Utility of Projection Network for Air-Craft-Engine Fault Diagnosis

2004 ◽  
Author(s):  
Chaiyakorn Jansuwan ◽  
C. James Li
Keyword(s):  
Network Architecture ◽  
Power Plants ◽  
Dynamic Network ◽  
Aircraft Engine ◽  
Parameter Tuning ◽  
Critical Systems ◽  
Safety And Reliability ◽  
Compressor Inlet ◽  
Detection And Diagnosis ◽  
Projection Network

Turbine engines are frequently used in critical systems including the power plants and propulsion systems of aircrafts and ships. Frequent inspection and periodic maintenance have been necessary to ensure their proper functionality. Condition based maintenance of jet engines can significantly reduce their operational and maintenance costs, and, in the mean time, enhance safety and reliability. This study investigates the feasibility of establishing the utility of a dynamic network, i.e., projection network, to recognize hot air pass faults from measurements of e.g., fan speed, core speed, compressor inlet and exit temperatures and pressures, turbine exit temperatures, etc. Projection network is a nonlinear dynamic network architecture that provides stable oscillatory or non-oscillatory attractors. In contrast to the static mapping provided by e.g., neural networks and fuzzy systems, the projection network offers more functionality through its rich dynamics. When properly setup, its nonlinear dynamics can filter out noise from measurements, and classify/recognize complex patterns. This study established the utility of projection network for detection and diagnosis of several aircraft engine faults. This paper will also describe methods for both structure training and parameter tuning. Using these methods, projection networks were setup to recognize baseline, fan damage, high pressure turbine fault, and customer bleed valve fault.

Verification of FPGA Based NPP I&C Systems Considering Multiple Faults: Technique and Automation Tool

2017 ◽  
Author(s):  
Alexander Yasko ◽  
Eugene Babeshko ◽  
Vyacheslav Kharchenko
Keyword(s):  
Power Plants ◽  
Failure Modes ◽  
Fault Injection ◽  
Reliability Assessment ◽  
International Standards ◽  
Verification And Validation ◽  
Critical Systems ◽  
Multiple Faults ◽  
Safety And Reliability ◽  
Detailed Technique

Instrumentation and Control (I&C) systems for Nuclear Power Plants (NPP) are exceedingly complicated electronic solutions that include thousands of different components such as microcontrollers, Field-Programmable Gate Arrays (FPGAs), integrated circuits etc. Deployment of such safety-critical systems cannot be performed without complex safety and reliability assessment, verification and validation (V&V) activities that are addressed to exposing of overlooked faults. The examples of such activities are Fault Tree Analysis (FTA), Failure Modes and Effects Analysis (FMEA), Fault Injection Testing (FIT). Due to complexity of NPP I&C systems in most cases the process of assessment is very time consuming and the results mostly depend on experts’ qualification. Traditional safety and reliability assessment methods are being constantly modified and enhanced so as to comply with increasing demands of national and international standards and guidance, as well as to be applied for I&C systems that contain number of complex components like FPGA. Although much work related to analysis of FPGA-based systems has been performed, there is a lack of detailed technique for FPGA-based I&C systems failure identification that considers probability of several faults at the same time (multi-faults), development of preventive strategies for controlling or reducing of the risk related to such failures, as well as automation of this technique so as to make it utilizable for real NPP industry tasks. FIT as verification for Failure Modes, Effects and Diagnostics Analysis (FMEDA) was used during Safety Integrity Level 3 (SIL3) certification process of RadICS NPP I&C platform, while the parts of proposed technique were used as internal verification and validation activities applied on several modules of the platform.

scholarly journals Safety and Reliability Assessment of NPP Instrumentation and Control Systems Considering Different Communication Architectures

2020 ◽  
pp. 38-43
Author(s):  
E. Babeshko ◽  
O. Illiashenko ◽  
V. Kharchenko ◽  
E. Ruchkov
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Reliability Assessment ◽  
Assessment Model ◽  
Analytical Models ◽  
Critical Systems ◽  
Safety Critical ◽  
Communication Architectures ◽  
Safety And Reliability ◽  
And Control

Safety and reliability assessment of instrumentation and control (I&C) systems used in different safety-critical industries is a responsible and challenging task. Different assessment models recommended by international and national regulatory documents and used by experts worldwide still have disadvantages and limitations. Therefore, studies of assessment model improvements and refinements are essential. This paper proposes that the assessment models be improved by taking into account different architectures of communications both between different systems and within one particular system. In most models, communication lines are considered absolutely reliable, but the analysis performed shows that the communications should be necessarily addressed. Several analytical models are described to assess the reliability of safety-critical systems for nuclear power plants with different communication options.

