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学者姓名：王普
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Abstract ：
Fault monitoring can find out-of-control conditions of equipment operation in a timely manner, which is essential for eliminating faults and for stable operation of industrial systems in batch processes. Many conventional data-driven fault detection methods focus less on the non-Gaussian and Multi-stage characteristics of batch process data, which may result in degradation of monitoring performance. In this paper, a Multi-stage Fourth Order Moment Staked Autoencoder (M-FOM-SAE) is designed to solve the above problems. The proposed method firstly automatically determines the number of clusters and divides the batch process into multiple stages. After that, the FOM-SAE model is established in each sub-stage, which can not only effectively learn the nonlinear features of process data, but also extract the non-Gaussian information. The proposed strategy is applied to real-world industrial processes. Experimental results indicate that it can better capture the non-Gaussian and Multi-stage characteristics of process data, and improve the ability to monitor abnormalities.
Keyword ：
Fault monitoring Fault monitoring Stacked Autoencoder Stacked Autoencoder Multi-stage Multi-stage non-Gaussian non-Gaussian Batch process Batch process
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| GB/T 7714 | Chen, Jin , Pu, Wang , Kai, Wang . Batch Process Monitoring Based on Multi-stage Fourth Order Moment Stacked Autoencoder [C] . 2020 : 721-728 . |
| MLA | Chen, Jin 等. "Batch Process Monitoring Based on Multi-stage Fourth Order Moment Stacked Autoencoder" . (2020) : 721-728 . |
| APA | Chen, Jin , Pu, Wang , Kai, Wang . Batch Process Monitoring Based on Multi-stage Fourth Order Moment Stacked Autoencoder . (2020) : 721-728 . |
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Abstract ：
Aiming at nonlinearity and multimodal batch trajectories in semiconductor manufacturing processes, principal component analysis and k nearest neighbor (kNN)-related methods were previously presented. However, these methods require data unfolding and are not capable of extracting crucial features, which affects the performance of fault detection. In this paper, an automated fault detection method using convolutional auto encoder (CAE) and k nearest neighbor rule is proposed. Firstly, data collected in one batch is considered as a two-dimensional gray-scale image, and is input to CAE for feature unsupervised learning, with no need of data preprocessing and data labels. Secondly, kNN rule is incorporated into CAE to construct the monitoring index and perform fault detecting. Finally, the effectiveness of the proposed method is verified with a benchmark semiconductor manufacturing process.
Keyword ：
fault detection fault detection convolutional auto encoder convolutional auto encoder k nearest neighbor k nearest neighbor semiconductor manufacturing process semiconductor manufacturing process
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| GB/T 7714 | Zhang, Haili , Wang, Pu , Gao, Xuejin et al. Automated Fault Detection Using Convolutional Auto Encoder and k Nearest Neighbor Rule for Semiconductor Manufacturing Processes [C] . 2020 : 83-87 . |
| MLA | Zhang, Haili et al. "Automated Fault Detection Using Convolutional Auto Encoder and k Nearest Neighbor Rule for Semiconductor Manufacturing Processes" . (2020) : 83-87 . |
| APA | Zhang, Haili , Wang, Pu , Gao, Xuejin , Gao, Huihui , Qi, Yongsheng . Automated Fault Detection Using Convolutional Auto Encoder and k Nearest Neighbor Rule for Semiconductor Manufacturing Processes . (2020) : 83-87 . |
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Abstract ：
High-precision indoor localization plays a vital role in various places. In recent years, visual inertial odometry (VIO) system has achieved outstanding progress in the field of indoor localization. However, it is easily affected by poor lighting and featureless environments. For this problem, we propose an indoor localization algorithm based on VIO system and three-dimensional (3D) map matching. The 3D map matching is to add height matching on the basis of previous two-dimensional (2D) matching so that the algorithm has more universal applicability. Firstly, the conditional random field model is established. Secondly, an indoor three-dimensional digital map is used as a priori information. Thirdly, the pose and position information output by the VIO system are used as the observation information of the conditional random field (CRF). Finally, the optimal states sequence is obtained and employed as the feedback information to correct the trajectory of VIO system. Experimental results show that our algorithm can effectively improve the positioning accuracy of VIO system in the indoor area of poor lighting and featureless.
