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A Wear Debris Segmentation Method for Direct Reflection Online Visual Ferrography

Song Feng, Guang Qiu, Jiufei Luo, Leng Han, Junhong Mao, Yi Zhang
2019 Sensors  
Wear debris in lube oil was observed using a direct reflection online visual ferrograph (OLVF) to monitor the machine running condition and judge wear failure online.  ...  Reports on the segmentation algorithm of the wear debris ferrograms under reflected light are lacking.  ...  Acknowledgments: We thank Bo Li at Xi'an Shiyou University for his help with this article.  ... 
doi:10.3390/s19030723 fatcat:5k4mcxp2xjh43mngnmmgz5xxsu

Segmentation of Online Ferrograph Images with Strong Interference Based on Uniform Discrete Curvelet Transformation

Leng Han, Song Feng, Guang Qiu, Jiufei Luo, Hong Xiao, Junhong Mao
2019 Sensors  
Based on this possibility, a jam-proof uniform discrete curvelet transformation (UDCT)-based method for the binarization of wear debris images was proposed.  ...  Through real-time acquisition of the visual characteristics of wear debris in lube oil, an on-line visual ferrograph (OLVF) achieves online monitoring of equipment wear in practice.  ...  Online visual ferrography (OLVF) is an important image wear detection sensor.  ... 
doi:10.3390/s19071546 fatcat:s64phk7w4jckrgssyd6p6ah4ue

Online monitoring of oil wear debris image based on CNN

Han Wang, Hongfu Zuo, Zhenzhen Liu, Di Zhou, Hongsheng Yan, Xin Zhao, Michael Pecht
2022 Mechanics & Industry  
A motion object extraction algorithm based on background differences and the Otsu method is used to extract debris and bubble images, and a convolutional neural network (CNN) algorithm is used to distinguish  ...  Images of the wear particles and bubbles are then collected for subsequent training and verification of image classification algorithms.  ...  Offline measurement methods such as spectroscopy and ferrography are still the most common methods used for oil debris monitoring.  ... 
doi:10.1051/meca/2022006 fatcat:ilh2uxbgkvhxtmbzg7nwkfrhkq

Intelligent Recognition of Ferrographic Images Combining Optimal CNN with Transfer Learning Introducing Virtual Images

Hongwei Fan, Shuoqi Gao, Xuhui Zhang, Xiangang Cao, Hongwei Ma, Qi Liu
2020 IEEE Access  
Ferrography analysis(FA) is an important approach to detect the wear state of mechanical equipment. Ferrographic image recognition based on deep learning needs a large number of image samples.  ...  Therefore, the recognition method for small sample ferrographic images based on the convolutional neural network(CNN) and transfer learning(TL) is proposed.  ...  Wu [20] built a Wear-Net wear particle image classification model and wear-SSD target detection model based on Reference [19] to classify the single type debris and detect the composite debris.  ... 
doi:10.1109/access.2020.3011728 fatcat:peeueiafabdgtdboeth3reeivm

A Review and Methodology Development for Remaining Useful Life Prediction of Offshore Fixed and Floating Wind turbine Power Converter with Digital Twin Technology Perspective

Krishnamoorthi Sivalingam, Marco Sepulveda, Mark Spring, Peter Davies
2018 2018 2nd International Conference on Green Energy and Applications (ICGEA)  
In terms of cost, size, accuracy, and development, suitable oil monitoring technologies are online ferrography, selective fluorescence spectroscopy, scattering measurements, Fourier transform infrared  ...  Active yaw consists of a motor that actively aligns the turbine with the wind direction, see Bearing failures, pinion and bull gear teeth pitting, yaw brake failure, pinion and bull gear teeth wear-out  ... 
doi:10.1109/icgea.2018.8356292 fatcat:7ievhpobkvaojnul4gb6jfcp3i