Lubricity Monitoring of Engine Bearing Rotor System Based on Enhanced Vibration Analysis

  • Solomon Okhionkpamwonyi

Student thesis: Doctoral Thesis

Abstract

Condition monitoring of internal combustion engine have always posed a challenge due to difficulty in establishing consistent monitoring parameters and effective diagnostic analysis. These challenges are attributed to several factors such as the complexity of the systems involved, complexity of failure modes, high variability in operating conditions, significant vibration and induced mechanical stresses. Monitoring of the lubricated components within the engine, such as internal bearings also present unique challenges, especially for real-time on-line monitoring and early-stage fault detection, due the issue of limited accessibility, complicated dynamics and weak correlation between internal events and vibroacoustic external responses. These practical issues necessitate the application of robust non-intrusive sensing method, advanced data processing and diagnostic approach. Conventional method of vibration analysis relies on wired accelerometer fixed on engine body or stationary component housing. While the signals obtained through this means may have wide frequency spectrum, their complexity is greater as they are more strongly influenced by housing coupling effects and structural damping or complex transfer paths. As a viable solution, this research is centred on the advancement and implementation of wireless “direct” vibration measurement and monitoring methodologies tailored for complex rotating systems based on vibration analysis to assess the lubrication conditions and tribological effects on the journal bearings of IC engine crankshaft. In view of this, the research addresses two critical concerns: signal sources and weak signatures in on-line lubrication monitoring and wear fault diagnosis of IC engines. The methodology of the research combined structural vibration analysis with a hydrodynamic lubrication model, employing both comprehensive experimental validations and theoretical modelling simulations to investigate the correlation between tribological behaviours of lubricated components and the dynamic responses by leveraging advanced capabilities of micro-electromechanical systems (MEMS) based On-rotor sensor (ORS) for measuring vibration signals with high signal to noise ratio in acquiring the high order modal response of the crank journal and subsequently extracting meaningful information corresponding to tribological properties of the crankshaft bearings. This approach was aimed at establishing a vibration-based method to monitor tribological behaviour and precisely evaluate its effects. Analysis of the crankshaft incorporates the consideration of hydrodynamic lubrication at the interface of the bearing surfaces. The theoretical modelling considers the influence of the bearing tribology on crankshaft dynamics to reveal the mechanism of bearing lubrication. This research investigated the dynamic behaviour of diesel engine crankshafts through experimental modal analysis and combustion-based response characterization. The results emphasized the resonance frequency that dominate crankshaft behaviour, the role structural elements (journals, flywheel) in shifting the natural frequencies and the diagnostic value of the identified modes. Modal testing and transfer functions at selected excitation points revealed resonances between 200 Hz to 3000 Hz for main and connecting rod journals, with extracted natural frequencies and damping ratios using parametric methods. Frequency response functions (FRFs) revealed modal densities and resonance behaviours with dominant higher frequencies around 1440 Hz relate to local modes of the crank pin. Under combustion, dominant excitations around 1kHz 2.2 kHz and 3.8 kHz were observed, while motored conditions were dominated by low-frequency components (below 500 Hz) linked to valve operations and gas pressure fluctuations. These findings enhance understanding of crankshaft vibration behaviour and provide diagnostic capabilities for lubrication-induced impacts and system resonances. Based on the analysis of vibration modes and transfer function of IC engine crankshaft bearings, the tri-axial dynamic responses measured by the ORS sensor attached directly to free end of rotating crankshaft are analysed using advanced signal processing methods in joint time-frequency domain to characterise exhibited non-stationary and non-linear behaviours of modal responses. Temporal and spectral features extracted are based on for diagnosing the tribological condition of the crankshaft bearings. This study evaluated the effects of lubricant viscosity, temperature, and wear-induced faults on the dynamic responses of diesel engine crankshafts. Vibrations measured using ORS sensors revealed that higher viscosity oils reduced vibration levels through improved damping, especially at elevated temperatures. Under wear conditions, increased bearing clearance led to distinct frequency shifts and intensified frequency responses around 1 kHz at high speeds and loads. Time-frequency analysis also identified critical frequency bands 2.8 kHz to 4.5 kHz sensitive to lubrication and wear states. The results confirm that the ORS sensing method can provide a more straightforward indication due to capturing responses more related to the source events. The main findings demonstrate the feasibility of vibration diagnostics based on ORS sensing approach for detecting lubrication performance and tribological wear in heavy-duty engines.
Date of Award5 Feb 2025
Original languageEnglish
SupervisorFengshou Gu (Main Supervisor) & Andrew Ball (Co-Supervisor)

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