Research on Elevator Fault Information Extraction and Prediction Diagnosis

Author(s):  
Xiaomei Jiang ◽  
Michael Namokel ◽  
Chaobin Hu ◽  
Ran Tian
Author(s):  
Xiaoli Xu ◽  
Xiuli Liu

Due to the influence of random wind shear in the atmospheric phenomenon, the random vibration of the main shaft of the wind turbine generator is generated. This vibration signal will be mixed with the misalignment signal of the high-speed shaft, which will cause interference to the fault diagnosis. Based on the analysis of the phenomenon of wind shear and the fault, the independent component analysis was carried out on the high-speed shaft mixed vibration signals on the basis of using rapid fixed point algorithm based on kurtosis, and the weak fault information is extracted successfully. At the same time, this method was compared with the weak information extraction method based on wavelet denoising, which proved the superiority of the proposed method. The experimental results show that the method has good field applicability and has a good application prospect in the field of weak information extraction for rotating machinery of wind power generation.


2013 ◽  
Vol 631-632 ◽  
pp. 1457-1460
Author(s):  
Wei Jin Ma ◽  
Mi Rui Wang ◽  
Feng Lan Li ◽  
Jun Yuan Wang

The wavelet and EMD method are taken in order to accurately extract the fault information from the audio signal with a lot of noise. The bearings were studied for the object. This paper proposed a method based on wavelet and EMD frequency characteristics of the acoustic signal information extraction, and the method used in bearing fault feature extraction. The experimental results show that: the method can effectively extract the fault characteristic frequency of bearing.


2013 ◽  
Vol 7 (2) ◽  
pp. 574-579 ◽  
Author(s):  
Dr Sunitha Abburu ◽  
G. Suresh Babu

Day by day the volume of information availability in the web is growing significantly. There are several data structures for information available in the web such as structured, semi-structured and unstructured. Majority of information in the web is presented in web pages. The information presented in web pages is semi-structured.  But the information required for a context are scattered in different web documents. It is difficult to analyze the large volumes of semi-structured information presented in the web pages and to make decisions based on the analysis. The current research work proposed a frame work for a system that extracts information from various sources and prepares reports based on the knowledge built from the analysis. This simplifies  data extraction, data consolidation, data analysis and decision making based on the information presented in the web pages.The proposed frame work integrates web crawling, information extraction and data mining technologies for better information analysis that helps in effective decision making.   It enables people and organizations to extract information from various sourses of web and to make an effective analysis on the extracted data for effective decision making.  The proposed frame work is applicable for any application domain. Manufacturing,sales,tourisum,e-learning are various application to menction few.The frame work is implemetnted and tested for the effectiveness of the proposed system and the results are promising.


Sign in / Sign up

Export Citation Format

Share Document