Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis

Bartelmus, Walter; Chaari, Fakher; Zimroz, Radosław; Haddar, Mohamed

doi:10.1016/j.euromechsol.2010.03.002

Cited by 136 publications

(81 citation statements)

References 17 publications

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“…Therefore, TF based condition monitoring methods can use another healthy system as a reference. This practice has been adopted by many other researchers as reported in [25], [26], [27], [5] where a healthy system was used as a reference to inspect the possible damage in a system of the same nature.…”

Section: Wind Turbine Bearing Condition Monitoringmentioning

confidence: 99%

Generalized Transmissibility Damage Indicator With Application to Wind Turbine Component Condition Monitoring

Zhang

Lang

Papaelias

2016

IEEE Trans. Ind. Electron.

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Abstract-Frequency methods such as frequency spectrum analysis, frequency spike detection, demodulation, envelope spectrum method have been widely used for condition monitoring of engineering structural systems. Different from the conventional frequency methods, the transmissibility function (TF) represents the relationship between different system output responses such as, e.g. vibration and acoustic emission sensor measurements. This paper introduces a simple and effective generalized transmissibility damage indicator (GTDI) for TF based condition monitoring. Unlike the conventional transmissibility damage indicator (TDI), the new GTDI can improve the detection sensitivity, reduces noise effects and avoid dynamic loadings effects. This is achieved by combining multiple groups of data to obtain more accurate transmissibility analysis, exploiting all the available TFs, and using multiple references. This has two advantages. First, it does not require any other priori knowledge about the system responses. Therefore the method can be used for the condition monitoring of a wide range of components or systems. Further, the method can be easily implemented using Fast Fourier transform (FFT) or power spectra density (PSD) methods and therefore is computationally efficient. These make the method very suitable for implementing online real-time condition monitoring. The method is investigated by simulation studies and then applied to analyze the vibration data of the main bearing of operating wind turbines, producing very promising results.

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Section: Wind Turbine Bearing Condition Monitoringmentioning

confidence: 99%

Generalized Transmissibility Damage Indicator With Application to Wind Turbine Component Condition Monitoring

Zhang

Lang

Papaelias

2016

IEEE Trans. Ind. Electron.

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“…To validate the obtained results with real object measurements, the case of a mining machine (MM) is considered [18][19][20]. The main component of this machine is the driving unit (DU) consisting in a motor, a coupling, a multistage gearbox.…”

Section: Experimental Validationmentioning

confidence: 99%

Gearbox Vibration Signal Amplitude and Frequency Modulation

Chaari

Bartelmus

Zimroz

et al. 2012

Shock and Vibration

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Abstract. Gearboxes usually run under fluctuating load conditions during service, however most of papers available in the literature describe models of gearboxes under stationary load conditions. Main task of published papers is fault modeling for their detection. Considering real situation from industry, the assumption of stationarity of load conditions cannot be longer kept. Vibration signals issued from monitoring in maintenance operations differ from mentioned models (due to load non-stationarity) and may be difficult to analyze which lead to erroneous diagnosis of the system. The objective of this paper is to study the influence of time varying load conditions on a gearbox dynamic behavior. To investigate this, a simple spur gear system without defects is modeled. It is subjected to a time varying load. The speed-torque characteristic of the driving motor is considered. The load variation induces speed variation, which causes a variation in the gearmesh stiffness period. Computer simulation shows deep amplitude modulations with sidebands that don't differ from those obtained when there is a defective tooth. In order to put in evidence the time varying load effects, Short Time Fourier Transform and then Smoothed Wigner-Ville distribution are used. Results show that the last one is well suited for the studied case.The experimental validation presented at the end of the paper confirms the obtained results. Such results offer useful information when diagnosing gear transmissions by avoiding confusing conclusions from vibration signals.

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“…The typical approach to dynamic modeling of the transmission [30,31] is to determine the deflection of mating teeth and by taking into account the variable meshing stiffness, to calculate the meshing force. This approach must take into account that during teeth mating instantaneous points of teeth contact move along the line (or plane in helical gears) of contact, deviating from the theoretical line (or surface).…”

Section: Model Of the Helical Gearboxmentioning

confidence: 99%

Model-based detection of local defects in gears

Mączak¹,

Jasiński²

2017

Arch Appl Mech

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The paper is presenting a methodology for developing model-based method of gear fault diagnostics. First the simulation model of the helical gearbox is discussed allowing analysis of the phenomena taking place during teeth mating in the presence of manufacturing and assembly errors. It includes observation of influence of errors on the generated signals. The model was initially used to analyze the teeth contact in the presence of pitch errors and later to verify the sensitiveness of proposed diagnostic methods and their availability to detect the fatigue damages of teeth. The common feature of discussed approach is the direct use of time signal processing algorithms, and in contrary to the methods based on spectral analysis it allows precise localization of gear defects like pitting and tooth fracture associating them to the particular pinion or gear teeth. Their advantage is the simplicity and speed of action that is of great significance for the implementation in the autonomous transmission diagnostic systems and diagnostic systems working online. Presented methods of signal processing were first tested on a simulation model of the gear assembly and later verified during the experiments on a back-to-back test stand.

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Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis

Cited by 136 publications

References 17 publications

Generalized Transmissibility Damage Indicator With Application to Wind Turbine Component Condition Monitoring

Generalized Transmissibility Damage Indicator With Application to Wind Turbine Component Condition Monitoring

Gearbox Vibration Signal Amplitude and Frequency Modulation

Model-based detection of local defects in gears

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