With the rapid development of social economy,the market and enterprises have higher and higher requirements for application-oriented talents,and secondary vocational schools,as an important position for cultivating vocational and technical talents,should actively adapt to the requirements of the times and change the way of talent training.And with the development of the times,the disadvantages of the traditional teaching mode of secondary vocational schools of"emphasizing theory over practice"have gradually emerged,which has been unable to meet the personalized learning needs of students,and can not adapt to the requirements of the development of the times for talents,so teaching reform is imperative.In this context,this paper will focus on the secondary vocational CNC machining major.Through the what,why,and how to do the line of thought,starting from the concept of"integration of theory and practice"teaching mode,the study goes deep into the necessity of application in CNC machining major,and then explores relevant teaching strategies,aiming to realize the efficient application of the"integration of theory and practice"teaching mode in CNC machining,so as to improve the teaching quality and teaching efficiency,further enhance the professional ability and professionalism of students,and achieve comprehensive development.
Lidaris an important sensing component of the intelligent connected vehicle. Its performance is critical to the safety and reliability of automated driving system. Angle precision and accuracy are key performance indexes of lidar. Accurate testing is of great significance for improving the performance and safety of the automated driving system. This paper proposes three testing methods for the angle precision and accuracy of lidar, namely plate method, pyramid method and average method. By selecting key indicators, analyzing errors, and comparing advantages and disadvantages of these three methods, recommended testing methods for lidar with different scanning methods are provided, providing reference for the testing of lidar and its application in vehicles.
With the rapid development of machine-learning technology,more and more insurers are applying machine-learning methods to improve their car insurance pricing strategies.Measuring car insurance pricing factors is of great importance to insurers and car owners,as it can reveal the extent to which different factors affect insurance premiums and help develop more accurate and personalized insurance strategies.This study aims to compare the performance of different machine learning methods in measuring the importance of car insurance pricing factors,focusing on standard methods such as generalized linear models(GLM),random forests,and XGBoost,and to conduct an empirical study based on two real car insurance datasets.Through experiments and data analysis,we find consistency and variability in the essential measures of car insurance pricing factors across different algorithmic models.Some factors have consistent importance measures across the models,such as the reward and penalty coefficients and the manufacturer's guide price.However,there were also instances where some factors were inconsistent across models,which may be due to differences in model algorithms and data characteristics.These measures provide an essential reference for insurers and guide further improvements to car insurance pricing models and methods.
Proton Exchange Membrane (PEM) fuel cell is one of the most popular fuel cells because of its higher efficiency among the other fuel cells. Because of the expensive materials in designing of this type of fuel cell, it should be first design and simulated in the best and optimum way to reduce the construction costs as much as possible. In the present study, a new model identification is proposed for optimal parameters identification of the PEM fuel cells. The major idea in this study is to provide a new optimal methodology to parameters estimation of the unknown variables in the PEM fuel cell model so that the absolute error (IAE) between the estimated data based on the proposed model and the real data has been minimized. The proposed method uses a new improved design of Archimedes Optimization Algorithm (IAOA) to this purpose. The designed model is then implemented on two practical case studies and the results are compared with some well-known methods. Final results shows that the proposed method with 0.10 and 0.14 error values for Nexa and NedStack PS6 models, respectively, provides the best solution among the other comparative methods.
Advanced Materials Science and Technology is a peer-reviewed open access journal published semi-annual online by Omniscient Pte. Ltd. The journal covers the properties, applications and synthesis of new materials related to energy, environment, physics, chemistry, engineering, biology and medicine, including ceramics, polymers, biological, medical and composite materials and so on.
This paper analyses application status and technology of C-V2X intelligent sweeper, and research the test and evaluation method of C-V2X intelligent sweeper. Then through the domestic driverless sweeper test verification the test results meet the requirements of the test standard. This paper improves the test and evaluation system of domestic unmanned sweeper and provides reference for the test of domestic unmanned sweeper.
近年来,为了进一步深入落实高校立德树人的根本任务,全国高校及学科专业不断探索课程思政建设新方法、新途径,确保将课程思政充分融入充分到课堂教学建设中,全面提升人才培养能力.《机械制图》作为工学机械类和近机械类专业学生的一门必修专业基础课,如何切实有效地开展课程思政工作对于促进人才培养质量的全面提升尤为重要.本文围绕《机械制图》课程的特点,分析与挖掘《机械制图》中蕴含的课程思政元素,探索思政元素的融入方式,以塑造学生正确的价值观,鼓舞学生科技报国的家国情怀与使命感.
在机械制造、文化艺术、医学研究、教育教学等领域,3D 打印技术因其制作周期短、使用方便快捷等优点而得到了广泛应用.本文立足于 3D打印技术的发展现状,以丰富课堂教学、深化教学实践、提升学生创新能力为出发点,从高职高专机械类专业教学的特点和问题出发,对机械类专业学生培养中应用3D打印技术进行了探讨.
在综合考虑兰州新区现代有轨电车线网规划的基础上,基于BP神经网络建立现代有轨电车适用性研究分析训练模型,利用Matalab软件实现神经网络学习过程,根据训练结果,对兰州新区现代有轨电车适用性进行评价.