Recent Patents on Valve Mechanism Device

2020 ◽  
Vol 13 (3) ◽  
pp. 230-241
Author(s):  
Ye Dai ◽  
Hui-Bing Zhang ◽  
Yun-Shan Qi
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Flow Direction ◽  
Research Progress ◽  
Valve Mechanism ◽  
Advantages And Disadvantages ◽  
Valve Structure ◽  
Valve Leakage ◽  
Safety And Reliability

Background: Valves are an important part of nuclear power plants and are the control equipment used in nuclear power plants. It can change the cross-section of the passage and the flow direction of the medium and has the functions of diversion, cutoff, overflow, and the like. Due to the earthquake, the valve leaks, which will cause a major nuclear accident, endangering people's lives and safety. Objective: The purpose of this study is to synthesize the existing valve devices, summarize and analyze the advantages and disadvantages of various devices from many literatures and patents, and solve some problems of existing valves. Methods: This article summarizes various patents of nuclear-grade valve devices and recent research progress. From the valve structure device, transmission device, a detection device, and finally to the valve test, the advantages and disadvantages of the valve are comprehensively analyzed. Results: By summarizing the characteristics of a large number of valve devices, and analyzing some problems existing in the valves, the outlook for the research and design of nuclear power valves was made, and the planning of the national nuclear power strategic goals and energy security were planned. Conclusion: Valve damage can cause serious safety accidents. The most common is valve leakage. Therefore, the safety and reliability of valves must be taken seriously. By improving the transmission of the valve, the problems of complicated valve structure and high cost are solved.

scholarly journals Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 955
Author(s):  
Zhiyuan Li ◽  
Ershuai Peng
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Dynamic Network ◽  
Parameter Tuning ◽  
Global Optimum ◽  
Research Field ◽  
Edge Computing ◽  
Transmission Delay ◽  
Smart Vehicles ◽  
Network Bandwidth

With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks.

Temperature Measurement Applications in Power Plants

2009 ◽  
Author(s):  
Ravi Jethra
Keyword(s):  
Power Plant ◽  
Temperature Measurement ◽  
Power Plants ◽  
New Technologies ◽  
Measurement Information ◽  
Safety Integrity Level ◽  
Safety And Reliability ◽  
Technical Advances ◽  
Incorrect Measurement ◽  
Major Equipment

Temperature is one of the most widely measured parameters in a power plant. Temperature is monitored and also used for control in some areas. The paper covers some of the basics of Temperature measurement, and leads into some of the technical advances that impart higher a degree of safety and reliability to power plant operation. These advances are based on some of the latest and innovative technologies that are being implemented in process instrumentation. Irrespective of the type of power plant (coal-fired, Oil or gas based), temperature measurement remains high on the list for operational excellence throughout the plant. Implementation of some of the new technologies results in improved Safety and lower installation and maintenance costs. Incorrect measurement information due to temperature effects, non linearity or stability can result in major equipment getting damaged. Ensuring instruments that have minimal downtime from a maintenance standpoint, not just devices that have been evaluated to provide Safety Integrity Level service in Safety Instrumented Systems, is crucial for daily operations in a power plant.

Fault diagnosis through Ferrography (Wear Particle Analysis)

2021 ◽  
pp. 303-322
Author(s):  
Anadi Sinha
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Wear Particle ◽  
Stage Ii ◽  
Lubricating Oil ◽  
Particle Analysis ◽  
Wear Particle Analysis ◽  
Analysis Technique ◽  
Detection And Diagnosis

The purpose of Plant Predictive Maintenance (PDM) programme is to improve Reliability of machineries through early detection and diagnosis of equipment problems, and degradation prior to equipment failure. Ferrography (Wear Particle Analysis) is one of the PDM techniques which allows detection, identification and evaluation of the degradation at the very incipient stage so that degradation is timely attended and mitigatory actions initiated. Ferrography is a Wear Particle Analysis technique based upon systematic collection and analysis of sample of lubricating oil from rotating and reciprocating machines. Ferrography analysis is conducted in 2 phases: Stage I – Quantitative, and Stage II – Qualitative. After Stage II analysis, recommendation is issued based on wear rating (Normal, Marginal, or Critical) so that operator can take timely action. Presently, 21 Nuclear Power Plants are operational in India and Forced Shutdown is a very costly affair. Lube oil of around 60 equipment from Indian Nuclear Power Plants is examined quarterly for Ferrography analysis, and failure of several equipment is avoided due to timely action. This paper will elaborate on the basic principles of Ferrography, and how systematic implementation of Ferrography has helped in avoiding forced failure of equipment, and hence prevent Forced Shutdown.

