性能数据驱动的机械产品关键设计参数识别方法

利用运行数据识别产品设计缺陷或薄弱环节是产品开发和更新换代的主要模式,也是保证产品服役性能稳定的重要途径.提出了一种性能数据驱动的产品关键设计参数(薄弱环节)识别方法.首先,利用极限学习机算法划分运行工况,提出了基于核主成分分析和高斯混合模型的多工况性能退化评估方法,消除了工况变化对性能退化评估的影响,得到性能退化严重的关键功能模块;其次,对性能监测数据进行聚类分析,识别出与模块性能退化密切相关的关键性能监测参数;最后,建立了“性能监测参数—性能参数—设计参数”三者之间的关联关系,识别出导致性能严重退化的关键设计参数.以某大吨位履带起重机作业机构为例,验证了方法的有效性.     

立式辊磨机健康状态综合评价与预测研究

立磨是一种常见的大型粉磨设备,广泛应用于水泥、矿渣、新材料等粉磨领域,其健康状态直接关系到安全生产和企业效益。针对其停机频繁、过度维护、劳动强度大等问题,建立了立磨的两级健康评价体系,提出了以加权健康度定量描述立磨的健康状态,通过组合赋权法和灰云聚类融合方法定性评估立磨的健康状态,并应用最小二乘支持向量机模型预测立磨健康状态变化趋势。结合实例表明立磨健康状态评估结果与实际情况相符,并且对立磨维护时间节点的预测误差较小,验证了该评价体系的可行性及预测结果的准确性,具有较大的工程应用价值。     

数据驱动的锂离子电池健康状态综合评分及异常电池筛选

锂离子电池是电动汽车和储能系统最重要的组成部分,其故障预测和健康管理对于运行维护至关重要.数据驱动的方法较基于模型的方法更适合大规模工程应用,针对实际应用中工况复杂和数据质量较差的场景,提出数据驱动的健康状态综合评分及异常筛选算法,具有较强的适应性.首先,针对电池实际运行工况提出一种新的特征提取方案,可适用于非恒流的不稳定工况.开发了基于多维特征和混合聚类算法的健康状态综合评分体系,该方案采用无监督学习的算法框架,对可提取特征的数量和质量要求不高,无需进行事先的模型训练和复杂的超参数调整.然后,在麻省理工学院和斯坦福大学提供的公开数据集进行了算法验证,基于电池生命周期各阶段特征集进行健康度等级预测,并应用于健康度高低分选,均能达到92％以上的准确率.在某用户侧储能电站实现了该算法的应用,采用早期运行数据即可快速筛选异常电池,有利于尽早维护,提高电池系统的安全性和经济性.     

航天发射场供气系统健康管理技术

针对新一代航天发射场采用全新的在线供气模式,难以有效评估单样本设备健康状态的问题,提出一种基于隐马尔可夫的设备健康状态管理与预测方法。首先,利用设备监测数据构建隐马尔可夫健康状态评估模型,通过对不同观测序列与不同观测次数下的预测准确率进行仿真,确定出最优的模型参数;其次,把实时数据代入模型,根据模型的计算结果取最小值,从而判断出设备的健康状态;最后,将当前数据与历史数据进行拟合,预测出系统的安全可靠寿命。经实际检验,该方法有效解决了单样本多状态设备的健康评估。     

一种基于SCADA参数关系的风电机组运行状态识别方法

提出一种基于SCADA参数关系的风电机组运行状态识别方法。首先,从风电机组运行特性出发,深入分析风电机组运行状态SCADA数据输入/输出参数关系;基于时间的滑动窗口模型,采用多项式回归拟合方法,构建风电机组运行状态输入/输出参数关系数学模型;然后,基于风电机组正常运行输入/输出参数关系数学模型,提出描述各个时刻风电机组运行状态异常程度的指标计算公式;对风电机组正常运行阶段的状态指标进行统计分析,获取其分布函数规律;最后,根据小概率事件假设,确定识别风电机组运行状态出现异常的阈值,据此对风电机组运行状态出现异常进行预警。以同风场同型号两台2 MW直驱式风电机组SCADA数据为例进行分析,结果表明:①基于SCADA数据的风电机组运行状态识别方法,可以实现对风电机组运行的异常状态识别和早期预警,该方法的特点是状态识别完全基于正常运行SCADA数据分析而无需异常运行SCADA数据进行挖掘训练和相关物理机制与故障模式方面的先验知识;②基于风电机组SCADA数据的运行状态识别方法,依据风电机组及其部件的运行状态输入/输出参数关系的层次结构,可以获得发生异常状态的相关部件信息,这对风电机组运行状态预警和维护决策具有重要意义。     

