Expert System for the Design of Single Speed Gear Boxes

Based on the characteristic peculiarities of mechanical design expert systems (MDES), the design process pf gear box and its components is introduced and the gear box design expert systems (GBES)is established. GBES employs the methods of knowledge representation to indicate the knowledge-unit-rule-process, table-vector-process. By taking the advantage of knowledge unit's indicator, it can make the units of knowledge base to to combine to form a whole in the feature of trees and nets so that it can give deduction conveniently. The knowledge base of GBES is organized in hierarchy, which provides the efficient managerial systems of knowledge base. It makes the knowledge base convenient greatly for establishing and using. The assistant modules of GBES are written in FORTRAN and the part of expert systems is written in LISP. It explains the I/O among each module and the forms of independent application. The GBES systems have been put into preliminary, use in practice.

DYNAMIC RESPONSE OF ROLLER GEAR INDEXING CAM SYSTEM CONSIDERING CLEARANCE AND MOTOR CHARACTERISTIC

The dynamic responses of roller gear indexing cam mechanism are investigated .With applying Lagarange equation and Gear method,motion equations of this mechanism including clearance,motor characteristic,torsion flexibility are developed and solved.The results show that clearance affects primarily the response on turret,and has little effects on the responses on rotary table.At the same time,the velocity fluctuation of motor shaft is not serious for the existence of inertia of reducer,and the high frequency of velocity fluctuation of camshaft is related with the torsion stiffness of shaft and the clearance between pairs.

Performances of a Balanced Hydraulic Motor with Planetary Gear Train

The current research of a balanced hydraulic motor focuses on the characteristics of the motor with three planet gears.References of a balanced hydraulic motor with more than three planet gears are hardly found.In order to study the characteristics of a balanced hydraulic motor with planetary gear train that includes more than three planet gears,on the basis of analysis of the structure and working principle of a balanced hydraulic motor with planetary gear train,formulas are deduced for calculating the hydraulic motor＇s primary performance indexes such as displacement,unit volume displacement,flowrate fluctuation ratio,etc.Influences of the gears＇ tooth number on displacement and flowrate characteristics are analyzed.In order to guarantee the reliability of sealing capability,the necessary conditions that tooth number of the sun gear and the planet gears should satisfy are discussed.Selecting large unit volume displacement and small displacement fluctuation ratio as designing objectives,a balanced hydraulic motor with three planet gears and a common gear motor are designed under the conditions of same displacement,tooth addendum coefficien and clearance coefficient.By comparing the unit volume displacement and fluctuation ratio of the two motors,it can be seen that the balanced hydraulic motor with planetary gear train has the advantages of smaller fluctuation ratio and larger unit volume displacement.The results provide theoretical basis for choosing gear tooth-number of this kind of hydraulic motor.

Study on Rolling Mill Gear Box and Design of Multichannel Fault Diagnosis

Gear box places an important role rolling mill.Its reliability decides the machine operation.Due to the important role,if the key machine is broken because of gear box′s malfunction,the whole production devices will be influeued.Therefore,it′s very important to monitor the gear box online.Good monitoring system can help companies to better process fault diagnosis.The design sets up a monitoring system with Enwatch polled mode on-line acquisition module and Odyssey software.By calculating the data,the problem of the monitoring system is find,the plans to collect signal is made,the problems of monitoring gear box′s multichannel vibration are solved and the malfunctions initially are estimated according to the signal,which has theoretical basis and practical meanings.

Gearbox Scheme in High Temperature Reactor Helium Gas Turbine System

Helium Turbine is used in High Temperature Reactor Helium Gas Turbine (HTR-GT) system, by which the direct helium circulation between the reactor and turbine generator system will come true. Between helium turbine and generator, there is gearbox device which reduces the turbine rotation speed to normal speed required by the generator. Three optional gearbox schemes are discussed. The first is single reduction cylindrical gearbox, which consists of one high speed gear and one low speed gear. Its advantage is simple structure, easy to manufacture, and high reliability, while its disadvantage is large volume and misalignment of input and output axle. The second is planetary gear mechanism with static planet carrier. The third is planetary gear mechanism with static internal gear. The latter two gearbox devices have similar structure. Their advantage is small volume and high reduction gear ratio, while disadvantage are complicated structure, many gears, low reliability and low mechanical efficiency.

Wavelets applied to early fault analysis of hoist gear box

Using wavelets, the vibration signal of a certain mine hoist gear box was analyzed. By multiple comparison analysis, the rational wavelet basis function was determined. Fault characteristic frequencies of hoist gear box were identified. The research indicates that the hoist＇s fault information is non-stationary, and non-stationary signal is clearly extracted by using db20 wavelet as basis function. The db20 wavelet is the proper wavelet base for vibration signal analysis of the hoist gear box.

