Research on Instantaneous Angular Speed Signal Separation Method for Planetary Gear Fault Diagnosis

Planetary gear train is a critical transmission component in large equipment such as helicopters and wind turbines. Conducting damage perception of planetary gear trains is of great significance for the safe operation of equipment. Existing methods for damage perception of planetary gear trains mainly rely on linear vibration analysis. However, these methods based on linear vibration signal analysis face challenges such as rich vibration sources, complex signal coupling and modulation mechanisms, significant influence of transmission paths, and difficulties in separating damage information. This paper proposes a method for separating instantaneous angular speed (IAS) signals for planetary gear fault diagnosis. Firstly, this method obtains encoder pulse signals through a built-in encoder. Based on this, it calculates the IAS signals using the Hilbert transform, and obtains the time-domain synchronous average signal of the IAS of the planetary gear through time-domain synchronous averaging technology, thus realizing the fault diagnosis of the planetary gear train. Experimental results validate the effectiveness of the calculated IAS signals, demonstrating that the time-domain synchronous averaging technology can highlight impact characteristics, effectively separate and extract fault impacts, greatly reduce the testing cost of experiments, and provide an effective tool for the fault diagnosis of planetary gear trains.

Shafting misalignment fault diagnosis by means of motor speed signal and SVD-HT method

Aiming at the deficiency of diagnosis method based on vibration signal,a novel method based on speed signal with singular value decomposition and Hilbert transform(SVD-HT)is proposed.The fault diagnosis mechanism based on the speed signal is obtained by constructing the shaft misalignment fault model firstly.Then the SVD-HT method is applied to the processing of the speed signal.The accuracy of the SVD-HT method is verified by comparing the diagnosis results of the order spectrum method and the SVD-HT method.After that,the diagnosis results based on vibration signal and speed signal under no-load and load patterns are compared.Under the no-load pattern,the amplitudes of the speed signal components f_(r),2f_(r) and 4f_(r) are linear with the misalignment.In addition,under the load pattern,the amplitudes of the speed signal components f_(r),2f_(r) and 4f_(r) have a linear relationship with the load.However,the diagnosis result of the vibration signal does not have the above characteristics.The comparison results verify the robustness and reliability of the speed signal and SVD-HT method.The method presented in this paper provides a novel way for misalignment fault diagnosis.

Research on Feature Extraction Method for Low-Speed Reciprocating Bearings Based on Segmented Short Signal Modulation Signal Bispectrum Slicing

Bearing condition monitoring and fault diagnosis (CMFD) can investigate bearing faults in the early stages, preventing the subsequent impacts of machine bearing failures effectively. CMFD for low-speed, non-continuous operation bearings, such as yaw bearings and pitch bearings in wind turbines, and rotating support bearings in space launch towers, presents more challenges compared to continuous rolling bearings. Firstly, these bearings have very slow speeds, resulting in weak collected fault signals that are heavily masked by severe noise interference. Secondly, their limited rotational angles during operation lead to a restricted number of fault signals. Lastly, the interference from deceleration and direction-changing impact signals significantly affects fault impact signals. To address these challenges, this paper proposes a method for extracting fault features in low-speed reciprocating bearings based on short signal segmentation and modulation signal bispectrum (MSB) slicing. This method initially separates short signals corresponding to individual cycles from the vibration signals based on encoder signals. Subsequently, MSB analysis is performed on each short signal to generate MSB carrier-slice spectra. The optimal carrier frequency and its corresponding modulation signal slice spectrum are determined based on the carrier-slice spectra. Finally, the MSB modulation signal slice spectra of the short signal set are averaged to obtain the overall average feature of the sliced spectra.

Research on Multi-System Ultra-High Speed Optical Signal Access System

In view of the small transmission capacity and single signal modulation format of the existing optical transmission system, this paper proposes an ultra-high-speed optical signal access scheme based on NEL0670, which can realize the transmission of 100 G DP-QPSK, 200 G DP-16QAM and 400 G DP-16QAM signals, and realize flexible and intelligent reception of multi-system optical signals.

A Recursive Method of Time-Frequency Analysis for the Signal Processing of Flutter Test with Progression Variable Speed

Focused on the non-statlonarity and real-time analysis of signal in flutter test with progression variable speed （FTPVS）, a new method of recursive time-frequency analysis is presented. The time-varying system is tracked on-line by building a time-varying parameter model, and then the relevant parameter spectrum can be obtained. The feasibility and advantages of the method are examined by digital simulation. The results of FTPVS at low-speed wind-tunnel promise the engineering application perspective of the method.

