Summary:Changes of maximum expiratory flow at 25%and 50%of vital capacity(MEF2s and MEFso,respectively),and predominant parameters indicating small airways function in asthmatics before and after bronchodilator(BD)rev...Summary:Changes of maximum expiratory flow at 25%and 50%of vital capacity(MEF2s and MEFso,respectively),and predominant parameters indicating small airways function in asthmatics before and after bronchodilator(BD)reversibility test have been less interpreted.Our study aimed to investigate the clinical role of changes of MEF2s and MEFso before and after BD reversibility test in diagnosing asthma.Forced expiratory volume in the first second(FEV),MEF2s,and MEFso were measured before and after BD reversibility test in 207 asthmatic patients using standard process.Forty healthy individuals were enrolled as controls.Receiver operating characteristic(ROC)curve was used to assess the diagnostic accuracy of reversibility of MEF2s and MEFgo before and after BD reversibility test(OMEF 2s%and AMEF so%,respectively)in diagnosing asthma.Among these functional criteria,AMEF2;%and 0MEFs%≥25%performed the best diagnostic performance.The sensitivity,specificity,and accuracy of AMEF 25%≥25%as an objcctive diagnostic test for asthma were 63.29%,87.50%,and 67.21%,and of AMEFs0%≥25%were 79.23%,85.00%,and 80.16%,respectively.The area under the ROC curve of the indicators was 0.8203 and 0.9104,respectively.By contrast,an increase in FEV≥12%and 200 mL demonstrated a sensitivity of 62.32%,specificity of 82.50%,and accuracy of 65.59%in diagnosing asthma.The changes of MEF2s and MEFso before and after BD reversibility test may be of additional value in the clinical diagnosis of asthma,with cutoff values of 25%being the most.展开更多
Directing at evaluation for qualifying rate in weaponry test,this article discusses firstly how field test information is flooded with lots of prior information.Then a fast Bayesian evaluation algorithm is presented b...Directing at evaluation for qualifying rate in weaponry test,this article discusses firstly how field test information is flooded with lots of prior information.Then a fast Bayesian evaluation algorithm is presented based on the elaborate analysis of prior information reliability and the second category of maximum likelihood.The example demonstrates that the algorithm presented in this article is better and more robust compared with classical evaluation algorithm for safe-or-failure test and normal Bayesian method,which can make the best of prior information.展开更多
Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the mach...Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the machine’s operating condition through its temperature. In this paper, an investigation of using the second-order statistical features of thermogram in association with minimum redundancy maximum relevance (mRMR) feature selection and simplified fuzzy ARTMAP (SFAM) classification is conducted for rotating machinery fault diagnosis. The thermograms of different machine conditions are firstly preprocessed for improving the image contrast, removing noise, and cropping to obtain the regions of interest (ROIs). Then, an enhanced algorithm based on bi-dimensional empirical mode decomposition is implemented to further increase the quality of ROIs before the second-order statistical features are extracted from their gray-level co-occurrence matrix (GLCM). The highly relevant features to the machine condition are selected from the total feature set by mRMR and are fed into SFAM to accomplish the fault diagnosis. In order to verify this investigation, the thermograms acquired from different conditions of a fault simulator including normal, misalignment, faulty bearing, and mass unbalance are used. This investigation also provides a comparative study of SFAM and other traditional methods such as back-propagation and probabilistic neural networks. The results show that the second-order statistical features used in this framework can provide a plausible accuracy in fault diagnosis of rotating machinery.展开更多
