Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data

Moleda, Marek; Momot, Alina; Mrozek, Dariusz

doi:10.3390/s20020571

Cited by 38 publications

(19 citation statements)

References 45 publications

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“…e.g., bearings are commonplace within rotary machinery and state-of-the-art algorithms have been applied to this area [45,49,55,67,91]. Another method of overcoming data reflecting a flexible operation is presented by Moleda et al [85]. Moleda et al [85] investigates a feedwater pump on a CHP in Poland.…”

Section: Pumps and Thermal Power Plantsmentioning

confidence: 99%

See 1 more Smart Citation

Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges

Olesen

Shaker

2020

Sensors

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Thermal power plants are an important asset in the current energy infrastructure, delivering ancillary services, power, and heat to their respective consumers. Faults on critical components, such as large pumping systems, can lead to material damage and opportunity losses. Pumps plays an essential role in various industries and as such clever maintenance can ensure cost reductions and high availability. Prognostics and Health Management, PHM, is the study utilizing data to estimate the current and future conditions of a system. Within the field of PHM, Predictive Maintenance, PdM, has been gaining increased attention. Data-driven models can be built to estimate the remaining-useful-lifetime of complex systems that would be difficult to identify by man. With the increased attention that the Predictive Maintenance field is receiving, review papers become increasingly important to understand what research has been conducted and what challenges need to be addressed. This paper does so by initially conceptualising the PdM field. A structured overview of literature in regard to application within PdM is presented, before delving into the domain of thermal power plants and pump systems. Finally, related challenges and trends will be outlined. This paper finds that a large number of experimental data-driven models have been successfully deployed, but the PdM field would benefit from more industrial case studies. Furthermore, investigations into the scale-ability of models would benefit industries that are looking into large-scale implementations. Here, examining a method for automatic maintenance of the developed model will be of interest. This paper can be used to understand the PdM field as a broad concept but does also provide a niche understanding of the domain in focus.

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Section: Pumps and Thermal Power Plantsmentioning

confidence: 99%

“…Another method of overcoming data reflecting a flexible operation is presented by Moleda et al [85]. Moleda et al [85] investigates a feedwater pump on a CHP in Poland. An approach utilising a bag of regression models is suggested.…”

Section: Pumps and Thermal Power Plantsmentioning

confidence: 99%

Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges

Olesen

Shaker

2020

Sensors

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“…Embedded sensors, software, controllers, connectivity, breakthroughs in networking, edge and fog computing, cloud technology, faster CPUs, cheaper memory, energy efficiency, and miniaturisation are all converging to create low-cost processing power and data storage everywhere and they became the key enabling technologies fuelling up the evolution in the paradigms [32][33][34]. As presented in Merluzzi and Brunetti [35] the "Reliability-Centered Maintenance" represents a systematic approach to evaluate a facility's equipment and resources to best mate the two and result in a high degree of facility reliability and costeffectiveness.…”

Section: Prescriptive Maintenance and Shared Valuementioning

confidence: 99%

New Business Models from Prescriptive Maintenance Strategies Aligned with Sustainable Development Goals

et al. 2020

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The industry has entered on the Fourth Industrial Revolution, the so-called Industry 4.0, with global markets and strong competition, some traditional manufacturing firms are implementing new maintenance innovations and policies, based on digitalisation and data driven approach, but also based on servitisation. The implementation of these new equipment maintenance business models, could require new organisational approach at different levels. Different sorts of integration are arranged, in vertical with a flat structure of intelligent, flexible and autonomous units working integrated, in horizontal with a strong external and internal supply chain integration, and in transverse, with an integrated approach that link internal and external stakeholders. A new prescriptive maintenance business model for equipment exploiting digitalisation opportunities, including stakeholder relationship is proposed. Different perspectives such as organisational, innovation and sustainability have been adopted to discuss the implications of the proposal. The social value potentially gained as well as the alignment with the SDGs are discussed as well.

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“…The use of mechanisms based on manual control, has shown in the operation of a boiler the lack of precision and with them the inefficient use of inputs (air and fuel) used in the production of steam [18]. Another important aspect of the manipulation of operators in the control of a boiler is the error in measurement of the operation indicators, since they express variation in what is needed and what it offers in terms of inputs [19].…”

Section: Introductionmentioning

confidence: 99%

Automation of the burner of a pirotubular boiler to improve the efficiency in the generation of steam

Chamorro-Atalaya

Goicochea-Vilela

Arce-Santillan

et al. 2021

IJEECS

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<span>The purpose of this article is to describe the automation developed by means of a programmable logic controller for the burner of a fire tube boiler, in order to improve the efficiency in the process of generating steam quantified through the percentage of oxygen generated. The implementation was developed under a control strategy based on the use of servomotors that allow to gradually open or close the solenoid valves that dose the amount of air and fuel; Considering that there are multiple elements, I limited the analysis to one of its main components, called the burner. After developing this automation, it was possible to demonstrate the decrease in the variability of the oxygen percentage in relation to the optimal or desired value in the boiler. The experimentally obtained data of the oxygen percentage, were subjected to a statistical analysis of dispersion, in which the value of the Pearson's correlation coefficient was determined, whose value was equal to 0.298; This result allowed to conclude that the degree of variability of the indicator in analysis with respect to time is very low, which means that the variable maintains a constant value, equal to the desired value, after automating the fire tube boiler</span><span lang="IN">.</span>

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Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data

Cited by 38 publications

References 45 publications

Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges

Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges

New Business Models from Prescriptive Maintenance Strategies Aligned with Sustainable Development Goals

Automation of the burner of a pirotubular boiler to improve the efficiency in the generation of steam

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