吡嘧司特钾片在中国健康志愿者空腹/餐后的生物等效性研究

目的比较单次空腹与餐后条件下吡嘧司特钾片在中国健康受试者体内的药代动力学,评价受试制剂(T)和参比制剂(R)的生物等效性。方法采用随机、开放、单剂量、两周期、双交叉生物等效性试验设计,空腹组与餐后组各入组26名与30名受试者,每周期在空腹状态或餐后状态下服用受试制剂与参比制剂10 mg,在给药周期前后按设计的时间点采集静脉血。用高效液相质谱联用法(LC-MS/MS)测定血浆中的吡嘧司特钾浓度,用Phoenix TM WinNonlin(8.3)软件计算药代动力学参数,对两制剂进行生物等效性分析。结果空腹单次口服给药受试制剂和参比制剂的t 1/2分别为(4.44±0.91)h和(4.49±0.93)h,t max中位数分别为(1.96±1.29)h和(2.18±1.25)h,C max分别为(867.12±205.56)μg·L^(-1)和(863.35±172.03)μg·L^(-1),AUC 0-t分别为(5513.23±1463.67)h·μg·L^(-1)和(5661.32±1628.65)h·μg·L^(-1),AUC 0-∞分别为(5699.81±1477.68)h·μg·L^(-1)和(5849.44±1644.75)h·μg·L^(-1);受试者的主要药代动力学参数C max、AUC 0-t、AUC 0-∞的90%置信区间的统计结果分别为92.49%~107.53%、94.71%~100.67%和95.28%~100.27%,均在80.00%~125.00%范围内,空腹口服受试制剂与参比制剂安全性良好;餐后单次口服给药受试制剂和参比制剂的t 1/2分别为(4.46±0.78)h和(4.51±0.84)h,t max中位数分别为(3.08±1.36)h和(3.28±1.28)h,C max分别为(683.83±111.87)μg·L^(-1)和(689.77±110.24)μg·L^(-1),AUC 0-t分别为(5695.99±1566.05)h·μg·L^(-1)和(5773.60±1551.04)h·μg·L^(-1),AUC 0-∞分别为(5914.06±1551.86)h·μg·L^(-1)和(5967.30±1552.89)h·μg·L^(-1);C max、AUC 0-t、AUC 0-∞的90%置信区间统计结果分别为93.56%~104.69%、96.43%~100.83%和97.29%~101.14%,均在80.00%~125.00%范围内,餐后口服受试制剂与参比制剂安全性良好。结论在空腹与餐后的单次口服给药条件下,两种吡嘧司特钾片具有较好的生物等效性。

制造业现场工程师职业能力养成模式与路径——基于产教融合行业共同体的探索

在制造行业中,现场工程师的职业能力直接决定了产品质量、生产效率以及企业的竞争力。行业共同体模式作为一种新型的职业能力培养方式,正逐渐在制造业现场工程师的职业能力养成中展现出其独特的优势。该模式强调行业内的多方参与和资源共享,通过理论与实践的结合,为现场工程师提供了一个全面、系统地学习和发展平台。通过分析当前制造业现场工程师职业能力存在的问题,结合当前制造业的发展趋势以及教育强国对职业教育质量提升工作的要求,提出行业共同体职业能力养成模式及其实施路径,为职业教育高质量人才培养提供一种新的实践模式。

Layered Structural PBAT Composite Foams for Efficient Electromagnetic Interference Shielding

The utilization of eco-friendly,lightweight,high-efficiency and high-absorbing electromagnetic interference(EMI)shielding composites is imperative in light of the worldwide promotion of sustainable manufacturing.In this work,magnetic poly(butyleneadipate-coterephthalate)(PBAT)microspheres were firstly synthesized via phase separation method,then PBAT composite foams with layered structure was constructed through the supercritical carbon dioxide foaming and scraping techniques.The merits of integrating ferroferric oxideloaded multi-walled carbon nanotubes(Fe3O4@MWCNTs)nanoparticles,a microcellular framework,and a highly conductive silver layer have been judiciously orchestrated within this distinctive layered configuration.Microwaves are consumed throughout the process of“absorption-reflection-reabsorption”as much as possible,which greatly declines the secondary radiation pollution.The biodegradable PBAT composite foams achieved an EMI shielding effectiveness of up to 68 dB and an absorptivity of 77%,and authenticated favorable stabilization after the tape adhesion experiment.

