RESONANCE 2023

Session

11 juil. 2023 à 10:40

Toulouse

Présidents de session

Survishno 2 / Fleet Monitoring

• Konstantinos Gryllias ()

Liste des contributions Ordre du jour

233. "FLEET#1 - Fleet Condition Monitoring in non-stationary conditions"

Achilleos Achilleas

11/07/2023 10:40

Machine condition monitoring is a challenging task. This paper presents a technique on the domain of rotating machine fleet condition monitoring for non-stationary operating with emphasis on gears and bearings as the most critical mechanical components. The machines are working on non-stationary conditions, on factual applications. This condition is causing an effect on the vibration signal as...

234. "FLEET#2 - Effective Identification of Cyclic Excitation and Resonance in Non-stationary Gearbox Vibration Monitoring"

Ahani Mojtaba

11/07/2023 11:00

Since as rotating machinery, the gearbox is an important source of vibration and the identification of signals and parameters of some critical components of the gearbox is necessary for the monitoring of the system. Inside this mechanism, the rotation of elements with periodic discrete geometries (bearings, gears, turbines, ...) is the origin for potential excitations which are commonly...

235. "FLEET#3 - Automated domain adaptation for bearings fault detection and classification"

Karkafi Fadi

11/07/2023 11:20

Effective fault classification of mechanical components based on vibration signals requires robust domain adaptation methods, particularly in scenarios where complete data on all fault types is unavailable. The challenge lies in monitoring the health of components with variable characteristics, such as speed, load, and torque, where the lack of information on their current state renders target...

236. "FLEET#4 - Results on Experimental Data Analysis of Independent Cart Systems in Non-Stationary Conditions"

Jabbar Abdul

11/07/2023 11:40

This paper presents an analysis of the vibration data obtained from an independent cart system. The study focuses on comparing the vibration data collected with and without the presence of outer race faults, while the 12 roller cart/mover maneuvers at different speeds. Vibration data was captured using accelerometers positioned along the system and acquired through the Beckhoff PLC and...

237. "FLEET#5 - Performance study of DTW-based spike measurement anomaly detection in sensors on real world tests."

Cornelis Bram

11/07/2023 12:00

Anomaly detection in sensor data plays a crucial role in various applications, including predictive maintenance, quality control, and prototype testing. The objective is to identify patterns that deviate from the expected results in the time series. This can be achieved through statistical analysis that exposes outliers or using domain knowledge to understand the expected values. Additionally,...

238. "FLEET#6 - Investigating the usage of Proxy-A-Distance as a measure of dataset shift detection and quantification in an automotive booming noise classification setting"

Kunte Deepti

11/07/2023 12:20

"Machine learning methods, which can be effective tools for NVH end-of-line testing applications, are typically data-demanding. Techniques like transfer learning and data augmentation have been proposed to overcome this need. For effective transfer learning, it is imperative to compare the source and target datasets and assess the disparity between the two.

In this paper, we study the...