Keyword ：
map matching map matching visual inertial odometry visual inertial odometry conditional random field conditional random field three-dimensional three-dimensional indoor localization indoor localization
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| GB/T 7714 | Zhang, Jitong , Ren, Mingrong , Wang, Pu et al. Indoor Localization Based on VIO System and Three-Dimensional Map Matching [J]. | SENSORS , 2020 , 20 (10) . |
| MLA | Zhang, Jitong et al. "Indoor Localization Based on VIO System and Three-Dimensional Map Matching" . | SENSORS 20 . 10 (2020) . |
| APA | Zhang, Jitong , Ren, Mingrong , Wang, Pu , Meng, Juan , Mu, Yuman . Indoor Localization Based on VIO System and Three-Dimensional Map Matching . | SENSORS , 2020 , 20 (10) . |
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Abstract ：
A visual-inertial odometer is used to fuse the image information obtained by a vision sensor with the data measured by an inertial sensor and recover the motion track online in a global frame. However, in an indoor environment, geometric transformation, sparse features, illumination changes, blurring, and noise will occur, which will either cause a reduction in or failure of the positioning accuracy. To solve this problem, a map matching algorithm based on an indoor plane structure map is proposed to improve the positioning accuracy of the system; this algorithm was implemented using a conditional random field model. The output of the attitude information from the visual-inertial odometer was used as the input of the conditional random field model. The feature function between the attitude information and the expected value was established, and the maximum probabilistic value of the attitude was estimated. Finally, the closed-loop feedback correction of the visual-inertial system was carried out with the probabilistic attitude value. A number of experiments were designed to verify the feasibility and reliability of the positioning method proposed in this paper.
Keyword ：
map matching map matching visual-inertial odometer visual-inertial odometer indoor positioning system indoor positioning system conditional random field conditional random field
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| GB/T 7714 | Meng, Juan , Ren, Mingrong , Wang, Pu et al. Improving Positioning Accuracy via Map Matching Algorithm for Visual-Inertial Odometer [J]. | SENSORS , 2020 , 20 (2) . |
| MLA | Meng, Juan et al. "Improving Positioning Accuracy via Map Matching Algorithm for Visual-Inertial Odometer" . | SENSORS 20 . 2 (2020) . |
| APA | Meng, Juan , Ren, Mingrong , Wang, Pu , Zhang, Jitong , Mou, Yuman . Improving Positioning Accuracy via Map Matching Algorithm for Visual-Inertial Odometer . | SENSORS , 2020 , 20 (2) . |
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Abstract ：
Ultrasensitive mid-infrared absorption spectroscopy is demonstrated by the use of a novel silica-based hollow-core negative curvature fiber (HC-NCF). The HC-NCF used in this article consists of a single ring of six nontouching cladding capillaries around the hollow core, thus forming a unique core boundary with a negative curvature. Such a silica HC-NCF enables the broadband single-mode transmission in the mid-infrared. By using the HC-NCF as a compact gas cell, a proof-of-principle experiment is conducted to detect the N2O line at 2778.37 cm(-1) with a distributed-feedback interband cascade laser emitting at 3.6 mu m. A minimum detectable absorbance of 3 x 10(-5) is achieved for a fiber length of 120 cm, corresponding to a noise equivalent absorption (NEA) coefficient of 2.5 x 10(-7) cm(-1). Silica HC-NCFs offer a new opportunity of developing sensitive and compact gas sensors using mid-infrared absorption spectroscopy.