衡阳植烟土壤理化性状和种植年限对烟叶化学成分的影响

为全面分析衡阳市烟田土壤理化特征和烟叶质量,采集衡阳市5个植烟县(市)的代表性紫色水稻土烟田土壤样品和烟叶样品,研究不同区域土壤理化性质和种植年限对烟叶化学成分的影响,并评价烟叶质量。结果表明:衡阳紫色烟田土壤的有机质含量总体处于适中和丰富水平(96.3%),速效养分含量总体处于适中及以上水平(88.9%~94.4%),pH值有68.5%的点位处于适中水平。衡南县、衡阳县、耒阳市和常宁市烟叶总氮含量较低(<1.5%);衡阳县和常宁市烟叶烟碱含量(<1.5%)和糖碱比(<8%)较低;衡南县烟叶还原糖含量偏低(<18%),其他县域烟叶水溶性总糖偏高(>22%)。相关性分析表明,不同烟区土壤磷、钾含量和微生物生物量是影响烟叶品质的重要因素。>2 mm团聚体百分含量在植烟10 a后显著下降,<2 mm团聚体百分含量显著增加。植烟年限超过10 a的土壤全氮、有机以质、微生物生物量的下降和物理结构的破坏会对烟叶品质产生负面的影响。因此,在土壤养分总量高的烟区可适当减少化肥施用,有机质含量低和土壤团聚体的破坏严重的烟区适当增施有机肥,有助于提升衡阳烟区土壤质量和烟叶品质。

An attention-based teacher-student model for multivariate short-term landslide displacement prediction incorporating weather forecast data

Predicting the displacement of landslide is of utmost practical importance as the landslide can pose serious threats to both human life and property.However,traditional methods have the limitation of random selection in sliding window selection and seldom incorporate weather forecast data for displacement prediction,while a single structural model cannot handle input sequences of different lengths at the same time.In order to solve these limitations,in this study,a new approach is proposed that utilizes weather forecast data and incorporates the maximum information coefficient(MIC),long short-term memory network(LSTM),and attention mechanism to establish a teacher-student coupling model with parallel structure for short-term landslide displacement prediction.Through MIC,a suitable input sequence length is selected for the LSTM model.To investigate the influence of rainfall on landslides during different seasons,a parallel teacher-student coupling model is developed that is able to learn sequential information from various time series of different lengths.The teacher model learns sequence information from rainfall intensity time series while incorporating reliable short-term weather forecast data from platforms such as China Meteorological Administration(CMA)and Reliable Prognosis(https://rp5.ru)to improve the model’s expression capability,and the student model learns sequence information from other time series.An attention module is then designed to integrate different sequence information to derive a context vector,representing seasonal temporal attention mode.Finally,the predicted displacement is obtained through a linear layer.The proposed method demonstrates superior prediction accuracies,surpassing those of the support vector machine(SVM),LSTM,recurrent neural network(RNN),temporal convolutional network(TCN),and LSTM-Attention models.It achieves a mean absolute error(MAE)of 0.072 mm,root mean square error(RMSE)of 0.096 mm,and pearson correlation coefficients(PCCS)of 0.85.Additionally,it exhibits enhanced prediction stability and interpretability,rendering it an indispensable tool for landslide disaster prevention and mitigation.

Enhancer of Shoot Regeneration 2(ESR2)regulates pollen maturation and vitality in watermelon(Citrullus lanatus)

Watermelon(Citrullus lanatus)holds global significance as a fruit with high economic and nutritional value.Exploring the regulatory network of watermelon male reproductive development is crucial for developing male sterile materials and facilitating cross-breeding.Despite its importance,there is a lack of research on the regulation mechanism of male reproductive development in watermelon.In this study,we identified that ClESR2,a VIIIb subclass member in the APETALA2/Ethylene Responsive Factor(AP2/ERF)superfamily,was a key factor in pollen development.RNA insitu hybridization confirmed significantClESR2 expression in the tapetum and pollen during the later stage of anther development.The pollens of transgenic plants showed major defects in morphology and vitality at the late development stage.The RNA-seq and protein interaction assay confirmed that ClESR2 regulates pollen morphology and fertility by interacting with key genes involved in pollen development at both transcriptional and protein levels.These suggest that Enhancer of Shoot Regeneration 2(ESR2)plays an important role in pollen maturation and vitality.This study helps understand the male reproductive development of watermelon,providing a theoretical foundation for developing male sterile materials.

