Tribology in Industry最新文献_第3页

Effects of Shot Peening Pressure on Friction and Wear of High Pressure Cold Sprayed Ti-6Al-4V Coatings Under Dry and Lubrication Conditions 喷丸压力对干润滑条件下高压冷喷涂Ti-6Al-4V涂层摩擦磨损的影响

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1466.03.23.05

Nay Win Khun, Pham Quang Trung, Adrian Wei YeeTan, Wen Sun, Erjia Liu, David Lee Butler

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Abrasive Wear Performance of Coir Fiber Reinforced Polymer Composite 椰壳纤维增强聚合物复合材料的磨料磨损性能

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1500.06.23.07

A. Shalwan, S. Mallampati, B.F. Yousif

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Assessing the Sensitivity of the Rundown of a Turbocharger Rotor Shaft to Determine Its Technical Condition 评估涡轮增压器转子轴磨损的敏感性以确定其技术状态

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1473.04.23.06

Alexandr Gritsenko, Vladimir Shepelev, Alexandr Burtsev, Adil Shaikemelov

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Influence of Nano-Lubrication On Tribological Behavior of AZ91 Magnesium Alloy Under Fretting Condition 微动条件下纳米润滑对AZ91镁合金摩擦学行为的影响

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1426.12.22.06

Bharat Kumar, Shahid Saleem, M.F. Wani, Rakesh Sehgal, Sanjay Kumar

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Structure and Properties of Boride Coatings Obtained by the Plasma-Arc Method 等离子弧法制备硼化物涂层的结构与性能

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1458.03.23.05

Nguyen Van Vinh, Nguyen Van Trieu, Andrey Evgenievich Balanovskiy, Astafieva Natalia Anatolievna Natalia Anatolievna

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Insight on the Effect of Nanoparticles addition in Oil Lubrication: A Review 纳米颗粒在润滑油润滑中的作用研究进展

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1437.01.23.05

Amrut S. Aher, Vijay Kumar Pandey

{"title":"Insight on the Effect of Nanoparticles addition in Oil Lubrication: A Review","authors":"Amrut S. Aher, Vijay Kumar Pandey","doi":"10.24874/ti.1437.01.23.05","DOIUrl":"https://doi.org/10.24874/ti.1437.01.23.05","url":null,"abstract":"The goal of this literature review was to assess, organize, and synthesize the growing body of research on the use of nonmaterial’s as lubricant additives and to help provide more effective guidelines for future study and development in this area. Through statistical comparison, the chemical, physical, and morphological characteristics of nanoparticles performance were investigated. Analysis was done on how those particles affected friction, wear and thermal conductivity. Using information gathered from the literature, mechanisms of lubrication using nanoparticles were examined. Energy saving, pollution reduction, and environmental preservation all benefit greatly from the use of lubricants with addition of nanofillers to reduce friction and wear. Nanolubricant compounds have seen substantial advances in both academic study and commercial use as a result of these two trends. This article provides an overview of the various types of nanofillers addition in lubricating oil to form compounds and provides examples of their tribological characteristics. Survey also focused that, based on the data, nanofluids have much higher heat transmission than the basic oil. It's more than just up-to-date with the latest tech. © 2023 Published by Faculty of Engineering","PeriodicalId":23320,"journal":{"name":"Tribology in Industry","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Ratio of Wheel/Rail Steel Hardness that Ensures Minimum Wear 确保最小磨损的轮轨钢硬度比

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1459.03.23.06

Azamat Kanayev, Amangeldy Kanayev, Aliya Moldakhmetova

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Role of Particle Shape on Slurry Erosion Wear of AA6063 颗粒形状对AA6063料浆冲蚀磨损的影响

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1503.06.23.08

Bhushan D. Nandre, Girish R. Desale

{"title":"Role of Particle Shape on Slurry Erosion Wear of AA6063","authors":"Bhushan D. Nandre, Girish R. Desale","doi":"10.24874/ti.1503.06.23.08","DOIUrl":"https://doi.org/10.24874/ti.1503.06.23.08","url":null,"abstract":"The shape of erodent particles is most critical parameter, which affects the material removal from the target surface. The effect of particle shape on slurry erosion is still under investigation. The kinetic energy of the impacting particle is, in principle, responsible for removal of material from the target surface, which is a function of particle size, shape, density and velocity. In the present work, the variation of the wear with particle size and shape has been analysed to establish relationship between the two. Also the effect of particle shape on the maximum wear and normal impact wear has been investigated. The variations of mass loss form AA6063 target material due to four different shapes of erodents, namely, mild steel shots, mild steel grits, S.S. shots and S.S. grits are determined at two orientation angles 45° and normal impact angle. The kinetic energy of impacting particles was kept constant during all experiments by varying other parameters like velocity of impacting particles, solid concentration and test duration. So the effect of impacting particle shape on erosion wear has been investigated with constant kinetic energy effect at 45° and 90° impact angles. The worn out surfaces have also been studied using SEM to understand the material removal mechanism. © 2023 Published by Faculty of Engineering","PeriodicalId":23320,"journal":{"name":"Tribology in Industry","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wear Behavior of PEEK-Based Composites Designed for Water Lubrication Bearings 水润滑轴承用peek基复合材料的磨损性能

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1516.06.23.08

Vladislav O. Alexenko, Dmitry G. Buslovich, Sergey V. Panin

引用次数: 0

Prediction of Gearbox Oil Degradation Based on Online Sensor Data and Machine Learning Algorithms 基于在线传感器数据和机器学习算法的齿轮箱油退化预测

Tribology in Industry Pub Date : 2023-09-15 DOI: 10.24874/ti.1491.06.23.08

Kunal Kumar Gupta, S.M. Muzakkir

{"title":"Prediction of Gearbox Oil Degradation Based on Online Sensor Data and Machine Learning Algorithms","authors":"Kunal Kumar Gupta, S.M. Muzakkir","doi":"10.24874/ti.1491.06.23.08","DOIUrl":"https://doi.org/10.24874/ti.1491.06.23.08","url":null,"abstract":"In most of the gearboxes, mixed lubrication conditions prevail, and to avoid the wear of gear surfaces, oil additives like extreme pressure, anti-wear, anti-rust and antioxidant additives are used. The lubricant additives form a lubricant film on gear surfaces, minimize metal-to-metal contact and protect the surfaces. But in this process, the lubricant additives are consumed, and oil quality deteriorates causing degradation of wear-prevention lubricant functionality. The degradation of lubricant with time, even without its usage is alarming and it has been reported in the present manuscript. To observe the consequence of degraded gear-oil on gear surface, an experimental setup has been developed. The results of experiments, conducted on commercially available two-gear oils have been detailed. Three cases of single stage spur-gear pair were considered: (1) Loaded with 40 Nm torque value and operated at 1200 rpm for 198 hours duration. (2) Loaded with 50 Nm torque value and operated at 500 rpm and. (3) Accelerated conditions generated by adding 0.0025 %v of mild (36% concentration) Hydrochloric acid in the lubricant in addition to accelerated conditions specified in case 2. For the cases 2 & 3, the setup was run for 90 minutes duration. The dataset of this study includes five parameters namely time, humidity, temperature, oil quality and generated Fe debris. Machine learning techniques have been used to reduce the actual number of experiments by applying LR, DTR, KNNR, RFR, ANN and SVM in predicting the Oil degradation rate.","PeriodicalId":23320,"journal":{"name":"Tribology in Industry","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0