基于格拉姆角场与深度卷积生成对抗网络的行星齿轮箱故障诊断

针对行星齿轮箱故障诊断中样本分布不均衡所引起的模型泛化能力差及诊断精度低等问题,采用格拉姆角场图像编码技术和深度卷积生成对抗网络相结合进行数据增强,融合AlexNet卷积神经网络进行故障诊断。将采集到的一维振动信号转化为格拉姆角场图,按比例划分训练集与测试集,将训练集样本与随机向量输入到深度卷积生成对抗网络模型中,交替训练生成器与判别器,达到纳什平衡,生成与原始样本类似的生成样本,从而实现故障样本的增广。用原始样本与生成的增广样本训练卷积神经网络分类模型,完成行星齿轮箱的故障识别。实验结果表明,所提方法能够有效提升样本不均衡条件下的行星齿轮箱故障诊断精度,使之达到99.15%,且能使收敛速度更快。

GEAR BOX CONCEPT DESIGN EXPERT SYSTEM OF NC MILLER BASED ON OBJECT─ORIENTED TECHNOLOGY

The method and basic structure of object─oriented knowledge representation are presented in detail and the hierarchical structurc of object description is explained Based on object─oriented technology.the gear box concept design expert cistem of NC miller (GBCDLS) has been developed and applied to practical use.Moreover. the design principlc and techniques of GBCDES are discussed and analyzed. and the main functions of GBCDES are described. From the results of applications.it can be seen that GBCDES is effective and successful.

基于MTF-Swin Transformer的风机齿轮箱故障诊断

针对风机齿轮箱实际工况复杂多变及含有强噪声,传统故障诊断方法对风机齿轮箱故障诊断识别准确率较低的问题,文章提出了MTF-Swin Transformer风机齿轮箱故障诊断模型。首先,采用马尔科夫变迁场(MTF)图形编码方法将原始一维振动时序信号转化为具有关联时间信息的二维特征图谱;然后,将特征图谱作为Swin Transformer模型的输入,基于自注意力机制进行自动特征提取;最后,实现对不同故障类型的分类。仿真结果表明,该方法对齿轮箱故障诊断准确率达到了99.48%,证明了该方法的有效性和优越性。

泵/马达困油现象充分缓解的等排量大模数方法

为了充分缓解外啮合齿轮泵/马达困油现象,在确保产品输出能力不变的等排量前提下,分析模数对困油腔内的负荷流量、泄漏流量和卸荷流量的影响,提出了一种等排量大模数的设计方法,并基于这3种流量的瞬时平衡和同齿形参数、不同模数下卸荷面积的演绎计算,计算出困油压力并由此判断出困油现象的缓解程度。结果表明,对于给定的齿轮副和工况条件,等排量下的齿宽系数反比例于模数的3次方,模数越大,困油现象越趋于缓解,且径向力越小,但齿宽系数越小;同齿形参数、不同模数下的卸荷面积等于模数的平方乘基准模数为1下的卸荷面积,从而为同齿形参数、不同模数下的卸荷面积计算,提供了极大方便;卸荷槽外通的进出口压力互为颠倒,导致泵较马达的困油现象更严重,但等排量小模数马达同样也会出现较为严重的困油现象。得出了选择最大化/较大的模数应为泵/马达的设计准则的重要结论。

外啮合液压齿轮马达输出特性的统一简约式

为正确认识任意侧隙大小/偏置卸荷槽不同类型下齿轮马达的输出特性,基于啮合齿廓/输出特性不同的啮合线区间,以衡量侧隙大小的类型值和双卸荷槽对称线与齿轮副中心线的偏置值为变量,构建出转速/转矩等输出特性的统一简约式。结果表明,输出转速/转矩曲线可以由啮合齿廓的啮合转速/转矩曲线,通过输出特性啮合线区间的截取而直接得到;对称卸荷槽类型下的均值转速最小,均值转矩最大,转速/转矩的脉动系数最小;小侧隙较大的卸荷槽偏置范围和调速/调矩范围更大;小侧隙和对称卸荷槽类型的均值转速更小,均值转矩更大,转速/转矩的脉动系数更小;马达转矩脉动式与齿轮泵流量脉动式完全一致;转矩脉动系数略小于转速脉动系数,大齿数情况下可近似为相等;追求高转速时,应选用大侧隙和卸荷槽极限偏置的类型组合;追求大转矩或高输出脉动质量时,应选用小侧隙和对称卸荷槽的类型组合等。得出的输出特性的获取方法更简单、原理更清晰、形式更简洁、结果更可靠。