Stable photocurrent-voltage characteristics of perovskite single crystal detectors obtained by pulsed bias

Photocurrent-voltage characterization is a crucial method for assessing key parameters in x-ray or y-ray semiconductor detectors,especially the carrier mobility lifetime product.However,the high biases during photocurrent measurements tend to cause severe ion migration,which can lead to the instability and inaccuracy of the test results.Given the mixed electronic-ionic charac teristics,it is imperative to devise novel methods capable of precisely measuring photocurrentvoltage characteristics under high bias conditions,free from interference caused by ion migration.In this paper,pulsed bias is employed to explore the photocurrent-voltage characteristics of MAPbBr_(3) single crystals.The method yields stable photocurrent-voltage characteristics at a pulsed bias of up to 30 V,proving to be effective in mitigating ion migration.Through fitting the modified Hecht equation,we determined the mobility lifetime products of 1.0×10^(2) cm^(2)·V^(-1)for hole and 2.78×10~(-3)cm^(2)·V^(-1)for electron.This approach offers a promising solution for accurately measuring the transport properties of carriers in perovskite.

Hierarchical Optimization Method for Federated Learning with Feature Alignment and Decision Fusion

In the realm of data privacy protection,federated learning aims to collaboratively train a global model.However,heterogeneous data between clients presents challenges,often resulting in slow convergence and inadequate accuracy of the global model.Utilizing shared feature representations alongside customized classifiers for individual clients emerges as a promising personalized solution.Nonetheless,previous research has frequently neglected the integration of global knowledge into local representation learning and the synergy between global and local classifiers,thereby limiting model performance.To tackle these issues,this study proposes a hierarchical optimization method for federated learning with feature alignment and the fusion of classification decisions(FedFCD).FedFCD regularizes the relationship between global and local feature representations to achieve alignment and incorporates decision information from the global classifier,facilitating the late fusion of decision outputs from both global and local classifiers.Additionally,FedFCD employs a hierarchical optimization strategy to flexibly optimize model parameters.Through experiments on the Fashion-MNIST,CIFAR-10 and CIFAR-100 datasets,we demonstrate the effectiveness and superiority of FedFCD.For instance,on the CIFAR-100 dataset,FedFCD exhibited a significant improvement in average test accuracy by 6.83%compared to four outstanding personalized federated learning approaches.Furthermore,extended experiments confirm the robustness of FedFCD across various hyperparameter values.

Effectivity and safety of trifocal intraocular lenses and capsular tension rings implantation for cataract patients with axial high myopia

●AIM:To assess effectivity and safety of trifocal intraocular lenses(IOLs)and capsular tension rings in treating cataract patients with axial high myopia.●METHODS:A prospective nonrandomized controlled clinical trial was conducted.Totally 98 eyes(74 patients)who underwent femtosecond laser-assisted cataract surgery(FLACS)with trifocal IOLs were enrolled in the study and followed up for 2y after surgery:46 eyes(33 patients)with capsular tension ring implantation in the long axial lengths(AL)group(26<AL<29 mm)and 52 eyes(41 patients)in the normal AL group(22<AL<24.5 mm).Postoperative outcomes about effectivity and safety,including the subjective and objective visual quality,and postoperative complications were assessed.●RESULTS:Uncorrected distance visual acuity at 5 m and uncorrected intermediate visual acuity at 60 and 80 cm in the long AL group were significantly worse than those in the normal AL group at 3mo postoperatively(P<0.05).The differences in reading speed,spectacle independence and potential visual complaints between the two groups were not statistically significant(P>0.05).The dysfunctional lens index and total modulation transfer function(MTF)average height were similar between the two groups.The postoperative internal coma aberrations in the axial high myopia eyes were significantly higher than that in the normal AL group(P<0.05).The total satisfaction score in the long AL group(91.32±2.76)was slightly higher than that in the normal AL group(90.36±3.47),but there was no difference(P=0.136).A statistically negative correlation was found between corrected distance visual acuity(CDVA)and dysfunctional lens index(r=-0.382,P=0.009),and between CDVA and the total MTF average height(r=-0.374,P=0.01).But there was no significant correlation between CDVA and total satisfaction score(r=0.059,P=0.696).Postoperative complications mainly presented as posterior capsular opacity(PCO),retinal detachment and cystoid macular edema.There was no difference in the incidence of fundus disease(6.5%vs 3.8%,P=0.663)or PCO(17.4%vs 7.7%,P=0.217)between the two groups at two years.●CONCLUSION:The utilization of trifocal IOL and capsular tension ring implantation is beneficial for cataract patients with axial high myopia undergoing FLACS.This approach not only ensures excellent subjective feelings and objective visual quality,but also does not increase the incidence of postoperative complications.

