Hybrid System Model Based Fault Diagnosis of Automotive Engines

2018 ◽  
pp. 153-178
Author(s):  
E. P. Nadeer ◽  
S. Mukhopadhyay ◽  
A. Patra
Keyword(s):  
Fault Diagnosis ◽  
Hybrid System ◽  
System Model ◽  
Automotive Engines ◽  
Model Based

scholarly journals A Hybrid System Model-Based Open-Circuit Fault Diagnosis Method of Three-Phase Voltage-Source Inverters for PMSM Drive Systems

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1251 ◽  
Author(s):  
Tao Chen ◽  
Yuedou Pan ◽  
Zhanbo Xiong
Keyword(s):  
Fault Diagnosis ◽  
Hybrid System ◽  
Open Circuit ◽  
System Model ◽  
Voltage Source ◽  
Phase Voltage ◽  
Voltage Source Inverters ◽  
Three Phase ◽  
Diagnosis Method ◽  
Drive Systems

This paper presents an open-circuit (OC) fault diagnosis method of three-phase voltage-source inverters (VSIs) for permanent magnet synchronous motor (PMSM) drive systems based on the hybrid system model (HSM). On the basis of phase voltage analysis, the HSM of the PMSM-inverter system was established, which can describe the system more accurately. To quickly diagnose whether the fault occurs, a current estimator was constructed based on the healthy HSM. Different fault types of the VSI can be simulated synchronously by the HSM, and the similarity between each simulated fault type and the actual one is evaluated based on the Euclidean distance method. Therefore, the fault isolation can be carried out according to the characteristics of Euclidean distances. The proposed method has the advantages of fast diagnosis speed and strong robustness, and it does not require additional sensors. By the presented diagnosis algorithm, the fault can be detected and isolated within a time interval about 5% and 10% of the current fundamental wave period, respectively. The simulation and experimental results verify the effectiveness of the proposed method.

On-Board Model Based Fault Diagnosis for CubeSat Attitude Control Subsystem: Flight Data Results

2021 ◽  
Author(s):  
Ryan Mackey ◽  
Allen Nikora ◽  
Cornelia Altenbuchner ◽  
Robert Bocchino ◽  
Michael Sievers ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Attitude Control ◽  
Flight Data ◽  
Control Subsystem ◽  
Model Based

Probabilistic Model-Based Fault Diagnosis of the Rotor System

2007 ◽  
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Rotating Machinery ◽  
Rotor System ◽  
Bayesian Network Model ◽  
Diagnosis System ◽  
Model Based ◽  
Core Components ◽  
Fault Diagnosis System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

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