The rotational frequency (RF) is an important information for multi-fault features detection of rolling bearing under varying speed conditions. In the traditional methods, such as the computed order ...analysis (COA) and the time–frequency analysis (TFA), the RF should be measured using an encoder or extracted by a complex algorithm, which bring challenge to bearing fault diagnosis. In order to address this issue, a novel iterative generalized demodulation (IGD) based method guided by the instantaneous fault characteristic frequency (IFCF) extraction and enhanced instantaneous rotational frequency (IRF) matching is proposed in this paper. Specifically, the resonance frequency band excited by bearing fault is first obtained by the band-pass filter, and its envelope time–frequency representation (TFR) is calculated using the Hilbert transform and the short-time Fourier transform (STFT). Second, the IFCF is extracted using the harmonic summation-based peak search algorithm from the envelope TFR. Third, the time-varying RF ridge is transformed into a line paralleling to the time axis using the IGD with the phase function (PF). The PF is calculated by the IFCF function and fault characteristic coefficient (FCC). Lastly, the iterative generalized demodulation spectrum (IGDS) is obtained using the fast Fourier transform (FFT) for identifying fault type corresponding to the extracted IFCF. Based on obtained fault type and FCC ratios, new PFs and frequency points (FPs) are calculated for detecting other faults. Both simulated and experimental results validate that multi-fault features of rolling bearing under time-varying rotational speeds can be effectively identified without RF measurement and extraction.
•An IGD-based bearing multi-fault diagnosis strategy under time-varying speeds conditions is proposed.•The technique is guided by IFCF extraction and enhanced RF matching.•The IGD is used to eliminate influence of rotational speed fluctuation.•The IGDS is constructed to quantitatively diagnose bearing fault.
Planetary gearbox is a critical component for many mechanical systems. It is essential to monitor the planetary gearbox health and performance in order to maintain the whole machine works well. The ...methodology of mechanical fault diagnosis is increasingly intelligent with the extensive application of deep learning. However, the cross-domain issue caused by varying working conditions becomes an enormous encumbrance to fault diagnosis based on deep learning. In this paper, in order to fully excavate potentialities of deep neural network architectures, a novel generative adversarial learning method was introduced for a completely new fault diagnosis based on a deep convolution neural network. In addition, the intelligent fault diagnostic scheme for planetary gearbox under varying speed conditions was developed. After that, some experiments on measured vibration signals of planetary gearbox were conducted to verify the validity and efficiency of the fault diagnostic scheme. The results showed that the proposed method enhanced the capability of the intelligent diagnosis for planetary gear faults under varying speed conditions.
Twisted Generalized Reed-Solomon (TGRS) Codes are a class of linear codes which contain MDS codes but are not equivalent to GRS code. In recent years, many scholars have studied the construction of ...MDS self-dual codes through TGRS code. Among these works, the number of twists is actually quite small, and an important step in showing a TGRS code is self-dual is to find its parity-check matrix. In this paper, we focus on the computation of parity-check matrices of TGRS codes with almost no restrictions on twist and hook vectors. By application of elementary row (column) operations in linear algebra, we present a unified but elementary approach to obtain the parity-check matrices of TGRS codes. This paper creates a foundation for further study of MDS self-dual TGRS codes on a much broader scope.
Alzheimer's disease (AD) is a fatal neurodegenerative disease characterized by progressive cognitive decline and memory loss. However, several therapeutic approaches have shown unsatisfactory ...outcomes in the clinical setting. Thus, developing alternative therapies for the prevention and treatment of AD is critical. Salidroside (SAL) is critical, an herb-derived phenylpropanoid glycoside compound, has been shown to attenuate lipopolysaccharide (LPS)-induced cognitive impairment. However, the mechanism underlying its neuroprotective effects remains unclear. Here, we show that SAL has a therapeutic effect in the senescence-accelerated mouse prone 8 (SAMP8) strain, a reliable and stable mouse model of AD.
