As one of the most important components in rotating machinery, it's necessary and essential to monitor the rolling bearing operating condition to prevent equipment failure or accidents. However, in vibration signal processing, the bearing initial fault detection under background noise is quite difficult. Therefore, in this paper a new feature extraction method combining sparse reconstruction and Multiscale Dispersion Entropy (MDErms) is proposed. Firstly, the Sliding Matrix Sequences (SMS) truncation and sparse reconstruction by Hankel-matrix are applied to the vibration signal. Then MDErms is utilized as a characteristic index of vibration signal, which is suitable for a short time series. Additionally, the MDErms is employed in the sparse reconstructed matrix sequences to achieve the Multiscale Fusion Entropy Value Sequence (MFEVS). The MFEVS keeps the fault potential feature information in different scales and is superior in distinguishing fault periodic impulses from heavy background noise. Finally, the designed FIR bandpass filter based on the MFEVS, shows prominent features in denoising and detecting weak bearing faults, which is separately verified by simulation studies and artificial fault experiments in different cases. By comparison with traditional methods like EEMD, Wavelet Packet (WP), and fast kurtogram, it can be concluded that the proposed method has a remarkable ability in removing noise and detecting rolling bearing faint fault.

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Currently, there is very limited understanding of a gas explosion process inside residential buildings. In this study, a numerical model of gas explosion in a residential building was developed using Computational Fluid Dynamics (CFD). The numerical simulations were performed for different gas cloud filling regions and equivalence ratios to identify the initial scenario, and the simulation results were compared with the real consequences of gas explosion. Additionally, the temporal and spatial evolvement characteristics of explosion overpressure and indoor temperature were analyzed. Furthermore, the effects of vent area ratio and the activation pressure of vent panels in the kitchen were investigated to propose effective mitigation measures for the gas explosions inside residential buildings. The results show that the simulation results reproduced by the CFD model are in good agreement with the real accident consequences. During the explosion process, the overpressure distribution in a room is almost uniform at the same moment and there exists little spatial difference. The maximum temperature can reach up to 1953°C, which can cause secondary fire accidents easily. The maximum flame speed is in the range of 34.3 m/s and 230.9 m/s. It indicates that gas explosion inside residential buildings is a typical deflagration process. When the vent area ratio is less than 0.3, the overpressure peaks decrease rapidly with the increase of the vent area ratio. However, when the vent area ratio is larger than 0.3, the overpressure peaks are almost independent on the vent area ratio. There is a proportional relationship between the overpressure peaks and the activation pressure of vent panels. These achievements provide reliable reference data for the accident investigation of gas explosion and subsequent treatment.

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