Search results

1 – 3 of 3
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 8 May 2018

Yiling Li, Yinhu Xi and Yijun Shi

This paper aims to present a method to measure the rolling friction coefficient in an easy and fast way. The aim is also to measure the rolling friction coefficient between a…

126

Abstract

Purpose

This paper aims to present a method to measure the rolling friction coefficient in an easy and fast way. The aim is also to measure the rolling friction coefficient between a small steel ball and a cylindrical aluminum surface.

Design/methodology/approach

An analytical model of the tribosystem of a freely rolling ball and a cylindrical surface is established. The rolling friction coefficient is evaluated from images recorded by a high-speed camera. The coefficient between a 1.58-mm diameter steel ball and a cylindrical aluminum surface is measured. A background subtraction algorithm is used to determine the position of the small steel ball.

Findings

The angular positions of the ball are predicted using the analytical model, and a good agreement is found between the experimental and theoretical results.

Originality/value

An optical method for evaluating the rolling friction coefficient is presented, and the value of this coefficient between a small steel ball and a cylindrical aluminum surface is evaluated.

Details

Industrial Lubrication and Tribology, vol. 70 no. 4
Type: Research Article
ISSN: 0036-8792

Keywords

Access Restricted. View access options
Article
Publication date: 4 November 2024

Yinhu Xi, Jinhui Deng, Baokun Li, Yanbiao Li and Haishun Deng

The purpose of this study is to detect the bolt loosening under conditions of impact loading with a low-cost self-powered triboelectric nanogenerator sensor.

43

Abstract

Purpose

The purpose of this study is to detect the bolt loosening under conditions of impact loading with a low-cost self-powered triboelectric nanogenerator sensor.

Design/methodology/approach

In this work, an Al/PTFE-based triboelectric nanogenerator (AP-TENG) is used as a sensor. A pendulum impact device and a force hammer were used to apply the impact loads. The bolt status and the applied torque can be monitored under impact loading conditions by using the output voltage results of the AP-TENGs.

Findings

The output voltage results of the current AP-TENG sensor under five different bolt torques, i.e. from 0.5 to 2.5 N m, were measured. The measurements revealed that a thicker buffer layer significantly contributed to the generation of higher voltages. Besides, the AP-TENG was also used to light ten commercial green LEDs in series, and the brightness of the LEDs was high enough even for the daytime, which showed that it can be used as the alarm device. In addition, a sudden loose test was also carried out, and the obvious voltage spikes can be seen without the external impact. The force hammer impact tests have expanded the application scope of the AP-TENG in the bolt loosening detection.

Originality/value

The bolt loosening monitoring is important and useful for the safe operation. The application of TENG technology for detecting bolt loosening remains relatively unexplored. In addition, ten commercial green LEDs can be driven by the AP-TENG sensor, which can be used for the early warning of the bolted loosening status.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0216/

Details

Industrial Lubrication and Tribology, vol. 76 no. 10
Type: Research Article
ISSN: 0036-8792

Keywords

Access Restricted. View access options
Article
Publication date: 12 May 2023

Yinhu Xi, Jinhui Deng and Yiling Li

The purpose of this study is to solve the Reynolds equation for finite journal bearings by using the physics-informed neural networks (PINNs) method. As a meshless method, it is…

285

Abstract

Purpose

The purpose of this study is to solve the Reynolds equation for finite journal bearings by using the physics-informed neural networks (PINNs) method. As a meshless method, it is unnecessary to use big data to train the neural networks, but to satisfy the Reynolds equation and the corresponding boundary conditions by using the known physics information.

Design/methodology/approach

Here, the boundary conditions are enforced through the loss function firstly, i.e. the soft constrain method. After this, an equation was constructed to build a surrogate model for satisfying the corresponding boundary conditions naturally, i.e. the hard constrain method.

Findings

For the soft one, in brief, the pressure results agree well with existing results, apart from the ones on the boundaries. While for the hard one, it can be noted that the discrepancies on the boundaries are reduced significantly.

Originality/value

The PINNs method is used to solve the Reynolds equation for finite journal bearings, and the error values on the boundaries for the results of the soft constrain method are improved by using the hard constrain method. Therefore, the hard constraint maybe also a good option when the pressure results on the boundaries are emphasized.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0045/

Details

Industrial Lubrication and Tribology, vol. 75 no. 5
Type: Research Article
ISSN: 0036-8792

Keywords

1 – 3 of 3
Per page
102050