To improve the stability of rolling bearing fault signal denoising under different working conditions, this study proposes a multi-condition rolling bearing fault denoising method based on RIME-VMD. According to the characteristics of rolling bearing fault signal, RIME (frost and ice algorithm) is utilized to obtain adaptive optimization of the modal number and penalty factors in VMD (variational mode decomposition) algorithm, and then the optimized core parameters are input into VMD to decompose the rolling bearing fault signal. The fitness function is established by introducing the fusion of power spectrum entropy and kurtosis value; these intrinsic modal functions (IMFs) with high correlation based on original rolling bearing fault signal are selected to reconstruct the rolling bearing fault denoising signal. The experimental results show that the RIME-VMD method can effectively remove most of the noise in the rolling bearing fault signal, and the performance evaluation indexes of this method are better than other existing optimization algorithms. The research achievement of this study can provide effective data support for the fault diagnosis of bearing equipment.

A novel method was proposed to fabricate a ZnO seed layer with a protrusion and matrix structure, and then ZnO nanorods could be synthesized on it using the hydrothermal method to form ZnO nanoflower arrays (NFAs) easily. A patterned sapphire with a matrix cavity was used as the template, ZnO gel was deposited on the multilayer substrates using spinning coating, and the prepared seed layer with a protrusion and an array-patterned structure was moved to a Si substrate using the lift-off method. Because the ZnO seed layer exhibited a matrix and protrusion structure, ZnO nanorods were grown vertically downwards and formed ZnO NFAs. The XRD patterns resulting from analyses showed that the diffraction peaks of the five growth directions of ZnO NFAs increased as growth time increased. Furthermore, SEM and FIB analyses indicated that the length, width, aspect ratio, and total surface area of ZnO NFAs grown on the transferred seed layer increased as the synthesis time increased. Different ZnO NFAs synthesized for varying synthesis times were used to investigate methylene blue degradation, with the effect of ZnO NFAs on methylene blue degradation determined using the Beer–Lambert law. Our results demonstrate that the effect of ZnO NFAs on methylene blue degradation was enhanced with increasing synthesis time.

In this study, we utilized a sapphire substrate with a matrix protrusion structure as a template. We employed a ZnO gel as a precursor and deposited it onto the substrate using the spin coating method. After undergoing six cycles of deposition and baking, a ZnO seed layer with a thickness of 170 nm was formed. Subsequently, we used a hydrothermal method to grow ZnO nanorods (NRs) on the aforementioned ZnO seed layer for different durations. ZnO NRs exhibited a uniform outward growth rate in various directions, resulting in a hexagonal and floral morphology when observed from above. This morphology was particularly evident in ZnO NRs synthesized for 30 and 45 min. Due to the protrusion structure of ZnO seed layer, the resulting ZnO nanorods (NRs) displayed a floral and matrix morphology on the protrusion ZnO seed layer. To further enhance their properties, we utilized Al nanomaterial to decorate the ZnO nanoflower matrix (NFM) using a deposition method. Subsequently, we fabricated devices using both undecorated and Al-decorated ZnO NFMs and deposited an upper electrode using an interdigital mask. We then compared the gas-sensing performance of these two types of sensors towards CO and H₂ gases. The research findings indicate that sensors based on Al-decorated ZnO NFM exhibit superior gas-sensing properties compared to undecorated ZnO NFM for both CO and H₂ gases. These Al-decorated sensors demonstrate faster response times and higher response rates during the sensing processes.