Search

The fault diagnosis of early failure bearing can discover the potential danger in the mechanical equipment in time. It remains a great challenge due to the noise interference. Although many diagnosis methods have been proposed, the characteristics of signal have not yet been fully investigated, which leads to unsatisfactory diagnosis results. To solve this problem, a weak fault detection method with a two-stage key frequency focusing model is designed. Translation invariance in time domain and translation variance in frequency domain are systematically considered. The effectiveness is verified on four constructed datasets. The results show that the designed network has the best comprehensive performance comparing to the state-of-the-art methods. • The attributes of TITD and TIFD are considered simultaneously • A model is proposed to solve the challenge of considering TITD and TVFD • Both the accuracy and the lightness of the model have been improved • The validity of the method is verified by four datasets [ABSTRACT FROM AUTHOR]

The selection of the filter band for demodulation is crucial to extract the weak repetitive transients of fault rolling element bearing (REB). However, when the signal to noise is low, traditional methods for finding a suitable filter band are susceptible to the cyclostationary (CS) interference and the abnormal shock. In order to solve this problem, a new extraction method with reweighted singular value decomposition and improved Fast_kurtogram, namely RWSVD_IFK, is proposed. Firstly, by combining the new weight factors with singular components, a novel denoised strategy is presented to preprocess the original signal for reducing the CS interference. Secondly, considering that the kurtosis index is sensitive to the abnormal shock, the proposed method introduces the autocorrelation function into Fast_kurtogram to weaken the interference of the abnormal shock. And then, the squared envelope is applied to extract the weak repetitive transients from the optimal filtered signal. The simulated data and measured data of the fault REB are used to verify the validity of the proposed RWSVD_IFK. The results show that the proposed method can overcome the CS interference and the abnormal shock in finding the optimal filter band and effectively extract the weak repetitive transients of fault REB. • RWSVD-IFK is proposed for extracting weak repetitive transients of fault bearing. • A novel strategy for decreasing cyclostationary noise is proposed by using RWSVD. • Improved Fast_kurtogram (IFK) overcomes the influence of the abnormal shock. • Simulation and experiment highlight the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Whiskers have been extensively used in ceramics as excellent reinforcing phases during the past decades. Despite in-depth investigation of whisker-reinforced ceramics (WRC), however, the time-consuming, environmentally unfriendly, content design blindness of experimental method as well as pathogenicity of whiskers force people to explore quick and green research approaches. Therefore, this work aims at developing a modeling approach of WRC and predicting the mechanical properties of WRC, thereby compensating for the disadvantages of traditional experimental method. Initially, a modeling approach of WRC based on Voronoi tessellation was presented. Then, taking β-Si 3 N 4w and Si 3 N 4 as research objects, the prediction models of mechanical properties of 0–6 wt% β-Si 3 N 4w -reinforced Si 3 N 4 ceramics (SWRSC) were established. Finally, the effect of β-Si 3 N 4w content on mechanical properties of Si 3 N 4 -based ceramics was discussed, and the enhancement mechanism of β-Si 3 N 4w was revealed. Results indicated that the flexural strength of SWRSC was significantly advanced with increasing β-Si 3 N 4w content. Crack deflection and intergranular fracture induced by β-Si 3 N 4w as well as load-bearing effect of β-Si 3 N 4w were the mainly responsible for the reinforcement of Si 3 N 4 -based ceramics. The enhancement mechanisms, previously observed experimentally, were effectively simulated. The fracture toughness reached a maximum of 6.17 MPa m1/2 when β-Si 3 N 4w amount was 1 wt%, which was approximately 36.50% higher than monolithic Si 3 N 4 ceramic. The predicted value of β-Si 3 N 4w optimal content was consistent with relevant experimental conclusions. When β-Si 3 N 4w content was 3 wt%, the hardness of Si 3 N 4 -based ceramics reached the maximum value of 23.21 GPa. The effectiveness of prediction results and the presented modeling method were confirmed by comparing with related test values. [ABSTRACT FROM AUTHOR]

