Fault Diagnosis of Construction Elevator Based on Fuzzy Recognition

2012 ◽  
Vol 529 ◽  
pp. 459-462
Author(s):  
Li Mei Liu ◽  
Jian Bin Li
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Relation ◽  
Recognition Method ◽  
Diagnosis System ◽  
Fault Diagnosis System ◽  
Fuzzy Relation Matrix ◽  
Fuzzy Recognition ◽  
Fuzzy Vector ◽  
Relation Matrix

Fault eigenvector, fault fuzzy vector and fuzzy relation matrix of the construction elevator is built on using the fuzzy recognition method in the fault diagnosis system of the elevator. On the basis of every fault membership obtained through fuzzy recognition, the equipment fault is confirmed according to max membership principle. The test shows it can effectively help to estimate cause of fault and to avoid the accidents when the fuzzy recognition method is used.

Fault Diagnosis of Shearer Based on Fuzzy Inference

2011 ◽  
Vol 52-54 ◽  
pp. 1577-1580 ◽  
Author(s):  
Feng Gao ◽  
Lin Jing Xiao ◽  
Wei Yan Zhong ◽  
Wei Liu
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Inference ◽  
Characteristic Parameter ◽  
Fuzzy Relation ◽  
Inference System ◽  
Knowledge Expression ◽  
Human Thinking ◽  
Fuzzy Relation Matrix ◽  
Fuzzy Vector ◽  
Relation Matrix

The purpose of this study is to provide a correct and timely diagnosis mechanism of shearer failures by knowledge acquisition through a fuzzy inference system which could approximate expert experience. Concerning a question of uncertain knowledge expression and reasoning in shearer malfunction, the fuzzy inference theory is used in shearer malfunction fault diagnosis. The fuzzy relation matrix of faults and signs is deduced based on deep research of failure mechanism and expert experience, which agrees with fault and fault symptoms non one-to-one relationship and human thinking. Fault characteristic parameter is calculated to corresponding subordinate degree, then is operated with fuzzy relation matrix and get fault fuzzy vector. Finally, the shearer malfunction fault is diagnosed according to certain diagnosis principle. The example proves that the method has less calculation, explicit conclusion and other merits.

scholarly journals Fault Diagnosis Based on Fuzzy Relation Matrix and Recognition

1999 ◽  
Vol 32 (2) ◽  
pp. 7844-7848
Author(s):  
Ying Huo ◽  
Chaozhen Hou ◽  
Shuangxi Liu
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Relation ◽  
Fuzzy Relation Matrix ◽  
Relation Matrix

Study on Remote Control and Fault Diagnosis for Ultrahigh Speed Grinding

2007 ◽  
Vol 359-360 ◽  
pp. 518-522
Author(s):  
Wan Shan Wang ◽  
Tian Biao Yu ◽  
Xing Yu Jiang ◽  
Jian Yu Yang
Keyword(s):  
Remote Control ◽  
Fault Diagnosis ◽  
Knowledge Acquisition ◽  
Rough Set ◽  
Theoretical Research ◽  
Reduction Rule ◽  
Diagnosis System ◽  
Linear Speed ◽  
Fault Diagnosis System ◽  
Diagnosis Model

Remote control and fault diagnosis of ultrahigh speeding grinding is studied, which is based on the theory of rough set. Knowledge acquisition and reduction rule of fault diagnosis, realization method of remote control for ultrahigh speed grinding are studied, diagnosis model is established. Based on the theoretical research and ultrahigh speed grinder with a linear speed of 250 m/s, the remote control and fault diagnosis system of ultrahigh speed grinding is developed. Results of the system running show that the environment is improved, the mental pressure of workers is relieved and the efficiency is improved. At the same time, it proves that the ability to diagnosis and the accuracy of diagnosis for the ultrahigh speed grinding are improved and the time for diagnosis is shortened by applying rough set.

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