasing number of data breaches in their localization approaches.This proposed research efficiently integrates authentication and localization processes in such a way that they complement each other without compromising on security or accuracy.The proposed framework aims to detect active attacks within IoT networks,precisely localize malicious IoT devices participating in these attacks,and establish dynamic implicit authentication mechanisms.This integrated framework proposes a Correlation Composition Awareness(CCA)model,which explores innovative approaches to device correlations,enhancing the accuracy of attack detection and localization.Additionally,this framework introduces the Pair Collaborative Localization(PCL)technique,facilitating precise identification of the exact locations of malicious IoT devices.To address device authentication,a Behavior and Performance Measurement(BPM)scheme is developed,ensuring that only trusted devices gain access to the network.This work has been evaluated across various environments and compared against existing models.The results prove that the proposed methodology attains 96%attack detection accuracy,84%localization accuracy,and 98%device authentication accuracy.

考虑时滞效应的模糊主动隔振系统的设计与性能

为了更好地实现精密仪器的振动控制,提出基于考虑时滞效应的模糊主动控制隔振系统。该系统采用神经网络,根据当前时刻模糊控制器的输出以及平台的输出数据,实时预测下一时刻平台的运动状态,提前施加作动力对平台进行主动控制。仿真实验表明,神经网络的预测较为准确,可靠度较高且设计方案合理,能有效预测实时信号并且抑制信号的振荡。系统融合了神经网络对时滞效应的补偿作用和模糊控制器对不确定性的处理能力,可实现精密仪器振动的智能化控制。

基于多智能体强化学习的多联机空调节能控制

多联机空调系统目前是空调发展的主要趋势,其节能控制研究逐渐成为空调领域的研究热点。然而传统的空调节能控制方法在非线性特征表示、高泛化性机理建模、设备参数精确自调节等方面存在较大挑战。对此,提出一种基于多智能体强化学习的多联机空调节能控制方法。首先,筛选多联机空调节能控制参数,实现参数的解耦与降维,利用深度神经网络构建了高泛化性的多联机空调运行模型,降低多智能体强化学习模型的训练时长;然后,提出多智能体协作的多联机空调智能化节能控制方法,设计了智能体的状态空间、动作空间和奖励函数;智能体采用集中式训练、分布式执行的方式,优化空调控制策略,同时设计了环境初始化条件,增加了环境多样性;最后,在包含3个地区、2个季节的空调运行历史数据集上开展广泛实验,结果表明该方法能够有效控制室内温度,能效比提高约18%。

基于GA-BP网络的数控机床动态误差预测研究

动态误差是高速高精度数控机床的重要误差源,针对实际加工过程中动态误差对工件精度影响较大的问题,提出了一种基于遗传算法优化的反向传播(GA-BP)神经网络以预测动态误差。首先,为了提高神经网络对动态误差的预测精度,从线性特征与非线性特征两方面对动态误差影响因素进行了深入分析,确定了神经网络输入输出参数;然后,采用了遗传算法对BP神经网络进行了优化,建立了动态误差模型,获得了最优网络学习参数,从而实现了对动态跟随误差的精准预测;之后,采用三次样条插值的方法对理想轨迹与实际轨迹之间的轮廓误差进行了计算,有效提高了轮廓误差估算精度;最后,采用了五轴数控机床进行了实验,对模型的有效性进行了验证。研究结果表明:所建神经网络模型可以精准预测机床反向越冲特性对轮廓误差的影响,各轴的动态误差预测精度为±3μm,复杂轨迹轮廓误差预测精度为±1.5μm。实验结果验证了所建模型的可靠性,为后续机床动态误差建模与控制研究提供了一定的参考价值。

工作面高效回采智能化调控技术研究

针对采煤机和刮板输送机连续高速运转造成的能源浪费和运输效率低的问题,基于多传感器信息融合技术,选取采煤机摇臂振动信号、截割电机电流信号以及调高油缸压力信号作为表征信号,利用RBF神经网络识别参数得到采煤机的煤岩截割状态。开展采煤机煤岩截割实验,读取采煤机截割煤、岩时的参数信号进行分析,验证预测效果为97.2%.对采煤机双向割煤过程中刮板输送机载煤量的变化进行分析,探究负载与电机电流的关系,为刮板输送机-采煤机协同调速提供依据和控制策略,有效解决采煤机和刮板输送机恒速运行模式下刮板输送机负载变化过大,避免了煤量短时过度累积和卸载。研究结果为加强矿区的安全建设提供一定的技术依据,避免了各种装置及设备的损失,对提高提煤矿的经济效益具有重要意义。