随着Best fit技术在北京奔驰的使用,传统的人工装配白车身四门两盖工作已经逐步被更加机械化、自动化、智能化的机器人装配所取代,本文通过Best fit技术在北京奔驰汽车装配制造过程的应用实践,结合Best fit技术的基本原理,在此基础上,介绍了车门尺寸在装配过程中的自动调整功能,该功能使车门装配尺寸结果更接近设置的理论目标值,同时使Best fit装配的稳定性进一步提升,提高生产效率.
机车车辆整车总成课程作为铁道机车专业、铁道车辆专业、机车车辆制造与维护专业的核心课程,是铁路相关专业学生的必修课程.本文通过对教材内容,教学过程进行研究分析,并结合铁路相关背景,提炼出了机车车辆检修课程中的课程思政内容,并将其应用到了教学实践中.
当前我国智能网联汽车产业发展迅猛,专业技术人才供需的结构性矛盾十分突出.因此,智能车辆工程新工科专业应运而生.本文介绍了哈工大(威海)智能车辆工程专业的培养目标和课程体系;分析了智能车辆环境感知技术课程教学过程中存在的突出问题;基于成果导向的教学理念对智能车辆环境感知技术的教学目标、教学设计、课程团队、教材开发等方面提出了改革措施,希望为相关院校智能车辆工程专业课程改革提供借鉴.
本文主要讨论汽轮发电机组进汽与抽汽调节阀冗余控制策略.通过某石化企业50MW汽轮机机组DEH硬件配置与运行过程中的实际案例分析,探讨伺服控制的冗余配置方案.针对该机组在现行硬件配置下优化的可行性方案.
汽车工厂的夏季空调主要是为了满足生产工艺需求兼顾人员劳动环境,夏季空调系统用电量占汽车工厂公共设施能源消耗的 34%,是汽车工厂重点管控的能源设备.空调系统应用智能合理的控制策略是实现设备节能运行的重要管理手段,也是汽车工厂降低单车能耗的重要途径.传统的空调自控系统主要通过冷冻水回水温度和压力反馈信号对末端冷冻水管上的电磁阀进行调节,通过冷冻水变流量实现节能控制.本文结合工程改造实例,利用车间工艺设备运行状态和办公区智能照明系统的人体感应器,对空调设备进行精益化的时间管理,结合物联网和AI技术,从而实现空调系统智慧节能运行,消除了传统空调系统依靠温度和压力反馈信号控制的延迟性.空调系统设计优化方法具有简单、有效、准确的优势,推广应用简单.
汽车是一个关系到国计民生的特殊产品,消费者不仅需要汽车的功能与性能,还希望能有舒适的驾驶感觉、安全的驾驶环境,更希望在开车时获得愉悦的心情,体验一种享受.汽车营销要做到这一点,就要创造出让消费者愿意坐进车内与之一起分享、交流、共同享受汽车的体验式营销.体验式营销是指消费者参与到企业产品的生产过程中,通过亲身参与去感知产品及服务,并通过消费者的反馈信息改进企业产品或服务.本文即就体验式营销方法在汽车销售之中的应用情况展开理论技术层面以及实践成果层面的分析阐述,以期优化汽车销售路径,提升企业效益.
在能源危机与全球气候变暖的压力驱使下,新能源汽车产业迎来了爆发式增长,经过使用的新能源汽车动力电池也迎来了退役潮.尽管退役电池已不能满足新能源汽车继续使用的要求,但将其回收并梯次利用后仍有着相当的价值,在其他地方贡献余热.本文梳理了国内外动力电池回收模式、运输相关规定、转运包装情况.最后提出了一系列建议,希望能促进动力电池回收产业进一步发展,走向健全.
新能源汽车作为现代产业体系中"皇冠上的明珠",产业链长、覆盖面广、带动能力强、产业融合度高,已成为国内各个省份竞相发展的风口产业.通过梳理我省新能源汽车产业的基础现状,针对产业还存在规模小,"三电"核心零部件短板突出,科技、人才、金融等关键要素的供给不足等问题,应紧紧抓住整车生产这个产业链发展的"牛鼻子"、引育结合加快提高核心零部件产业协作配套能力、加快提升产业链技术创新能力、持续优化产业生态等,加快推动我省汽车产业实现高质量发展.
低碳零碳技术是当前企业新的竞争力,作为汽车行业实现低碳零碳最好的出路是发展电动汽车.对于电动汽车,备受关注的是电池续航里程,而作为汽车上不可缺少的空调系统,会减少一部分电池续航里程.出于节能环保,降低对续航里程的影响,主要介绍电动汽车空调系统在发展中出现的,电动压缩机制冷+PTC制热的系统、节能的热泵系统及制冷剂的应用.
由于数智化在供应链中的应用,很多物流企业面临着商业领域的快速发展和院校体系的慢速发展之间的矛盾,在现代化、智能化等高端人才需求上,企业出现了招聘困难,与院校培养的物流人才衔接不当的矛盾.如何解决这一矛盾,对高校培养物流人才提出了更高的要求.文章通过分析数智供应链对物流人才的需求,针对高校物流教育人才培养现状问题,提出高校物流专业基于数智化供应链的人才培养模式创新.