Keyword ：
hollow core fiber hollow core fiber mid-infrared absorption spectroscopy mid-infrared absorption spectroscopy Gas sensor Gas sensor microstructured optical fiber microstructured optical fiber optical fiber sensor optical fiber sensor
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| GB/T 7714 | Yao, Chenyu , Gao, Shoufei , Wang, Yingying et al. Silica Hollow-Core Negative Curvature Fibers Enable Ultrasensitive Mid-Infrared Absorption Spectroscopy [J]. | JOURNAL OF LIGHTWAVE TECHNOLOGY , 2020 , 38 (7) : 2067-2072 . |
| MLA | Yao, Chenyu et al. "Silica Hollow-Core Negative Curvature Fibers Enable Ultrasensitive Mid-Infrared Absorption Spectroscopy" . | JOURNAL OF LIGHTWAVE TECHNOLOGY 38 . 7 (2020) : 2067-2072 . |
| APA | Yao, Chenyu , Gao, Shoufei , Wang, Yingying , Wang, Pu , Jin, Wei , Ren, Wei . Silica Hollow-Core Negative Curvature Fibers Enable Ultrasensitive Mid-Infrared Absorption Spectroscopy . | JOURNAL OF LIGHTWAVE TECHNOLOGY , 2020 , 38 (7) , 2067-2072 . |
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Abstract ：
We demonstrated MIR-pump NIR-probe photothermal spectroscopy with the first harmonic (PTS-1f) detection of formaldehyde, one of the most common volatile organic compounds (VOCs), in a silica hollow-core negative curvature fiber (HC-NCF). The photothermal gas sensor adopts a mid-infrared interband cascade pump laser at 3.6 mu m and a near-infrared fiber probe laser at 1.56 mu m. At the optimal modulation frequency (8 kHz) and modulation index (1.8) of the pump laser, we obtained a normalized noise equivalent absorption (NNEA) coefficient of 4 x 10(-9) cm(-1)WHz(-1/)2. The use of HC-NCF with an inner diameter of 65 mu m enables the sensitive photothermal detection even for a very low pump power of micro-watts. The background-free PTS-1f detection was observed to enhance the sensitivity by a factor of 2.4 compared to the second harmonic (2f) detection. A theoretical model was established in this work to interpret the experimental results.
Keyword ：
gas sensor gas sensor Photothermal spectroscopy Photothermal spectroscopy optical fiber sensor optical fiber sensor hollow core fiber hollow core fiber
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| GB/T 7714 | Yao, Chenyu , Gao, Shoufei , Wang, Yingying et al. MIR-Pump NIR-Probe Fiber-Optic Photothermal Spectroscopy With Background-Free First Harmonic Detection [J]. | IEEE SENSORS JOURNAL , 2020 , 20 (21) : 12709-12715 . |
| MLA | Yao, Chenyu et al. "MIR-Pump NIR-Probe Fiber-Optic Photothermal Spectroscopy With Background-Free First Harmonic Detection" . | IEEE SENSORS JOURNAL 20 . 21 (2020) : 12709-12715 . |
| APA | Yao, Chenyu , Gao, Shoufei , Wang, Yingying , Wang, Pu , Jin, Wei , Ren, Wei . MIR-Pump NIR-Probe Fiber-Optic Photothermal Spectroscopy With Background-Free First Harmonic Detection . | IEEE SENSORS JOURNAL , 2020 , 20 (21) , 12709-12715 . |
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Abstract ：
序批式反应器(SBR)的处理过程的数据具有非高斯分布和高度非线性的特点,传统特征提取方法在进行特征提取时仅仅考虑信息最大化而忽略数据的簇结构信息导致数据特征提取的不完整.由于多向核熵成分分析是一种新的监测方法,在监测过程中的应用表明能够克服传统监测方法的缺陷,减少误报警率.因此本文结合多向核熵成分分析的的优势,提出多向核熵独立成分分析方法用于SBR过程监测及故障诊断.首先,将三维SBR过程数据利用一种新的数据展开技术变为二维数据;其次,利用核熵成分分析将展开后的二维数据映射到高维空间用独立成分分析进行独立成分提取;最后提出一种基于多向核熵独立成分分析的故障诊断方法进行故障诊断.将该方法和传统方法应用于80升的SBR处理过程的监测结果表明,本文提出的方法优于传统的多向独立成分分析方法.
Keyword ：
多向核熵独立成分 多向核熵独立成分 序批式反应器 序批式反应器 故障诊断 故障诊断 故障检测 故障检测
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| GB/T 7714 | 常鹏 , 乔俊飞 , 王普 et al. 非线性和非高斯性共存的序批次反应处理过程故障诊断 [J]. | 控制理论与应用 , 2019 , 36 (5) : 728-736 . |
| MLA | 常鹏 et al. "非线性和非高斯性共存的序批次反应处理过程故障诊断" . | 控制理论与应用 36 . 5 (2019) : 728-736 . |
| APA | 常鹏 , 乔俊飞 , 王普 , 高学金 . 非线性和非高斯性共存的序批次反应处理过程故障诊断 . | 控制理论与应用 , 2019 , 36 (5) , 728-736 . |
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Abstract ：
The common energy efficiency model of chiller in subway station has nonlinear interference, which leads to low prediction accuracy and reliability. To solve the above problems, this paper proposes a model of chiller efficiency prediction based on error correction. This model focuses on the error, trains the historical data of prediction error by SVR, and then corrects the prediction result of traditional model to get the final prediction value of energy efficiency. Through the verification of operation data from air conditioning units on a Beijing subway platform , the results show that this model is superior to the traditional model , the average relative error of predictive value decreased from 4.04*10(-2) to 6.69*10(-)(11).