基于贝叶斯推论和自组织映射的轴承性能退化评估方法

为在线识别和评估轴承的动态运行状态,提出一种基于贝叶斯推论和自组织映射的轴承性能退化评估方法。首先运用独立成分分析算法从原始特征集提取表征轴承正常运行的特征集,建立描述轴承健康状态的基准自组织映射模型,进而提出基于负对数似然概率的设备性能量化评估指标和基于贝叶斯推论的失效概率计算方法,在线识别和评估轴承的动态运行状态。通过在轴承全寿命测试床的实验结果表明,与一些传统的特征值指标和基于支持向量数据描述的性能退化评估方法相比,提出的评估指标可有效地量化轴承的全寿命性能退化过程,为进一步制定维护计划提供重要的设备健康信息。     

基于UKF的轴承剩余寿命预测方法研究

针对轴承从早期故障发生到失效的非线性退化问题,提出一种基于无迹卡尔曼滤波算法(UKF)的轴承剩余寿命预测方法。该方法包括轴承性能评估和剩余寿命预测两个部分。在性能评估部分,首先利用轴承振动信号建立反映其健康状态的指数,基于对正常工作时指数的学习获得用于判断轴承健康状态的异常阈值并截取出轴承从早期故障发生到失效这一性能退化阶段的数据;在剩余寿命预测部分,利用双指数函数拟合分析轴承退化数据,构建出与轴承退化过程相符的非线性状态空间模型,模型参数利用Dempster-Shafer方法进行初始化后采用UKF算法对其进行更新,并预测轴承的剩余寿命。基于轴承全寿命周期试验数据的分析,结果显示所提方法有效地评估了轴承的健康状况,通过对比分析其他剩余寿命预测方法,发现所提方法较好地预测了轴承的剩余寿命。     

角域多信息熵融合算法的EHA柱塞泵滑靴副状态评估方法

滑靴副是电静液执行器(Electro-hydrostatic Actuator,EHA)柱塞泵中受力最为复杂和薄弱环节,在变转速极端工况下对其健康状态进行有效评估对于EHA的安全稳定运行尤为重要。针对滑靴副在变转速工况下磨损故障特征机理复杂、难以揭示的问题。提出一种基于角域多信息熵融合算法的新状态评估方法,结合阶比分析与信息熵理论,针对EHA变转速极端工况提出“角域信息熵”新概念,运用BP神经网络和D-S证据理论构建基于角域多信息熵融合的滑靴磨损状态评估模型;最后在恒压变转速工况条件下,以滑靴外边缘偏磨磨损故障为例对评估模型进行测试试验验证和结果分析,证实状态评估方法有效性和评估结果的准确性。     

基于GMM的流体旋转设备运行可靠性在线评价方法

针对流体旋转设备运行工况多变且难以区分,导致运行可靠性评价准确率低的问题,提出了一种基于高斯混合模型（GMM）的流体旋转设备运行可靠性在线性评价方法。首先,根据设备历史运行数据,基于快速搜索和发现密度峰值的聚类算法（DPC）,进行工况划分,构建不同工况条件下的基于GMM的运行可靠性基准模型;其次,使用XGBoost算法对设备实时运行状态进行工况识别,约减冗余指标,构建设备运行可靠性的评价指标体系;然后,计算度量评价指标与对应工况下基准模型指标的偏离程度,以马氏距离作为度量标准,进一步计算得到设备运行可靠性评价指数;最后,以矿用离心机设备为例,进行了多工况下的运行可靠性实例分析和模型验证。研究结果表明,该方法能够在线实时反应设备当前的运行可靠性水平,当离心机设备运行可靠性低于0.857时,认为设备进入劣化状态,且评价准确率达到98%以上。     

