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Multivariate Statistical Kernel PCA for Nonlinear Process Fault Diagnosis in Military Barracks
Kaiwen Luo,Shenglin Li,Ren Deng,Wei Zhong,Hui Cai 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.1
Because of the nonlinear characteristics of monitoring system in military barracks, the traditional KPCA method either have low sensitivity or unable to detect the fault quickly and accurately. In order to make use of higher-order statistics to get more useful information and meet the requirements of real-time fault diagnosis and sensitivity, a new method of fault detection and diagnosis is proposed based on multivariate statistical kernel principal component analysis (MSKPCA), which combines statistic pattern analysis framework (SPA) and kernel principal component analysis (KPCA). First, the transformation of multivariate statistics and kernel function are conducted in which technology of moving time window is used. Then, PCA is executed to analysis the kernel function obtained from the first step. Moreover, the statistics of T^2 and SPE and the control limits of them are calculated. Finally, simulations on a typical nonlinear numerical example show that the proposed MSKPCA method is more effective than PCA and KPCA in terms of fault detection and diagnosis.
Effects of air staging on Exhaust Tube Vortex structure in a swirl-stabilized pulverized coal flame
Kaiwen Deng,Xinzhou Li,Minsung Choi,Gyungmin Choi 한국연소학회 2019 KOSCOSYMPOSIUM논문집 Vol.2019 No.11
This paper presents the experimental investigations of the effect of the exhaust tube vortex (ETV) on NOx emission and CO emission. Both exhaust gas and measured by in-furnace gas concentration to understand the shape of ETV in a swirl-stabilized pulverized coal-fired furnace. In order to better understand the shape of ETV, this experiment picked two completely different conditions which generates swirling coal flame derived from co-swirl and counter-swirl through five staging air injection positions. ETV structure can be roughly e stimated from the concentration of various gases in the furnace and the burnout ratio of the central axis sample.
Fabrication of graphene‑assisted voltammetry platform for the detection of nitrate ions in PM2.5
Huadong Li,Yang Zhang,Kaiwen Feng,Chuan Wei 한국탄소학회 2023 Carbon Letters Vol.33 No.7
This study presents the fabrication and application of a graphene-assisted voltammetry platform for the sensitive detection of nitrate ions in PM2.5 (atmospheric aerosols with a maximum diameter of 2.5 μm). The MoS2/ reduced graphene oxide/ glassy carbon electrode ( MoS2/rGO/GCE) was prepared using a simple and efficient electrochemical deposition method. The rationale behind selecting MoS2/ rGO stems from their individual properties that, when combined, can enhance the electrode’s performance. MoS2 offers excellent electro-catalytic activity and selectivity for nitrate ion detection, while rGO provides high conductivity and a large surface area for enhanced sensitivity. The electrochemical performance of MoS2/ rGO/GCE was investigated and compared with MoS2/ GCE and bare GCE using cyclic voltammetry and electrochemical impedance spectroscopy. The results demonstrated that MoS2/ rGO/GCE exhibited enhanced electro-catalytic activity, high conductivity, and improved selectivity for nitrate ion detection. The optimal pH value for detecting nitrate ions was determined to be 8.0. Differential pulse voltammetry (DPV) was employed to investigate the linear range and detection limit of nitrate ions on MoS2/ rGO/GCE, resulting in a linear range from 1 to 300 μM and a detection limit of 0.35 μM. The reproducibility and the stability of MoS2/ rGO/GCE were assessed, showing satisfactory performance. Real sample analysis from Chengdu City showed a strong correlation between the results obtained using MoS2/ rGO/GCE and ion chromatography, highlighting its potential application in monitoring nitrate ions in PM2.5. The findings of this study contribute to the development of a graphene-assisted voltammetry platform for sensitive nitrate ion detection in PM2.5, offering potential benefits for real-time air pollution monitoring and environmental health assessments.