The trial-and-error method used in ceramics research has certain limitations such as the high blindness of material component design. Moreover, calculations of the toughness of ceramics using the extended finite element method, which is the most broadly applied technique, are complicated. To overcome these issues, in this study, multilayer graphene (MLG)/Si 3 N 4 whisker (Si 3 N 4w)-reinforced Si 3 N 4 ceramics (MWSCs) were used as the model material, and the modeling of MWSCs was conducted using Voronoi tessellation. Additionally, a more concise novel approach was applied for the prediction of the fracture toughness of MWSCs. Furthermore, the optimal MLG and Si 3 N 4w contents were predicted, and then they were verified by fabricating MWSCs using spark plasma sintering (SPS). Simulation results indicated that the optimum MLG and Si 3 N 4w contents to enable the toughness and hardness to reach the maximum values (9.87 MPa·m1/2 and 23.19 GPa) were 1 wt% and 3 wt%, which were consistent with the experimental results. Consequently, the effectiveness of the proposed method was verified. Moreover, the experimental values of the maximum fracture toughness and hardness were 11.04 MPa·m1/2 and 20.29 GPa, which were 47.20% and 12.10% higher than those of Si 3 N 4 ceramics reinforced with 1 wt% MLG, respectively. The synergistic toughening effects of MLG and Si 3 N 4w were significantly reflected. The load-bearing effect, bridging, and crack deflection induced by MLG and Si 3 N 4w were the key reasons for the improvement in the mechanical properties of MWSCs. [ABSTRACT FROM AUTHOR]

Imbalance is a typical characteristic of data in the field of intelligent fault diagnosis. As a data augmentation method that both balances data and extends information, the generative adversarial network has aroused widespread concern in the data imbalance problem. However, it still suffers from high difficulty in model training and poor quality of generated samples. To address this issue, this paper proposes a progressive generative adversarial network, which is a strategy able to gradually generate complex signals from low-frequency signals to wide-frequency signals. In the developed network, on the one hand, decomposing signals into different frequency bands explicitly reduces the difficulty of directly generating high-dimensional and wide-frequency signals. On the other hand, different generative models can focus on different frequency bands, avoiding the interference of high-energy signals on the fault feature frequencies. In order to achieve good generative performance, the generators and training method for the progressive generative adversarial network are elaborately designed. The correlation shortcut avoids information suppression due to the poor selection of noise amplitudes, and the focusing shortcut forces the body of the generator to focus on key feature bands. Ultimately, the superiority of the progressive generative network is verified by evaluating the quality of the generated samples on three datasets and applying the generated samples to solve the data imbalance problem. • A progressive generation framework is proposed to improve the quality of the generated signal. • The proposed generator retains the correlation between low and high frequencies. • The proposed generator can focus on specific frequency bands. • Model at each level is trained independently to avoid the accumulation of errors. [ABSTRACT FROM AUTHOR]

Exploring ceramic-based self-lubricating materials with low coefficient of friction (COF) has become one of the hot directions to advance the service performance and life of high-end equipment. In this work, the tribological properties of multilayer graphene (MLG)/β-Si 3 N 4 whisker (β-Si 3 N 4w)/Si 3 N 4 ceramics were investigated. The effects of load and linear speed on the dry sliding COF were discussed. The friction-reducing and self-lubricating mechanisms of MLG and β-Si 3 N 4w were deeply analyzed according to the wear morphology and mechanical properties of Si 3 N 4 -based ceramics. The friction frequency was proposed to analyze the wear mechanism. Results indicated that MLG and β-Si 3 N 4w led to a breakthrough reduction in COF. At the load of 5–20 N, the COF reached an ultra-low level of 0.04–0.07, which was a further 89.86% lower than the reported studies. The comprehensive enhancement of mechanical properties and the existence of MLG lubricating film were the mainly responsible for the ultra-low COF. The COF of MLG/β-Si 3 N 4w /Si 3 N 4 ceramics raised to 0.24–0.31 at 50–200 mm/s, but it was still 33.88–47.64% lower than that of graphene/Si 3 N 4 ceramics. The increase in COF was attributed to the high wear induced by the raised friction frequency. The furrow wear and adhesive wear were the main wear forms of MLG/β-Si 3 N 4w /Si 3 N 4 ceramics. [ABSTRACT FROM AUTHOR]

