基于电信号特征分析的电机故障诊断技术

介绍了电机故障诊断技术平台的组成,分析了电机常见故障下电信号的特征。利用宜昌和景洪工厂两台电机进行了实际对比测试,宜昌工厂电机定子电流特征频率在49.2Hz时表现出峰值-36.08dB,在50.8Hz时表现峰值则为-37.23dB,表明电机存在转子断条故障;景洪工厂电机在转子特征频率为113.51Hz时,出现峰值-58.47dB,表明电机存在静态偏心故障。经电机现场抽芯检查,验证了电机故障快速诊断平台给出的电机健康状态评估结果,证实了基于电信号特征分析的电机故障诊断技术的准确性。     

一种直升机避障电力线检测方法

电力线是一类形状细长、特征稀疏、随着视角的变化容易混淆在大量背景信息中的特殊障碍物，常规电力线检测识别算法得到的目标框对电力线所在位置的估计不够准确。为此，提出了一种相对角度估计方法，基于常规电力线目标检测与识别算法，并结合电力线相对角度估计，从而提高电力线的检测识别过程中所在位置的精度。相比电力线绝对角度回归的方法，提出的相对角度估计方法容易训练易收敛，计算量小，适用于实时性要求较高的应用场合。     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.     

Cheese ripening in nonconventional conditions: A multiparameter study applied to Protected Geographical Indication Canestrato di Moliterno cheese

A multiparameter study was performed to evaluate the effect of fondaco, a traditional ripening cellar without any artificial temperature and relative humidity control, on the chemical, microbiological, and sensory characteristics of Protected Geographical Indication Canestrato di Moliterno cheese. Ripening in such a nonconventional environment was associated with lower counts of lactococci, lactobacilli, and total viable bacteria, and higher presence of enterococci, in comparison with ripening in a controlled maturation room. Moreover, fondaco cheese underwent accelerated maturation, as demonstrated by faster casein degradation, greater accumulation of free AA, and higher formation of volatile organic compounds. Secondary proteolysis, as assessed by liquid chromatography-mass spectrometry of free AA and low molecular weight peptides, did not show any qualitative difference among cheeses, but fondaco samples evidenced an advanced level of peptidolysis. On the other hand, significant qualitative differences were observed in the free fatty acid profiles and in the sensory characteristics. Principal component analysis showed a clear separation of the fondaco and control cheeses, indicating that ripening in the natural room conferred unique sensory features to the product.     

Development of a stakeholder identification and analysis method for human factors integration in work system design interventions – Change Agent Infrastructure

In any work system design intervention—for example, a physical workplace re-design, a work process change, or an equipment upgrade—it is often emphasized how important it is to involve stakeholders in the process of analysis and design, to gain their perspectives as input to the development, and ensure their future acceptance of the solution. While the users of an artifact or workplace are most often regarded as being the most important stakeholders in a design intervention, in a work-system context there may be additional influential stakeholders who influence and negotiate the design intervention's outcomes, resource allocation, requirements, and implementation. Literature shows that it is uncommon for empirical ergonomics and human factors (EHF) research to apply and report the use of any structured stakeholder identification method at all, leading to ad-hoc selections of whom to consider important. Conversely, other research fields offer a plethora of stakeholder identification and analysis methods, few of which seem to have been adopted in the EHF context. This article presents the development of a structured method for identification, classification, and qualitative analysis of stakeholders in EHF-related work system design intervention. It describes the method's EHF-related theoretical underpinnings, lessons learned from four use cases, and the incremental development of the method that has resulted in the current method procedure and visualization aids. The method, called Change Agent Infrastructure (abbreviated CHAI), has a mainly macroergonomic purpose, set on increasing the understanding of sociotechnical interactions that create the conditions for work system design intervention, and facilitating participative efforts.     

Microscopic Methods for Identification of Sulfate-Reducing Bacteria from Various Habitats

This paper is devoted to microscopic methods for the identification of sulfate-reducing bacteria (SRB). In this context, it describes various habitats, morphology and techniques used for the detection and identification of this very heterogeneous group of anaerobic microorganisms. SRB are present in almost every habitat on Earth, including freshwater and marine water, soils, sediments or animals. In the oil, water and gas industries, they can cause considerable economic losses due to their hydrogen sulfide production; in periodontal lesions and the colon of humans, they can cause health complications. Although the role of these bacteria in inflammatory bowel diseases is not entirely known yet, their presence is increased in patients and produced hydrogen sulfide has a cytotoxic effect. For these reasons, methods for the detection of these microorganisms were described. Apart from selected molecular techniques, including metagenomics, fluorescence microscopy was one of the applied methods. Especially fluorescence in situ hybridization (FISH) in various modifications was described. This method enables visual identification of SRB, determining their abundance and spatial distribution in environmental biofilms and gut samples.     

Strong tribocatalysis of strontium titanate nanofibers through harvesting friction energy for dye decomposition

Friction is a common clean energy and can be harvested and converted into electricity energy via triboelectricity, which can electrochemically drive dye decomposition in theory. In this work, the tribocatalytic Rhodamine B dye decomposition has been experimentally realized in strontium titanate (SrTiO₃) nanofibers, which are synthesized via a hydrothermal method. In the tribocatalytic dye decomposition process, the friction is exerted in the interface between catalyst surface and a polytetrafluoroethylene (PTFE) Teflon rod setup with the different stirring speed. The RhB dye decomposition ratios of SrTiO₃ nanofibers at these stirring speeds of 200 rpm, 400 rpm, 600 rpm, and 800 rpm are respectively 24.2%, 51.8%, 73.9% and 88.6%, yielding to these reaction rate constants of ～0.0112 h^?1, ～0.0260 h^?1, ～0.0562 h^?1 and ～0.0877 h^?1. The main active species, which play an important role in tribocatalytic process, are the superoxide radicals and holes on basis of the active species quenching experiment results. The excellent tribocatalysis activity makes SrTiO₃ nanofibers potential for application in dye wastewater treatment through utilizing the environmental friction energy.     

物料堆场智能化管理经验分享

华润水泥（罗定）有限公司根据物料储存需求，共有三个长堆棚分为9个室内料场堆放原材料及混合材，厂内有4台铲车无规则轮流在这8个料场内作业，同时外来运料货车、公司化验及验收人员也会不间断地进入不同堆棚。由于料场内空间狭窄，驾驶员视线不好，如果堆棚料场内铲车在作业时，有其他人员或车辆进入铲车工作区域共同作业，在没有检测装置对进入的人、车进行识别，提醒铲车驾驶员的情况下，容易发生碾压进入人员或车辆碰撞的安全事故。公司根据现场实际，自2020年起决定实施从堆场出入口智能红外感应技术、装载机车载识别系统、智能声光语音提醒、实时监控显示、照明、堆场硬件设施等五方面实施物料堆场车辆智能化安全预警系统项目。     

车辆高速避让路径跟踪控制策略

建立车辆动力学模型,研究车辆在高速避让工况下的路径跟踪控制策略。基于自抗扰控制设计车辆横摆角速度以及道路曲率2种不同的路径跟踪控制器;设计基于车辆偏航位移和偏航角度加权的线性二次最优控制器;对3种控制器控制效果进行仿真验证,分析路径跟踪侧向位移误差、侧向加速度、前轮转向角以及偏航角度变化。越野车实车测试结果表明,路径跟踪控制策略正确。