基于MMDFE⁃DA的滚动轴承故障诊断方法

针对变工况条件下轴承训练数据集和测试数据集存在分布差异,导致智能诊断模型泛化能力不足,且需针对不同任务分别建模问题,提出一种基于多尺度混合域特征提取(multi?scale mixed domain feature extraction,简称MMDFE)和领域自适应(domain adaptation,简称DA)的滚动...     

基于多模态步行意图识别的助行机器人柔顺控制

在辅助行走或步行康复训练过程中,助行机器人在紧密跟随人体步态的基础上,准确识别异常行为是人机交互的重要研究内容。为此,提出一种兼具通用性、鲁棒性与便捷性的非接触式多模态步行意图识别方法,能够准确识别多种步态并柔顺地控制机器人运行。首先,分析了步行辅助机器人和步行康复训练机器人的结构、功能与运动学模型,建立了内嵌式机载步态信息检测系统,从而准确描述步态变化规律;其次,为有效解决标志点丢失问题,提出了一种新型的扩展集员滤波算法来精确估计膝关节角度;最后,通过引入用户步态信息,建立了一种基于步态补偿的柔性控制方法并进行了实验研究。实验表明,提出的算法能够在有效克服标记点丢失的情况下,准确识别交互过程中的正常步态,并柔顺地控制机器人运动,同时对跌倒和拖拽步态进行有效识别,识别率分别达到91.3%和89.3%。该非接触式步态意图识别方法可以应用于具有类似结构的助行器及其日常助行与康复训练场景。     

CBS/ZrO_2体系玻璃陶瓷结构与性能研究

采用SEM、XRD、网络分析仪等分析测试手段研究了ZrO_2含量对CBS/ZrO_2复合陶瓷结构与性能的影响。研究结构表明:随着ZrO_2量的增加,CBS/ZrO_2复合陶瓷的介电常数先增加后降低,介电损耗先降低后增加;ZrO_2量为25%时,CBS/ZrO_2复合陶瓷的介电常数达到最高为7.81,密度最大达到3.144g/cm3;ZrO_2量为15%时,CBS/ZrO_2复合陶瓷介电损耗最低为1.55×10~(-3)。CBS玻璃烧结后主要晶相为CaSiO3,CBS/ZrO_2复合陶瓷主要晶相为CaSiO3和ZrO_2。     

Artificial Intelligence in Aptamer–Target Binding Prediction

Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization.     

基于混合建模的水泥生料分解过程动态特性研究

为掌握水泥分解炉运行过程的动态特性,采用机理建模与神经网络相结合的方法构建了水泥分解炉一维特性模型,并结合工业数据对该方法的可行性进行验证。结果表明,模型能够准确地计算炉内温度、气体浓度等参数,具有良好的泛化性能。基于所提出的模型,研究了炉内各状态参数的稳态分布特性。此外,对喷煤量、生料下料量、喷氨量以及高温风机转速等操作变量进行阶跃实验,分析上述操作变量改变时分解炉出口温度及出口NO _x 含量的动态响应情况。研究所得相关动态特性规律可以为控制系统的分析、设计和优化提供参考与依据。     

EPS颗粒对超轻水泥基复合保温材料性能的影响

聚苯乙烯泡沫塑料颗粒(EPS颗粒)作为水泥基复合保温材料的超轻骨料,对水泥基复合保温材料力学性能、热工性能影响显著。以水泥为胶凝材料,EPS颗粒、混合材、泡沫剂和改性剂、水等为主要原料,采用物理发泡工艺制备干表观密度不大于120 kg/m³的超轻水泥基复合保温材料(UCIM)。通过设计不同体积掺量的EPS颗粒,分析EPS颗粒掺量对泡沫混凝土基体孔结构、超轻水泥基复合保温材料强度和热工性能的影响规律。结果表明,适宜掺量EPS颗粒可显著提高超轻水泥基复合保温材料抗压强度和抗拉强度,并确保超轻水泥基复合保温材料具有良好的热工性能,即通过EPS颗粒与泡沫混凝土基体的协同作用,协调力学性能和热工性能,制备出高性能超轻水泥基复合保温材料。     

高温合金切削刀具的研究现状及进展

高温合金具有较高的强度、抗高温氧化性等性能,被广泛应用于各种领域中,其加工时切削温度高、加工硬化严重、刀具磨损严重,是最难加工的材料之一。本文综述了国内外高温合金切削刀具的研究现状。阐述了高温合金的切削特性,重点对高速钢、硬质合金、涂层硬质合金、陶瓷、PCVB这几类高温合金切削刀具材料的研究现状进行了分析;同时,也对国内外切削高温合金刀具的结构、切削加工工艺参数以及磨损机理的研究现状进行了概述。在此基础上,发现高温合金切削刀具虽然已经研发设计出了多种新刀具材料、新切削工艺参数,但仍然需要进一步了解影响刀具性能的因素及刀具磨损机理。因此,本文提出了建立评估刀具使用性能体系和研发高性能的刀具材料是高温合金切削刀具的主要研究方向。     

γ-TiAl合金纳米切削过程中随机表面粗糙度影响的原子模拟

采用分子动力学模拟方法研究了随机粗糙度对γ-TiAl合金纳米尺度切削的影响。为了模拟真实工件表面,在考虑刀具不同前角和切削深度的情况下,采用多参数的Weierstrass-Mandelbrot（W-M）函数生成随机表面粗糙度,用工件的等效高度来量化切削深度。结果表明,粗糙度对工件的纳米切削有不可忽视的影响。此外,粗糙度的影响在不同切削参数的情况下也不同。     

Reaction Engineering Approach (REA) to model the drying kinetics of droplets with different initial sizes—experiments and analyses

Droplets with different initial sizes, which are typical in conventional liquid atomization for spray drying applications, will result in varying drying and crust formation histories. It is essential for any droplet drying model to accurately capture such fundamental phenomena. This study used a newly constructed glass-filament single droplet rig to evaluate the applicability of the Reaction Engineering Approach (REA) in describing such effect. For the three initial sizes (1, 2 and 3 μL) tested, the glass filament gravimetric method clearly distinguished the different drying kinetics and the crust formation phenomenon, delineated by the drying behavior. Analysis from the drying kinetics revealed that the main premise of the REA, which utilizes a material-specific master activation energy curve, is applicable to droplets of different initial sizes at all the three air temperatures tested. This allowed the REA to accurately predict the different temperature and moisture histories given by droplets with different initial sizes. The result supports the REA as a good modeling approach for a wide range of initial droplet conditions. A new master curve approach was proposed to predict the diameter change of droplets with different initial concentrations. Validation with the current and past experimental data revealed that this approach has strong potential to account for the different feed concentrations typically found in spray drying applications.