HARDWARE IMPLEMENTATION USING XSG OF NEW FAULT DETECTION METHOD APPLIED TO ROBOT MANIPULATOR

2020 ◽  
Vol 48 (1) ◽  
Author(s):  
Abdel O. Ghrieb ◽  
Yahia Kourd ◽  
Kamel Messaoudi ◽  
Djamel M. Mouss ◽  
Toufik Bakir
Keyword(s):  
Fault Detection ◽  
Hardware Implementation ◽  
Detection Method ◽  
Robot Manipulator

scholarly journals Analysis of the Effects of Arc Volt–Ampere Characteristics on Different Loads and Detection Methods of Series Arc Faults

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 323 ◽  
Author(s):  
Qiwei Lu ◽  
Zeyu Ye ◽  
Yilei Zhang ◽  
Tao Wang ◽  
Zhixuan Gao
Keyword(s):  
Fault Detection ◽  
Research And Development ◽  
Hardware Implementation ◽  
Detection Method ◽  
Low Cost ◽  
Experimental Methods ◽  
Experimental Results ◽  
National Standard ◽  
Detection Methods ◽  
The Relationship

Owing to the shortcomings of existing series arc fault detection methods, based on a summary of arc volt–ampere characteristics, the change rule of the line current and the relationship between the voltage and current are deeply analyzed and theoretically explained under different loads when series arc faults occur. A series arc fault detection method is proposed, and the software flowchart and principles of the applied hardware implementation are given. Finally, a prototype of an arc fault detection device (AFDD) with a rated voltage of 220 V and a rated current of 40 A is developed. The prototype was tested according to experimental methods provided by the Chinese national standard, GB/T 31143-2014. The experimental results show that the proposed detection method is simple and practical, and can be implemented using a low-cost microprocessor. The proposed method will provide good theoretical guidance in promoting the research and development of an AFDD.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

A fault detection method for new PV module strufure

2010 ◽  
Vol 24 (2) ◽  
pp. 131-136 ◽  
Author(s):  
Ze Cheng ◽  
Bingfeng Li ◽  
Li Liu ◽  
Yanli Liu
Keyword(s):  
Fault Detection ◽  
Detection Method ◽  
Pv Module
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