SAMP8 mice were treated with SAL, donepezil (DNP) or saline, and cognitive behavioral impairments were assessed using the Morris water maze (MWM), Y maze, and open field test (OFT). Fecal samples were collected and analyzed by 16S rRNA sequencing on an Illumina MiSeq system. Brain samples were analyzed to detect beta-amyloid (Aβ) 1-42 (Aβ1-42) deposition by immunohistochemistry (IHC) and western blotting. The activation of microglia and neuroinflammatory cytokines was detected by immunofluorescence (IF), western blotting and qPCR. Serum was analyzed by a Mouse High Sensitivity T Cell Magnetic Bead Panel on a Luminex-MAGPIX multiplex immunoassay system.
Our results suggest that SAL effectively alleviated hippocampus-dependent memory impairment in the SAMP8 mice. SAL significantly 1) reduced toxic Aβ1-42 deposition; 2) reduced microglial activation and attenuated the levels of the proinflammatory factors IL-1β, IL-6, and TNF-α in the brain; 3) improved the gut barrier integrity and modified the gut microbiota (reversed the ratio of Bacteroidetes to Firmicutes and eliminated Clostridiales and Streptococcaceae, which may be associated with cognitive deficits); and 4) decreased the levels of proinflammatory cytokines, particularly IL-1α, IL-6, IL-17A and IL-12, in the peripheral circulation, as determined by a multiplex immunoassay.
In summary, SAL reversed AD-related changes in SAMP8 mice, potentially by regulating the microbiota-gut-brain axis and modulating inflammation in both the peripheral circulation and central nervous system. Our results strongly suggest that SAL has a preventive effect on cognition-related changes in SAMP8 mice and highlight its value as a potential agent for drug development.
Abstract
Background
Alzheimer’s disease (AD) is a neurodegenerative disease. Ferroptosis plays a critical role in neurodegenerative diseases. Nuclear factor E2-related factor 2 (Nrf2) is considered ...an important factor in ferroptosis. Studies have demonstrated that salidroside has a potential therapeutic effect on AD. The intrinsic effect of salidroside on ferroptosis is unclear. The purpose of this study was to investigate the protective effects and pharmacological mechanisms of salidroside on alleviating neuronal ferroptosis in Aβ
1−42
-induced AD mice and glutamate-injured HT22 cells.
Methods
HT22 cells were injured by glutamate (Glu), HT22 cells transfected with siRNA Nrf2, and Aβ
1−42
-induced WT and Nrf2
−/−
AD mice were treated with salidroside. The mitochondria ultrastructure, intracellular Fe
2+
, reactive oxygen species, mitochondrial membrane potential, and lipid peroxidation of HT22 cells were detected. Malondialdehyde, reduced glutathione, oxidized glutathione disulfide, and superoxide dismutase were measured. The novel object recognition test, Y-maze, and open field test were used to investigate the protective effects of salidroside on Aβ
1−42
-induced WT and Nrf2
−/−
AD mice. The protein expressions of PTGS2, GPX4, Nrf2, and HO1 in the hippocampus were investigated by Western blot.
Results
Salidroside increased the cell viability and the level of MMP of Glu-injured HT22 cells, reduced the level of lipid peroxidation and ROS, and increased GPX4 and SLC7A11 protein expressions. These changes were not observed in siRNA Nrf2 transfected HT22 cells. Salidroside improved the ultrastructural changes in mitochondria of HT22 cells and Aβ
1−42
-induced AD mice, but not in Aβ
1−42
-induced Nrf2
−/−
AD mice. Salidroside increased protein expression levels of GPX4, HO1, and NQO1 and decreased protein expression of PTGS2 in Aβ
1−42
-induced AD mice but not in Aβ
1−42
-induced Nrf2
−/−
AD mice.
Conclusions
Salidroside plays a neuroprotective role by inhibiting neuronal ferroptosis in Aβ
1−42
-induced AD mice and Glu-injured HT22 cells, and its mechanism is related to activation of the Nrf2/HO1 signaling pathway.