Wang Wu,Li Kaiwen,Guo Yuchuan,Jia Conglong,Li Zeguang,Wang Kan 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.12
The ability to calculate the material density sensitivity coefficients of power with respect to the material density has broad application prospects for accelerating Monte Carlo-Thermal Hydraulics iterations. The second-order material density sensitivity coefficients for the general Monte Carlo score have been derived based on the differential operator sampling method in this paper, and the calculation of the sensitivity coefficients of cell power scores with respect to the material density has been realized in continuous-energy Monte Carlo code RMC. Based on the power-density sensitivity coefficients, the sensitivity coefficients of power scores to some other physical quantities, such as power-boron concentration coefficients and power-temperature coefficients considering only the thermal expansion, were subsequently calculated. The effectiveness of the proposed method is demonstrated in the power-density coefficients problems of the pressurized water reactor (PWR) moderator and the heat pipe reactor (HPR) reflectors. The calculations were carried out using RMC and the ENDF/B-VII.1 neutron nuclear data. It is shown that the calculated sensitivity coefficients can be used to predict the power scores accurately over a wide range of boron concentration of the PWR moderator and a wide range of temperature of HPR reflectors.
Research on MR-Tree Spatial Query Authenticated Index Introduced Neighbor Relationship
Xiaofu Wei,Shenglin Li,Zuofei Tan,Kaiwen Luo,San Zhang 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.10
In database outsourcing, the data owner delegates the tasks of data management to a third-party service provider. As the service provider may be untrusted or susceptible to attacks, query authentication is an essential part. Merkle R-tree (MR-tree) is one of the most efficient authenticated index that combines Merkle hash tree with R*-tree. MR-tree can provide an efficient range query authentication, however, as it uses the traditional R*-tree query structure in neighbor queries, a large number of unnecessary nodes may be accessed, and that can affect the efficiency of the query. In this paper, the neighbor relationship is introduced into the construction of MR-tree, and we propose a new index structure, called VMR-tree that incorporates the Voronoi diagram into MR-tree. In order to utilize VMR-tree index structure, we propose algorithms for spatial nearest neighbor queries and experiments to verify it has a better efficiency in spatial neighbor query authentication.
Lv Bingchang,Shi Liwei,Liu Kaiwen,Li Lintao,Ding Hongshan 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.5
To reduce the use of rare earth materials and improve the performance of the motor, a new hybrid pole structure is proposed. The equivalent air-gap magnetic density model is established, and the N-th harmonic analytical expression of the air-gap magnetic density under the hybrid pole is derived; The optimal parameters of the hybrid pole structure are obtained by using sensitivity analysis to stratify the optimized parameters, using a mixture of Box-Behnken Design (BBD) method and Multi-Objective Genetic Algorithm-II (MOGA-II) for the first level parameters, and Central Composite Design (CCD) method for the second level parameters. The electromagnetic performance of the motor under different slots was analyzed based on the finite element method, and the results showed that the cogging torque and the no-load back electromotive force total harmonic distortion of the 48-slot compared to the 12-slot motor under the hybrid pole structure decreased by 45.2 and 47.3%, respectively. At the same time, the hybrid pole structure uses 19% less-rare-earth compared to the conventional structure.
Weimin Sun,Yiran Dong,Pin Gao,Meiyan Fu,Kaiwen Ta,Jiwei Li 한국미생물학회 2015 The journal of microbiology Vol.53 No.6
Although oilfields harbor a wide diversity of microorganisms with various metabolic potentials, our current knowledge about oil-degrading bacteria is limited because the vast majority of oil-degrading bacteria remain uncultured. In the present study, microbial communities in nine oil-contaminated soils collected from Daqing and Changqing, two of the largest oil fields in China, were characterized through highthroughput sequencing of 16S rRNA genes. Bacteria related to the phyla Proteobacteria and Actinobacteria were dominant in four and three samples, respectively. At the genus level, Alkanindiges, Arthrobacter, Pseudomonas, Mycobacterium, and Rhodococcus were frequently detected in nine soil samples. Many of the dominant genera were phylogenetically related to the known oil-degrading species. The correlation between physiochemical parameters within the microbial communities was also investigated. Canonical correspondence analysis revealed that soil moisture, nitrate, TOC, and pH had an important impact in shaping the microbial communities of the hydrocarbon-contaminated soil. This study provided an in-depth analysis of microbial communities in oilcontaminated soil and useful information for future bioremediation of oil contamination.