An Efficient Algorithm for the Tensor Product Model Transformation

Jianfeng Cui,Ke Zhang,Tiehua Ma 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.5

The tensor-product (TP) model transformation was proposed recently as a numerical and automaticallyexecutable method which is capable of transforming linear parameter varying (LPV) state-space models into thehigher order singular value decomposition (HOSVD) based canonical form of polytopic models. The crucial disadvantageof the TP model transformation is that its computational load explodes with the density of discretization andthe dimensionality of the parameter vector of the parameter-varying state-space model. In this paper we propose anew algorithm that leads to considerable reduction of the computation in the TP model transformation. The mainidea behind the modified algorithm is to minimize the number of discretized points to acquire as much informationas possible. The modified TP model transformation can readily be executed on a regular computer efficiently andconcisely, especially in higher dimensional cases when the original TP model transformation fails. The paper alsopresents numerical examples to show the effectiveness of the new algorithm.

Visible light photocatalytic removal performance and mechanism of diclofenac degradation by Ag3PO4 sub-microcrystals through response surface methodology

Jianfeng Gou,Qiuling Ma,Yuqi Cui,Xiaoyong Deng,Huixuan Zhang,Xiuwen Cheng,Xiaoli Li,Mingzheng Xie,Qingfeng Cheng,Huiling Liu 한국공업화학회 2017 Journal of Industrial and Engineering Chemistry Vol.49 No.-

In this study, high visible light response and charge separation efficiency of body-centered cubic Ag3PO4sub-microcrystals were fabricated through ultrasound-precipitation process. Additionally, the parameterswere optimized by photocatalytic (PC) removal degradation of diclofenac based on response surfacemethodology. Results indicated that the PC removal efficiency of diclofenac was significantly affected byAg3PO4 content and pH value. Under the optimized conditions, 99.9% of diclofenac could be degradedwithin 16 min Xenon illumination. Furthermore, three PC removal degradation pathways of diclofenacwere proposed, including OH-adduct to aromatic ring, direct oxidation by photoinduced holes anddecarboxylation of side chain from the parent compound.

Discrimination of American ginseng and Asian ginseng using electronic nose and gas chromatography-mass spectrometry coupled with chemometrics

Cui, Shaoqing,Wu, Jianfeng,Wang, Jun,Wang, Xinlei The Korean Society of Ginseng 2017 Journal of Ginseng Research Vol.41 No.1

Background: American ginseng (Panax quinquefolius L.) and Asian ginseng (Panax ginseng Meyer) products, such as slices, have a similar appearance, but they have significantly different prices, leading to widespread adulteration in the commercial market. Their aroma characteristics are attracting increasing attention and are supposed to be effective and nondestructive markers to determine adulteration. Methods: The aroma characteristics of American and Asian ginseng were investigated using gas chromatography-mass spectrometry(GC-MS) and an electronic nose (E-nose). Their volatile organic compounds were separated, classified, compared, and analyzed with different pattern recognition. Results: The E-nose showed a good performance in grouping with a principle component analysis explaining 94.45% of variance. A total of 69 aroma components were identified by GC-MS, with 35.6% common components and 64.6% special ingredients between the two ginsengs. It was observed that the components and the number of terpenes and alcohols were markedly different, indicating possible reasons for their difference. The results of pattern recognition confirmed that the E-nose processing result is similar to that of GC-MS. The interrelation between aroma constituents and sensors indicated that special sensors were highly related to some terpenes and alcohols. Accordingly, the contents of selected constituents were accurately predicted by corresponding sensors with most $R^2$ reaching 90%. Conclusion: Combined with advanced chemometrics, the E-nose is capable of discriminating between American and Asian ginseng in both qualitative and quantitative angles, presenting an accurate, rapid, and nondestructive reference approach.

