Research graph
References from Quantitative color characterization of wear debris for material identification and wear mechanism analysis. Local targets link to admitted publications; unresolved targets remain external evidence.
Research on abrasive particle target detection and feature extraction for marine lubricating oil
10.3390/jmse12040677 · 2024 · External reference
Investigation on wear diagnosis of aero-engine mechanical system based on lubricant wear particle analysis
2023 · External reference
An object detection network for wear debris recognition in ferrography images
10.1007/s40430-022-03375-4 · 2022 · External reference
FWDNet: a novel recognition network for ferrography wear debris image analysis
2022 · External reference
Wear particle classification considering particle overlapping
10.1016/j.wear.2019.01.060 · 2019 · External reference
A lubricating oil condition monitoring system based on wear particle kinematic analysis in microfluid for intelligent aeroengine
10.3390/mi12070748 · 2021 · External reference
A microfluidic oil particles monitoring system based on raspberry Pi
2022 · External reference
Ferrographic wear particle identification of marine lubricating oil based on YOLO v5s and attention mechanism
2023 · External reference
Imaged wear debris separation for on-line monitoring using gray level and integrated morphological features
10.1016/j.wear.2014.04.014 · 2014 · External reference
Watershed-based morphological separation of wear debris chains for On-Line ferrograph analysis
10.1007/s11249-013-0280-1 · 2014 · External reference
Intelligent prediction of wear location and mechanism using image identification based on improved Faster R-CNN model
10.1016/j.triboint.2022.107466 · 2022 · External reference
Online monitoring of oil wear debris image based on CNN
2022 · External reference
A microfluidic device for three-dimensional wear debris imaging in online condition monitoring
10.1177/1350650116684707 · 2017 · External reference
Morphological feature extraction based on multiview images for wear debris analysis in On-line fluid monitoring
10.1080/10402004.2016.1174325 · 2017 · External reference
Integrated model of BP neural network and CNN algorithm for automatic wear debris classification
10.1016/j.wear.2018.12.087 · 2019 · External reference
Real-time ferrogram segmentation of wear debris using multi-level feature reused unet
10.3390/s24082444 · 2024 · External reference
A hybrid convolutional neural network for intelligent wear particle classification
10.1016/j.triboint.2019.05.029 · 2019 · External reference
WP-DRnet: a novel wear particle detection and recognition network for automatic ferrograph image analysis
10.1016/j.triboint.2020.106379 · 2020 · External reference
FECNN: a promising model for wear particle recognition
10.1016/j.wear.2019.202968 · 2019 · External reference
Probability-weighted ensemble support vector machine for intelligent recognition of moving wear debris from joint implant
10.1016/j.triboint.2023.108583 · 2023 · External reference
Unsupervised segmentation of wear particle's image using local texture feature
10.1108/ilt-09-2017-0275 · 2018 · External reference
Online wear characterisation of rolling element bearing using wear particle morphological features
10.1016/j.wear.2019.05.005 · 2019 · External reference
Description of wear debris from On-Line ferrograph images by their statistical color
10.1080/10402004.2012.686086 · 2012 · External reference
Dimensional description of on-line wear debris images for wear characterization
10.3901/cjme.2014.0808.132 · 2014 · External reference
Oxidation wear monitoring based on the color extraction of on-line wear debris
10.1016/j.wear.2014.12.047 · 2015 · External reference
Binarization method for On-Line ferrograph image based on Uniform Curvelet transformation
2018 · External reference
Wear particle chain segmentation based on the nearest neighbor method
2019 · External reference
A wear debris segmentation method for direct reflection online visual ferrography
10.3390/s19030723 · 2019 · External reference
A hybrid search-tree discriminant technique for multivariate wear debris classification
10.1016/j.wear.2017.09.022 · 2017 · External reference
Motion-blurred particle image restoration for On-Line wear monitoring
