BITS Faculty Publications
Permanent URI for this communityhttp://localhost:4000/handle/123456789/1867
Browse
3 results
Search Results
Item Order Tracking Using Variational Mode Decomposition to Detect Gear Faults Under Speed Fluctuations, in 11th Annual Conference of the PHM Society 2019(Prognostics and Health Management Society, 2019-09) Choudhury, Madhurjya DevFault detection in gearboxes plays a significant role in ensuring their reliability. Vibration signals collected during gearbox operation contain a wealth of valuable condition information that can be exploited for fault detection. However, in an industrial environment machine operating speed always fluctuates around its nominal value, which causes smearing of the gearbox vibration spectrum. Considering operating speed fluctuation and multi-component nature of measured gearbox vibration signals, an order-tracking method combining the variational mode decomposition (VMD) and the fast dynamic time warping (FDTW) is proposed in this paper. Firstly, the multi-component vibration signal is decomposed into several intrinsic mode functions (IMFs) using VMD in order to extract a signal component with higher signal-to-noise ratio (SNR). Then, the sensitive fault information carrying IMF is exploited to estimate the instantaneous speed profile in order to construct the shaft rotational vibration signal. The measured vibration signal is then resampled based on the optimal warping path obtained by FDTW, which performs an “elastic” stretching and compression along the time axis of the extracted shaft vibration signal with respect to a sinusoidal reference signal of constant shaft rotational frequency. Finally, the gear fault is detected by constructing the order spectrum of the resampled vibration signal. The effectiveness of the proposed algorithm is demonstrated using simulation results.Item A Methodology to Handle Spectral Smearing in Gearboxes Using Adaptive Mode Decomposition and Dynamic Time Warping(IEEE, 2021-02) Choudhury, Madhurjya DevTacho-less order tracking is an effective tool for fault detection in gearboxes operating under speed fluctuations. This technique's performance depends on extracting instantaneous shaft speed information from a complex multicomponent gearbox signal, which is first preprocessed by a bandpass filter. However, spectral overlap resulting from the time-varying frequency components makes it challenging to isolate the shaft speed harmonic mono-component using this approach. In order to overcome such issues, an adaptive tacho-less order-tracking (OT) method combining the variational mode decomposition (VMD) and the fast dynamic time warping (FDTW) is proposed in this article. The proposed method first decomposes the measured gearbox vibration signal using VMD to estimate the instantaneous shaft speed profile to construct the shaft vibration signal. The gearbox vibration signal is then resampled based on the optimal warping path obtained by FDTW, which performs an “elastic” stretching and compression along the time axis of the extracted shaft vibration signal with respect to a sinusoidal reference signal with a constant shaft rotational frequency. Finally, the presence of gear fault is detected by constructing the order spectrum of the resampled vibration signal. The effectiveness of the proposed algorithm is demonstrated using both simulation analysis and experimental validation using measurements from two different wind-turbine gearboxes collected under test and field conditions, respectively.Item A novel tacholess order analysis method for bearings operating under time-varying speed conditions(Elsevier, 2021-12) Choudhury, Madhurjya DevOrder tracking (OT) of vibration envelope signal based on instantaneous frequency (IF) estimated from a time-frequency representation (TFR) is generally applied to detect bearing defects under time-varying speed conditions. However, these TFR based OT approaches require a high resolution for accurate estimation of the IF. To overcome these issues, a tacholess OT technique based on the fast dynamic time warping (FDTW) algorithm is applied to detect bearing defects for the first time in this paper. FDTW based signal transformation is initially applied to align a filtered shaft signal to a reference signal of constant frequency, followed by reconstructing the bearing envelope signal. The resulting envelope signal is able to provide a richer fault indication than the original signal. The efficacy of the developed OT method is established using a simulation analysis followed by experimental validation using measurements obtained from a laboratory test-rig and a wind turbine bearing.