scholarly journals New Model-Based Fault Detection Approach using Black Box Observer

2019 ◽  
Vol 3 (1) ◽  
pp. 42-51
Author(s):  
M. Abdullah Eissa ◽  
R. R. Darwish ◽  
A. M. Bassiuny
Keyword(s):  
Fault Detection ◽  
Black Box ◽  
New Model ◽  
Model Based ◽  
Detection Approach

A semantic model-based fault detection approach for building energy systems

2021 ◽  
pp. 108548
Author(s):  
Tingting Li ◽  
Yang Zhao ◽  
Chaobo Zhang ◽  
Kai Zhou ◽  
Xuejun Zhang
Keyword(s):  
Fault Detection ◽  
Energy Systems ◽  
Building Energy ◽  
Semantic Model ◽  
Model Based ◽  
Detection Approach ◽  
Building Energy Systems

Hidden Markov Model-Based Fault Detection Approach for a Multimode Process

2016 ◽  
Vol 55 (16) ◽  
pp. 4613-4621 ◽  
Author(s):  
Fan Wang ◽  
Shuai Tan ◽  
Yawei Yang ◽  
Hongbo Shi
Keyword(s):  
Fault Detection ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Model Based ◽  
Detection Approach

scholarly journals A new model-based approach for power plant Tube-ball mill condition monitoring and fault detection

2014 ◽  
Vol 80 ◽  
pp. 10-19 ◽  
Author(s):  
Shen Guo ◽  
Jihong Wang ◽  
Jianlin Wei ◽  
Paschalis Zachariades
Keyword(s):  
Power Plant ◽  
Fault Detection ◽  
Condition Monitoring ◽  
Ball Mill ◽  
New Model ◽  
Model Based

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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