scholarly journals Performance Assessment for Process Monitoring and Fault Detection Methods

2016 ◽  
Author(s):  
Kai Zhang
Keyword(s):  
Fault Detection ◽  
Performance Assessment ◽  
Process Monitoring ◽  
Detection Methods

scholarly journals NARX NETWORK BASED DATA-DRIVEN ALGORITHM FOR DETECTION OF TRAY FAULTS IN NONLINEAR DYNAMIC DISTILLATION COLUMN

2020 ◽  
Vol 82 (5) ◽  
Author(s):  
Syed Ali Ammar Taqvi ◽  
Haslinda Zabiri ◽  
Lemma Dendena Tufa ◽  
Fahim Uddin ◽  
Syeda Anmol Fatima ◽  
...  
Keyword(s):  
Fault Detection ◽  
Process Monitoring ◽  
Nonlinear Dynamic ◽  
Distillation Column ◽  
Fault Detection And Diagnosis ◽  
Data Driven ◽  
Detection Methods ◽  
Maintenance Cost ◽  
Monitoring And Control ◽  
Process Industries

Efficient monitoring of highly complex process industries is essential for better management, safer operations and high-quality production. Timely detection of various faults helps to improve the performance of the complex industries, prevent various unfavorable consequences and reduce the maintenance cost. Fault Detection and Diagnosis (FDD) for process monitoring and control has been an active field of research for the past two decades. Distillation columns are inherently nonlinear, and thus to have an accurate and robust performance, the fault detection methods should be based on nonlinear dynamic methods. The paper presents a robust data-driven fault detection approach for realistic tray upsets in the distillation column. The detection of tray faults in the distillation column is conducted by Nonlinear AutoRegressive with eXogenous Input (NARX) network with Tapped Delay Lines (TDL). Aspen Plus® Dynamic simulation has been used to generate normal and faulty datasets. The study shows that the proposed method can be used for the detection of tray faults in distillation column for dynamic process monitoring. The performance of the proposed method has been evaluated by the Missed Detection Rate (MDR) and the Detection Delay (DD).

Fault Detection Methods for Interconnects in Reconfigurable Hardware

2014 ◽  
Vol 2 (4) ◽  
pp. 12-19
Author(s):  
Pradeep C ◽  
◽  
Radhakrishnan R ◽  
Keyword(s):  
Fault Detection ◽  
Reconfigurable Hardware ◽  
Detection Methods

scholarly journals Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework

2020 ◽  
Author(s):  
Muhammad Nawaz ◽  
Abdulhalim Shah Maulud ◽  
Haslinda Zabiri ◽  
Syed Ali Ammar Taqvi ◽  
Alamin Idris
Keyword(s):  
Fault Detection ◽  
Process Monitoring

scholarly journals A Comparative Study on Fault Detection Methods for Gas Turbine Combustion Systems

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 389
Author(s):  
Jinfu Liu ◽  
Zhenhua Long ◽  
Mingliang Bai ◽  
Linhai Zhu ◽  
Daren Yu
Keyword(s):  
Fault Detection ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Detection Methods ◽  
Distribution Model ◽  
Outlet Temperature ◽  
Combustion System ◽  
Comparison Results ◽  
Gas Turbine Combustion

As one of the core components of gas turbines, the combustion system operates in a high-temperature and high-pressure adverse environment, which makes it extremely prone to faults and catastrophic accidents. Therefore, it is necessary to monitor the combustion system to detect in a timely way whether its performance has deteriorated, to improve the safety and economy of gas turbine operation. However, the combustor outlet temperature is so high that conventional sensors cannot work in such a harsh environment for a long time. In practical application, temperature thermocouples distributed at the turbine outlet are used to monitor the exhaust gas temperature (EGT) to indirectly monitor the performance of the combustion system, but, the EGT is not only affected by faults but also influenced by many interference factors, such as ambient conditions, operating conditions, rotation and mixing of uneven hot gas, performance degradation of compressor, etc., which will reduce the sensitivity and reliability of fault detection. For this reason, many scholars have devoted themselves to the research of combustion system fault detection and proposed many excellent methods. However, few studies have compared these methods. This paper will introduce the main methods of combustion system fault detection and select current mainstream methods for analysis. And a circumferential temperature distribution model of gas turbine is established to simulate the EGT profile when a fault is coupled with interference factors, then use the simulation data to compare the detection results of selected methods. Besides, the comparison results are verified by the actual operation data of a gas turbine. Finally, through comparative research and mechanism analysis, the study points out a more suitable method for gas turbine combustion system fault detection and proposes possible development directions.

Comparison of fault detection methods for a hydraulic accumulator loading circuit

2020 ◽  
Author(s):  
Kurt Pichler ◽  
Rainer Haas ◽  
Christian Kastl ◽  
Andreas Plockinger ◽  
Paul Foschum
Keyword(s):  
Fault Detection ◽  
Detection Methods ◽  
Hydraulic Accumulator
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