Cardioprotective Potential of Cymbopogon citratus Essential Oil against Isoproterenol-induced Cardiomyocyte Hypertrophy:Possible Involvement of NLRP3 Inflammasome and Oxidative Phosphorylation Complex Subunits

Objective:Cymbopogon citratus(DC.)Stapf is a medicinal and edible herb that is widely used for the treatment of gastric,nervous and hypertensive disorders.In this study,we investigated the cardioprotective effects and mechanisms of the essential oil,the main active ingredient of Cymbopogon citratus,on isoproterenol(ISO)-induced cardiomyocyte hypertrophy.Methods:The compositions of Cymbopogon citratus essential oil(CCEO)were determined by gas chromatography-mass spectrometry.Cardiomyocytes were pretreated with 16.9µg/L CCEO for 1 h followed by 10µmol/L ISO for 24 h.Cardiac hypertrophy-related indicators and NLRP3 inflammasome expression were evaluated.Subsequently,transcriptome sequencing(RNA-seq)and target verification were used to further explore the underlying mechanism.Results:Our results showed that the CCEO mainly included citronellal(45.66%),geraniol(23.32%),and citronellol(10.37%).CCEO inhibited ISO-induced increases in cell surface area and protein content,as well as the upregulation of fetal gene expression.Moreover,CCEO inhibited ISO-induced NLRP3 inflammasome expression,as evidenced by decreased lactate dehydrogenase content and downregulated mRNA levels of NLRP3,ASC,CASP1,GSDMD,and IL-1β,as well as reduced protein levels of NLRP3,ASC,pro-caspase-1,caspase-1(p20),GSDMD-FL,GSDMD-N,and pro-IL-1β.The RNA-seq results showed that CCEO inhibited the increase in the mRNA levels of 26 oxidative phosphorylation complex subunits in ISO-treated cardiomyocytes.Our further experiments confirmed that CCEO suppressed ISO-induced upregulation of mt-Nd1,Sdhd,mt-Cytb,Uqcrq,and mt-Atp6 but had no obvious effects on mt-Col expression.Conclusion:CCEO inhibits ISO-induced cardiomyocyte hypertrophy through the suppression of NLRP3 inflammasome expression and the regulation of several oxidative phosphorylation complex subunits.

An overview of the geology and production of the Fuling shale gas field,Sichuan Basin,China

The Fuling shale gas field in China is the largest shale gas field as well as the largest of its type discovered in any Lower Paleozoic formation.In this study,the geology and production of the upper and lower gas layers in the Fuling shale gas field are evaluated in terms of structure,shale quality,fault,initial production,and estimated ultimate recovery(EUR).The shale in the lower gas layer of the Jiaoshiba anticline is a high-quality reservoir,where the space is dominated by organic pores in kerogen,and the gas content is high.The shale gas wells reveal relatively high initial production and EUR.However,the shale in the upper gas layer of the Jiaoshiba anticline has reservoir space mainly composed of clay mineral pores and organic pores within bitumen,and the gas content is low.In terms of structure,primary gas migration may occur in the upper gas layer,resulting in free gas accumulation in the structural high,where the development effects are generally better than those in the structural low.The lower gas layer in the Pingqiao anticline,is the main interval for shale gas accumulation and development due to the high-quality shale.Under the influence of faults,the efficiency of exploration wells emplaced on top of the anticline is much lower a compared with those in the flanks.The residual synclines close to the Sichuan Basin,including the Baima and Baitao anticlines,are characterized by more recent uplifts,larger area,greater distance from the deep and large faults,and early fracture closure.Therefore,we recommend that the shale gas exploration and development should be carried out preferentially in areas close to the center of the residual synclines,featuring relatively high-pressure coefficient and moderate burial depth.

