Vibration Analysis and Diagnostics of a High Speed Centrifuge for Fast Reactor Fuel Reprocessing Applications

The cladding of fast reactor fuel rods, made of stainless steel, presents significant challenges in cutting due to its ductility, which leads to increased tool wear and poor cut quality with traditional mechanical methods. Laser cutting has emerged as a superior alternative, offering non-contact precision, high efficiency, and suitability for radioactive environments. This study systematically investigates the effects of laser cutting parameters—cutting speed, focal position, power, and gas pressure—on the cutting quality of simulated fast reactor fuel rods. The results show that optimal cutting is achieved with a cutting speed of 1 m/min, a focal position between − 20 and − 25 mm, a laser power between 7200 and 9600 W, and a gas pressure of 10 MPa. These parameters provide the best balance between cutting efficiency, surface roughness, and minimal slag formation. This study contributes valuable insights into optimizing laser cutting technology for nuclear fuel rod processing, with potential applications in fuel reprocessing and decommissioning.

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Rolling Element Bearing Fault Identification using Vibration Data

Prawin

2023

Int. J. Str. Stab. Dyn.

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Early fault detection and diagnosis of rolling element bearing is of paramount importance in wind turbines as it contributes to around 70% of gearbox and 21%–70% of generator failure. When a rolling element bearing strikes a local fault in the inner or outer race, a shock (high frequency) is introduced, and repetitive impact occurs due to continuous rotation. Extracting the fault-sensitive repetitive impact frequency component from the measured signal containing multiple frequencies (discrete gear and shaft frequency, bearing fault frequency and high-frequency noise) is challenging. This paper presents two vibration techniques based on enhanced envelope analysis and blind deconvolution technique for bearing fault identification. The improved envelope analysis diagnosis bearing faults using the three-step process of removing gear and shaft frequency components by auto-regression model, followed by spectral kurtosis to extract fault-sensitive features and envelope analysis to identify bearing faults. On the contrary, the enhanced blind deconvolution extracts the fault-sensitive component by finding the best inverse finite impulse response filter from the measured vibration signal by adaptively demodulating resonance bands due to repetitive impact and reducing the periodic noise component in a single step. The application of the two bearing fault diagnosis techniques and their comparative study has been demonstrated through numerical simulations and two industrial testrig bearing benchmark datasets. Investigations concluded that both methods extract the transient impulse features due to bearing fault; however, the enhanced blind deconvolution technique outperforms the envelope analysis in the case of measured vibration signal with outliers.

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Vibration Analysis and Diagnostics of a High Speed Centrifuge for Fast Reactor Fuel Reprocessing Applications

Cited by 5 publications

References 16 publications

Experimental study on the laser cutting process of the stainless steel hexagonal tube of fast reactor simulate assembly

Experimental study on the laser cutting process of the stainless steel hexagonal tube of fast reactor simulate assembly

Experimental study on laser cutting process of simulated fast Reactor fuel rods

Rolling Element Bearing Fault Identification using Vibration Data

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