10.3390/s150408173 · 2015 · External reference
An oil wear particles inline optical sensor based on motion characteristics for rotating machines condition monitoring
10.3390/machines10090727 · 2022 · External reference
Oil debris and viscosity monitoring using optical measurement based on Response Surface Methodology
10.1016/j.measurement.2022.111152 · 2022 · External reference
Watershed-based morphological separation of wear debris chains for On-Line ferrograph analysis
10.1007/s11249-013-0280-1 · ExternalCitation · doi-reference
An object detection network for wear debris recognition in ferrography images
10.1007/s40430-022-03375-4 · ExternalCitation · doi-reference
Oil debris and viscosity monitoring using optical measurement based on Response Surface Methodology
10.1016/j.measurement.2022.111152 · ExternalCitation · doi-reference
A hybrid convolutional neural network for intelligent wear particle classification
10.1016/j.triboint.2019.05.029 · ExternalCitation · doi-reference
WP-DRnet: a novel wear particle detection and recognition network for automatic ferrograph image analysis
10.1016/j.triboint.2020.106379 · ExternalCitation · doi-reference
Intelligent prediction of wear location and mechanism using image identification based on improved Faster R-CNN model
10.1016/j.triboint.2022.107466 · ExternalCitation · doi-reference
Probability-weighted ensemble support vector machine for intelligent recognition of moving wear debris from joint implant
10.1016/j.triboint.2023.108583 · ExternalCitation · doi-reference
Imaged wear debris separation for on-line monitoring using gray level and integrated morphological features
10.1016/j.wear.2014.04.014 · ExternalCitation · doi-reference
Oxidation wear monitoring based on the color extraction of on-line wear debris
10.1016/j.wear.2014.12.047 · ExternalCitation · doi-reference
A hybrid search-tree discriminant technique for multivariate wear debris classification
10.1016/j.wear.2017.09.022 · ExternalCitation · doi-reference
Integrated model of BP neural network and CNN algorithm for automatic wear debris classification
10.1016/j.wear.2018.12.087 · ExternalCitation · doi-reference
Wear particle classification considering particle overlapping
10.1016/j.wear.2019.01.060 · ExternalCitation · doi-reference
Online wear characterisation of rolling element bearing using wear particle morphological features
10.1016/j.wear.2019.05.005 · ExternalCitation · doi-reference
FECNN: a promising model for wear particle recognition
10.1016/j.wear.2019.202968 · ExternalCitation · doi-reference
Description of wear debris from On-Line ferrograph images by their statistical color
10.1080/10402004.2012.686086 · ExternalCitation · doi-reference
Morphological feature extraction based on multiview images for wear debris analysis in On-line fluid monitoring
10.1080/10402004.2016.1174325 · ExternalCitation · doi-reference
Unsupervised segmentation of wear particle's image using local texture feature
10.1108/ilt-09-2017-0275 · ExternalCitation · doi-reference
A microfluidic device for three-dimensional wear debris imaging in online condition monitoring
10.1177/1350650116684707 · ExternalCitation · doi-reference
Research on abrasive particle target detection and feature extraction for marine lubricating oil
10.3390/jmse12040677 · ExternalCitation · doi-reference
An oil wear particles inline optical sensor based on motion characteristics for rotating machines condition monitoring
10.3390/machines10090727 · ExternalCitation · doi-reference
A lubricating oil condition monitoring system based on wear particle kinematic analysis in microfluid for intelligent aeroengine
10.3390/mi12070748 · ExternalCitation · doi-reference
Motion-blurred particle image restoration for On-Line wear monitoring
10.3390/s150408173 · ExternalCitation · doi-reference
A wear debris segmentation method for direct reflection online visual ferrography
10.3390/s19030723 · ExternalCitation · doi-reference
Real-time ferrogram segmentation of wear debris using multi-level feature reused unet
10.3390/s24082444 · ExternalCitation · doi-reference
Dimensional description of on-line wear debris images for wear characterization
10.3901/cjme.2014.0808.132 · ExternalCitation · doi-reference
