Hospitalization Due to Asthma Exacerbation: A China Asthma Research Network (CARN) Retrospective Study in 29 Provinces Across Mainland China

Jiangtao Lin,Bin Xing,Huaping Tang,Lan Yang,Yadong Yuan,Yuhai Gu,Ping Chen,Xiaoju Liu,Jie Zhang,Huiguo Liu,Changzheng Wang,Wei Zhou,Dejun Sun,Yiqiang Chen,Zhuochang Chen,Mao Huang,Qichang Lin,Chengpin 대한천식알레르기학회 2020 Allergy, Asthma & Immunology Research Vol.12 No.3

Purpose: Details of patients hospitalized for asthma exacerbation in mainland China are lacking. To improve disease control and reduce economic burden, a large sample survey among this patient population is indispensable. This study aimed to investigate the clinical characteristics and outcomes of such patients. Methods: A retrospective study was conducted on patients hospitalized for asthma exacerbation in 29 hospitals of 29 regions in mainland China during the period 2013 to 2014. Demographic features, pre-admission conditions, exacerbation details, and outcomes were summarized. Risk factors for exacerbation severity were analyzed. Results: There were 3,240 asthmatic patients included in this study (57.7% females, 42.3% males). Only 28.0% used daily controller medications; 1,287 (39.7%) patients were not currently on inhaled corticosteroids. Acute upper airway infection was the most common trigger of exacerbation (42.3%). Patients with severe to life-threatening exacerbation tended to have a longer disease course, a smoking history, and had comorbidities such as hypertension, chronic obstructive pulmonary disease (COPD), and food allergy. The multivariate analysis showed that smoking history, comorbidities of hypertension, COPD, and food allergy were independent risk factors for more severe exacerbation. The number of patients hospitalized for asthma exacerbation varied with seasons, peaking in March and September. Eight patients died during the study period (mortality 0.25%). Conclusions: Despite enhanced education on asthma self-management in China during recent years, few patients were using daily controller medications before the onset of their exacerbation, indicating that more educational efforts and considerations are needed. The findings of this study may improve our understanding of hospital admission for asthma exacerbation in mainland China and provide evidence for decision-making.

Acoustic signal analysis for gear fault diagnosis using a uniform circular microphone array

Chi Li,Changzheng Chen,Xiaojiao Gu 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.11

In this paper, a far-field acoustic signal processing method based on a uniform circular microphone array is proposed for the gear fault detection. The method takes ensemble empirical mode decomposition (EEMD) as a preprocessing approach, and the estimation of signal parameters via rotational invariance techniques (ESPRIT) is applied as the beamformer, which offers an adaptive and convenient approach to solve the serious aliasing and distortion in acoustic signals. The method greatly reduces the inherent demands for the microphone numbers and the computational load while holding a satisfying accuracy, making it more promising in practical engineering applications. Besides, aiming at the situation that gear failures cannot be judged solely by gear meshing frequencies (GMF) and sound source locations, seventeen statistical feature parameters are applied to the processed signals for the fault severity recognition, and six of them are found efficient, which provides a further reference for acoustic gear diagnosis.

Adaptive parameter-matching method of SR algorithm for fault diagnosis of wind turbine bearing

Xiaojiao Gu,Changzheng Chen 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.3

The fault diagnosis of wind turbine bearings is challenging because of the heavy background noise and changes in wind speed. Stochastic resonance (SR) is an effective method of detecting fault signal from noise. However, the benefit of SR is seriously limited by the system parameters and the frequency of the input signal. A novel fault diagnosis method for wind turbine bearings, combining an adaptive SR algorithm that is based on quantum particle swarm optimization (QPSO) and frequency conversion based on frequency information exchange (FIE), is proposed. First, the frequency information of the fault characteristic signal is exchanged with the reference frequency by FIE, which can eliminate the limitation of the frequency band. Then, the SR system parameters are optimized by QPSO to avoid blind parameter selection. The signal after FIE is processed by the optimized SR system. The results of case study show that under the same input signal, the proposed method can achieve better signal-to-noise ratio and response amplitude than can the traditional double-side band modulation method and an SR method that is combined only with an optimization algorithm.