Graphical Abstract
Renal fibrosis progression is closely associated with aging, which ultimately leads to renal dysfunction. Salidroside (SAL) is considered to have broad anti-aging effects. However, the roles and ...mechanisms of SAL in aging-related renal fibrosis remain unclear. The study aimed to evaluate the protective effects and mechanisms of SAL in SAMP8 mice. SAMP8 mice were administered with SAL and Ferrostatin-1 (Fer-1) for 12 weeks. Renal function, renal fibrosis, and ferroptosis in renal tissue were detected. The results showed that elevated blood urea nitrogen (BUN) and serum creatinine (SCr) levels significantly decreased, serum albumin (ALB) levels increased, and mesangial hyperplasia significantly reduced in the SAL group. SAL significantly reduced transforming growth factor-β (TGF-β) and α-smooth muscle actin (α-sma) levels in SAMP8 mice. SAL treatment significantly decreased lipid peroxidation in the kidneys, and regulated iron transport-related proteins and ferroptosis-related proteins. These results suggested that SAL delays renal aging and inhibits aging-related glomerular fibrosis by inhibiting ferroptosis in SAMP8 mice.
Deep learning has the characteristics of high efficiency, high accuracy and low knowledge dependence, and has become a hot method in the research field of rotating machinery fault diagnosis. The ...time–frequency transform can show both the time and frequency characteristics of the vibration signal, so the time–frequency image is often used as the input of deep learning networks. At present, there are many time–frequency transform methods, and how to choose one is a problem worth discussing. This paper proposed a time–frequency image quality evaluation method based on improved local interpretable model-agnostic explanations (LIME). With the input of deep learning networks as the application background, this method evaluates the time–frequency image quality of rotating machinery vibration signals from two aspects: the accuracy of the diagnosis results and the consistency of the interpretation results with prior knowledge. The feasibility of the proposed evaluation method is verified by experiments on the measured data set, and engineers’ trust in the deep learning model is improved.
With the great leaps forward in the development of the railway, the importance of safe operation and maintenance has become increasingly prominent. Varistor is the key component insurge protective ...devices for railway communication and signaling equipment, it is necessary to study a description model of the varistor degradation process and predict its lifetime through condition monitoring. Among the monitoring parameters, nonlinear coefficient is an important index to measure the health of varistors. Considering that the degradation process of varistors is the cumulative effect of surge history, and its nonlinear coefficient has a time–series relationship, a life prediction model for varistors based on BiLSTM is proposed. The model innovatively uses nonlinear coefficient as the characterization of the deterioration degree of varistors and uses a small-scale network to predict the development trend of nonlinear coefficient automatically and accurately. Verified by surge impact experiments, the model can accurately predict the state of nonlinear coefficient according to historical data and has the potential for engineering applications in predicting the life of varistors.
This paper proposes a fault diagnosis method for rotating machinery based on evolutionary convolutional neural network (ECNN). With the time-frequency images as the network input, with the help of ...the global optimization ability of the genetic algorithm, the structure of the convolutional neural network can evolve autonomously, and the adaptive configuration of the structural hyperparameters for the target task is realized. In this paper, the proposed method is verified by the measured signal of the planetary gearbox. The results show that the proposed method is helpful to obtain a convolutional neural network structure with better performance and achieve higher fault diagnosis accuracy.
Nanostructured ceramic coatings are a promising research hotspot in the field of thermal protection coatings. Suspension plasma spraying is a practical thermal spaying technique to produce ...nanostructured thermal barrier coatings. In this paper, nanostructured 8YSZ (8 wt.% yttria-stabilized zirconia) thermal barrier coatings were fabricated using feedstocks of nano-8YSZ suspension by suspension plasma spraying, which was improved from air plasma spraying equipment attached to the atomizer feedstock device. Coatings microstructural analysis and testing were carried out by scanning electron microscope (SEM), and porosity was measured in cross-sectional SEM micrograph. The single scanning deposition status of 8YSZ coatings was investigated, analyzing SEM micrographs of single scanning coatings using different process parameters that included other solvents and additional locations in the plasma jet. The results show that deposition efficiency is higher using alcohol as a solvent, and a better melting state existed in the middle of the plasma jet. The cross-sectional microstructures in different thickness coatings were comparatively researched. More defects were observed in the microstructure of thicker coating, which can be produced by more residual thermal stress. This dramatically improves the thermal cycling performance of the coating.
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