润滑油中磨损颗粒在线监测传感器研究进展*

油液监测是判断设备健康状况和提供设备故障隐患预警的有效方法。综述了用于监测润滑油中磨损颗粒的最新各类在线传感器的基本原理,包括批量磁吸附式传感器、微流体电容传感器、金属扫描传感器、双层平面线圈传感器、超声波传感器和光学传感器等,并讨论各种传感方法的优缺点以及未来发展面临的挑战;指出了高通量、高灵敏度、能区别金属与非金属磨粒、可采集磨粒图像信息的集成式传感器是未来研究的重点,集成式、智能化、无线传输的传感器是未来研发方向。     

Changes in the content and antioxidative activity of β-carotene and its metabolite vitamin A during gastrointestinal digestion and absorption and optimisation of HPLC-based detection

The β-Carotene (BC), an important precursor of vitamin A (VA), possesses antioxidant activity but is fat-soluble and has low bioavailability. In previous in-vitro assays evaluating antioxidant and 2,2′-azobis(2-amidinopropane) dihydrochloride (AAPH) free radical scavenging, both BC and VA showed a strong ability to scavenge radicals and protected cells from oxidative stress. Here, we used artificially simulated gastrointestinal digestion and Caco-2 cell absorption models to evaluate the bioavailability of the BC during gastrointestinal digestion and absorption using high-performance liquid chromatography (HPLC) analysis. We observed high absorptive and transfer rates of BC and detected retinol metabolites (Vitamin A). Therefore, BC can be detected in the acidic gastrointestinal environment using HPLC. Optimised method provided better separation of BC and VA in the column, improving the accuracy of the test results.     

基于形态特征提取的急性下壁心肌梗死BiLSTM网络辅助诊断算法

急性下壁心肌梗死是一种病发急、进展快、致死率高的心脏疾病,该文提出一种新颖的基于形态特征提取的BiLSTM神经网络分类的急性下壁心肌梗死辅助诊断算法,可大幅度提高医生对急性下壁心肌梗死疾病的诊断效率并有助于及时确诊.算法包括:对胸痛中心数据库心拍信号进行降噪及心拍分割;根据临床心内科医学诊断指南提取了12导联波形距离特征和分导联波形幅值特征;依据提取的特征搭建LSTM与BiLSTM神经网络进行心拍的分类识别;使用PTB公开数据库和胸痛中心数据库多临床中心进行交叉验证.实验结果表明,加入胸痛中心真实临床数据后,基于形态特征提取BiLSTM神经网络的急性下壁心肌梗死辅助诊断算法准确率达到99.72％,精度达到99.53％,灵敏度达到100.00％,同时F1-Score达到99.76.该算法比其他现有算法准确率提高至少1％,该项研究具有非常重要的临床应用价值.     

磨料有序排布电镀砂轮的制备及其把持力研究

为解决电镀砂轮磨削加工中容屑空间不足的问题，采用点胶微粘接的方法制备了磨料有序排布的电镀砂轮，分析了磨料粘接效果和镀层力学性能。通过SEM分析了磨料/镀层/导电胶的结合界面，并进行了干磨削试验。研究结果表明，直径约为磨料粒径40%的胶点可粘接住磨料，单个胶点上粘接多颗磨料的占比小于6%；双脉冲电镀工艺制备的镀层显微硬度大于500HV，表层残余应力小于100MPa，磨料/镀层/导电胶之间的界面贴合紧密，无明显缺陷；砂轮在磨削时没有出现磨料脱落现象。     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Effects of non-thermal plasma treating wheat kernel on the physicochemical properties of wheat flour and the quality of fresh wet noodles

The effects of non-thermal plasma (NTP) on the physicochemical properties of wheat flour and the quality of fresh wet noodles ( FWN) were investigated. The results showed that NTP effectively decreased the total plate count (TPC), yeast and mould count (YMC) and Bacillus spp. in wheat flour. Wet gluten contents and the stability time reached the maximum when treated for 20 s. The viscosity of starch increased significantly after treatment due to the increased of damaged starch. The contents of secondary structure were altered to some extent, which was because that the ordered network structure of gluten protein broken. Furthermore, compared with the control, texture properties of FWN were enhanced significantly at 20 s, and the darkening rate of FWN was greatly inhibited due to the low polyphenol oxidase (PPO) activity. Consequently, the most suitable treatment was 500 W for 20 s, providing a basis for the application of NTP in flour products.