Remaining Useful Life Prediction of Gas Turbine Engine using Autoregressive Model

Ahsan, Shazaib; Lemma, Tamiru Alemu

doi:10.1051/matecconf/201713104014

Cited by 14 publications

(5 citation statements)

References 24 publications

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“…Mathew et al [7] found that the random forest algorithm outperformed others in estimating the remaining useful life (RUL). Ahsan et al [8] proposed a semi-supervised model to investigate the impact of limited labeled training data on estimating remaining useful life (RUL). Several studies have recognized the superior performance of the convolutional neural network (CNN) approach compared to the long short-term memory (LSTM) method [12][13][14].…”

Section: Related Workmentioning

confidence: 99%

Uninhibited Positional and Contextual Attention in Spectral-Based (SPT) Transformer with Multi-head Shortcut for Improved Remaining Useful Life Forecasting in Industry 4.0

2024

IJIES

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This research paper aims to forecast equipment's remaining useful life (RUL) to improve maintenance planning and reduce costs. This paper presents the spectral-based transformer (SPT) model, designed for predicting the remaining useful life (RUL) in the evolving maintenance landscape of industry 4.0. Proactive maintenance is becoming increasingly important as it improves performance and reduces losses. SPT utilizes advanced attention mechanisms and innovations, which have been evaluated on the C-MAPSS dataset to simulate various operations. The contributions include discrete cosine transform attention (DCTA), uninhibited positional and contextual attention (UPCA), multi-head shortcuts, and bidirectional structures. Component efficacy is rigorously assessed through ablations. The results demonstrate that SPT exhibits superior performance compared to other methods, with a notable advantage on the challenging FD002 and FD004 sub-datasets within the C-MAPSS dataset. The proposed method decreases the root mean square error (RMSE) by 14% and enhances the performance scores of FD002 and FD004 by 10% and 24%, respectively. Additionally, it reduces the RMSE of FD004 by 15%. The model outperforms current methods, showing stability and generalization across different subsets of data. SPT demonstrates proficiency in capturing degradation patterns, which shows the potential for accurate remaining useful life (RUL) prediction. This tool is designed for time-series regression and has potential applications in various industries. Future research could focus on expanding the system's capabilities to process higher frequencies and broader contexts effectively. The SPT method provides a thorough approach for predicting the remaining useful life (RUL). It can potentially improve maintenance decisions and system performance in the context of Industry 4.0.

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Section: Related Workmentioning

confidence: 99%

Uninhibited Positional and Contextual Attention in Spectral-Based (SPT) Transformer with Multi-head Shortcut for Improved Remaining Useful Life Forecasting in Industry 4.0

2024

IJIES

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“…Monitoring these results makes it possible to track the performance degradation of gas turbines. The data can be used for prediction and decision-making on maintenance and repair of gas turbine units [16,17].…”

Section: Operation Of the Techniquementioning

confidence: 99%

Estimation of the driven gas turbine unit technical performance using the standard measuring systems

2020

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In large pipeline gas transport systems the operation and maintenance of gas pumping units are carried according to the current number of equivalent working hours of centrifugal gas compressors and gas turbines. Modern terms of lean production require the maintenance procedure to be done according to the current technical performance of equipment. The paper presents a designed and verified methodology of technical performance estimation of gas turbine units using the standard measuring systems. This method includes a verified high-order mathematical model based on the gas dynamic function for the precise analytical description of turbomachinery aerodynamics. The models are defined for different types of multi-shaft gas turbines. In this article the results of technical performance estimation of different gas turbine units are discussed.

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“…In comparison to alternative frameworks that can fulfill similar requirements, LCC involves analyzing cash flow by calculating the difference between cash inflow and cash outflow associated with system acquisition and ownership. The study is conducted at the Gas District Cooling (GDC) plant, equipped with gas-turbine ships responsible for power production (Ahsan and Lemma, 2017;Akbar and Mokhtar, 2017), along with Electrical Chillers and TES tanks. Static parameters, selected either during installation or the feasibility study, serve as the foundation for predicting the monetary or cost aspects in current life cycle costing models.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Energy Efficiency: An Integrated Life Cycle Costing Approach for Centralized Cooling Plants

Raza,

Maryam,

Haroon

2023

jobams

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Gas District Cooling (GDC) is an emerging technology utilizing natural gas-based systems for efficient district-scale cooling. This study develops a comprehensive Life Cycle Costing (LCC) model integrating capital expenditure (CAPEX) and operational expenditure (OPEX) for Thermal Energy Storage (TES) and Electrical Chillers (ECs) within GDC plants. Validated through a case study at an academic institute's GDC plant in Malaysia, the model assesses breakeven scenarios, revealing that project feasibility is optimal under case-II conditions, emphasizing the importance of operational efficiency for sustained economic viability throughout the plant's lifespan. These insights enhance understanding of financial considerations and investment strategies for adopting GDC technology in urban cooling applications, highlighting the need for strategic planning and lifecycle management to optimize economic performance and support broader sustainable development goals. Ongoing research will further refine LCC models, advancing the economic competitiveness of GDC as a key component of sustainable urban cooling solutions.

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Remaining Useful Life Prediction of Gas Turbine Engine using Autoregressive Model

Cited by 14 publications

References 24 publications

Uninhibited Positional and Contextual Attention in Spectral-Based (SPT) Transformer with Multi-head Shortcut for Improved Remaining Useful Life Forecasting in Industry 4.0

Uninhibited Positional and Contextual Attention in Spectral-Based (SPT) Transformer with Multi-head Shortcut for Improved Remaining Useful Life Forecasting in Industry 4.0

Estimation of the driven gas turbine unit technical performance using the standard measuring systems

Optimizing Energy Efficiency: An Integrated Life Cycle Costing Approach for Centralized Cooling Plants

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