Model of Traffic Speed-Flow Relationship at Signal Intersections

Speed-flow relationship is the fundamental for the traffic simulation and traffic volume forecast. Traditional quadratic polynomial model can’t reflect the saturate flow at signal intersections. In order to determine the speed-flow relationship at signal intersections, the speed and time-headway of vehicles at two signal intersections were investigated and the accuracy of software used to get the speed was tested. After vehicle starting-up from queuing, the time-headway reduces gradually with the increase of speed. The relationship of power exponential function between speed and time-headway is formulated. Traffic volume can be calculated by the vehicle time-headway. Then the speed-flow relationship was developed and an S-shaped curve model was built in this paper. In the S-shaped curve model, traffic flow approaches to the saturate when the speed doesn’t increase. Thus, S-shaped curve model is better to describe the speed-flow relationship at signal intersection. The results can provide a reference to determine the parameters in traffic simulation and for the study of level of service of intersections.

基于ZigBee通信网络的农机作业监测系统设计

首先,介绍了ZigBee通信网络技术,并设计了系统总体设计方案;然后,分别从转速测量模块、振动信号采集模块和割台高度检测设计了系统硬件部分;最后,针对设备节点和协调器两部分设计了ZigBee无线网络传输软件,实现了农机作业监测系统。测试结果表明:系统能够正确采集农机作业参数并通过无线网络发送到云平台,证明系统的可靠性和可行性。

基于车速引导和感应控制的干线协调优化方法

干线信号协调通常基于固定带速和时段性统计流量,但实际运行中,车辆的行驶车速和交通流量往往呈波动变化,导致信号方案与实际最优带速和交通流需求不相匹配,影响交叉口的通行效率。基于车路协同环境,运用Maxband模型,以绿波带宽最大、干线车辆延误、干线停车次数与次路方向延误最小为优化目标,建立了干线信号协调多目标优化模型,并采用改进的多目标粒子群算法对模型求解,获得协调路口全局控制方案参数;根据交叉口进口道车辆位置和信号状态提出了车速引导模型;根据干线交叉口进口道的车辆饱和度情况,应用感应控制策略在全局协调的基础上对各路口绿灯时间进行实时调整。仿真结果表明:优化模型将车速引导和信号协调相结合,考虑主线路口负荷度情况,动态调整绿灯时间,降低了交叉口处的延误和停车次数,有效提升了干线协调控制效率。

裂纹对弹性波在混凝土中传播特性的影响研究

目的为研究混凝土中裂纹对弹性波传播特性的影响,方法采用COMSOL软件构建弹性波在不同形态混凝土裂纹中的传播数值模型,并开展带裂纹混凝土的弹性波传播试验,系统研究混凝土裂纹特征(裂纹角度、裂纹深度、裂纹距声发射源距离、裂纹数量等)与弹性波传播之间的关系。结果研究发现:数值模拟结果与试验现象吻合较好,验证了数值模型的可靠性。其中,裂纹数量和裂纹距声发射源距离的变化对回波峰值影响较大,距声发射源2 cm裂纹的回波峰值最大,为3.46×10^(6)Pa;对波速和信号损伤影响最大的因素为裂纹深度,60 mm深度裂纹损伤率高达62.14%、波速衰减至2590.674 m/s,其次为裂纹数量,信号损伤率达31.28%。基于不同裂纹特征的波速变化规律,对裂纹角度和深度的波速关系模型进行回归分析,回归曲线拟合优度较好,R^(2)均大于0.95。结论混凝土中存在的裂纹和裂纹特征对弹性波传播具有显著影响,本文研究结果为混凝土无损检测技术提供了理论支撑。

战斗部破片光电测速系统设计

战斗部破片的飞行速度是体现其性能指标的重要参数;针对目前在战斗部破片速度参数测试中存在对测试环境要求高,测试面积小,设备结构易被破片误击而损坏,成本昂贵等问题,设计了非接触式战斗部破片光电测速系统,包含原向反射膜、反射式光电探测装置、光电转换电路、信号处理电路及测速装置;阐述了系统结构组成和测速原理,通过反射式光电探测装置与光电转换电路,将得到的光信号转换为电信号,利用集成信号处理电路对电信号滤波放大,比较整形处理,由FPGA,STM32及其他外设组成的测速装置自动处理数据输出并显示战斗部破片的飞行速度结果;实验结果表明:该系统能够可靠,稳定地完成战斗部破片速度的测量任务;与传统测速系统相比,具有不受限于环境,测试区域大,易维护,低成本,操作简单等优势。

