A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

With the development of multi-signal monitoring technology,the research on multiple signal analysis and processing has become a hot subject.Mechanical equipment often works under variable working conditions,and the acquired vibration signals are often non-stationary and nonlinear,which are difficult to be processed by traditional analysis methods.In order to solve the noise reduction problem of multiple signals under variable speed,a COT-DCS method combining the Computed Order Tracking(COT)based on Chirplet Path Pursuit(CPP)and Distributed Compressed Sensing(DCS)is proposed.Firstly,the instantaneous frequency(IF)is extracted by CPP,and the speed is obtained by fitting.Then,the speed is used for equal angle sampling of time-domain signals,and angle-domain signals are obtained by COT without a tachometer to eliminate the nonstationarity,and the angledomain signals are compressed and reconstructed by DCS to achieve noise reduction of multiple signals.The accuracy of the CPP method is verified by simulated,experimental signals and compared with some existing IF extraction methods.The COT method also shows good signal stabilization ability through simulation and experiment.Finally,combined with the comparative test of the other two algorithms and four noise reduction effect indicators,the COT-DCS based on the CPP method combines the advantages of the two algorithms and has better noise reduction effect and stability.It is shown that this method is an effective multi-signal noise reduction method.

Gabor Order Tracking Filtering Technology in Rotary Machinery

Order analysis is one of the most important technique means of condition monitoring and fault diagnosis for rotary machinery.The traditional order analyses usually employ the Vold-Kalman filtering,however this method is confined to the expensive hardware equipments.This paper starts from Gabor transform and applies the Gabor time-frequency filtering to vibration signal.The order component's time-frequency coefficients are extracted by mask operation.The order component is reconstructed from the obtained coefficients.The following four key technologies,such as smoothing rotary speed curve,defining filtering band width,constructing the mask operation matrix and reconstructing signal component,are also deeply discussed.Moreover,the technique to smooth the rotary speed curve based on polynomial approximation,the method to determine filtering band width,the arithmetic to constitute mask array and the iterative algorithm to reconstruct signal based on minimum mean square error are specifically analyzed.The 4th order component is successfully gained by using the methods that Gabor time-frequency filter,and the validity and feasibility of this method are approved.This method can solve the problem of order tracking filter technologies which used to depend on hardware and efficiently improve the accuracy of order analysis.

Considerations for Application of SOBI to Order Tracking

Current methods of order tracking, such as synchronous resampling, Gabor filtering, and Vold-Kalman filtering have undesirable traits. Each method has two or more of the following deficiencies: requires measurement or estimate of rotational speed over time, failure to isolate the contribution of crossing orders in the vicinity of the crossing time, large computational expense, end effects. In this work a new approach to the order tracking problem is taken. The Second Order Blind Identification (SOBI) algorithm is applied to synthesized data. The technique is shown to be very successful at isolating crossing orders and circumvents all of the above deficiencies. The method has its own restric-tions: multiple sensors are required and sensors must be mounted on a structure that responds quasi-statically to exci-tation of the rotational system.

Tracking of a third-order maneuvering target under an arbitrary topology

We explore the tracking problem of a maneuvering target. Tracking agents with third-order kinematics can communicate with each other via wireless network. The communication network topology is arbitrary rather than switches among several fixed topologies. The information sharing and interaction among agents are position, velocity, and acceleration. Some sufficient conditions of tracking strategy have been proposed. Finally, a numerical example is employed to demonstrate the effectiveness of proposed tracking strategy.

Distributed event-triggered consensus tracking of second-order multi-agent systems with a virtual leader

This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which is intermittently examined at constant sampling instants. Only partial neighbor information and local measurements are required for event detection. Then the corresponding event-triggered consensus tracking protocol is presented to guarantee second-order multi-agent systems to achieve consensus tracking. Numerical simulations are given to illustrate the effectiveness of the proposed strategy.

Bounded consensus tracking of second-order multi-agent systems with sampling delay under directed networks

The bounded consensus tracking problems of second-order multi-agent systems under directed networks with sampling delay are addressed in this paper.When the sampling delay is more than a sampling period,new protocols based on sampled-data control are proposed so that each agent can track the time-varying reference state of the virtual leader.By using the delay decomposition approach,the augmented matrix method,and the frequency domain analysis,necessary and sufficient conditions are obtained,which guarantee that the bounded consensus tracking is realized.Furthermore,some numerical simulations are presented to demonstrate the effectiveness of the theoretical results.