双调制式轴向永磁齿轮电动机气隙磁场与转矩计算

针对轴向永磁齿轮电动机(Axial Magnetic Gear Motor,AMGM)整体尺寸偏大导致的转矩密度偏低(≤70 kN·m/m^(3))等缺陷,提出了一种双调制式轴向永磁齿轮电动机(Dual-modulation Axial Magnetic Gear Motor,DAMGM)。采用高速侧及低速侧两个调磁环对DAMGM低速转子进行调制,且两个调磁环中的非导磁部分均为永磁体,有效提高了低速转子的输出转矩;另外,与现有AMGM相比,将驱动电动机置于DAMGM高速永磁转子内部,减小了整体轴向尺寸,大幅提高了低速转子的转矩密度(150 kN·m/m^(3))。针对现有3D有限元计算时间长、计算机资源浪费严重等问题,给出一种基于圆柱坐标系的DAMGM三维分析方法。根据调磁环的3种边界条件,建立了调制后DAMGM气隙磁场及电磁转矩的数理模型,不仅计算结果准确(与3D有限元相比,平均计算误差≤5%),而且计算时间短(仅为3D有限元的1/10),便于DAMGM不同参数结构的分析、比较与优化。

磁力齿轮异步电机共用磁轭分析及优化

分析了复合电机共用磁轭厚度对共用磁轭磁密的影响,以及磁力齿轮内转子极对数对复合电机各层气隙磁密和电机性能的影响,提出了两种针对共用磁轭的优化结构。首先,用磁路法进行计算,得出共用磁轭部分在一定磁密条件下的理论厚度和三层气隙中的谐波次数,分析共用磁轭厚度变化对共用磁轭磁密的影响,以及不同次数的谐波对电机性能的影响。然后,为了削弱磁力齿轮和异步电机的相互影响,提出两种新结构,一种在共用磁轭部分加入隔磁层,另一种将磁力齿轮内转子的排列方式改为Halbach阵列。最后,用有限元仿真验证了理论分析的正确性和新结构对电机性能的改进。

基于HMFDE和t-SNE的旋转机械故障诊断方法

针对旋转机械的故障特征提取较难,以及单一类型的特征无法全面反映故障特性的问题,提出了一种基于混合多尺度波动散布熵(HMFDE)、t分布-随机邻域嵌入(t-SNE)和郊狼优化算法(COA)优化极限学习机(ELM)的旋转机械故障诊断方法。首先,采用特征加权提出了混合多尺度波动散布熵方法,并将其用于提取旋转机械振动信号的故障特征;随后,采用t-SNE方法对混合故障特征进行了特征降维,挑选出了最能够反映故障特性的特征子集,构建了敏感特征样本;最后,采用郊狼优化算法对极限学习机的输入权重和隐含层阈值进行了优化,完成了旋转机械的故障识别和分类;以齿轮箱和滚动轴承故障数据集为对象,对基于HMFDE、t-SNE和COA-ELM的故障诊断方法进行了实验,验证了方法的有效性。研究结果表明:采用HMFDE-t-SNE-CAO-ELM故障诊断方法可以取得100%的故障识别准确率,该方法能够有效地诊断旋转机械的不同故障类型和损伤;相较于基于单一类型特征的故障诊断方法,其准确率分别可以提高0.68%、22.42%、29.18%(齿轮箱)和1.43%、8.23%、23.67%(滚动轴承),虽然牺牲了一定的计算效率,但准确率得到了明显的提高;相较于其他常规故障分类器,COA-ELM的故障识别准确率具有明显的优势。

IMIBSE与ISOMAP在旋转机械故障诊断中的应用

针对基本熵的区域划分标准不理想,导致无法有效测量振动信号的复杂度,使故障诊断的准确率不佳这一问题,提出了一种基于改进多尺度改进基本熵(IMIBSE)、等距特征映射(ISOMAP)和随机森林(RF)的旋转机械故障诊断方法。首先,采用基于方差的区域划分准则对基本熵进行了改进,结合改进的粗粒化处理,提出了IMIBSE,并将其用于提取故障特征;随后,利用ISOMAP对原始故障特征进行了特征降维,选择了对分类贡献最大的一组特征作为故障敏感特征;最后,基于RF建立了多故障分类器,将故障敏感特征输入至RF模型进行了训练和测试,实现了旋转机械的故障识别,利用齿轮箱和离心泵两种故障数据集将IMIBSE方法与复合多尺度基本熵、多尺度改进基本熵、多尺度基本熵进行了比较和分析。研究结果表明:IMIBSE不仅具有最佳的可视化效果,而且取得的识别准确率最高,二者均达到了100%,而二者的平均分类准确率分别为100%和99.8%;相较于其他故障诊断方法,IMIBSE方法的准确率更高,而且适用于小样本的故障识别问题。