Initial fault diagnosis of bearing based on AVMD-SE and multiscale enhanced morphological top-hat filter

Tong Wang,Changzheng Chen,Yuanqing Luo,Siyu Zhao,Shaohui Huang 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.12

Early fault signature detection and background noise removal are essential for bearing fault diagnosis. A novel multiscale enhanced morphological top-hat filter fault diagnosis method, adaptive variational mode decomposition-sample entropy-multiscale enhanced top-hat filter (AVMD-SE-MEMTF), is proposed based on AVMD-SE noise reduction. First, gray wolf optimization algorithm is proposed to optimize the VMD to achieve the optimal decomposition parameters adaptively and combine with SE to eliminate the high noise components and improve the noise reduction effect. Then, based on the pulse extraction property of morphological operations, the concept of MEMTF is proposed. To enhance the multiscale index selection strategy, a synthesis method of eigenfrequency envelope coefficients is constructed to increase the accuracy of the operator during the vibration signal process. Finally, experimental and engineering results show that the proposed method has good diagnostic performance for weak faults in the presence of noise interference.

Integrated Optimization Design of Carbon Fiber Composite Framework for Small Lightweight Space Camera

Shuai Yang,Wei Sha,Changzheng Chen,Xingxiang Zhang,Jianyue Ren 한국광학회 2016 Current Optics and Photonics Vol.20 No.3

A Carbon Fiber Composite (CFC) framework was designed for a small lightweight space camera. According to the distribution characteristics of each optical element in the optical system, CFC (M40J)was chosen to accomplish the design of the framework. TC4 embedded parts were used to solve the lowaccuracy of the CFC framework interface problem. An integrated optimization method and the optimizationstrategy which combined a genetic global optimization algorithm with a downhill simplex local optimizationalgorithm were adopted to optimize the structure parameters of the framework. After optimization, thetotal weight of the CFC framework and the TC4 embedded parts is 15.6 kg, accounting for only 18.4%that of the camera. The first order frequency of the camera reaches 104.8 Hz. Finally, a mechanicalenvironment test was performed, and the result demonstrates that the first order frequency of the camerais 102 Hz, which is consistent with the simulation result. It further verifies the rationality and correctnessof the optimization result. The integrated optimization method mentioned in this paper can be applied tothe structure design of other space cameras, which can greatly improve the structure design efficiency.

Ocean Economy and Fault Diagnosis of Electric Submersible Pump applied in Floating platform

Panlong ZHANG,Tingkai CHEN,Guochao WANG,Changzheng PENG 국제이네비해양경제학회 2017 International Journal of e-Navigation and Maritime Vol.6 No.1

Ocean economy plays a crucial role in the strengthening maritime safety industry and in the welfare of human beings. Electric Submersible Pumps (ESP) have been widely used in floating platforms on the sea to provide oil for machines. However, the ESP fault may lead to ocean environment pollution, on the other hand, a timely fault diagnosis of ESP can improve the ocean economy. In order to meet the strict regulations of the ocean economy and environmental protection, the fault diagnosis of ESP system has become more and more popular in many countries. The vibration mechanical models of typical faults have been able to successfully diagnose the faults of ESP. And different types of sensors are used to monitor the vibration signal for the signal analysis and fault diagnosis in the ESP system. Meanwhile, physical sensors would increase the fault diagnosis challenge. Nowadays, the method of neural network for the fault diagnosis of ESP has been applied widely, which can diagnose the fault of an electric pump accurately based on the large database. To reduce the number of sensors and to avoid the large database, in this paper, algorithms are designed based on feature extraction to diagnose the fault of the ESP system. Simulation results show that the algorithms can achieve the prospective objectives superbly.

