Operational Reliability Improvement of Plants Through Intelligent Fault Detection and Diagnosis

2003 ◽  
Author(s):  
E. Ricky Odoom
Keyword(s):  
Fault Detection ◽  
Intelligent Systems ◽  
Operational Reliability ◽  
Fault Detection And Diagnosis ◽  
Complex Dynamic ◽  
Artificial Intelligent ◽  
Reliability Improvement ◽  
Process Plants ◽  
Basic Concepts ◽  
Detection And Diagnosis

Real-time Fault Detection and Diagnosis of modern dynamic process plants are continuously receiving increasing attention both theoretically and practically. In recent years, attempts have been made to apply Artificial Intelligence techniques to the Fault Detection Diagnosis task for improving the operational reliability of complex dynamic plants. The aim of this paper is to discuss the basic concepts, issues and tools of some of the emerging intelligence technologies for Fault Detection and Diagnosis schemes. The emphasis is given to the methods, which are based on Artificial Intelligent systems and which are appropriate for diagnosing faults in complex dynamic plants.

scholarly journals Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors

2021 ◽  
Vol vm02 (is01) ◽  
pp. 15-21
Author(s):  
Dinh-dung Nguyen ◽  
Hong Son Tran ◽  
Thi Thuy Tran ◽  
Dat Dang Quoc ◽  
Hong Tien Nguyen
Keyword(s):  
Fault Diagnosis ◽  
Angular Velocity ◽  
Fault Detection ◽  
Intelligent Systems ◽  
Fault Detection And Diagnosis ◽  
Process Models ◽  
State Observers ◽  
Improvement Method ◽  
Detection And Diagnosis ◽  
Sensor Detection

Angular velocity sensor detection and diagnosis become increasingly essential for the improvement of reliability, safety, and efficiency of the control system on aircraft. The classical methods for fault detection and diagnosis are limit or trend checking of some measurable output variables. Due to they do not give a deeper insight and usually do not allow a fault diagnosis, model-based methods of fault detection and diagnosis were developed by using input and output signals and applying dynamic process models. These approaches are based on parameter estimation, parity equations, or state observers. This paper presents an improvement method to build algorithm fault diagnosis for angular velocity sensors on aircraft. Based on proposed method, results of paper can be used in designed intelligent systems that can automatically fault detection on aircraft.

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