A maintenance mode decision method for traction power supply system of high-speed railway

Wang, Qi; He, Zhengyou; Feng, Donglai

doi:10.1109/icphm.2015.7245041

Cited by 5 publications

(3 citation statements)

References 21 publications

(19 reference statements)

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“…(3) RTF maintenance: RTF maintenance is only performed after the equipment has failed. After the equipment has failed, production is reinstated through breakdown maintenance or corrective maintenance (Wang and Zhengyou, 2015).…”

Section: Maintenance Methods Used In Railway Systemsmentioning

confidence: 99%

Lean implementation for rail substation processes

Croucamp

Telukdarie

2018

JQME

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Purpose Traction substations are an integral part of the railway infrastructure. In order to ensure that machinery and equipment is available and utilised at full capacity, intelligent maintenance methods should be implemented. The purpose of this paper is to focus on the development of lean maintenance strategies implemented on traction substations and offer the maintenance manager an alternative maintenance method to be utilised during optimisation initiatives. Design/methodology/approach The rail company under consideration has various improvement options, the maintenance supply chain is a priority. The existing maintenance process of 3 kVDC traction substations is examined and all operations and activities directly and indirectly associated with maintenance are analysed with lean methodologies. The analysis of maintenance operations and activities reveals that some of these operations and activities are non-value-adding and, therefore, regarded as waste. These activities only prolong the maintenance process without adding value to the process. Alternative operations and activities are suggested and simulated. Findings The application of lean indicates that the maintenance process could be optimised to deliver on a more efficient process, which would improve the quality of maintenance by ensuring that maintenance is timeously carried out. Through reducing the downtime caused by maintenance, the availability of the system is preserved and the railway lines could be used to capacity. Research limitations/implications The research is limited to 3 kVDC traction substations and the associated maintenance process, as this was the area of opportunity for the company. The track and overhead traction equipment maintenance is not included. Practical implications The practical application of this research is in optimisation of the value chain for maintenance, specifically in the rail industry. Originality/value This research could be applied by maintenance managers to effectively implement if a run-to-failure (RTF) maintenance philosophy is being utilised. The research offers maintenance techniques within the RTF maintenance scope which reduces the maintenance cycle and equipment downtime.

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Section: Maintenance Methods Used In Railway Systemsmentioning

confidence: 99%

Lean implementation for rail substation processes

Croucamp

Telukdarie

2018

JQME

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“…Furthermore, a comprehensive framework was developed for the AI applications in high-speed rail transportation, considering operational efficiency and customer comfort criteria. Along with the aforementioned efforts, many other studies applied various AI-based methods, optimization, simulation, and other operations research techniques to address different decision problems and issues that are related to train operations, including energy and power sources [80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96], train speed control and trajectory control [97][98][99][100][101][102][103][104][105][106], timetable synchronization and optimization [107][108][109][110][111][112][113][114][115][116][117], as well as intelligent maintenance and prognostics [118][119][120][121][122][123]…”

Section: Figure 16 Iiot-enabled Technologies For Rail Transportationmentioning

confidence: 99%

Deployment of Autonomous Trains in Rail Transportation: Current Trends and Existing Challenges

et al. 2021

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Automation is expected to effectively address the growing demand for passenger and freight transportation, safety issues, human errors, and increasing congestion. The growth of autonomous vehicles using the state-of-the-art connected vehicle technologies has paved the way for the development of passenger and freight autonomous trains (ATs), also known as driverless trains. ATs are fully automated trains that are centrally controlled using advanced communication and internet technologies, such as highspeed internet (5G) technology, Internet of Things, dedicated short range communications, digital video detection cameras, and artificial intelligence-based methods. The current study focuses on a detailed up-todate review of the existing trends, technologies, advancements, and challenges in the deployment of ATs with a full automation level in rail transportation. The basic AT features along with the key technologies that are instrumental for the AT deployment and operations are discussed in detail. Furthermore, a comprehensive evaluation of the state-of-the-art research efforts is performed as well with a specific emphasis on the issues associated with the AT deployment, user perception and outlook for ATs, innovative concepts and models that could be used for the AT design, and the AT operations at highway-rail grade crossings. Based on the conducted review, this study determines the main advantages and challenges from the AT deployment. The identified challenges have to be collaboratively addressed by the relevant stakeholders, including railroad companies, researchers, and government representatives, to facilitate the AT development and deployment considering the perspectives of future users and without affecting the safety level.INDEX TERMS Autonomous trains, driverless trains, connected vehicles, autonomous vehicles, automation trends, automation challenges.

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“…S INCE firstly completed and put into operation in 2008, high-speed railway (HSR) in China has experienced tremendous and expeditious development over the past decade. With massive existing lines at present as well as an increasing number of new lines entering service in the near future, the HSR operators are being challenged by formidable maintenance tasks and enormous maintenance pressure unprecedentedly [1]. In HSR, the traction power supply system (TPSS) plays a vital role to feed the high-speed trains and constitutes the essential power lifeline.…”

Section: Introductionmentioning

confidence: 99%

Achieving Predictive and Proactive Maintenance for High-Speed Railway Power Equipment With LSTM-RNN

Wang

2020

IEEE Trans. Ind. Inf.

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Current maintenance mode for high-speed railway (HSR) power equipment are so outdated that can hardly adapt to the high-standard modern HSR. Therefore, a new possibility is proposed in this paper to update the obsoleting maintenance mode of the HSR power equipment by adopting both predictive maintenance and proactive maintenance. With the combination of data-driven (predictive) and model-based (proactive) approaches, two principal constituents-the sample generator and the maintenance predictor-are designed. The maintenance predictor which is powered by the long short-term memory recurrent neural network (LSTM-RNN) is developed to realize the goal of predictive maintenance. The sample generator which is formulated by the physical degradation and failure model of HSR power equipment is proposed towards the goal of proactive maintenance. Test results on a gas-insulated switchgear have shown the powerful collaboration between the generator and the predictor, to not only accurately predict future maintenance timing of the switchgear based on historical sample data, but also enrich the data supply proactively to deal with potential data deficiency problems.

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A maintenance mode decision method for traction power supply system of high-speed railway

Cited by 5 publications

References 21 publications

Lean implementation for rail substation processes

Lean implementation for rail substation processes

Deployment of Autonomous Trains in Rail Transportation: Current Trends and Existing Challenges

Achieving Predictive and Proactive Maintenance for High-Speed Railway Power Equipment With LSTM-RNN

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