Routine reliability index method, first order second moment (FOSM), may not ensure convergence of iteration when the performance function is strongly nonlinear. A modified method was proposed to calculate reliability ...Routine reliability index method, first order second moment (FOSM), may not ensure convergence of iteration when the performance function is strongly nonlinear. A modified method was proposed to calculate reliability index based on maximum entropy (MaxEnt) principle. To achieve this goal, the complicated iteration of first order second moment (FOSM) method was replaced by the calculation of entropy density function. Local convergence of Newton iteration method utilized to calculate entropy density function was proved, which ensured the convergence of iteration when calculating reliability index. To promote calculation efficiency, Newton down-hill algorithm was incorporated into calculating entropy density function and Monte Carlo simulations (MCS) were performed to assess the efficiency of the presented method. Two numerical examples were presented to verify the validation of the presented method. Moreover, the execution and advantages of the presented method were explained. From Example 1, after seven times iteration, the proposed method is capable of calculating the reliability index when the performance function is strongly nonlinear and at the same time the proposed method can preserve the calculation accuracy; From Example 2, the reliability indices calculated using the proposed method, FOSM and MCS are 3.823 9, 3.813 0 and 3.827 6, respectively, and the according iteration times are 5, 36 and 10 6 , which shows that the presented method can improve calculation accuracy without increasing computational cost for the performance function of which the reliability index can be calculated using first order second moment (FOSM) method.展开更多
分布式新能源以“点多面广”的特征并入各级配电网,电网呈现新能源多层级接入、一体化消纳的特征。为促进新能源的充分消纳与高效利用,提出了一种多层级配电网新能源最大消纳空间测算模型,并将分布式新能源最大消纳空间测算问题转换为...分布式新能源以“点多面广”的特征并入各级配电网,电网呈现新能源多层级接入、一体化消纳的特征。为促进新能源的充分消纳与高效利用,提出了一种多层级配电网新能源最大消纳空间测算模型,并将分布式新能源最大消纳空间测算问题转换为各层级配电网新能源最大消纳空间测算子问题,实现了各层级配电网分布式新能源最大消纳空间的精确测算。首先,以多层级配电网新能源接入量最大为目标函数,基于Distflow潮流模型建立多层级配电网分布式新能源消纳空间测算模型;然后,针对模型非凸以及求解效率低等问题,基于二阶锥松弛将模型转化为混合整数二阶锥规划模型,采用交替方向乘子法(alternating direction method of multipliers,ADMM),将多层级配电网新能源消纳空间测算问题转化为各级配电网新能源最大消纳空间子问题,将消纳空间模型转化为多层级配电网分布式新能源最大消纳空间分解测算模型;最后,以IEEE 6、7、9、10、12、15测试系统为例,验证该方法的有效性。展开更多
针对旋转矢量(rotary vector, RV)减速器多源耦合严重,行星齿轮局部故障所引起的冲击易被其他干扰分量所淹没,故障特征提取困难的问题,结合编码器信号的优势提出了一种基于自适应最大二阶循环平稳盲解卷积(adaptive maximum second orde...针对旋转矢量(rotary vector, RV)减速器多源耦合严重,行星齿轮局部故障所引起的冲击易被其他干扰分量所淹没,故障特征提取困难的问题,结合编码器信号的优势提出了一种基于自适应最大二阶循环平稳盲解卷积(adaptive maximum second order cyclostationarity blind deconvolution, ACYCBD)的RV减速器行星齿轮局部故障检测方法。首先,拾取伺服电机内置光编码器信号,并利用向前差分计算获得瞬时角速度(instantaneous angular speed, IAS)信号;然后,依据特征评价指标(characteristic evaluation indicator, CEI)最大化原则自适应确定ACYCBD优化滤波器长度,并对IAS信号进行增强;最后,通过识别时域中与故障冲击周期相匹配的理论齿数实现RV减速器故障检测。通过试验数据分析,并将所提方法与现有的稀疏低秩分解算法和增强CYCBD算法对比,验证了所提方法的有效性。展开更多
目的:研究流量-容积(flow-volume,F-V)曲线下降支夹角在慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)患者临床表型及病情严重度评估中的临床价值。方法:选取2021年12月—2022年12月在南京医科大学第一附属医院进行肺...目的:研究流量-容积(flow-volume,F-V)曲线下降支夹角在慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)患者临床表型及病情严重度评估中的临床价值。方法:选取2021年12月—2022年12月在南京医科大学第一附属医院进行肺功能检查的患者共101例,其中,存在F-V曲线下降支夹角的稳定期COPD患者(夹角组)33例,与夹角组第1秒用力呼气容积占预计值百分比(forced expiratory volume in the first second as a percentage of predicted value,FEV1%pred)匹配的无下降支夹角的稳定期COPD患者(无夹角组)38例,既往无心肺疾病,且肺功能检测正常的受试者(对照组)30例。收集并比较各组患者基本资料、临床症状评分[COPD自我评估测试(COPD assessment test,CAT)、改良版英国医学研究委员会呼吸困难问卷(modified medical research council dyspnoea scale,mMRC)]、肺功能参数和运动后指脉氧参数。采用多因素Logistic回归分析F-V曲线下降支夹角的相关因素。采用受试者工作特征(receiver operating characteristic,ROC)曲线分析F-V曲线下降支夹角对COPD随访1年内急性加重的预测价值。结果:夹角组肺功能受损程度严重,第1秒用力呼气容积(forced expiratory volume in the first second,FEV1)和用力肺活量(forced vital capacity,FVC)分别为0.91±0.24、2.11±0.63;夹角组CAT评分、mMRC评分、ΔSpO_(2)高于无夹角组及对照组,步行运动后SpO_(2)L低于无夹角组及对照组,差异有统计学意义(P<0.05);夹角组CAT评分≥12分、m MRC评分≥2分、ΔSpO_(2)≥13%是F-V曲线下降支更易出现夹角的主要相关因素;F-V曲线下降支夹角预测重度稳定期COPD急性加重的曲线下面积为0.777,当角度<129.1°时其预测灵敏度、特异度均为最佳,分别为72.73%、67.35%。结论:F-V曲线呈现下降支夹角的COPD患者其肺功能常严重受损,且更易发生活动后低氧血症和急性加重。因此,COPD肺功能报告中应关注F-V曲线下降支是否存在夹角,以便尽早识别COPD高危人群。展开更多
基金This project was supported by the National Natural Science Foundation of China(No.81970024)partly by Scientific Research Project of Wuhan Health Committee(No.WX16C45).
