Automatic zero sequence fault monitoring and diagnosis analysis

2020 ◽  
Vol 2 (1) ◽  
pp. 8-16
Author(s):  
Chen Xiufen
Keyword(s):  
Monitoring And Diagnosis ◽  
Fault Monitoring ◽  
Zero Sequence

Implementation of a research prototype onboard fault monitoring and diagnosis system

1987 ◽  
Author(s):  
MICHAEL PALMER ◽  
KATHY ABBOTT ◽  
PAUL SCHUTTE ◽  
WENDELL RICKS
Keyword(s):  
Diagnosis System ◽  
Monitoring And Diagnosis ◽  
Fault Monitoring ◽  
Research Prototype

General Fault Monitoring and Diagnosis Expert System Based on Fault Tree and Multi-Sensor Information

2011 ◽  
Vol 121-126 ◽  
pp. 4481-4485
Author(s):  
Ai Yu Zhang ◽  
Xiao Guang Zhao ◽  
Lei Zhang
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Expert Knowledge ◽  
Sensor Failure ◽  
Fault Trees ◽  
Intelligent Algorithms ◽  
Monitoring And Diagnosis ◽  
Backward Reasoning ◽  
Fault Monitoring ◽  
Sensor Information

Due to the limited generality of traditional fault diagnosis expert system and its low accuracy of extracting failure symptoms, a general fault monitoring and diagnosis expert system has been built. For different devices, users can build fault trees in an interactive way and then the fault trees will be saved as expert knowledge. A variety of sensors are fixed to monitor the real-time condition of the device and intelligent algorithms such as wavelet transform and neural network are used to assist the extraction of failure symptoms. On the basis of integration of multi-sensor failure symptoms, the fault diagnosis is realized through forward and backward reasoning. The simulation diagnosis experiments of NC device have shown the effectiveness of the proposed method.

scholarly journals A New Hybrid "Park's Vector - Time Synchronous Averaging" Approach to the Induction Motor-fault Monitoring and Diagnosis

2014 ◽  
Vol 9 (2) ◽  
pp. 559-568 ◽  
Author(s):  
Nabil Ngote ◽  
Said Guedira ◽  
Mohamed Cherkaoui ◽  
Mohammed Ouassaid
Keyword(s):  
Induction Motor ◽  
Monitoring And Diagnosis ◽  
Fault Monitoring

Intelligent Systems in aerospace

1990 ◽  
Vol 5 (3) ◽  
pp. 147-166 ◽  
Author(s):  
Moonis Ali
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Planning And Scheduling ◽  
Monitoring And Diagnosis ◽  
Aerospace Applications ◽  
Fault Monitoring ◽  
Aerospace Systems ◽  
Operations And Maintenance ◽  
And Control ◽  
And Robotics

AbstractAn overview of research in the areas of aerospace applications of artificial intelligence, expert Systems, neural networks and robotics is presented. Challenges associated with aerospace projects require increasingly complex aerospace Systems which in turn demand automation and fault tolerance. We have addressed these issues and provided a survey of the research on intelligent Systems that has been carried out in an attempt to meet these challenges. The application areas we have overviewed include fault monitoring and diagnosis, generation and management of power in space, efficient and effective command and control, operations and maintenance of space stations, planning and scheduling, automation, and cockpit management.

AMPERES: A REAL-TIME FAULT MONITORING AND DIAGNOSIS KNOWLEDGE-BASED SYSTEM FOR SPACE POWER SYSTEMS

1991 ◽  
Vol 5 (3) ◽  
pp. 281-308 ◽  
Author(s):  
S.C. LEE ◽  
MICHELLE RATLIFF ◽  
CRAIG PETERSON ◽  
LOUIS F. LOLLAR
Keyword(s):  
Power Systems ◽  
Real Time ◽  
Knowledge Based System ◽  
Monitoring And Diagnosis ◽  
Knowledge Based ◽  
Fault Monitoring ◽  
Space Power Systems

A Flight Expert System (FLES) For On-Board Fault Monitoring And Diagnosis

1986 ◽  
Author(s):  
M. Ali ◽  
D. .. Scharnhorst ◽  
C. S. Ai ◽  
H. J. Ferber
Keyword(s):  
Expert System ◽  
Monitoring And Diagnosis ◽  
Fault Monitoring
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