Engine Diagnostics Using Acoustic Emissions Sensors

Kaul, Brian; Lawler, Benjamin; Zahdeh, Akram

doi:10.4271/2016-01-0639

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…In addition, the data used are accelerometer recordings [23], while we investigate the usage of acoustic emission sensors. We decided to focus on AE because these signals are commonly used in the automotive industry to test the performance, in terms of mechanical and combustion fulfillments and have the potential to detect physical phenomena that could be missed at lower frequencies [7][8][9][10][11][12][13]. Nevertheless, due to the analog nature of the signal in both cases, the approach proposed by Zhe Li et al [23] can be adapted to the current use case.…”

Section: Related Workmentioning

confidence: 99%

“…The ACUME_HV project (Acoustic Emission Monitoring of Historical Vehicles), conducted at HE-Arc between 2018 and 2020, was the first attempt to use Acoustic Emission techniques as NDT, to diagnose and monitor the state of preservation of engines in historical vehicles. AE is commonly used in the automotive industry to test the performance, in terms of mechanical and combustion fulfillments, of newly produced engines [7][8][9][10][11][12][13]. However, the technique has not been used before on ancient engines, where scaling of lubricants, long periods of inactivity, wear of the moving parts and presence of oxide scales can significantly affect the engine mechanism's performance.…”

Section: Introductionmentioning

confidence: 99%

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Data analysis techniques for the visualization and classification of historical vehicle engines’ health status using data-driven solutions

Carrino,

Meyer,

Dreyer

et al. 2023

Cons. Património

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In the field of cultural heritage, the use of non-destructive techniques to determine the state of conservation of an artifact is of the utmost importance, to avoid damage to the object itself. In this paper, we present a data pipeline and several machine learning techniques for the visualization, analysis and characterization of engines in historical vehicles. The paper investigates the use of vibro-acoustic signals acquired from the engines in different states of conservation and working conditions to train machine learning solutions. Data are classified according to their state of health and the presence of anomalies. The t-SNE algorithm is used for dimensionality reduction for data visualization. The machine learning algorithms tested showed encouraging performance in associating acoustic emission data with the engine signature, the type of anomaly and the working conditions. Nevertheless, a larger dataset would allow us to improve and strengthen the results.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data analysis techniques for the visualization and classification of historical vehicle engines’ health status using data-driven solutions

Carrino,

Meyer,

Dreyer

et al. 2023

Cons. Património

View full text Add to dashboard Cite

show abstract

“…AE is already known and used in the field of automotive industry in the context of faults' diagnostic of newly produced engines [2][3][4][5][6][7][8][9][10]. However, adapting similar AE methods to historical vehicles is more complex mostly due to the presence of oxidation products, residues, dust and scaling of lubricants.…”

Section: (): V-volmentioning

confidence: 99%

Acoustic emission techniques for the detection of simulated failures in historical vehicles engines

Brambilla

Chalançon²,

Buch

et al. 2021

Eur. Phys. J. Plus

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Technical and industrial heritage artefacts are characterized by the presence of mechanisms. The possibility to activate, or reactivate, these mechanisms is an integral part of the cultural values of this kind of patrimony. The artefacts’ functionality, however, requires an effective diagnostic in order to detect the onset of malfunctioning at a very early stage to avoid wear and breakdowns. The assessment of moving mechanisms of heritage objects may be performed using non-destructive methods, such as acoustic emission (AE). The ACUME_HV project aimed at developing diagnostic and monitoring protocols for historical vehicles’ engines using AE techniques. The case studies were performed on 2-cylinders Renault AG1 vehicles (collection of the “Musée National de l’Automobile – Collection Schlumpf” of Mulhouse, France). These cars are maintained in working conditions, and their engines are started periodically. After a first phase consisting in recording the reference signals of the selected engines, the project focused on detecting faults simulated on purpose, the latter reproducing common failures occurring in historical vehicles' engines.

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“…Torii [12] presented a technique to separate the engine noise radiation into the contributions of combustion and mechanical noise. Kaul et al [13] investigated the acoustic emissions response caused by various engine cycle events.…”

Section: Introductionmentioning

confidence: 99%

Remote Combustion Sensing in Diesel Engine via Vibration Measurements

Chiavola¹,

Recco²,

Chiatti³

2018

Improvement Trends for Internal Combustion Engines

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An efficient control of the combustion process is required in order to comply with regulations on pollutant emissions from internal combustion engines. Literature presents investigations devoted to explore the potentiality of externally mounted sensor (speed sensor, microphone, and accelerometer) for combustion diagnosis. A relationship exists between the combustion event measured via an in-cylinder pressure transducer and engine block vibration measured via an accelerometer. Time and frequency domain processing of acquired signals highlighted the correlation between parameters able to characterize the combustion development and features derived from the engine block vibration data. A methodology was developed by the authors that demonstrated to be suitable for real-time estimation of combustion progress based on engine vibration. A two-cylinder common rail diesel engine of small displacement was tested; two configurations were investigated, naturally aspirated, and turbocharged. The in-cylinder pressure and block vibration signals were acquired and processed in time and frequency domains. The vibrational components mainly related to the combustion process were extracted, and indicators of the combustion positioning were computed. The angular positions of start of combustion (SOC) and MFB50 computed via the heat release curve by means of the in-cylinder pressure measurements were compared to those obtained by means of the accelerometer signal. High correlation coefficients were obtained for the data acquired during the testing of both naturally aspirated and turbocharged configurations in the complete engine operative field.

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Engine Diagnostics Using Acoustic Emissions Sensors

Cited by 9 publications

References 9 publications

Data analysis techniques for the visualization and classification of historical vehicle engines’ health status using data-driven solutions

Data analysis techniques for the visualization and classification of historical vehicle engines’ health status using data-driven solutions

Acoustic emission techniques for the detection of simulated failures in historical vehicles engines

Remote Combustion Sensing in Diesel Engine via Vibration Measurements

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