装配式建筑PC构件产销一体化管理系统研究

混凝土预制(Precast Concrete,PC)构件是装配式建筑主体结构的基础,提升其生产的智能化、信息化水平尤为关键。文章以PC构件厂的生产管理模式和普遍管理现状为研究对象,基于PC构件生产线模式的需求分析,设计管理系统的基本组成架构、静态和动态信息模块,完成管理系统的开发。通过订单跟踪和生产管理在管理系统中的集成,完成PC构件的多品种、小批量生产的一体化管理;并基于数字孪生模型与PC构件生产设备之间的信息交互,实现订单跟踪的可视化管理。结果表明:管理系统通过对PC构件的订单跟踪和质量管理,可实现订单数据的全面分析和精细化管理,并有效提升生产效率和决策管理水平。

无转速阶次跟踪的滚动轴承故障诊断方法

机械装备轴承运行速度多变导致振动监测信号频谱模糊,一定程度影响了轴承故障诊断的准确性.目前的无转速阶次跟踪技术在转速波动较小且转频谐波不重叠时效果较好,但当轴承转频谐波重叠时则难以进行分析.针对以上问题,提出了一种基于广义解调的无转速阶次跟踪轴承故障诊断方法.首先,采用广义傅里叶变换和改进的基于成本函数脊线提取技术准确提取出轴承的转频谐波分量;同时,采用快速谱峭度算法和带通滤波器对轴承振动信号进行去噪处理;然后,通过角度重采样将去噪后的时域信号转换为角域信号;最后,通过包络谱分析得到轴承的阶次谱信息,从而识别轴承的故障类型.研究结果表明:通过数值模拟信号和实际轴承监测信号验证了提出方法的有效性,通过与传统包络谱方法对比可知,提出的方法可进行无转速信息时的滚动轴承阶次跟踪故障诊断.

基于分数阶滑模控制的无人机轨迹跟踪控制器设计

四旋翼无人机在农业、工业和国防等领域广泛应用,但其复杂的系统特性和对扰动的敏感性使得控制变得困难。首先,考虑分数阶方法具有良好的鲁棒性以及调节灵活性的优点,将整数阶积分滑模面和改进的分数阶指数趋近律相结合,设计出了一种新的分数阶积分滑模控制器。然后,将所设计的分数阶积分滑模控制器应用于四旋翼无人机轨迹跟踪控制问题。仿真结果表明,所提控制器作用下的四旋翼无人机进行轨迹跟踪时响应速度快、无超调,且对外界干扰具有较强的鲁棒性。

北斗三号仅用作追踪的机载设备适航要求分析

随着北斗三号卫星导航系统服务正式开通,北斗二号相关适航标准已无法满足当前机载设备应用场景需求,严重制约了北斗在民航领域的应用进程,急需开展北斗三号相应标准的研究与制定。针对北斗在民用航空器中应用第1阶段“仅用作航空器追踪”,对北斗二号与北斗三号开展差异性分析,提出标准修订总体方案,综合考虑适航安全性、机载设备应用场景,结合工业实践,根据设备构型提出指标修订方案,形成审定要素及符合性方法建议,为设备研发与适航取证提供标准支持。仿真分析了设备天线增益、卫星可见性等关键参数,验证了所修订技术指标的正确性。

基于EOE_LMD和阶次跟踪分析的变转速轴承故障诊断

振动信号分析是轴承故障诊断中的重要技术手段之一。变转速工况下的滚动轴承振动信号是典型的非平稳信号,并且在转频变化较小的工况中还存在噪声干扰的问题,使传统的时频分析技术难以应用。为解决该问题,提出了一种基于经验最优包络(empirical optimal envelope,EOE)的局部均值分解(local mean decomposition,LMD)和采用分段线性插值的计算阶次跟踪(computing order tracking,COT)算法相结合的故障诊断方法。首先,确定低通滤波器的截止频率和滤波阶数,对滚动轴承振动信号进行滤波,并对滤波后的包络信号进行COT,以获得角域平稳信号。然后,利用EOE_LMD对重采样后的平稳信号进行处理,得到若干乘积函数(product function,PF)分量。最后,通过计算各分量的信息熵和相关系数,选取合适的分量进行阶次分析,以判断变转速滚动轴承的故障类型。结果表明,该方法可以消除转速波动对故障特征提取的影响,在不同转速变化条件下对滚动轴承具有良好的故障诊断能力。

煤矿装备瞬态非平稳工况下故障特征提取研究

煤矿机械设备高转速、强冲击的瞬态非平稳工况,导致轴承故障特征难以提取。针对上述问题,结合回归滤波器与阶次跟踪,提出一种基于阶次跟踪的轴承故障特征提取方法。首先对轴承的非平稳信号进行基于短时线性调频小波变换的时频分析方法估计谐波的瞬时频率,然后通过回归滤波器自适应跟踪提取瞬态变化谐波分量以估计出瞬时相位,指导信号进行角度域重采样,最后进行阶次谱分析。实验结果表明:所提方法能够以较小的误差准确地表示出相应故障特征阶次,即能够准确提取出煤矿机械轴承的故障特征。

基于二阶注意力的Siamese网络视觉跟踪算法

为提升基于Siamese网络视觉跟踪算法的特征表达能力和判别能力,以获得更好的跟踪性能,提出了一种轻量级的基于二阶注意力的Siamese网络视觉跟踪算法。使用轻量级VGG-Net作为Siamese网络的主干,获取目标的深度特征;在Siamese网络的末端并行使用所提残差二阶池化网络和二阶空间注意力网络,获取具有通道相关性的二阶注意力特征和具有空间相关性的二阶注意力特征;使用残差二阶通道注意力特征和二阶空间注意力特征,通过双分支响应策略实现视觉跟踪。利用GOT-10k数据集对所提算法进行端到端的训练,并在OTB100和VOT2018数据集上进行验证。实验结果表明:所提算法的跟踪性能取得了显著提升,与基准算法SiamFC相比,在OTB100数据集上,精度和成功率分别提高了0.100和0.096,在VOT2018数据集上,预期平均重叠率(EAO)提高了0.077,跟踪速度达到了48帧/s。

