Research on the fault diagnosis method for high-speed loom using rough set and Bayesian network

2020 ◽  
Vol 39 (1) ◽  
pp. 1147-1161
Author(s):  
Yanjun Xiao ◽  
Heng Zhang ◽  
Wei Zhou ◽  
Feng Wan ◽  
Zhaozong Meng
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Rough Set ◽  
High Speed ◽  
Diagnosis Method

An Adaptive Multi-Sensor Fault Diagnosis Method for High-Speed Train Traction Converters

2020 ◽  
pp. 1-1
Author(s):  
Honghui Dong ◽  
Fuzhao Chen ◽  
zhipeng wang ◽  
Limin Jia ◽  
Yong Qin ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
High Speed Train ◽  
Sensor Fault ◽  
Diagnosis Method

A Fault Diagnosis Method for the Roller-Marks in Offset Printing Machine Based on Texture Recognition

2012 ◽  
Vol 262 ◽  
pp. 361-366
Author(s):  
Zhuo Fei Xu ◽  
Hai Yan Zhang ◽  
Ling Hui Ren
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
Solution Method ◽  
Offset Printing ◽  
Texture Recognition ◽  
Defect Image ◽  
Diagnosis Method ◽  
The Difference ◽  
Detecting Method ◽  
Printing Machine

Roller-mark is a common problem in offset printing and its solution method is important for printing. A new detecting method of texture analysis was given in this paper. In this study, printing image was acquired with high-speed CCD. Compared the difference between printing image and standard image, a defective image was obtained. Then the reason of roller-marks was given by the texture recognition of defect image. Finally, experiments were taken to prove the feasibility and effectiveness of this new method for the roller-marks diagnosis in the offset printing machine.

Fault Detection and Discrimination of Rotating Machinery Using Frequency Symptom Parameter and Bayesian Network

2013 ◽  
Vol 470 ◽  
pp. 683-688
Author(s):  
Hai Yang Jiang ◽  
Hua Qing Wang ◽  
Peng Chen
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Bayesian Network ◽  
Frequency Domain ◽  
Evaluation Method ◽  
Roller Bearing ◽  
Rotating Machinery ◽  
Discrimination Index ◽  
Vibration Signals ◽  
Diagnosis Method

This paper proposes a novel fault diagnosis method for rotating machinery based on symptom parameters and Bayesian Network. Non-dimensional symptom parameters in frequency domain calculated from vibration signals are defined for reflecting the features of vibration signals. In addition, sensitive evaluation method for selecting good non-dimensional symptom parameters using the method of discrimination index is also proposed for detecting and distinguishing faults in rotating machinery. Finally, the application example of diagnosis for a roller bearing by Bayesian Network is given. Diagnosis results show the methods proposed in this paper are effective.

scholarly journals A Semi-Quantitative Information Based Fault Diagnosis Method for the Running Gears System of High-Speed Trains

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 38168-38178 ◽  
Author(s):  
Chao Cheng ◽  
Xinyu Qiao ◽  
Hao Luo ◽  
Wanxiu Teng ◽  
Mingliang Gao ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
Quantitative Information ◽  
High Speed Trains ◽  
Diagnosis Method
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