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Publication date: 2 October 2018

Hong Liu, Haijun Wei, Haibo Xie, Lidui Wei and Jingming Li

The possibility of using a pattern recognition system for wear particle analysis without the need of a human expert holds great promise in the condition monitoring industry…

151

Abstract

Purpose

The possibility of using a pattern recognition system for wear particle analysis without the need of a human expert holds great promise in the condition monitoring industry. Auto-segmentation of their images is a key to effective on-line monitoring system. Therefore, an unsupervised segmentation algorithm is required. The purpose of this paper is to present a novel approach based on a local color-texture feature. An algorithm is specially designed for segmentation of wear particles’ thin section images.

Design/methodology/approach

The wear particles were generated by three kinds of tribo-tests. Pin-on-disk test and pin-on-plate test were done to generate sliding wear particles, including severe sliding ones; four-ball test was done to generate fatigue particles. Then an algorithm base on local texture property is raised, it includes two steps, first, color quantization reduces the total quantity of the colors without missing too much of the detail; second, edge image is calculated and by using a region grow technique, the image can be divided into different regions. Parameters are tested, and a criterion is designed to judge the performances.

Findings

Parameters have been tested; the scale chosen has significant influence on edge image calculation and seeds generation. Different size of windows should be applied to varies particles. Compared with traditional thresholding method along with edge detector, the proposed algorithm showed promising result. It offers a relatively higher accuracy and can be used on color image instead of gray image with little computing complexity. A conclusion can be drawn that the present method is suited for wear particles’ image segmentation and can be put into practical use in wear particles’ identification system.

Research limitations/implications

One major problem is when small particles with similar texture are attached, the algorithm will not take them as two but as one big particle. The other problem is when dealing with thin particles, mainly abrasive particles, the algorithm usually takes it as a single line instead of an area. These problems might be solved by introducing a smaller scale of 9 × 9 window or by making use of some edge enhance technique. In this way, the subtle edges between small particles or thin particles might be detected. But the effectiveness of a scale this small shall be tested. One can also magnify the original picture to double or even triple its size, but it will dramatically increase the calculating time.

Originality/value

A new unsupervised segmentation algorithm is proposed. Using the property of the edge image, we can get target out of its background, automatically. A rather complete research is done. The method is not only introduced but also completely tested. The authors examined parameters and found the best set of parameters for different kinds of wear particles. To ensure that the proposed method can work on images under different condition, three kinds of tribology tests have been carried out to simulate different wears. A criterion is designed so that the performances can be compared quantitatively which is quite valuable.

Details

Industrial Lubrication and Tribology, vol. 70 no. 9
Type: Research Article
ISSN: 0036-8792

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Article
Publication date: 9 March 2015

Lidui Wei, Haijun Wei, Shulin Duan and Yu Zhang

The purpose of this paper is to develop a good calculation model to accurately predict the lubrication characteristic of main bearings of diesel engine and improve the service…

1397

Abstract

Purpose

The purpose of this paper is to develop a good calculation model to accurately predict the lubrication characteristic of main bearings of diesel engine and improve the service life.

Design/methodology/approach

Based on the coupling of the whole flexible engine block and the flexible crankshaft reduced by the Component Mode Synthesis (CMS) method, considering mass-conserving boundary conditions, the average flow model equation and Greenwood/Tripp asperity contact theory, an elastohydrodynamic (EHD)-mixed lubrication model of the main bearings for the diesel engine is developed and researched with the finite volume method and the finite element method.

Findings

Obviously, the mixed lubrication of bearings is normal, while full hydrodynamic lubrication is transient. The results show that under the whole flexible block model, maximum oil film pressure, maximum asperity contact pressure and radial shell deformation decrease, while minimum oil film thickness increases. Oil flow over edge decreases, and so does friction loss. Therefore, coordination deformation ability of whole engine block is favorable to mean load. In the whole block model, friction contact happens on both upper shell and lower shell positions. In addition, average oil film fill ratio at the key position becomes smaller in the whole engine block model, and consequently increases the chances of cavitations erosion more. So, wearing resistance of both upper and lower shells and anti-cavitations erosion ability must be enhanced simultaneously.

Originality/value

Based on the coupling of the whole flexible engine block and the flexible crankshaft reduced by the CMS method, considering mass-conserving boundary conditions, the average flow model equation and Greenwood/Tripp asperity contact theory, an EHD-mixed lubrication model of the main bearings for the diesel engine is built, which can predict the lubrication of journal bearings more accurately.

Details

Industrial Lubrication and Tribology, vol. 67 no. 2
Type: Research Article
ISSN: 0036-8792

Keywords

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Article
Publication date: 14 September 2015

Hong Liu, Haijun Wei, Lidui Wei, Jingming Li and Zhiyuan Yang

This study aims to use a deterministic tourist walk to build a system that can identify wear particles. Wear particles provide detailed information about the wear processes taking…

172

Abstract

Purpose

This study aims to use a deterministic tourist walk to build a system that can identify wear particles. Wear particles provide detailed information about the wear processes taking place between mechanical components. Identification of the type of wear particles by image processing and pattern recognition is key to effective online monitoring algorithm. There are three kinds of particles that are particularly difficult to distinguish: severe sliding wear particles, fatigue spall particles and laminar particles.

Design/methodology/approach

In this study, an identification method is tested using the deterministic tourist walking (DTW) method. This study examined whether this algorithm can be used in particle identification. If it does, can it outperform the traditional texture analysis methods such as Discrete wavelet transform or co-occurrence matrix. Different parameters such as walk’s memory size, size of image samples, different inputting vectors and different classifiers were compared.

Findings

The DTW algorithm showed promising result compared to traditional texture extraction methods: discrete wavelet transform and co-occurrence matrix. The DTW method offers a higher identification accuracy and a simple feature vector. A conclusion can be drawn that the DTW method is suited for particle identification and can be put into practical use in condition monitoring systems.

Originality/value

This paper combined DTW algorithm with wear particle identification problem.

Details

Industrial Lubrication and Tribology, vol. 67 no. 6
Type: Research Article
ISSN: 0036-8792

Keywords

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