Fourier Neural Networks and Generalized Single Hidden Layer Networks in Aircraft Engine Fault Diagnostics

2005 ◽  
Vol 128 (4) ◽  
pp. 773-782 ◽  
Author(s):  
H. S. Tan
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Fourier Transforms ◽  
Aircraft Engine ◽  
Fault Classification ◽  
Noise Robustness ◽  
Fault Diagnostics ◽  
Multiple Faults ◽  
Hidden Layer

The conventional approach to neural network-based aircraft engine fault diagnostics has been mainly via multilayer feed-forward systems with sigmoidal hidden neurons trained by back propagation as well as radial basis function networks. In this paper, we explore two novel approaches to the fault-classification problem using (i) Fourier neural networks, which synthesizes the approximation capability of multidimensional Fourier transforms and gradient-descent learning, and (ii) a class of generalized single hidden layer networks (GSLN), which self-structures via Gram-Schmidt orthonormalization. Using a simulation program for the F404 engine, we generate steady-state engine parameters corresponding to a set of combined two-module deficiencies and require various neural networks to classify the multiple faults. We show that, compared to the conventional network architecture, the Fourier neural network exhibits stronger noise robustness and the GSLNs converge at a much superior speed.

FMEDA and FIT-Based Safety Assessment of NPP I&C Systems Considering Expert Uncertainty

2018 ◽  
Author(s):  
Alexander Yasko ◽  
Eugene Babeshko ◽  
Vyacheslav Kharchenko
Keyword(s):  
Emotional Disorders ◽  
Nuclear Power ◽  
Safety Assessment ◽  
Failure Modes ◽  
Reliability Assessment ◽  
Software Tool ◽  
Critical Systems ◽  
System Specification ◽  
Multiple Faults ◽  
Safety And Reliability

The complexity of modern safety critical systems is becoming higher with technology level growth. Nowadays the most important and vital systems of automotive, aerospace, nuclear industries count millions of lines of software code and tens of thousands of hardware components and sensors. All of these constituents operate in integrated environment interacting with each other — this leads to enormous calculation task when testing and safety assessment are performed. There are several formal methods that are used to assess reliability and safety of NPP I&C (Nuclear Power Plant Instrumentation and Control) systems. Most of them require significant involvement of experts and confidence in their experience which vastly affects trustworthiness of assessment results. The goal of our research is to improve the quality of safety and reliability assessment as result of experts involvement mitigation by process automation. We propose usage of automated FMEDA (Failure Modes, Effects and Diagnostic Analysis) and FIT (Fault Insertion Testing) combination extended whith multiple faults approach as well as special methods for quantitative assessment of experts involvement level and their decisions uncertainty. These methods allow to perform safety and reliability assessment without specifying the degree of confidence in experts. Traditional FMEDA approach has several bottlenecks like the need of manual processing of huge number of technical documents (system specification, datasheets etc.), manual assignment of failure modes and effects based on personal experience. Human factor is another source of uncertainty. Such things like tiredness, emotional disorders, distraction or lack of experience could be the reasons of under- and over-estimation. Basing on our research in field of expert-related errors we propose expert involvement degree (EID) metric that indicates the level of technique automation and expert uncertainty degree (EUD) metric which is complex measure of experts decisions uncertainty within assessment. We propose usage of total expert trustworthiness degree (ETD) indicator as function of EID and EUD. Expert uncertainty assessment and Multi-FIT as FMEDA verification are implemented in AXMEA (Automated X-Modes and Effects Analysis) software tool. Proposed Multi-FIT technique in combination with FMEDA was used during internal activities of SIL3 certification of FPGA-based (Field Programmable Gate Array) RadICS platform for NPP I&C systems. The proposed expert trustworthiness degree calculation is going to be used during production activities of RPC Radiy (Research and Production Corporation). Our future work is related to research in expert uncertainty field and extension of AXMEA tool with new failure data sources as well as software optimization and further automation.

scholarly journals Redesigning a compressor inlet guide vane for 0 to 60 degree stagger angles

2021 ◽  
Author(s):  
Stephanie Waters
Keyword(s):  
Fuel Consumption ◽  
Guide Vane ◽  
Leading Edge ◽  
Aircraft Engine ◽  
Inlet Guide Vane ◽  
Pressure Loss Coefficient ◽  
Compressor Inlet ◽  
Curvature Distribution ◽  
Stagger Angle ◽  
Total Pressure Loss Coefficient

This report's objective is to reduce the total pressure loss coefficient of an inlet guide vane (IGV) at high stagger angles and to therefore reduce the overall fuel consumption of an aircraft engine. IGVs are usually optimized for cruise where the stagger angle is approximately 0 degrees. To reduce losses, four different methodologies were tested: increasing the leading edge radius, increasing the camber, creating a "drooped nose", and creating an "S" curvature distribution. A baseline IGV was chosen and modified using these methodologies to create 10 new IGV designs. CFX was used to perform a CFD analysis on all 11 IGV designs at 5 stagger angles from 0 to 60 degrees. Typical missions were analyzed and it was discovered that the new designs decreased the fuel consumption of the engine. The IGV with the "S" curvature and thicker leading edge was the best and decreased the fuel consumption by 0.24%.

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