Reliability model of the railway transportation system with respect to hazard states

Restel, Franciszek J.; Zając, Mateusz

doi:10.1109/ieem.2015.7385805

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…Border

\mathop {\lim }\limits_{n \to \infty } p( n ) = \Pi

(if it exists) is called the boundary distribution of the Markov chain [33]. Probability borders play an important role because they describe the behaviour of the process over a long time [23].…”

Section: Methods Of Research and Analysismentioning

confidence: 99%

“…Several sets of technical and organizational solutions that allow the increase of the readiness factor of buses were subjected to simulation tests. Research work on modelling the reliability and safety of the rail transport system with respect to danger states is reported by Restel and Zajac [33]. A 12-state model was built, including 4 states of danger.…”

Section: Introductionmentioning

confidence: 99%

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Stochastic operation model for readiness assessment of small wind turbines based on Markov theory

Zalewska‐Lesiak,

Małachowski,

Szkutnik‐Rogoż

2023

IET Renewable Power Gen

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Wind energy is now one of the most important alternative sources of renewable energy. The development of wind power generation is a prerequisite to meet environmental and sustainable development requirements while achieving energy security goals. The condition for the effectiveness of the proper operation of a wind power plant is its ability to perform the intended functions, which can be expressed by the coefficient of technical readiness. This article presents an original analysis of the readiness of small wind turbines. As part of the research, an original stochastic operation model was developed based on the application of the Markov process theory. Based on the collected data, a 3‐state phase space of the studied process was identified. Various analyses were carried out to calculate the operating coefficients of wind power plants. The ergodic (boundary) probabilities were calculated using three methods. The conditional probabilities were then determined based on the initial distribution. The resulting readiness factors, not exceeding 30%, indicate the low operational efficiency of the small wind turbines in question. Furthermore, an analysis of the sensitivity of the performance factors was carried out for the analysed objects.

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“…Border

\mathop {\lim }\limits_{n \to \infty } p( n ) = \Pi

(if it exists) is called the boundary distribution of the Markov chain [33]. Probability borders play an important role because they describe the behaviour of the process over a long time [23].…”

Section: Methods Of Research and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stochastic operation model for readiness assessment of small wind turbines based on Markov theory

Zalewska‐Lesiak,

Małachowski,

Szkutnik‐Rogoż

2023

IET Renewable Power Gen

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show abstract

“…In the paper [33], we find an analytical approach to estimating the reliability of a transhipment system using a deterministic approach based on a Markov model. Similarly, Markov modelling issues for train scheduling are referenced in [34] and [35]. There has also been a discussion on the use of slightly more flexible damage functions for transhipment systems [36].…”

Section: Assigning Operations To Handling Equipment At Container Term...mentioning

confidence: 99%

Determining the Probability of Unproductive Manipulations in Inland Intermodal Terminal Operations

Zając

Rožić

Naletina

2023

PROMTT

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The paper concerns the method of determining the probability of unproductive manipulations during operations, maintenance or repairs on an inland intermodal terminal. The method is mathematically based on the semi-Markov process. The developed method enables revision of unproductive manipulation frequency and duration. It provides an opportunity to analyse and change inland terminal operations so as to increase productivity.

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“…Frequent delays have caused some problems for KTMB, which can cause significant inconvenience for passengers and reduce the efficiency of the system [3]. There are two main concepts in all transport systems, particularly in the rail sector; safety [4][5][6] and reliability [7]. Due to the ongoing need to improve rail safety, several European research projects are working on any situation that may pose a threat to rail safety [8].…”

Section: Introductionmentioning

confidence: 99%

Obstacle Detection System for Railways using IoT Sensors

Aziz

Mohamad

Alias

2020

Periodicals of Evolution in Electrical and Electronic Engineering 2020/1

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Accidents that involve trains on the railway is a crucial issue and need to be avoided. Detecting obstacles is vitally essential nearby and on the railway to ensure the smooth running of the trains. Thus, Keretapi Tanah Melayu Berhad (KTMB) has provided a safety system by relying on visual inspection to monitor the railway. This project aims to provide an alternative precaution measurement that can aid the railway's existing safety system. The project uses two mediums to collect and monitor data about the detecting obstacles nearby and on the railway. The first medium used in this project is the IoT-based system by using FavorIoT as a cloud server platform at the prototype for storing and monitoring data about the distance between obstacles and the prototype. Another medium used is a radar display by using Processing Software to display the distance between obstacles and the device in the range between 0 – 40 cm. Three ultrasonic sensors are used to provide a dependable notification system to detect the obstacles nearby and on the railway, which placed at the front, right and left sides. Arduino IDE is used to program Arduino NodeMCU, which acts as the brain of the system. The system commands the three ultrasonic sensors to detect the distance between obstacles and the device and send the data via Wifi to the FavorIoT as a cloud server. The prototype managed to collect data in a data stream of FavorIoT and monitor data in the radar display form.

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Reliability model of the railway transportation system with respect to hazard states

Cited by 11 publications

References 14 publications

Stochastic operation model for readiness assessment of small wind turbines based on Markov theory

Stochastic operation model for readiness assessment of small wind turbines based on Markov theory

Determining the Probability of Unproductive Manipulations in Inland Intermodal Terminal Operations

Obstacle Detection System for Railways using IoT Sensors

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