scholarly journals An Improved Threshold Determination Method Based on PSO Algorithm for Sensor Fault Diagnosis

2019 ◽  
Author(s):  
Yao Li ◽  
◽  
Hanling Xu ◽  
Chunyan Hu ◽  
◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Pso Algorithm ◽  
Determination Method ◽  
Sensor Fault ◽  
Threshold Determination

scholarly journals Sensor Fault Diagnosis Based on Adaptive Arc Fuzzy DBN-Petri Net

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 20305-20317
Author(s):  
Shenglei Zhao ◽  
Jiming Li ◽  
Xuezhen Cheng
Keyword(s):  
Fault Diagnosis ◽  
Petri Net ◽  
Sensor Fault

scholarly journals Vibration Monitoring for Position Sensor Fault Diagnosis in Brushless DC Motor Drives

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2248
Author(s):  
Dimitrios A. Papathanasopoulos ◽  
Konstantinos N. Giannousakis ◽  
Evangelos S. Dermatas ◽  
Epaminondas D. Mitronikas
Keyword(s):  
Fault Diagnosis ◽  
Harmonic Component ◽  
Motor Drives ◽  
Brushless Dc Motor ◽  
Position Sensor ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Brushless Dc ◽  
Non Invasive ◽  
Dc Motor Drives

A non-invasive technique for condition monitoring of brushless DC motor drives is proposed in this study for Hall-effect position sensor fault diagnosis. Position sensor faults affect rotor position feedback, resulting in faulty transitions, which in turn cause current fluctuations and mechanical oscillations, derating system performance and threatening life expectancy. The main concept of the proposed technique is to detect the faults using vibration signals, acquired by low-cost piezoelectric sensors. With this aim, the frequency spectrum of the piezoelectric sensor output signal is analyzed both under the healthy and faulty operating conditions to highlight the fault signature. Therefore, the second harmonic component of the vibration signal spectrum is evaluated as a reliable signature for the detection of misalignment faults, while the fourth harmonic component is investigated for the position sensor breakdown fault, considering both single and double sensor faults. As the fault signature is localized at these harmonic components, the Goertzel algorithm is promoted as an efficient tool for the harmonic analysis in a narrow frequency band. Simulation results of the system operation, under healthy and faulty conditions, are presented along with the experimental results, verifying the proposed technique performance in detecting the position sensor faults in a non-invasive manner.

An Adaptive Multi-Sensor Fault Diagnosis Method for High-Speed Train Traction Converters

2020 ◽  
pp. 1-1
Author(s):  
Honghui Dong ◽  
Fuzhao Chen ◽  
zhipeng wang ◽  
Limin Jia ◽  
Yong Qin ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
High Speed Train ◽  
Sensor Fault ◽  
Diagnosis Method

Investigation of unknown input observer for sensor fault diagnosis for a CSTR process

2021 ◽  
Author(s):  
V. Kamatchi Kannan ◽  
R. Srimathi ◽  
V. Gomathi ◽  
R. Valarmathi ◽  
L.T. PrithiEkammai
Keyword(s):  
Fault Diagnosis ◽  
Unknown Input ◽  
Unknown Input Observer ◽  
Sensor Fault

scholarly journals Sensor Fault Diagnosis

2016 ◽  
Vol 3 (1-2) ◽  
pp. 1-248 ◽  
Author(s):  
Vasso Reppa ◽  
Marios M Polycarpou ◽  
Christos G. Panayiotou
Keyword(s):  
Fault Diagnosis ◽  
Sensor Fault

Isolability of faults in sensor fault diagnosis

2011 ◽  
Vol 25 (7) ◽  
pp. 2733-2744 ◽  
Author(s):  
Reza Sharifi ◽  
Reza Langari
Keyword(s):  
Fault Diagnosis ◽  
Sensor Fault

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

Online sensor fault diagnosis for robust chiller sequencing control

2010 ◽  
Vol 49 (3) ◽  
pp. 589-602 ◽  
Author(s):  
Yongjun Sun ◽  
Shengwei Wang ◽  
Gongsheng Huang
Keyword(s):  
Fault Diagnosis ◽  
Sensor Fault ◽  
Online Sensor
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