scholarly journals Model-Based Fault Diagnosis System Verification Using Reachability Analysis

2019 ◽  
Vol 49 (4) ◽  
pp. 742-751 ◽  
Author(s):  
Jinya Su ◽  
Wen-Hua Chen
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu

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.


2003 ◽  
Vol 125 (1) ◽  
pp. 80-95 ◽  
Author(s):  
Kyusung Kim ◽  
Alexander G. Parlos

Early detection and diagnosis of incipient faults is desirable for on-line condition assessment, product quality assurance, and improved operational efficiency of induction motors. At the same time, reducing the probability of false alarms increases the confidence of equipment owners in this new technology. In this paper, a model-based fault diagnosis system recently proposed by the authors for induction motors is experimentally compared for fault detection and false alarm performance with a more traditional signal-based motor fault estimator. In addition to the nameplate information required for the initial set-up, the proposed model-based fault diagnosis system uses measured motor terminal currents and voltages, and motor speed. The motor model embedded in the diagnosis system is empirically obtained using dynamic recurrent neural networks, and the resulting residuals are processed using wavelet packet decomposition. The effectiveness of the model-based diagnosis system in detecting the most widely encountered motor electrical and mechanical faults, while minimizing the impact of false alarms resulting from power supply and load variations, is demonstrated through extensive testing with staged motor faults. The model-based fault diagnosis system is scalable to motors of different power ratings and it has been successfully tested with fault data from 2.2kW,373kW, and 597kW induction motors.


Author(s):  
Woohyun Hwang ◽  
Kwangjin Han ◽  
Kunsoo Huh ◽  
Jongki Kim ◽  
Joogon Kim ◽  
...  

The brake-by-wire units such as EMB (Electro-Mechanical Brake) will be applied to the intelligent vehicles because the brake-by-wire units are lighter in weights and have faster response compared to conventional hydraulic brake units. However, the brake-by-wire units such as EMB should be at least as reliable as the conventional hydraulic brake units. Because there are no mechanical links between the brake pedal and brake-by-wire actuators, FDI (Fault detection and isolation) is essential in implementing EMB units. In this study, a model-based fault diagnosis system is developed for monitoring the brake status utilizing the analytical redundancy method. The performance of the proposed model-based fault diagnosis system is verified in simulations in various faulty cases.


2008 ◽  
Author(s):  
Kunsoo Huh ◽  
Kwangjin Han ◽  
Daegun Hong ◽  
Joogon Kim ◽  
Hyungjin Kang ◽  
...  

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