高速低载频比传感信号下的逆变器有源阻尼自适应控制

逆变器工作在高频运行和控制载波比低的情况下,存在谐振尖峰抑制,提出了高速低载频比传感信号下的逆变器有源阻尼自适应控制技术。在高速低载频比传感信号下,构建逆变器数学模型。输出电流到电容电压与定子电流之间的传递函数,将逆变器的有源阻尼等效成一个控制电压环。调整有源阻尼自适应控制回路的参数,制定逆变器有源阻尼自适应控制策略。实验结果表明:文中技术的稳定裕度由2.46 dB下降至1.18 dB,可以保证逆变器的稳定运行;在不同采样频率下,可以控制逆变器输出与电网电压相同相位和频率的并网电流,其中在采样频率为5.9f时,输出并网电流和电压均表现为正弦状态,波动范围分别为[35 A,58 A]和[185 V,225 V],具有较好的控制效果。

零速信号在机车电气控制中的应用

随着机车电气控制技术的不断发展,零速信号在机车电气控制中扮演着重要的角色,零速信号是指机车制动或牵引系统中用来检测车辆是否处于零速状态的信号,它能够帮助系统实时监测车辆的运行状态,从而实现精确的控制和调节,文章探讨了零速信号在机车电气控制中的应用,希望能够为机车电气的控制发展提供借鉴。

基于脑电信号特征的高铁调度员疲劳状态识别

为增强铁路行车的稳定性与安全性,有效识别调度员的疲劳状态对行车组织的影响,基于脑电(EEG)信号特征,提出一种调度员疲劳状态识别方法,根据作业时间段划分调度员的疲劳状态,设计高铁调度模拟试验获取脑电信号数据,通过小波级数展开和傅里叶变换提取高铁调度被试的3种脑电波频域幅值作为特征值,结合调度员作业特征和脑电信号特征,验证疲劳状态的划分结果,通过Python语言环境搭建ResNet18+SoftMax和MobileNet V2+SoftMax这2种模型,基于深度学习方法,将输入特征转换为三维立体矩形模型,并优化调整权重,获得最优模型,从而判断高铁调度员的疲劳状态。研究结果表明:ResNet18+SoftMax和MobileNet V2+SoftMax神经网络模型对高铁调度试验参与人员的疲劳状态识别准确率分别为92.78%和99.17%;相较于支持向量机(SVM)模型,这2种模型可提升清醒状态和疲劳状态的识别精度,并降低运算时间,其中,MobileNet V2+SoftMax模型的识别准确率和运行速度最优。以MobileNet V2+SoftMax模型原理为内核,可以更快速准确地识别高铁调度员在长时间作业条件下的潜在疲劳风险。

基于多传感数据融合的变速运行齿轮异常振动故障诊断

变速运行齿轮异常振动故障诊断性能过差会增加汽车维护成本,缩短齿轮使用寿命。为了及时识别齿轮故障,保证汽车变速器总成具有良好的振动特性,提出基于多传感数据融合的变速运行齿轮异常振动故障诊断方法。通过分析多传感器数据融合技术,掌握变速运行齿轮异常振动故障诊断的理论框架,并以此为基础,参考传感器融合模块、特征级并行多神经网络局部诊断模块和终端分类模块,结合变分模态分解、多通道加权融合和单隐层前馈神经网络训练算法,从信号采集、信号特征提取和信号特征分类3个步骤实现变速运行齿轮异常振动故障诊断。实验结果表明:在齿轮发生轻度磨损时,磨损振动信号的幅值在20~40 mV之间,磨损振动信号的频率在0~4000 Hz区间;中度磨损时,信号的幅值在30~55 mV之间,信号频率在3000~7000 Hz区间;重度磨损时,信号幅值在50~70 mV之间,信号频率在6000~12000 Hz区间,且各阶段诊断结果均与故障程度的实际转折点吻合。由此可知在各样本数量均相同的情况下,提出的故障诊断方法预测值与真实值均相同,故障程度和故障类型的诊断性能均较好。

基于MEEMD算法的二冲程柴油发动机机体振动分析

二冲程低速柴油机具有复杂的振动特性,传统的经验模态分解(Empirical Mode Decomposition,EMD)算法对其振动信号处理效果不理想。为此,采用修正多元集合经验模态分解(Modified Ensemble Empirical Mode Decomposition,MEEMD)算法对低速柴油机机体振动信号进行分解。首先,采用三轴加速度计测量发动机机体振动。然后利用均方根(Root Mean Square,RMS)对三轴振动强度进行分析。最后,对x轴上的信号进行MEEMD分析。结果表明:砌块在x轴方向的振动强度最大;与EMD算法相比,MEEMD算法可以抑制模态混合,有助于更好地识别块振动激励。