基于高阶递归神经网络的AUV鲁棒控制方法

目的 提出一种基于高阶递归神经网络的AUV鲁棒控制方法。方法 利用结构简单但逼近效果优越的高阶递归神经网络,对建模不确定性和外部未知干扰进行估计,并将其补偿到输入控制律中,以提高控制性能。之后,基于HJI理论和Lyapunov稳定性分析导出神经网络权重自适应更新律和AUV自适应控制律,设计反步滑模方法作为对比方法,并进行仿真实验。结果 设计的基于高阶递归神经网络的AUV鲁棒控制方法的跟踪误差、调节时间等控制指标均优于反步滑模方法。设计的鲁棒控制方法可以控制AUV精确跟踪目标轨迹,同时具有优秀的控制性能和鲁棒性。结论 这一研究为AUV轨迹跟踪控制领域提供了一种高效且有效的方法,有望在复杂、不确定的水下环境中得到应用。

压缩机用直线振荡电机频率跟踪控制

作为一种新型压缩机,直线压缩机具有效率高、体积小、噪声和震动小的优势,但要发挥其效率高的优点,需对驱动频率进行控制,以跟踪其机械谐振频率。针对该特性,提出了一种基于二阶广义积分器(SOGI)和双相关相位检测算法的直线振荡电机频率跟踪控制算法。该控制算法与基于位移电流积平均值(ASCP)的频率跟踪控制算法相比,具有动态响应快、变工况下运行稳定的优点,且增强了对外界干扰的抑制效果,提高了控制系统的稳定性。仿真和实验表明,所提出的控制算法可以快速跟踪电机固有频率,验证了理论的合理性和有效性。

联合高阶目标感知与相似匹配的目标跟踪算法

视觉目标跟踪算法利用自注意力机制增强上下文联系,但面对复杂场景时,自注意力机制中的相关性易发生失配,为此提出一种联合高阶目标感知与相似匹配的目标跟踪算法。构建高阶目标感知模型,针对自注意力机制中的一阶自注意图,利用坍塌的极化过滤方式进行空间和通道维度的正交化建模,优化内部相关性;同时组合非线性拟合函数避免坍塌引起的信息损失,进而获得高阶自注意图,捕获具有高阶上下文信息的感知特征。通过不同维度分解目标的感知特征来细化匹配区域,抑制背景噪声并约束当前帧的响应图,提高网络的判别力。在OTB100和UAV123基准的实验结果表明,所提算法有更好的跟踪性能,可以有效应对相似干扰等问题。

基于分数阶S面模型的四旋翼轨迹跟踪控制

四旋翼无人机具有欠驱动、非线性、强耦合的特点。针对四旋翼无人机轨迹跟踪控制中跟踪精度低,抗外界干扰能力弱的特点,通过对四旋翼无人机进行四元数建模,使用误差四元数作为控制器输入,消除了无人机在机动角度过大时的奇点问题,提出了一种分数阶S面的控制方法,即将分数阶PID控制与S面控制融合,作为一个新的控制器。轨迹跟踪试验表明,分数阶S面控制器在四旋翼无人机控制模型中的累计误差明显小于分数阶PID,证明了该方法具有抗风扰能力强、跟踪精度高的特点。

光伏跟踪电机的分数阶自抗扰控制方法

针对光伏跟踪系统运行时负载端产生高频振荡以及在运行过程中遇到的极端天气等不可控因素导致的系统失调、鲁棒性降低等问题,根据光伏跟踪系统中负载反馈模型实现速度控制,设计了一种改进型分数阶自抗扰控制器。该控制器采用函数优化后的分数阶跟踪微分器和线性组合的分数阶扩张状态观测器来抑制高频振荡,加快负载端速度响应并提高系统抗干扰能力。实验结果表明,改进后的分数阶自抗扰控制器使得抑制了负载端39.60%的高频振荡,系统稳态时间缩短了20.83%,转速波动减少了36.97%,有效改善了系统控制性能,提高了系统鲁棒性。

上海市产业园区“三线一单”和规划环评跟踪评估

产业园区既是产业高质量发展的承载区,也是环境污染治理和风险防范的重点区域,落实“三线一单”和规划环评的生态环境管控是产业园区提高环境综合管理水平的重要抓手。连续5年的跟踪评估试点显示,上海市产业园区生态环境分区管控和规划环评效力不断提升,约90%的入园项目可以简化环评手续,营商环境优化明显,有力助推市域产业的高质量发展。跟踪评估试点工作具有显著的借鉴意义,值得全国推广。