文摘Summary:Changes of maximum expiratory flow at 25%and 50%of vital capacity(MEF2s and MEFso,respectively),and predominant parameters indicating small airways function in asthmatics before and after bronchodilator(BD)reversibility test have been less interpreted.Our study aimed to investigate the clinical role of changes of MEF2s and MEFso before and after BD reversibility test in diagnosing asthma.Forced expiratory volume in the first second(FEV),MEF2s,and MEFso were measured before and after BD reversibility test in 207 asthmatic patients using standard process.Forty healthy individuals were enrolled as controls.Receiver operating characteristic(ROC)curve was used to assess the diagnostic accuracy of reversibility of MEF2s and MEFgo before and after BD reversibility test(OMEF 2s%and AMEF so%,respectively)in diagnosing asthma.Among these functional criteria,AMEF2;%and 0MEFs%≥25%performed the best diagnostic performance.The sensitivity,specificity,and accuracy of AMEF 25%≥25%as an objcctive diagnostic test for asthma were 63.29%,87.50%,and 67.21%,and of AMEFs0%≥25%were 79.23%,85.00%,and 80.16%,respectively.The area under the ROC curve of the indicators was 0.8203 and 0.9104,respectively.By contrast,an increase in FEV≥12%and 200 mL demonstrated a sensitivity of 62.32%,specificity of 82.50%,and accuracy of 65.59%in diagnosing asthma.The changes of MEF2s and MEFso before and after BD reversibility test may be of additional value in the clinical diagnosis of asthma,with cutoff values of 25%being the most.
基金the National Defense Research Foundation of China(No.4010203010401)
文摘Directing at evaluation for qualifying rate in weaponry test,this article discusses firstly how field test information is flooded with lots of prior information.Then a fast Bayesian evaluation algorithm is presented based on the elaborate analysis of prior information reliability and the second category of maximum likelihood.The example demonstrates that the algorithm presented in this article is better and more robust compared with classical evaluation algorithm for safe-or-failure test and normal Bayesian method,which can make the best of prior information.
文摘Thermal image, or thermogram, becomes a new type of signal for machine condition monitoring and fault diagnosis due to the capability to display real-time temperature distribution and possibility to indicate the machine’s operating condition through its temperature. In this paper, an investigation of using the second-order statistical features of thermogram in association with minimum redundancy maximum relevance (mRMR) feature selection and simplified fuzzy ARTMAP (SFAM) classification is conducted for rotating machinery fault diagnosis. The thermograms of different machine conditions are firstly preprocessed for improving the image contrast, removing noise, and cropping to obtain the regions of interest (ROIs). Then, an enhanced algorithm based on bi-dimensional empirical mode decomposition is implemented to further increase the quality of ROIs before the second-order statistical features are extracted from their gray-level co-occurrence matrix (GLCM). The highly relevant features to the machine condition are selected from the total feature set by mRMR and are fed into SFAM to accomplish the fault diagnosis. In order to verify this investigation, the thermograms acquired from different conditions of a fault simulator including normal, misalignment, faulty bearing, and mass unbalance are used. This investigation also provides a comparative study of SFAM and other traditional methods such as back-propagation and probabilistic neural networks. The results show that the second-order statistical features used in this framework can provide a plausible accuracy in fault diagnosis of rotating machinery.