The performance of intelligent fault diagnosis models is often hindered by the lack of available samples, a common issue in both the few-shot learning and imbalanced learning problems. While data generation has been shown to be an effective strategy for addressing this issue, existing methods tend to focus solely on the similarity of the generated samples, overlooking their diversity. In this regard, a self-reasoning training strategy that enables the participation of highly reliable generated samples in the training process is proposed. By augmenting the training samples, the strategy provides the generation model with diverse input information, effectively enhancing the diversity of the samples generated by the model. To assess the reliability of the generated samples, Pearson correlation coefficient between the generated and real samples in the amplitude–frequency domain is utilized. To this end, an amplitude–frequency domain generation model is constructed. In order to avoid issues such as gradient disappearance and convergence degradation during the generation process in the amplitude–frequency domain, a phase-frequency domain generation model as well as a time domain discriminator model are developed. While the phase-frequency domain generation model enhances the diversity of the generated samples in that domain, the time domain discriminator model ensures sample similarity by correlating the amplitude–frequency domain generation model with the phase-frequency domain generation model. Through experiments, it is demonstrated that the proposed method can effectively address the overfitting problem of generative adversarial networks with few samples, improving the diversity of the generated samples. Moreover, the improvement in fault diagnosis performance achieved by the samples generated by the proposed method further underscores its potential and superiority in practical applications. • A self-reasoning training strategy is proposed. • A generation model driven by multi-domain information is developed. • The quality (similarity and diversity) of the generated samples is enhanced. [ABSTRACT FROM AUTHOR]

High-efficiency quantum cutting materials have great application prospects in improving the photoelectric conversion efficiency of silicon-based photoelectric devices. Herein, La3+ and Yb3+ ions co-doped CsPbCl 3 perovskite quantum dots (PQDs) were prepared successfully via the modified hot-injection method. La3+ and Yb3+ ions codoping makes the PLQY of CsPbCl 3 PQDs increase from 5% to 168%. This is because Yb3+ ions doping makes the effective quantum cutting process happen, as well as La3+ ions doping effectively reduces non-radiative transition in CsPbCl 3 PQDs and further improves the quantum cutting efficiency. Finally, La3+ and Yb3+ ions co-doped CsPbCl 3 PQDs film were integrated on silicon-based photodetectors. The spectral range of silicon-based photodetectors is extended to the ultraviolet (UV) region (200–400 nm) besides the visible spectral region. The external quantum efficiency (EQE) is around 67%, and the responsivity is 0.14 A/W, which is comparable to the highest value previously reported. This work provides a new strategy to improve the quantum cutting efficiency and the performance of silicon-based photodetectors. • The PLQY of CsPbCl 3 PQDs increase from 5% to 168% via La3+ and Yb3+ codoping. • La3+/Yb3+ co-doped CsPbCl 3 PQDs were integrated on silicon photodetectors. • The response spanning of silicon photodetectors is extended to the ultraviolet. [ABSTRACT FROM AUTHOR]

Lead-free perovskites are a new type of luminescent material with non-toxic, stability and excellent photoelectric properties, which have great application in the field of photoelectric detection, solar cells, bio-imaging, etc. Here, we reported a new kind of uniform spherical rare-earth based double perovskite Cs 2 NaYCl 6 nanocrystals (NCs) as versatile hosts to accommodate ionic dopants for improving photoelectric properties especially the luminescent properties. In contrast to the low quantum yield of only 5.62%, the luminescent intensity of Cs 2 NaYCl 6 NCs can be impressively enhanced via doping Sb3+ and Mn2+ ions in the rare earth-based double perovskite lattices. For the Sb3+-doping, the photoluminescence quantum yield (PLQY) increases from 5.62% to 22.48%. On this basis, the luminescence colors can be tuned from blue to white and red via Mn2+ ions doping and the maximum PLQY can be further improved to 38.66%. Finally, the Sb3+, Sb3+/Mn2+ ions doped Cs 2 NaYCl 6 NCs based blue, red and white LEDs were explored, which indicates that these are potential materials in multicolor LEDs applications. [ABSTRACT FROM AUTHOR]