基于多元状态估计的电厂设备状态评估和故障预警研究

针对电厂生产环境复杂，设备故障频发且不易及时发现的特点，为了提高机组运行效率和设备健康度，提出了一种基于多元状态估计的电厂设备状态评估和故障预警方法。首先，分析设备状态监测所需的监测参数，根据参数采集历史运行数据，筛选健康运行状态数据，筛选典型运行状态数据构建记忆矩阵；然后，搭建状态评估和故障预警模型，利用健康运行状态数据对模型进行训练得到成熟模型，利用成熟模型即可对设备实时运行状态进行健康度评估和故障预警。本文以某燃气发电厂燃气轮机为对象开展研究论证，结果表明，该方法能准确地评估设备运行状态，提早发现设备故障，有效实现设备故障早期预警。     

Development of the reference model for a residential heat pump system for cooling mode fault detection and diagnosis

Development of a reference model to predict the value of system parameters during fault-free operation is a basic step for fault detection and diagnosis (FDD). In order to develop an accurate and effective reference model of a heat pump system, experimental data that cover a wide range of operating conditions are required. In this study, laboratory data were collected under various operating conditions and then filtered through a moving window steady-state detector. Over five thousand scans of steady-state data were used to develop polynomial regression models of seven system features. A reference model was also developed using an artificial neural network (ANN), and it is compared to the polynomial models.     

Dynamics and cutting stability of the dynamically loaded worktable subjected to simply supported conditions

This paper aims to explore the dynamic characteristics and cutting stability of a surface grinder. In simulated grinding, the dynamically loaded worktable is described by the Euler–Bernoulli beam theory. In the model, the elastic worktable has both ends simply supported on a movable and massless rigid base. The analysis of the dynamics and stability of the worktable is complex due to the operating worktable being dynamically loaded in variable positions. With the Lagrange energy method combined with the assumed mode expansion method, the system dynamic equations are derived and a state space model for the dynamically loaded worktable subjected to simply supported conditions is developed. In this study, the maximum negative real part of the overall dynamic compliance and the limiting depth of cut are used as indicators to assess the structural static and dynamic performance of the worktable in various positions. The effects of worktable damping, contact stiffness, and damping between the tool and the workpiece on the system performance are studied. Based on the regenerative chatter and stability theory, the 3D stability lobes diagram is analyzed to optimize the maximum depth of cut at the highest available spindle speed. The cutting stability is verified by comparing the results obtained in the time domain analysis with the stability lobe diagram. The procedure illustrated in this study to improve the dynamics performance of a surface grinder can also be implemented in a similar fashion for many machine tool applications.     

基于湿法粉碎的研磨介质运动仿真系统的研究及应用

搅拌磨机的粉碎效果与磨机的结构尺寸、磨机的工况有直接关系。基于湿法粉碎原理，对一种新型鼠笼式搅拌磨机磨腔内流体场进行分析，建立磨介运动数学模型，找出磨介在流体场中运动规律，采用面向对象模块化设计方法，开发了鼠笼式搅拌磨机研磨介质运动仿真系统。该系统可实现鼠笼式磨机结构分析、不同工况下磨介运动的分析，优化得到最佳的研磨条件，为磨机设计和粉碎效果分析提供有价值的参考数据。     

Mathematical models of operating time and cutting capacity for various stages of flat creep feed grinding of horizontal surface by circle of direct profile

Mathematical models of volume reduced operating time and cutting and instantaneous cutting capacity for the operation of a flat creep feed grinding of horizontal surfaces by a circle of direct profile at all stages of the process (incision, additional set of depth, a constant length of arc of contact and exit) are obtained. On the basis of the models obtained, the maximum indicators of the process reliability are defined. The regularities of changes in the components of the force of deep grinding with a continuous revision of the circle of the blanks of titanium alloy BT8 are studied. A correlation between the instantaneous cutting power and the grinding force that allows the patterns of change in the actual treatment conditions to be predicted is established.     

