Fault Detection Using Kernel Computational Intelligence Algorithms

2018 ◽  
pp. 263-281
Author(s):  
Adrián Rodríguez-Ramos ◽  
José Manuel Bernal-de-Lázaro ◽  
Antônio José Silva Neto ◽  
Orestes Llanes-Santiago
Keyword(s):  
Fault Detection ◽  
Computational Intelligence

Computational Intelligence Techniques to Fault Detection in the Semiconductor Manufacturing Process

2011 ◽  
Vol 52-54 ◽  
pp. 1171-1176 ◽  
Author(s):  
Kittisak Kerdprasop ◽  
Nittaya Kerdprasop
Keyword(s):  
Fault Detection ◽  
Process Control ◽  
High Precision ◽  
Computational Intelligence ◽  
Manufacturing Process ◽  
Semiconductor Manufacturing ◽  
Semiconductor Industry ◽  
Classification Model ◽  
Minimal Set ◽  
Margin Of Error

The semiconductor industry deals with the production at a scale of nanometer, thus resulting in the process control with little margin of error. Timely detection of faults during the manufacturing process is critical to the improvement in product yields. Difficulty of detecting accurately faulty processes and products is due to the abundant of data obtained from hundreds of tool-state and process-state sensors. We thus analyze this problem through the computational intelligence techniques. The analysis results reveal the minimal set of features for fault detection as well as the high precision classification model of faults.

scholarly journals High-impedance fault detection in medium-voltage distribution network using computational intelligence-based classifiers

2019 ◽  
Vol 31 (12) ◽  
pp. 9127-9143 ◽  
Author(s):  
Veerapandiyan Veerasamy ◽  
Noor Izzri Abdul Wahab ◽  
Rajeswari Ramachandran ◽  
Mariammal Thirumeni ◽  
Chitra Subramanian ◽  
...  
Keyword(s):  
Fault Detection ◽  
Computational Intelligence ◽  
Distribution Network ◽  
Voltage Distribution ◽  
Medium Voltage ◽  
High Impedance ◽  
High Impedance Fault

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

2011 ◽  
Vol 9 (4) ◽  
pp. 522-527 ◽  
Author(s):  
Lucca Zamboni ◽  
Ivan Nunes da Silva ◽  
Leandro Nascimento Soares ◽  
Ricardo Augusto Souza Fernandes
Keyword(s):  
Fault Detection ◽  
Computational Intelligence ◽  
Power Distribution ◽  
Distribution Systems ◽  
Power Distribution Systems

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.

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