• Three groups of glycosyltransferase 64 (GT64) family are widely conserved in Angiospermae. • Four rice GT64 genes all localize to the Golgi apparatus and show distinct tissue-specific expression patterns. • Genomic variation analysis of OsGT64s revealed that the indica – japonica or latitudinal differentiation exists in their coding sequences. • Promoter element and expression analysis of OsGT64s suggested that they may play a role in different stress responses and hormone signaling pathways. The glycosyltransferase 64 (GT64) family is widely conserved in many species, including animals and plants. The functions of GT64 family genes in animals have been well characterized in the biosynthesis of extracellular heparan sulfate, whereas two GT64 members in Arabidopsis thaliana are involved in the glycosylation of plasma membrane glycosylinositol phosphorylceramides (GIPCs). GIPCs are the main components of plant sphingolipids and serve as important signal molecules in various developmental processes and stress responses. Rice (Oryza sativa), a model monocot plant, contains four GT64 members in its genome. Using phylogenetic analysis, 73 GT64s from 19 plant species were divided into three main groups. Each group can be represented by the three members in Arabidopsis and show a trend of monocot-eudicot divergence. A promoter and genomic variation analysis of GT64s in rice showed that various stress-related regulatory elements exist in their promoters, and many sequence variations were found between the two main rice subspecies, japonica and indica. Additionally, transmembrane domain and subcellular localization analyses revealed that these genes all encode membrane-bound glycosyltransferases and are localized to the Golgi apparatus. Finally, expression analysis of the four GT64 genes in rice, as assessed by quantitative real-time PCR, showed that they have distinct tissue-specific expression patterns and respond to different hormone treatments or abiotic stresses. Our results indicated that this family of genes may play a role in different stress responses and hormone signaling pathways in rice, which will provide fundamental information for further investigation of their functions in future. [ABSTRACT FROM AUTHOR]

This work aimed at investigating the superiorities of multilayer graphene (MLG) and β-Si 3 N 4 whisker (β-Si 3 N 4w) in synergistically enhancing the toughness of Si 3 N 4 ceramic composites. First, Si 3 N 4 ceramic composites with hybrid 1 wt% MLG and 0 – 5 wt% β-Si 3 N 4w were sintered by spark plasma sintering. Phase constitutions and microstructures of Si 3 N 4 -based ceramic composites were characterized by X-rays diffraction, Raman spectra, and scanning electron microscope. Then, the optimal β-Si 3 N 4w content and sintering process of MLG/β-Si 3 N 4w -toughened Si 3 N 4 ceramic composites were comprehensively optimized by orthogonal experiments. Results indicated that in the case of maintaining the hardness of 15.87 – 18.84 GPa, the fracture toughness of Si 3 N 4 ceramic composites incorporated with 1 wt% MLG and 3 wt% β-Si 3 N 4w was advanced to 11.04 MPa·m1/2, which was 11.29% and 87.12% higher than that of 1 wt% MLG- and 3 wt% β-Si 3 N 4w -reinforced Si 3 N 4 ceramic composites, respectively. Orthogonal experiments demonstrated that 1 wt% MLG/3 wt% β-Si 3 N 4w -toughened Si 3 N 4 ceramic composites sintered at 1600 ℃, 40 MPa, and holding time for 6 min had optimum comprehensive mechanical properties. MLG wrapping and the synergistic effects of pull out, crack deflection, crack branching, and bridging resulted by MLG and β-Si 3 N 4w were the main responsible for the enhancement of toughness. [Display omitted] • MLG/β-Si 3 N 4w synergistic toughened Si 3 N 4 ceramics were sintered by SPS. • Fracture toughness of Si 3 N 4 -based ceramics was enhanced to 11.04 MPa·m1/2. • Optimal contents of MLG and β-Si 3 N 4w were 1 wt% and 3 wt%. • Optimum sintering process were 1600 ℃, 40 MPa, and holding time for 6 min. [ABSTRACT FROM AUTHOR]

• The dynamic transition of FCPBB's contact states was revealed under high-speed conditions. • Three-point contact state of FCPBB for specific conditions was optimized. • Eccentricity has a substantial effect on the FCPBB performance. • A smaller curvature coefficient or larger eccentricity can reduce bearing sliding. Three-point contact state is a common state for four-point contact ball bearings (FPCBB), significantly improving the performance in high-speed and light-load conditions. However, in this case, the internal contact state is in a dynamic transition between two-point and three-point contact, with substantial frictional losses. To this end, a nonlinear dynamic model of FPCBB, considering the lubrication traction and the bearing assemblies' dynamic features, is proposed to optimize the FPCBB's performance for three-point contact state. The dynamic changes of contact states under high-speed and light-load conditions are revealed, and four sets of conditions are picked as optimization conditions. Beside, groove curvature coefficient and curvature center eccentricity, depending on outer ring structure, are selected as optimized structural parameters. On this basis, the behavior performance in three-point contact state is optimized for specific operating conditions. The results show that with the gradual growth of eccentricity, the bearing fatigue life first extends slowly and then reduces rapidly, where an optimum value exists; for bearings possibly serving in skidding condition, it is better to prefer a larger eccentricity or a smaller curvature coefficient to reduce sliding damage. [Display omitted] [ABSTRACT FROM AUTHOR]