Reduced Scale Laboratory for Training and Research in Condition-Based Maintenance Strategies for Combustion Engine Power Plants and a Novel Method for Monitoring of Inlet and Exhaust Valves

Assuncao, Frederico de Oliveira; Borges-da-Silva, Luiz Eduardo; Villa-Nova, Helcio Francisco; Bonaldi, Erik Leandro; Oliveira, Levy Ely Lacerda; Lambert‐Torres, Germano; Teixeira, Carlos Eduardo; Sant’Ana, Wilson Cesar; Lacerda, Josue; Silva, Jose Luiz Marques da; Silva, Edenio Gomes da

doi:10.3390/en14196298

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…These operation modes often lead the engine off-design and can be interpreted as the root cause of genset anomalies and failures. Therefore, the research on automatic Fault Detection (FD) of gensets based on proper Condition-Based Maintenance (CBM) strategies is of paramount importance to monitor the operation, reduce downtime and ensure the reliability and productivity of the overall heat supply process [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data

et al. 2023

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Increasing interest in natural gas-fired gensets is motivated by District Heating (DH) network applications, especially in urban areas. Even if they represent customary solutions, when used in DH, duty regimes are driven by network thermal energy demands resulting in discontinuous operation, which affects their remaining useful life. As such, the attention on effective condition-based maintenance has gained momentum. In this paper, a novel unsupervised anomaly detection framework is proposed for gensets in DH networks based on Supervisory Control And Data Acquisition (SCADA) data. The framework relies on multivariate Machine-Learning (ML) regression models trained with a Leave-One-Out Cross-Validation method. Model residuals generated during the testing phase are then post-processed with a sliding threshold approach based on a rolling average. This methodology is tested against nine major failures that occurred on the gas genset installed in the Aosta DH plant in Italy. The results show that the proposed framework successfully detects anomalies and anticipates SCADA alarms related to unscheduled downtime.

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Section: Introductionmentioning

confidence: 99%

Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data

et al. 2023

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“…The literature presents some methods to detect damage on the internal combustion engines that convert the chemical energy of the fuels into rotational mechanical energy at their crankshafts (which are tied to synchronous generators in order to produce electrical energy). Such methods may rely on the direct measurement of internal parameters of the engine (such as pressure and temperature at different parts of the engine) [ 8 , 9 ] or even the use of voltage and current signals of the synchronous generator [ 10 ] in order to indirectly detect mechanical issues within the engine. However, these methods cannot test the fuel quality, which may cause a problem that will only be manifested in the long term.…”

Section: Introductionmentioning

confidence: 99%

An Ultrasonic-Capacitive System for Online Characterization of Fuel Oils in Thermal Power Plants

Campos

Borges-da-Silva

Arantes

et al. 2021

Sensors

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This paper presents a ultrasonic-capacitive system for online analysis of the quality of fuel oils (FO), which are widely used to produce electric energy in Thermal Power Plants (TPP) due to their elevated heating value. The heating value, in turn, is linked to the quality of the fuel (i.e., the density and the amount of contaminants, such as water). Therefore, the analysis of the quality is of great importance for TPPs, either in order to avoid a decrease in generated power or in order to avoid damage to the TPP equipment. The proposed system is composed of two main strategies: a capacitive system (in order to estimate the water content in the fuel) and an ultrasonic system (in order to estimate the density). The conjunction of the two strategies is used in order to estimate the heating value of the fuel, online, as it passes through the pipeline and is an important tool for the TPP in order to detect counterfeit fuel. In addition, the ultrasonic system allows the estimation of the flow rate through the pipeline, hence estimating the amount of oil transferred and obtaining the total mass transferred as a feature of the system. Experimental results are provided for both sensors installed in a TPP in Brazil.

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Metaverse‐based remote support system with smooth combination of free viewpoint observation and hand gesture instruction

Numata,

Ogi,

Mitani

et al. 2024

J Soc Info Display

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In field operations with large machines, onsite large task spaces have been typically required. In these cases, remote skilled workers have to provide a step‐by‐step guide by observing the onsite situation around the large task spaces in three dimensions, instructing onsite unskilled workers on how to perform the tasks with the correct hand gestures at the right position, and switching between observation and instruction frequently during the remote support. In this study, we developed a Metaverse‐based remote support system with a seamless user interface for switching between free viewpoint observation and hand gesture instruction. The proposed system enables remote skilled workers to observe the onsite field from any viewpoint, transfer hand gesture instruction to onsite workers, and seamlessly switch between free viewpoint observation and free hand gesture instruction without having to change devices. We compared the time efficiency of the proposed system and a conventional system through experiments with 28 users and found that our system improved the observation time efficiency by 65.7%, the instruction time efficiency by 27.9%, and the switching time efficiency between observation and instruction by 14.6%. These results indicate that the proposed system enables remote skilled workers to support onsite workers quickly and efficiently.

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Reduced Scale Laboratory for Training and Research in Condition-Based Maintenance Strategies for Combustion Engine Power Plants and a Novel Method for Monitoring of Inlet and Exhaust Valves

Cited by 5 publications

References 17 publications

Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data

Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data

An Ultrasonic-Capacitive System for Online Characterization of Fuel Oils in Thermal Power Plants

Metaverse‐based remote support system with smooth combination of free viewpoint observation and hand gesture instruction

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