Fault Diagnoses Using Inverse Fuzzy Model

2014 ◽  
Vol 571-572 ◽  
pp. 171-176
Author(s):  
Hui Jun Zheng ◽  
Qiao Fu
Keyword(s):  
Reliability Analysis ◽  
System Performance ◽  
Fuzzy Model ◽  
New Method ◽  
Model Method ◽  
Measured System

This paper investigates a new method of fault diagnoses and reliability analysis based on inverse fuzzy model method. The proposed method employs inverse fuzzy model solving method to estimate the component state based on the measured system performance and relationship about component state and system performance which is constructed by expert. The method is proved to be effective in fault diagnoses.

Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Reza Pourhassan ◽  
Sadigh Raissi ◽  
Arash Apornak
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Performance ◽  
Failure Process ◽  
State System ◽  
Failure Behavior ◽  
Simulation Approach ◽  
Critical System ◽  
Content Type ◽  
System Reliability Analysis

PurposeIn some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.Design/methodology/approachIn some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.FindingsThis study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.Originality/valueThe results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

A new imputation-based incomplete data-driven fuzzy modeling for accuracy improvement in ubiquitous computing applications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sonia Goel ◽  
Meena Tushir
Keyword(s):  
Parameter Estimation ◽  
Missing Data ◽  
Incomplete Data ◽  
Model Identification ◽  
Fuzzy Model ◽  
New Method ◽  
Content Type ◽  
Ubiquitous Environment ◽  
Sugeno Model ◽  
Takagi Sugeno

Purpose In real-world decision-making, high accuracy data analysis is essential in a ubiquitous environment. However, we encounter missing data while collecting user-related data information because of various privacy concerns on account of a user. This paper aims to deal with incomplete data for fuzzy model identification, a new method of parameter estimation of a Takagi–Sugeno model in the presence of missing features. Design/methodology/approach In this work, authors proposed a three-fold approach for fuzzy model identification in which imputation-based linear interpolation technique is used to estimate missing features of the data, and then fuzzy c-means clustering is used for determining optimal number of rules and for the determination of parameters of membership functions of the fuzzy model. Finally, the optimization of the all antecedent and consequent parameters along with the width of the antecedent (Gaussian) membership function is done by gradient descent algorithm based on the minimization of root mean square error. Findings The proposed method is tested on two well-known simulation examples as well as on a real data set, and the performance is compared with some traditional methods. The result analysis and statistical analysis show that the proposed model has achieved a considerable improvement in accuracy in the presence of varying degree of data incompleteness. Originality/value The proposed method works well for fuzzy model identification method, a new method of parameter estimation of a Takagi–Sugeno model in the presence of missing features with varying degree of missing data as compared to some well-known methods.

scholarly journals A method for estimating existence of pairwise STM transaction conflicts

2018 ◽  
Vol 232 ◽  
pp. 04037
Author(s):  
Miroslav Popovic ◽  
Branislav Kordic ◽  
Marko Popovic ◽  
Ilija Basicevic
Keyword(s):  
System Performance ◽  
Time Complexity ◽  
Scheduling Algorithms ◽  
False Positives ◽  
New Method ◽  
False Negatives ◽  
Transaction Scheduling ◽  
Data Races ◽  
Cost Of Time ◽  
The Cost

STM transaction schedulers were introduced to improve system performance. However, designing online transaction scheduling algorithms is challenging because at the same time they should: (i) introduce minimal scheduling overhead, (ii) minimize the resulting makespan, and (iii) minimize contention in the resulting schedule. In our previous work we developed the online transaction scheduler architecture and the four scheduling algorithms, named RR, ETLB, AC, and AAC (listed in increasing order of their quality), for scheduling transactions on the Python STM. Both AC and AAC use Bernstein conditions to check for pairwise data races between transactions, at the cost of time complexity that is proportional to the product of the sizes of transaction’s read and write sets, which may be significant. In this paper we propose a method for estimating existence of pairwise transaction conflicts whose time complexity is Θ(1). We validate this method by analysing the resulting transaction schedules for the three benchmark workloads, named RDW, CFW, and WDW. The result of this analysis is positive and encouraging – AAC using the new method produces the same result as when using Bernstein conditions. The limitation of the new method is that it may have false reports, both false negatives and false positives.

