A Semi-incremental Recognition Method for On-Line Handwritten Japanese Text

2013 ◽  
Author(s):  
Cuong Tuan Nguyen ◽  
Bilan Zhu ◽  
Masaki Nakagawa
Keyword(s):  
Japanese Text ◽  
Recognition Method ◽  
On Line ◽  
Incremental Recognition

scholarly journals Semi-Incremental Recognition of On-Line Handwritten Japanese Text

2016 ◽  
Vol E99.D (10) ◽  
pp. 2619-2628 ◽  
Author(s):  
Cuong-Tuan NGUYEN ◽  
Bilan ZHU ◽  
Masaki NAKAGAWA
Keyword(s):  
Japanese Text ◽  
On Line ◽  
Incremental Recognition

scholarly journals Electrostatic Sensor Application for On-Line Monitoring of Wind Turbine Gearboxes

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3574 ◽  
Author(s):  
Huijie Mao ◽  
Hongfu Zuo ◽  
Han Wang
Keyword(s):  
Wind Turbine ◽  
Wear Debris ◽  
Bench Test ◽  
Recognition Method ◽  
Wind Turbine Gearbox ◽  
Practical Applications ◽  
Electrostatic Induction ◽  
Oil Flow ◽  
On Line ◽  
Application Potential

The oil-line electrostatic sensor (OLES) is a new online monitoring technology for wear debris based on the principle of electrostatic induction that has achieved good measurement results under laboratory conditions. However, for practical applications, the utility of the sensor is still unclear. The aim of this work was to investigate in detail the application potential of the electrostatic sensor for wind turbine gearboxes. Firstly, a wear debris recognition method based on the electrostatic sensor with two-probes is proposed. Further, with the wind turbine gearbox bench test, the performance of the electrostatic sensor and the effectiveness of the debris recognition method are comprehensively evaluated. The test demonstrates that the electrostatic sensor is capable of monitoring the debris and indicating the abnormality of the gearbox effectively using the proposed method. Moreover, the test also reveals that the background signal of the electrostatic sensor is related to the oil temperature and oil flow rate, but has no relationship to the working conditions of the gearbox. This research brings the electrostatic sensor closer to practical applications.

scholarly journals Character-Position-Free On-Line Handwritten Japanese Text Recognition by Two Segmentation Methods

2016 ◽  
Vol E99.D (4) ◽  
pp. 1172-1181 ◽  
Author(s):  
Jianjuan LIANG ◽  
Bilan ZHU ◽  
Taro KUMAGAI ◽  
Masaki NAKAGAWA
Keyword(s):  
Japanese Text ◽  
Text Recognition ◽  
Segmentation Methods ◽  
Character Position ◽  
On Line

Pattern Recognition for UHF Partial Discharge of Power Transformer Using LS-SVM

2012 ◽  
Vol 588-589 ◽  
pp. 384-387
Author(s):  
Jin Sha Yuan ◽  
Hai Kun Shang
Keyword(s):  
Pattern Recognition ◽  
High Frequency ◽  
Power Transformer ◽  
Partial Discharge ◽  
Small Samples ◽  
Support Vector ◽  
Discharge Diagnosis ◽  
Recognition Method ◽  
On Line ◽  
Pattern Recognition Approach

Partial discharge diagnosis is an important tool for detecting insulation defects in power equipments. This paper presents a pattern recognition approach based on Least Squares Support Vector Machine (LS-SVM) for Ultra High Frequency (UHF) partial discharge diagnosis of power transformer. Six different feature parameters were extracted from the data obtained from Partial Discharge (PD) on-line monitoring system. LS-SVM was used to discriminate between 4 different PD sources. Experimental results demonstrate that the proposed approach has higher recognition accuracy compared with traditional BPNN recognition method under condition of small samples, and has great potential for use of field data.

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