基金Project(50978112) supported by the National Natural Science Foundation of China
文摘Routine reliability index method, first order second moment (FOSM), may not ensure convergence of iteration when the performance function is strongly nonlinear. A modified method was proposed to calculate reliability index based on maximum entropy (MaxEnt) principle. To achieve this goal, the complicated iteration of first order second moment (FOSM) method was replaced by the calculation of entropy density function. Local convergence of Newton iteration method utilized to calculate entropy density function was proved, which ensured the convergence of iteration when calculating reliability index. To promote calculation efficiency, Newton down-hill algorithm was incorporated into calculating entropy density function and Monte Carlo simulations (MCS) were performed to assess the efficiency of the presented method. Two numerical examples were presented to verify the validation of the presented method. Moreover, the execution and advantages of the presented method were explained. From Example 1, after seven times iteration, the proposed method is capable of calculating the reliability index when the performance function is strongly nonlinear and at the same time the proposed method can preserve the calculation accuracy; From Example 2, the reliability indices calculated using the proposed method, FOSM and MCS are 3.823 9, 3.813 0 and 3.827 6, respectively, and the according iteration times are 5, 36 and 10 6 , which shows that the presented method can improve calculation accuracy without increasing computational cost for the performance function of which the reliability index can be calculated using first order second moment (FOSM) method.
基金supported by the Natural Science Foundation of Shandong Province(Grant Nos.ZR2020MA032,ZR2022MA029)the National Natural Science Foundation of China(Grant No.72171133)the high-quality course for postgraduate education in Shandong Province《Intermediate Econometrics(Graded Teaching)》(SDYKC21137).
文摘分布式新能源以“点多面广”的特征并入各级配电网,电网呈现新能源多层级接入、一体化消纳的特征。为促进新能源的充分消纳与高效利用,提出了一种多层级配电网新能源最大消纳空间测算模型,并将分布式新能源最大消纳空间测算问题转换为各层级配电网新能源最大消纳空间测算子问题,实现了各层级配电网分布式新能源最大消纳空间的精确测算。首先,以多层级配电网新能源接入量最大为目标函数,基于Distflow潮流模型建立多层级配电网分布式新能源消纳空间测算模型;然后,针对模型非凸以及求解效率低等问题,基于二阶锥松弛将模型转化为混合整数二阶锥规划模型,采用交替方向乘子法(alternating direction method of multipliers,ADMM),将多层级配电网新能源消纳空间测算问题转化为各级配电网新能源最大消纳空间子问题,将消纳空间模型转化为多层级配电网分布式新能源最大消纳空间分解测算模型;最后,以IEEE 6、7、9、10、12、15测试系统为例,验证该方法的有效性。
文摘目的:研究流量-容积(flow-volume,F-V)曲线下降支夹角在慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)患者临床表型及病情严重度评估中的临床价值。方法:选取2021年12月—2022年12月在南京医科大学第一附属医院进行肺功能检查的患者共101例,其中,存在F-V曲线下降支夹角的稳定期COPD患者(夹角组)33例,与夹角组第1秒用力呼气容积占预计值百分比(forced expiratory volume in the first second as a percentage of predicted value,FEV1%pred)匹配的无下降支夹角的稳定期COPD患者(无夹角组)38例,既往无心肺疾病,且肺功能检测正常的受试者(对照组)30例。收集并比较各组患者基本资料、临床症状评分[COPD自我评估测试(COPD assessment test,CAT)、改良版英国医学研究委员会呼吸困难问卷(modified medical research council dyspnoea scale,mMRC)]、肺功能参数和运动后指脉氧参数。采用多因素Logistic回归分析F-V曲线下降支夹角的相关因素。采用受试者工作特征(receiver operating characteristic,ROC)曲线分析F-V曲线下降支夹角对COPD随访1年内急性加重的预测价值。结果:夹角组肺功能受损程度严重,第1秒用力呼气容积(forced expiratory volume in the first second,FEV1)和用力肺活量(forced vital capacity,FVC)分别为0.91±0.24、2.11±0.63;夹角组CAT评分、mMRC评分、ΔSpO_(2)高于无夹角组及对照组,步行运动后SpO_(2)L低于无夹角组及对照组,差异有统计学意义(P<0.05);夹角组CAT评分≥12分、m MRC评分≥2分、ΔSpO_(2)≥13%是F-V曲线下降支更易出现夹角的主要相关因素;F-V曲线下降支夹角预测重度稳定期COPD急性加重的曲线下面积为0.777,当角度<129.1°时其预测灵敏度、特异度均为最佳,分别为72.73%、67.35%。结论:F-V曲线呈现下降支夹角的COPD患者其肺功能常严重受损,且更易发生活动后低氧血症和急性加重。因此,COPD肺功能报告中应关注F-V曲线下降支是否存在夹角,以便尽早识别COPD高危人群。