Keyword ：
error correction error correction thermodynamics thermodynamics support vector machine support vector machine chiller chiller
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| GB/T 7714 | Wang Pu , Zeng Wenhao , Gao Xuejin . Research on The Model of Chiller Efficiency Prediction Based on Error Correction [C] . 2019 : 1660-1665 . |
| MLA | Wang Pu et al. "Research on The Model of Chiller Efficiency Prediction Based on Error Correction" . (2019) : 1660-1665 . |
| APA | Wang Pu , Zeng Wenhao , Gao Xuejin . Research on The Model of Chiller Efficiency Prediction Based on Error Correction . (2019) : 1660-1665 . |
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Abstract ：
Recently, the map matching-assisted positioning method based on micro-electromechanical systems (MEMS) inertial devices has become a research hotspot for indoor pedestrian positioning; however, these are based on existing indoor electronic maps. In this paper, without prior knowledge of the map and through building an indoor main path feature point map combined with the simultaneous localization and map building (SLAM) particle filter (PF-SLAM) algorithm idea, a PF-SLAM indoor pedestrian location algorithm based on a feature point map was proposed through the inertial measurement unit to improve indoor pedestrian positioning accuracy. Aiming at the problem of inaccurate heading angle estimation in the pedestrian dead reckoning (PDR) algorithm, a turn-straight-state threshold detection method was proposed that corrected the difference of the heading angles during the straight-line walking of pedestrians to suppress the error accumulation of the heading angle. Aiming at the particles that are severely divergent at the corners, a feature point matching algorithm was proposed to correct the pedestrian position error. Furthermore, the turning point extracted the main path that failed to match the current feature point map as a new feature point was added to update the map. Through the mutual modification of SLAM and an inertial navigation system (INS) the long-time, high-precision, and low-cost positioning functions of indoor pedestrians were realized.
Keyword ：
indoor localization indoor localization particle filtering particle filtering simultaneous localization and map building (SLAM) algorithm simultaneous localization and map building (SLAM) algorithm inertial navigation system (INS) inertial navigation system (INS) feature point matching feature point matching
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| GB/T 7714 | Shi, Jingjing , Ren, Mingrong , Wang, Pu et al. Research on PF-SLAM Indoor Pedestrian Localization Algorithm Based on Feature Point Map [J]. | MICROMACHINES , 2018 , 9 (6) . |
| MLA | Shi, Jingjing et al. "Research on PF-SLAM Indoor Pedestrian Localization Algorithm Based on Feature Point Map" . | MICROMACHINES 9 . 6 (2018) . |
| APA | Shi, Jingjing , Ren, Mingrong , Wang, Pu , Meng, Juan . Research on PF-SLAM Indoor Pedestrian Localization Algorithm Based on Feature Point Map . | MICROMACHINES , 2018 , 9 (6) . |
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Abstract ：
In order to reduce the energy consumption of train operation, an optimization method based on genetic algorithm of golden section is proposed. Firstly, the Multi-particle train model is established. Secondly, the optimal operation strategy of subway trains is analyzed according to different ramps. Then, a golden section genetic algorithm (GR-GA) is proposed to solve the problem that genetic algorithm is easy to fall into local optimum. A golden section genetic algorithm (GR-GA) is proposed to search for the optimal transfer position of train and the best adaptive point of searching crossover and mutation operator with golden ratio is introduced, which improves the local optimization ability and convergence performance. Taking Yizhuang line as a simulation case, the results show that the proposed algorithm has a better optimization effect.
Keyword ：
Golden ratio Golden ratio Genetic algorithm Genetic algorithm Subway train Subway train Energy-saving optimization Energy-saving optimization Local optimum Local optimum
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| GB/T 7714 | Pu, Wang , Sheng, Ding , Gao, Xuejin et al. Optimization of train energy saving based on golden ratio genetic algorithm [C] . 2018 : 869-874 . |
| MLA | Pu, Wang et al. "Optimization of train energy saving based on golden ratio genetic algorithm" . (2018) : 869-874 . |
| APA | Pu, Wang , Sheng, Ding , Gao, Xuejin , Gao, Huihui . Optimization of train energy saving based on golden ratio genetic algorithm . (2018) : 869-874 . |
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