Bearing fault diagnosis of wind turbines based on dynamic multi-adversarial adaptive network

Miao Tian,Xiaoming Su,Changzheng Chen,Yuanqing Luo,Xianming Sun 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.4

Owing to the shortage of available labeled data on wind turbine bearings, a new wind turbine bearing fault diagnosis method based on a dynamic multi-adversarial adaptive network (DMAAN) was proposed. In this new method, a laboratory data were used to obtain fault diagnosis models for wind turbine bearings. The first step was evaluating the interdomain distribution difference and intraclass distribution differences between domains. The second step was setting a dynamic adversarial factor to dynamically measure the relative contribution of the two different distributions. The last step was, reducing the distribution difference through multiple adversarial training, to obtain the diagnosis results. The validity of DMAAN was verified via the transfer experiments of laboratory datasets and wind turbine generator measured datasets. The results showed that DMAAN has a higher diagnostic accuracy and better transmission capability in cross-machine transfer fault diagnosis in compare with the existing methods.

Integrated Modeling for the Design of Deformable Mirrors Using a Parametric Module Method

Junqing Zhu,Wei Sha,Changzheng Chen,Xingxiang Zhang,Jianyue Ren 한국광학회 2015 Current Optics and Photonics Vol.19 No.5

Active optics is a key technology for future large-aperture space telescopes. In the design of deformablemirrors for space applications, the design parameter trade-off between the number of regularly configuredactuators and the correction capability is essential but rarely analyzed, due to the lack of design legacy. This paper presents a parametric module method for integrated modeling of deformable mirrors withregularly configured actuators. A full design parameter space is explored to evaluate the correctioncapability and the mass of deformable mirrors, using an autoconstructed finite-element parametric modelingmethod that utilizes manual finite-element meshing for complex structures. These results are used to providedesign guidelines for deformable mirrors. The integrated modeling method presented here can be used forfuture applied optics projects

Pellet injectors for EAST and KSTAR tokamaks

Vinyar, Igor,Hu, Jiansheng,Park, Soo-Hwan,Lukin, Alexander,Yao, Xinjia,Li, Changzheng,Chen, Yue,Reznichenko, Pavel,Kim, Hong-Tack Elsevier 2017 Fusion engineering and design Vol.124 No.-

<P><B>Abstract</B></P> <P>The paper presents high frequency pellet injectors developed for edge localized mode mitigation and plasma fuelling of the EAST and KSTAR tokamaks. Each pellet injector is able to inject solid deuterium or hydrogen pellets at steady state mode. Injectors consist of modules including screw extruder cooled by liquid helium and pneumatic punchers for pellet fabrication and acceleration which are optimized to reach maximal injection frequency for specified pellet parameters.</P> <P>The EAST pellet injector is capable of injecting 1.5mm diameter and 1.2–1.8mm length pellets at frequency up to 50Hz with velocities 200–250m/s using two injection modules working in an alternating mode at 25Hz each. Injection reliability over 90% has been confirmed during several cycles of continuous D2 pellet injection at 50Hz. The KSTAR pellet injector has been designed to inject 2mm size pellets at frequency up to 20Hz and velocity 200m/s. Due to improved design of pellet fabrication and acceleration system the world record in continuous injection of 20,164 deuterium pellets (Ø2.0×1.5mm) for 1039s at 20Hz with reliability 97% has been achieved.</P> <P><B>Highlights</B></P> <P> <UL> <LI> 50Hz and 20Hz pellet injectors have been developed for edge localized mode mitigation and steady state plasma fuelling of the EAST and KSTAR tokamaks. </LI> <LI> Innovative pellet fabrication systems have been designed to achieve world record in continuous pellet injection during 1039s at 20Hz with reliability 97%. </LI> <LI> Both pellet injectors have achieved ITER relevant characteristics of plasma fuelling and ELM control. </LI> </UL> </P>