Finite element analysis of high-density polyethylene pipe in pipe gallery of nuclear power plants

Shi, Jianfeng,Hu, Anqi,Yu, Fa,Cui, Ying,Yang, Ruobing,Zheng, Jinyang Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.3

High density polyethylene (HDPE) pipe has many advantages over metallic pipe, and has been used in non-safety related application for years in some nuclear power plants (NPPs). Recently, HDPE pipe was introduced into safety related applications. The main difference between safety-related and non-safety-related pipes in NPPs is the design method of extra loadings such as gravity, temperature, and earthquake. In this paper, the mechanical behavior of HDPE pipe under various loads in pipe gallery was studied by finite element analysis (FEA). Stress concentrations were found at the fusion regions on inner surface of mitered elbows of HDPE pipe system. The effects of various factors were analyzed, and the influence of various loads on the damage of HDPE pipe system were evaluated. The results of this paper provide a reference for the design of nuclear safety-related Class 3 HDPE pipe. In addition, as the HDPE pipes analyzed in this paper were suspended in pipe gallery, it can also serve as a supplementary reference for current ASME standard on Class 3 HDPE pipe, which only covers the application for buried pipe application.

Early fault detection method for rolling bearing based on multiscale morphological filtering of information-entropy threshold

Lingli Cui,Jialong Wang,Jianfeng Ma 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.4

The scale of structure element is especially important to obtain good filtering results in multiscale morphological filtering (MMF) method. In general, the optimal scale of structure element is set to be a fixed value in traditional morphological filter, therefore it is difficult to extract the fault feature from rolling bearing vibration signal effectively. A novel multiscale morphological filtering algorithm is proposed based on information-entropy threshold (IET-MMF) for early fault detection of rolling bearing. Compared with traditional MMF method, several optimal scales of structure elements are achieved according to the energy distribution characteristic of different vibration signals. The information entropy theory is applied to quantify the analyzed signals, and the optimal threshold of information entropy is obtained by iterative algorithm to ensure integrity of useful information. The simulation and rolling bearing experimental analysis results show that the IET-MMF method can extract fault features of vibration signals effectively.

Design of Intelligent Information Monitoring System for Distribution Network and Adjustment of Alarm Threshold

Xiang Ma,Jianye Cui,Zhongming Xiang,Haoliang Du,Jianfeng Huang 한국정보과학회 2022 Journal of Computing Science and Engineering Vol.16 No.2

In the current distribution network information monitoring system, there are many false alarm information, which forms redundant interference to the fault alarm threshold, and it is difficult to ensure the alarm accuracy of the monitoring system. The distribution network intelligent information monitoring system and the alarm threshold adjustment method based on machine learning are designed, with the physical layer of the system designed to collect the operation status information of each line and equipment of the distribution network according to various sensors, and transfer it to the data layer. The data layer extracts, processes, and classifies the received information, stores it in the database, obtains the abnormal information in the information base, and adjusts the alarm threshold based on the fuzzy clustering method in machine learning, realizing intelligent monitoring of distribution network. The test results show that the detection performance of abnormal information is good, that the abnormal information in the data can be obtained accurately, and that the clustering of the target category of abnormal information can be completed according to the eigenvalue, and has a good threshold adaptive adjustment ability, to maximize the balance between human, machine, and power grid operation state in the process of distribution network monitoring information, ensure real-time and reliable monitoring and alarm results.

Vibration mechanism and improved phenomenological model of the planetary gearbox with broken ring gear fault

Yingchao Luo,Lingli Cui,Jianyu Zhang,Jianfeng Ma 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.5

Accurate modeling of the vibration signal model of planetary gearboxes is essential for the subsequent fault diagnosis. According to the existing improved phenomenological model based on the meshing vibration, this paper conducts further investigations on the vibration mechanism of the gearbox. The time delay phenomenon of faulty ring gear tooth participating in meshing is theoretically analyzed, and the assisted phases for experimental verification are proposed and deduced. Based on the improved model, the vibration signal under the fault condition is simulated and compared with the results of traditional methods. Subsequently, the paper proposes to divide and reconstruct this signal and use the maximum correlation kurtosis deconvolution (MCKD) to enhance its impact characteristics. The results show that the phase between the fault impact and its adjacent meshing impact is consistent with the proposed assisted phase. Finally, the correctness of the vibration mechanism and the improved phenomenological model are verified experimentally.