中医特色疗法对妊娠剧吐有效性的网状Meta分析

目的应用网状Meta分析评价中医特色治疗妊娠剧吐的有效性。方法检索从建库到2022年2月28日收录的中医特色治疗妊娠剧吐的随机对照试验,根据Cochrane偏倚风险评估工具对所筛选的文献进行质量评价,应用RevMan 5.3软件生成偏倚风险评估报告,Stata 13.1软件对数据进行统计分析及图形绘制。结果共纳入24篇文献,1660例患者,累计概率排序图(SUCRA)排序依次为:针刺>穴位按摩>艾灸>穴位注射>穴位贴敷>耳穴压豆>常规西医。结论6种中医特色治疗均优于单独常规西医治疗,且针刺疗效最佳。

Public Sentiment Analysis of Social Security Emergencies Based on Feature Fusion Model of BERT and TextLevelGCN

At present, the emotion classification method of Weibo public opinions based on graph neural network cannot solve the polysemy problem well, and the scale of global graph with fixed weight is too large. This paper proposes a feature fusion network model Bert-TextLevelGCN based on BERT pre-training and improved TextGCN. On the one hand, Bert is introduced to obtain the initial vector input of graph neural network containing rich semantic features. On the other hand, the global graph connection window of traditional TextGCN is reduced to the text level, and the message propagation mechanism of global sharing is applied. Finally, the output vector of BERT and TextLevelGCN is fused by interpolation update method, and a more robust mapping of positive and negative sentiment classification of public opinion text of “Tangshan Barbecue Restaurant beating people” is obtained. In the context of the national anti-gang campaign, it is of great significance to accurately and efficiently analyze the emotional characteristics of public opinion in sudden social violence events with bad social impact, which is of great significance to improve the government’s public opinion warning and response ability to public opinion in sudden social security events. .

An Analysis of the Evolution of Online Public Opinion on Public Health Emergencies by Combining CNN-BiLSTM + Attention and LDA

In this paper, the Foxconn epidemic event in Zhengzhou was taken as an example to analyze the evolution of online public opinion on public health emergencies. In order to improve the performance of online public opinion analysis, based on the life cycle theory and LDA theory, the emotional changes of Internet users in four stages of the Foxconn incident centered on the evolution of inscription were divided. The emotions of netizen speech at different stages are analyzed based on CNN-BiLSTM + Attention model, which uses Convolutional Neural Network (CNN) to extract local features. Bi-directional Long Short-Term Memory (BiLSTM) is used to efficiently extract contextual semantic features and long distance dependencies, and then combined with attention mechanism to add emotional features. Finally, Softmax classifier realizes text emotion prediction. The experimental results show that: compared with TextCNN, BiLSTM, BiLSTM + Attenion, CNN-BiLSTM model, the emotion classification model has better effects in the accuracy rate, accuracy rate, recall rate and F value. By analyzing the emotional distribution and evolution trend of public opinion under “text topic”, the paper accurately deconstructs the development characteristics of public opinion in public health emergencies, in order to provide reference for relevant departments to deal with public opinion in public health emergencies. .

Research on Prediction of Sentiment Trend of Food Safety Public Opinion

Emotion has a nearly decisive role in behavior, which will directly affect netizens’ views on food safety public opinion events, thereby affecting the development direction of public opinion on the event, and it is of great significance for food safety network public opinion to predict emotional trends to do a good job in food safety network public opinion guidance. In this paper, the dynamic text representation method XLNet is used to generate word vectors with context-dependent dependencies to distribute the text information of food safety network public opinion. Then, the word vector is input into the CNN-BiLSTM network for local semantic feature and context semantic extraction. The attention mechanism is introduced to give different weights according to the importance of features, and the emotional tendency analysis is carried out. Based on sentiment analysis, sentiment value time series data is obtained, and a time series model is constructed to predict sentiment trends. The sentiment analysis model proposed in this paper can well classify the sentiment of food safety network public opinion, and the time series model has a good effect on the prediction of food safety network public opinion sentiment trend. .

增材制造用新型镍基高温合金的设计与开发

为了满足增材制造专用镍基高温合金成分优化设计需求,采用机器学习(machine learning, ML)和抗裂因子筛选相结合的综合设计策略开发了新型镍基高温合金。热力学计算结果表明,该合金凝固温度范围窄,在临界温度区间内凝固速度快,且收缩总应变及最大应变速率很小,表现出良好的凝固特性。利用选区激光熔化技术制备了新型合金,在成形试样的纵截面和横截面金相中未发现明显裂纹,合金表现出良好的抗裂性能。通过热处理工艺优化,合金在900℃时效后γ′相分数达到44.6%,组织内未见任何TCP相析出,实现了镍基高温合金在增材制造中抗裂性与力学性能的平衡。提出的综合设计策略可为增材制造领域中新材料的快速研发提供新的思路。

