Individual Feature Selection of Rolling Bearing Impedance Signals for Early Failure Detection

Becker-Dombrowsky, Florian Michael; Koplin, Quentin Sean; Kirchner, Eckhard

doi:10.2139/ssrn.4379764

Cited by 6 publications

(2 citation statements)

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“…[226,227,233] Initial studies were conducted to better understand, model and predict the behavior of rolling bearings. [23,[234][235][236]239] The improved electric modeling of rolling element bearings enables their sensorial use. [239,238] Monitoring of the operational load on rolling element bearings enables a reasonable estimation of the remaining useful lifetime and improves the sustainable use of these machine elements.…”

Section: Electrical Behavior Of Rolling Contactsmentioning

confidence: 99%

A Review on Sensor‐Integrating Machine Elements

Kirchner,

Wallmersperger,

Gwosch

et al. 2024

Advanced Sensor Research

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This contribution summarizes the current state of research regarding so‐called sensor‐integrating machine elements as an enabler of digitalization in mechanical engineering and——if available—their application in industry. The focus is on the methodical aspects of the development of these machine elements in general as well as specific sensor‐integrating machine elements that are either already in use or currently under development. Developmental aspects include the robust design of initially evaluated concepts for sensor‐integrating machine elements as well as their modularization. Smart materials with sensory functions are included in the analysis as well as the differentiation with regard to add‐on sensors. The aim of the authors interlinked by a special research program funded by the German Research Foundation (DFG) is to facilitate the exchange with other researchers with the help of the comprehensive overview given in this contribution. The contribution concludes with a brief discussion of open challenges, such as the energy supply and data transfer in rotating systems and also data security.

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Section: Electrical Behavior Of Rolling Contactsmentioning

confidence: 99%

A Review on Sensor‐Integrating Machine Elements

Kirchner,

Wallmersperger,

Gwosch

et al. 2024

Advanced Sensor Research

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“…In industry, various methods are employed to monitor bearing health and identify early signs of failure [6]. These approaches encompass acquiring vibration signals and scrutinizing corresponding samples to detect alterations in vibration patterns indicative of potential bearing faults [7]. Thermal imaging cameras offer an alternative by detecting changes in bearing temperature, signaling abnormal wear or overheating [8].…”

Section: Introductionmentioning

confidence: 99%

Advancing Bearing Fault Diagnosis under Variable Working Conditions: A CEEMDAN-SBS Approach with Vibro-Electric Signal Integration

LOURARI,

SOUALHI,

BENKEDJOUH

2023

Preprint

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Bearings represent crucial components within rotating machinery, and unexpected failures can lead to significant damage and unplanned breakdowns. This paper introduces a novel approach to diagnose bearing faults under variable working conditions, leveraging the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Sequential Backward Selection (SBS). CEEMDAN automatically selects intrinsic mode functions (IMFs) from vibration and current signals to establish a comprehensive set of health indicators. Subsequently, the SBS algorithm identifies the most pertinent indicators for different bearing failure modes. The accuracy of the proposed method is evaluated on both vibration and electrical signals using data from a dedicated test bench at the Signal and Industrial Process Analysis Laboratory (LASPI). Results demonstrate the effectiveness of the proposed method in accurately identifying and classifying bearing faults across various working conditions, utilizing both types of signals. This approach holds promise for real-world industrial applications, offering a reliable method for condition monitoring and Diagnostics in bearing systems.

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Pitting Influence on Electrical Capacitance in EHL Rolling Contacts

Zaiat,

Ibrahim,

Kirchner

2023

Lubricants

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This work presents an investigation on the influence of pitting in EHL rolling contact. The pitting geometry comes as an extension on the architecture for multi-physical numerical calculations of rolling element bearing contacts based on OpenFOAM. The model utilized is built according to the state-of-the-art for fluid–solid interaction and electro-quasi-static fields. In this framework, the contact is reduced to be two dimensional in order to reduce the computing costs needed. The changes in the electric properties, which are caused by pittings, are measured using the electric capacitance of the contact and put in perspective with regard to the EHL contacts geometry. The investigation delivers an evaluation on how surface degradation, in both the pitting width w and pitting depth d of the contact, affects the electric properties. It can be seen that the maximum deviations with different reduced radii for the same pitting structures are around 5% and would therefore hardly be distinguishable with corresponding measurements. By comparing the same data for the same ratio of pitting width to reduced radius, on the other hand, differences of up to 50% can be seen.

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Individual Feature Selection of Rolling Bearing Impedance Signals for Early Failure Detection

Cited by 6 publications

References 0 publications

A Review on Sensor‐Integrating Machine Elements

A Review on Sensor‐Integrating Machine Elements

Advancing Bearing Fault Diagnosis under Variable Working Conditions: A CEEMDAN-SBS Approach with Vibro-Electric Signal Integration

Pitting Influence on Electrical Capacitance in EHL Rolling Contacts

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