基于维纳滤波的风电机组齿轮箱轴承故障诊断

存在轴承故障时,风电机组齿轮箱振动信号的幅度与频率都会发生明显改变,通过信号变化行为的测量能够判定出具体的轴承故障等级。为实现对轴承故障的准确判定,设计基于维纳滤波的风电机组齿轮箱轴承故障等级判定方法。通过获取轴承振动波的IMF分量,并完善维纳滤波算法,在此基础上,处理故障数据,实现基于维纳滤波的轴承故障特征提取。定义轴承故障特征的伪四阶矩,通过求解特征角度的方式,确定故障等级基准的判定范围,完成基于维纳滤波的风电机组齿轮箱轴承故障等级判定方法的设计。实验结果表明,利用上述方法,能够根据幅度和频率的变化行为,判定风电机组齿轮箱轴承的故障等级,符合实际应用需求。

基于Transformer和卷积神经网络的齿轮故障诊断方法

针对部分齿轮的运行环境复杂,导致采集的样本数据不够的问题,提出了一种基于Transformer和卷积神经网络(CNN)的迁移学习齿轮故障诊断方法。首先,采用高斯滤波对原始振动信号进行了预处理,使信号变得平滑,降低了噪声信号的干扰;再将信号处理成带有位置信息的补丁序列以作为Transformer的输入,并增强了Transformer特征提取的能力,提高了诊断精度;然后,将信号输入到CNN继续提取特征信息,在模型中添加了一个残差块以防止网络退化;接着,划分了实验室采集的齿轮数据集和东南大学齿轮箱数据集的源域和目标域,采用了源域数据预训练模型,选择了每种类型的齿轮各100个样本为目标域;最后,以不同数据集为源域共进行了4组10次重复实验,测试了模型的准确率。研究结果表明:以不同数据集为源域的4组10次迁移实验的齿轮故障诊断准确率较高,均在90%以上,最高准确率可达100%;与其他不含Transformer的卷积神经网络、多尺度卷积神经网络和二维卷积神经网络相比,Transformer-CNN的齿轮故障诊断平均准确率更高,其平均准确率可达到99.64%。因此,基于Transformer-CNN的迁移学习方法能在小样本下诊断齿轮的故障。

三维编织二级减速器箱体结构设计与性能分析

在分析三维五向编织纱线运动规律的基础上,将复合材料箱体设计为由编织底座和箱体壁两部分拼接的结构;在此基础上,得出了三维五向复合材料拼装箱体的编织和成型原理;根据编织原理和纱线运动规律,建立了拼装编织箱体的三维实体模型;对三维五向复合材料拼装箱体进行有限元分析,并通过应力和应变分析结果研究了编织复合材料箱体中基体和纤维的受力。在忽略摩擦、轴承等因素对系统影响的假设下,建立了考虑箱体两级齿轮传动系统的运动方程组,通过龙格-库塔法对两级齿轮传动系统进行数值分析,研究了激励对拼装编织系统动态特性的影响。

混合动力汽车无同步器AMT主动同步控制策略

以混合动力商用车电控机械式自动变速器(Automated Mechanical Transmission,AMT)换挡过程为研究对象,以减小换挡冲击和缩短换挡时间为目的,使用Simulink搭建了包含动力源动态协调与基于最优控制原理的电动机主动同步控制的无同步器换挡控制模型,并使用AMESim建立了动力系统及整车动力学仿真模型;以5挡升至6挡为例,采用AMESim与Simulink开展联合仿真分析,并与传统换挡策略的换挡性能进行了对比。仿真结果表明,换挡过程中,同步时间缩短21.42%,最大冲击度减少24.88%,整个换挡时间缩短18%。最后,基于dSPACE半实物仿真平台对所提控制策略进行了实时验证。

基于EMD分解和Levy-SSA-BP神经网络的齿轮故障诊断

为解决齿轮磨损早期故障诊断问题,提出了一种基于经验模态分解(Empirical Mode Decomposition,EMD)和算法优化反向传播(Back Propagation,BP)神经网络的故障诊断方法。首先,将声发射信号进行经验模态分解,得到本征模函数(Intrinsic Mode Function,IMF);其次,计算各IMF分量与原始信号的相关系数,并对各个分量进行特征提取,构成特征矩阵;最后,将特征矩阵放入经过Levy飞行和麻雀搜索算法优化后的BP神经网络中进行识别。对比BP神经网络和麻雀搜索算法优化后的神经网络,本文提出的算法准确率更高,且对轻微磨损故障的识别能力更好,可以用于早期齿轮故障诊断。