施用南荻生物炭对水稻养分利用特征的影响

为实现南荻秸秆炭化利用,缓解洞庭湖区因秸秆处置不当造成的环境压力,评估南荻生物炭农用增效潜力,本研究选用南方第四纪红土母质发育的红黄泥和花岗岩母质发育的麻砂泥水稻土,设置6个不同用量的南荻秸秆生物炭处理(质量比0、1%、2%、4%、6%和8%,0~20 cm土层),采用水稻盆栽试验,探究南荻秸秆生物炭不同施用量对两种类型土壤水稻养分利用特征的影响。结果表明,南荻秸秆生物炭不同施用量和土壤类型对水稻各器官及地上部干物质累积、养分吸收均有影响。与不添加生物炭相比,添加生物炭处理下的麻砂泥和红黄泥水稻地上部干质量分别提高了0.6%~18.6%和15.5%~42.4%;添加4%生物炭的麻砂泥水稻地上部氮、磷和钾养分累积量分别提高了8.6%、10.5%和82.5%,红黄泥水稻分别提高了33.8%、100.0%和125.3%;二次回归方程与肥炭耦合模型拟合表明,麻砂泥和红黄泥水稻氮素利用的生物炭适宜添加量分别为2.51%和4.80%,磷素利用的生物炭适宜添加量分别为4.33%和7.03%,钾素利用的生物炭适宜添加量分别为4.67%和4.81%。因此,施用南荻生物炭有利于促进水稻氮磷钾养分累积和生长,生物炭添加量与土壤条件是影响肥炭耦合效应的重要影响因素。

基于自适应TQWT与小波包奇异谱熵的滚动轴承早期故障诊断

滚动轴承早期故障诊断可有效地保证机械设备的运行安全,针对滚动轴承早期故障特征微弱,故障特征提取不佳的问题,提出可调品质因子小波变换(Tunable Q-factor wavelet transform,TQWT)与小波包奇异谱熵相结合提取特征的滚动轴承早期故障诊断方法。针对滚动轴承早期故障信号的冲击性与周期性特征,提出峭谱积(峭度和包络谱峰值因子的乘积,KEc)的新指标。以KEc为优化指标,采用网格搜索法确定TQWT最佳的品质因子Q,同时以中心频率比为优化指标,确定最佳的分解层数J。通过最佳参数Q和J对原始信号进行TQWT分解并单支重构,选择KEc最大的重构分量作为最佳分量。提取最佳分量的小波包奇异谱熵值作为故障特征向量,最后运用支持向量机(SVM)进行模式识别并进行早期故障诊断。为验证所提方法的有效性,以XJTU-SY滚动轴承加速寿命试验平台研究对象,运用加速度传感器获取的试验数据集进行验证,识别结果准确率为94.5%。同时,与优化指标为峭度等的SVM识别结果进行比较,所提方法识别率提高了约1%~7%。对比结果表明,运用所提方法对滚动轴承早期故障进行识别,可以准确有效地诊断出轴承的故障类型,具有一定的实用价值。

基于VMD-SVM的三相异步电机故障诊断方法

针对三相异步电机信号的不稳定性及故障特征提取困难问题,提出一种基于变分模态分解(VMD)与支持向量机(SVM)相融合的电机故障诊断方法。该方法首先将采集的信号通过VMD分解得到IMF分量;其次,计算各个IMF分量的能量,再将其构成特征向量;最后对每种状态随机选取400组输入SVM模型训练,将剩余每种状态100组用于测试,通过预测标签与实际标签的比较来判断电机的故障状态。采用该方法对4种不同的电机状态进行故障诊断,结果表明与完全自适应噪声集合经验模态分解(CEEMDAN)、变分模态分解(VMD)提取各IMF能量特征相比,基于VMD-SVM的三相异步电机故障诊断方法更具优越性。

CEEMDAN与参数优化多尺度排列熵结合的滚动轴承早期故障诊断

针对滚动轴承的早期故障特征微弱的特点,提出了自适应噪声完备集合经验模态分解(CEEMDAN)与多尺度排列熵(MPE)结合提取故障特征,采用支持向量机(SVM)进行故障状态判别的滚动轴承早期故障诊断方法。利用CEEMDAN将信号分解为若干分量,计算各分量与原信号的相关系数,将大于相关系数阈值的分量重构,对MPE的参数运用PSO算法寻优,计算重构后的信号的MPE值并作为故障特征向量,使用SVM对故障状态进行识别。将该方法运用于XJTU-SY滚动轴承加速寿命试验数据集,并与MPE参数未优化以及未CEEMDAN分解且MPE参数未优化得到的MPE值作为特征向量SVM进行识别的结果进行对比,结果表明本文所提方法的故障识别率分别提高了10.71%和14.28%。