跨平台操作系统数据记录模块技术研究

为了提高航空发动机实时记录数据的可靠性,提出了一款跨平台操作系统数据记录模块。该模块以Zynq7010芯片为核心,基于可移植操作系统接口标准,设计了统一的应用程序接口(API),兼容Linux和VxWorks 7.0操作系统。通过调用Linux的EXT4文件系统和VxWorks的TrueFFS文件系统驱动,结合用户数据报协议的网络通信方式,完成跨平台数据记录模块的存储操作。测试结果表明,该模块能以较快的速率实现两种操作系统下的数据记录过程,保障了航空发动机数据记录的准确性和可靠性。     

基于电涡流传感器的全闭环锯片磨床数控系统开发

详细介绍了在锯片磨床控制系统中采用电涡流传感器,实时在线测量锯片厚度,并反馈给数控系统,从而实现磨削过程全闭环控制的方法。所开发的全闭环数控磨削系统可在传感器线性范围内,通过简单的参数设置,自动适应不同加工条件和要求,具有高精度、高效率、操作简单、稳定性好等特点,在平面磨削加工中具有广阔的应用前景。     

A Study of the Development of an Ultraprecision Grinding System for Mirror-Like Grinding

In this study, a new system of optimum in-process electrolytic dressing and a microposition system are developed. This system can carry out optimum in-process dressing of superabrasive wheels, and gives effective control of the unstable dressing current and insulating layer. Therefore, ultraprecision grinding when using an optimum in-process electrolytic dressing system and microposition system is a good method for efficient mirror-like grinding of brittle materials.     

Modeling and evaluating of surface roughness prediction in micro-grinding on soda-lime glass considering tool characterization

The current research of micro-grinding mainly focuses on the optimal processing technology for different materials. However, the material removal mechanism in micro-grinding is the base of achieving high quality processing surface. Therefore, a novel method for predicting surface roughness in micro-grinding of hard brittle materials considering micro-grinding tool grains protrusion topography is proposed in this paper. The differences of material removal mechanism between convention grinding process and micro-grinding process are analyzed. Topography characterization has been done on micro-grinding tools which are fabricated by electroplating. Models of grain density generation and grain interval are built, and new predicting model of micro-grinding surface roughness is developed. In order to verify the precision and application effect of the surface roughness prediction model proposed, a micro-grinding orthogonally experiment on soda-lime glass is designed and conducted. A series of micro-machining surfaces which are 78 nm to 0.98 ~tm roughness of brittle material is achieved. It is found that experimental roughness results and the predicting roughness data have an evident coincidence, and the component variable of describing the size effects in predicting model is calculated to be 1.5x 107 by reverse method based on the experimental results. The proposed model builds a set of distribution to consider grains distribution densities in different protrusion heights. Finally, the characterization of micro-grinding tools which are used in the experiment has been done based on the distribution set. It is concluded that there is a significant coincidence between surface prediction data from the proposed model and measurements from experiment results. Therefore, the effectiveness of the model is demonstrated. This paper proposes a novel method for predicting surface roughness in micro-grinding of hard brittle materials considering micro-grinding tool grains protrusion topography, which would provide significant research theory and experimental reference of material removal mechanism in micro-grinding of soda-lime glass.     

管式微滤膜器压力测试系统的研究

研制了计算机控制的高精度在线管式膜器环隙压力测试系统。该系统基于Windows98操作系统，以Delphi6为软件开发工具，结合Access2000数据库管理系统进行数据测试、处理、存储，可准确、方便、可靠地测试出管式微滤膜器环隙内的转向与径向压力分布规律和相应的渗透通量。为进一步研究膜微滤机理，找出减少或解决浓差极化和膜污染的方法，提供了有效的手段。     

Constrained grinding optimization for time,cost, and surface roughness using NSGA-II

Selection of parameters in machining process significantly affects quality, productivity, and cost of a component. This paper presents an optimization procedure to determine the optimal values of wheel speed, workpiece speed, and depth of cut in a grinding process considering certain grinding conditions. Experimental studies have been carried out to obtain optimum conditions. Mathematical models have also been developed for estimating the surface roughness based on experimental investigations. A non-dominated sorting genetic algorithm (NSGA II) is then used to solve this multi-objective optimization problem. The objectives under investigation in this study are surface finish, total grinding time, and production cost subjected to the constraints of production rate and wheel wear parameters. The Pareto-optimal fronts provide a wide range of trade-off operating conditions which an appropriate operating point can be selected by a decision maker. The results show the proposed algorithm demonstrates applicability of machining optimization considering conflicting objectives.