scholarly journals Mechanical Damage Assessment for Pneumatic Control Valves Based on a Statistical Reliability Model

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3307
Author(s):  
Nirbhay Mathur ◽  
Vijanth Sagayan Asirvadam ◽  
Azrina Abd Aziz
Keyword(s):  
Weibull Distribution ◽  
Reliability Assessment ◽  
Mechanical Damage ◽  
Control Valve ◽  
Reliability Models ◽  
Statistical Reliability ◽  
Processing Plants ◽  
Simulated Process ◽  
Pneumatic Control Valves ◽  
Log Normal

A reliability assessment is an important tool used for processing plants, since the facility consists of many loops and instruments attached and operated based on other availability; thus, a statistical model is needed to visualize the reliability of its operation. The paper focuses on the reliability assessment and prediction based on the existing statistical models, such as normal, log-normal, exponential, and Weibull distribution. This paper evaluates and visualizes the statistical reliability models optimized using MLE and considers the failure mode caused during a simulated process control operation. We simulated the failure of the control valve caused by stiction running with various flow rates using a pilot plant, which depicted the Weibull distribution as the best model to estimate the simulated process failure.

scholarly journals Mechanical Damage Assessment for Pneumatic Control Valve Based on Statistical Reliability Model

2020 ◽  
Author(s):  
Nirbhay Mathur ◽  
Vijanth Sagayan Asirvadam ◽  
Azrina Abt Aziz
Keyword(s):  
Damage Assessment ◽  
Failure Modes ◽  
Reliability Assessment ◽  
Mechanical Damage ◽  
Control Valve ◽  
Pneumatic Control ◽  
Statistical Reliability ◽  
Process Plants ◽  
Log Normal ◽  
Best Fit

Reliability assessment is an important component and tool used for process plants since the facility consists of many loops and instruments attached and operates based on each other availability, thus it requires a statistical method to visualize the reliability. The paper focuses on reliability assessment and prediction based on available statistical models such as normal, log-normal, exponential, and Weibull distribution. This paper also visualizes, which model fits best for assessment and prediction and also considers failure modes caused during a simulation mode process control operation. A simulation model is designed in this paper to observe the failure of the control valve causing stiction to visualize the failure modes and predict the best-fit model for reliability assessment.

The log-normal modified Weibull distribution and its reliability implications

2019 ◽  
Vol 188 ◽  
pp. 6-22 ◽  
Author(s):  
Mohammed K. Shakhatreh ◽  
Artur J. Lemonte ◽  
Germán Moreno–Arenas
Keyword(s):  
Weibull Distribution ◽  
Modified Weibull Distribution ◽  
Modified Weibull ◽  
Log Normal

Reliability Models Using the Composite Generalizers of Weibull Distribution

2019 ◽  
Vol 6 (4) ◽  
pp. 807-829
Author(s):  
Gokarna R. Aryal ◽  
Keshav P. Pokhrel ◽  
Netra Khanal ◽  
Chris P. Tsokos
Keyword(s):  
Weibull Distribution ◽  
Reliability Models

Statistical Inferences of Lift-Off Velocity Distribution Function Form for Saltating Particles

2010 ◽  
Vol 108-111 ◽  
pp. 783-788
Author(s):  
Jian Jun Wu ◽  
Li Hong He
Keyword(s):  
Distribution Function ◽  
Weibull Distribution ◽  
Velocity Distribution ◽  
Goodness Of Fit ◽  
Velocity Distribution Function ◽  
Forward Direction ◽  
Distribution Functions ◽  
Velocity Distribution Functions ◽  
Lift Off ◽  
Log Normal

The lift-off velocity distribution of saltating particles, which have been proposed to characterize the dislodgement state of saltating particles, is one of the key issues in the theoretical study of windblown sand transportation. But there were various statistical relations in the early researches. In this paper, the Kolmogorov-Smirnov test for goodness-of-fit is adopted to make an inference of the most probable form of lift-off velocity distribution functions for saltating particles on the basis of the experimental data. The statistical results show that the distribution function of vertical lift-off velocities conforms better to Weibull distribution function than to the normal, log-normal, gamma and exponential ones; while, the distribution function of the absolute values of horizontal lift-off velocities is best described by log-normal distribution in forward direction and Weibull distribution in backward direction, respectively. Finally, two more examples prove to support the above conclusions.

scholarly journals Lifetime Estimation and Failure Risk Analysis in a Power Stage Used in Wind-Fuel Cell Hybrid Energy Systems

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1412 ◽  
Author(s):  
Sima Rastayesh ◽  
Sajjad Bahrebar ◽  
Amir Sajjad Bahman ◽  
John Dalsgaard Sørensen ◽  
Frede Blaabjerg
Keyword(s):  
Fuel Cell ◽  
Weibull Distribution ◽  
Cell Hybrid ◽  
Reliability Assessment ◽  
Energy Systems ◽  
Power Circuit ◽  
Hybrid Energy ◽  
Hybrid Energy Systems ◽  
Power Stage ◽  
Fuel Cell Hybrid

This paper presents a methodology based on the failure mode and effect analysis (FMEA) to analyze the failures in the power stage of wind-fuel cell hybrid energy systems. Besides, fault tree analysis (FTA) is applied to describe the probabilistic failures in the vital subcomponents. Finally, the reliability assessment of the system is carried out for a five-year operation that is guaranteed by the manufacturer. So, as the result, the reliability analysis proves that the metal oxide semiconductor field effect transistor (MOSFET) and electrolytic capacitor are the most critical components that introduce damages in the power circuit. Moreover, a comparative study on the reliability assessment by the exponential distribution and the Weibull distribution show that the B1 lifetime obtained by the Weibull distribution is closer to reality.

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