From electromagnetics to system performance: a new method for the error-rate prediction of atmospheric communications links

1997 ◽  
Vol 15 (4) ◽  
pp. 656-666 ◽  
Author(s):  
A. Vander Vorst ◽  
H. Vasseur ◽  
C. Vyncke ◽  
C. Amaya Byrne ◽  
D. Vanhoenacker-Janvier
Keyword(s):  
Error Rate ◽  
System Performance ◽  
New Method ◽  
Rate Prediction

Formulating and Solving an Optimization Problem with Heterogeneous Optimality Criteria in Evaluating the Dynamic System Performance

Vestnik MEI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 88-97
Author(s):  
Amin Kamal Abd Elraheem ◽  
◽  
Vladimir A. Shikhin ◽  
Keyword(s):  
Dynamic System ◽  
Performance Assessment ◽  
System Performance ◽  
Discrete Event ◽  
Fuzzy Model ◽  
Generalized Solution ◽  
Optimality Criteria ◽  
Performance Criteria ◽  
The Arctic ◽  
Interconnected System

An approach to formulating and solving the problem of comprehensively evaluating the dynamic system performance is proposed. A MicroGrid represented in a multi-agent system (MAS) form is taken as an example. A unified definition of agents applied to the class of dynamic systems formalized in the form of continuous, discrete and discrete-event models is introduced. The performance efficiency of both the MicroGrid and its individual components (agents) is assessed. The developed flowchart for MicroGrid performance assessment serves as a basis for optimizing the MicroGrid performance indicators in the online mode. By using the proposed solution, it becomes possible to formalize the integration of heterogeneous objective functions into unified criteria by certain types and also taking into account the performance assessments of individual components in the interconnected system. Technical, economic and environmental criteria are considered as standard performance criteria. To obtain a generalized solution with taking into account the heterogeneity of the considered efficiency criteria, a fuzzy model based on the fuzzy sets theory is proposed as a tool for convolution of these criteria. The flowchart of the algorithm for MicroGrid performance assessment is developed taking as an example the design of a hybrid-generating and environmentally safe power supply system for the Arctic enclave with a specified configuration.

Reliability analysis of a steam boiler system by expert judgment method and best-fit failure model method: a new approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Suyog Subhash Patil ◽  
Anand K. Bewoor
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Temperature Sensor ◽  
Expert Judgment ◽  
Failure Model ◽  
New Approach ◽  
Content Type ◽  
Model Method ◽  
Reliability Characteristics ◽  
Best Fit

PurposeIndia's textile industries play a vital role in the Indian economy. These industries consume the highest thermal energy (steam power). The demand of the steam in process industries is increasing rapidly, and this demand can be met by increasing the capacity utilization of steam boilers. The purpose of this paper is to present a new approach for reliability analysis by expert judgment method.Design/methodology/approachA lack of adequate life data is one of the biggest challenge in the reliability analysis of mechanical systems. This research provides an expert judgment approach for assessing the boiler's reliability characteristics. For this purpose, opinions of experts on time to failure and time to repair data were elicited in the form of statistical distributions. In this work, reliability analysis of the boiler system is carried out by expert judgment method and by using best-fit failure model. The system reliability along with preventive maintenance intervals of all components is also evaluated.FindingsIt is observed that the reliability analysis results obtained by expert judgment method and best-fit failure model method indicate that there are no significant differences. Therefore, in case when insufficient data are available, the expert judgment method can be effectively used. The analysis shows that the feedwater tank, feedwater pump, supply water temperature sensor, strainer, return water temperature sensor, condensate filter, mechanical dust collector, coal crusher and fusible plug are identified as critical components from a reliability perspective, and preventive maintenance strategy is suggested for these components.Originality/valueIn this research paper, a system reliability model by the expert judgment method is developed, and it can be effectively used where insufficient failure data are available. This paper is useful for the comparative evaluation of reliability characteristics of a boiler system by expert judgment method and best-fit failure model method.

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