基于规则的信号交叉口纯电动公交节能驾驶策略

为解决纯电动公交在通过信号交叉口时能耗较大的问题,本文提出一种旨在最小化电量消耗的基于规则的两阶段驾驶策略,能够实现通行策略场景的合理划分选择及充分优化加减速调整曲线凹凸性,同时,不牺牲乘客舒适度和通行时间。在策略第1阶段,结合车辆运行状态和通过车路协同技术获取的交叉口信号相位和时序信息,提出4种交叉口通行策略的划分与判断选择方式,包括匀速通过策略、加速通过策略、减速通过策略和制动停车策略;在策略第2阶段,利用基于XGBoost算法的能耗估算模型和基于加减速特征参数的曲线模型,优化策略场景中匀速过程、加速过程和减速过程的速度曲线;最后,结合VISSIM仿真验证4种通行策略的有效性。结果表明,所提出的策略可以有效减少电量消耗,在4种驾驶场景下,降低了29.8%~34.2%的能耗。此外,分析发现,在经济车速以上和以下的最佳速度节能曲线均为凹凸形曲线,因此,通过对比实验进行不同速度调整范围的最节能曲线凹凸性规律总结,该结论可以为纯电动公交车的节能驾驶提供更易于操作的驾驶引导。

基于振动信号和同步压缩小波变换的电动机测速方法及实验分析

针对部分工业现场电动机无法安装测速传感器,提出一种基于振动信号和同步压缩小波变换的电动机测速方法。对电动机振动信号进行Hilbert变换得到包络信号,解调出其中与转速相关的振动分量;利用同步压缩小波变换分析计算出包络信号的时频图;引入脊线的四分位距和方差对代价函数法进行改进,并利用该方法提取基频振动分量的时频脊线,得到电动机的转速曲线,达到无转速计测速的目的。实验与仿真分析表明,所提方法无论在稳态还是在非稳态工况下都能准确检测出电动机转速,且误差不超过5%。该方法的研究与实践过程可加深学生对调制解调、时频分析等理论知识的理解,提高理论联系实际的能力。

脉冲信号的奇异性分布熵特征分析

为了对低信噪比复杂环境下脉冲信号的奇异性差异进行有效的分析和标定,提出了一种基于模极大值理论的奇异性分布熵特征分析模型。首先对脉冲信号进行归一化并进行小波变换,计算各尺度下模极大值及其特定分布,可以体现具有奇异性差异的模极大值曲线族。为定量描述这种差异性,用熵值表达构成模极大值曲线族的模极大值点分布,并构建能有效分析脉冲信号奇异性差异的奇异性分布熵特征模型。该模型能对低噪比下信号的奇异性差异进行刻画。实验结果表明,在信噪比为-6 dB的环境下对典型的直升机脉冲信号(桨/涡干扰信号和高速脉冲信号)进行分析,能够得到89.25%和87.63%的正确率。

高速精确的光纤光栅信号解调方案设计

为提升光纤光栅的应用效果,为此,设计高速精确的光纤光栅信号解调方案。依据LPFG的光纤光栅信号解调原理,设计两个LPFG双边缘滤波器处理两路反射光,并且利用光电探测器探测光功率结果,以此解调光栅的中心波长;采用光纤干涉仪检测解调频率,对其进行正反扫描,依据光传播时延引起的解调误差和解调频率扫描方向之间的关联,完成解调结果补偿。测试结果显示:该方案具有较好可行性,光谱发生不同程度重叠时,光纤光栅信号的解调结果标准差均小于1.85 pm;光栅波长的解调误差均在-5~5 pm之间;有效降低解调误差,提升光纤光栅解调精度,可靠获取信号中的信息。

基于CALIOP双波长数据的海面测风信号筛选方法研究

基于海面后向散射模型,提出了一种利用CALIOP双波长海面信号进行数据质量控制的星载激光雷达数据筛选方法。选取CALIOP 2018年1―9月Version 4.1.0 level 1数据进行全球海面风速反演,为提高数据可利用率,在无云海域探测海面风速的条件下增加了可穿透云CALIOP数据,经过大气校正和双波长信号质量控制后进行风速反演,以准同步AMSR-2风速数据作为参考值进行检验。分别采用Cox-Munk和Hu模型的经验关系反演风速,对于1―3月数据,前者标准偏差分别为1.14、1.18、1.16 m/s,相关系数分别为0.90、0.91、0.91;后者标准偏差分别为1.17、1.19、1.17 m/s,相关系数分别为0.91、0.91、0.91。而相较于无云海域的反演研究,可利用数据量提高约45.5%,表明利用该方法既能保证反演精度同时又能有效提高数据可利用率,可为海面风场研究提供更多的数据源。