Kaixiang Peng

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research-article
Spatio-temporal feature extraction network based multi-performance indicators synergetic monitoring method for complex industrial processes
- Chi Zhang
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, Beijing 100083, PR China
  ,
- Jie Dong
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, Beijing 100083, PR China
  National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Kaixiang Peng
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, Beijing 100083, PR China
  National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Ruitao Sun
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, Beijing 100083, PR China
Expert Systems with Applications: An International Journal, Volume 257, Issue C•Dec 2024 • https://doi.org/10.1016/j.eswa.2024.125052
Abstract
In the context of smart manufacturing, modern industrial processes are becoming increasingly complex in terms of process flows, product varieties, and performance indicators (PIs). Performance-driven process monitoring attracts extensive ...
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review-article
Performance-driven closed-loop optimization and control for smart manufacturing processes in the cloud-edge-device collaborative architecture: A review and new perspectives
- Chi Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Yilin Wang
  Department of Automation, Tsinghua University, Beijing 100084, PR China
  ,
- Ziyan Zhao
  College of Information Science and Engineering, Northeastern University, Shenyang 110819, PR China
  ,
- Xiaolu Chen
  State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China
  ,
- Hao Ye
  Department of Automation, Tsinghua University, Beijing 100084, PR China
  ,
- Shixin Liu
  College of Information Science and Engineering, Northeastern University, Shenyang 110819, PR China
  ,
- Ying Yang
  State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
Computers in Industry, Volume 162, Issue C•Nov 2024 • https://doi.org/10.1016/j.compind.2024.104131
Abstract
With the transformation and upgrading of the manufacturing industry, manufacturing systems have become increasingly complex in terms of the structural functionality, process flows, control systems, and performance assessment criteria. Digital ...
Highlights

New technologies concerning performance optimization and control for smart manufacturing are reviewed.
A closed-loop performance optimization and control architecture with “cloud-edge-device” collaboration is proposed.
Based on ...
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A cloud–edge collaboration based quality-related hierarchical fault detection framework for large-scale manufacturing processes
- Xueyi Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Liang Ma
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  Key Laboratory of Metallurgical Industry Safety Risk Prevention and Control of Ministry of Emergency Management, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Chuanfang Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Muhammad Asfandyar Shahid
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
Expert Systems with Applications: An International Journal, Volume 256, Issue C•Dec 2024 • https://doi.org/10.1016/j.eswa.2024.124909
Abstract
Against the backdrop of the new-generation intelligent manufacturing and Industrial Internet of Things, manufacturing processes are evolving towards integration, large-scale operations, and complexity, and the requirements for process safety and ...
Highlights

A cloud–edge collaborative quality-related fault detection framework is proposed.
Two quality supervised training mechanisms based on MGU methods are respectively presented.
A federated bi-directional knowledge distillation-based ...
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research-article
Degradation modeling and remaining life prediction for a multi-component system under triple uncertainties
- Xuerui Cao
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
  Key Laboratory of Metallurgical Industry Safety & Risk Prevention and Control, Ministry of Emergency, University of Science and Technology Beijing, Beijing 100083, China
  ,
- Ruihua Jiao
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
Computers and Industrial Engineering, Volume 195, Issue C•Sep 2024 • https://doi.org/10.1016/j.cie.2024.110432
Abstract
As equipment systems are gradually moving toward large-scale and complex that comprise multi-components, the correlation between components significantly impacts the system’s degradation. Meanwhile, the system degradation process is subject to ...
Highlights

Machine learning and statistical-based models are utilized for RUL prediction.
A system-level RUL prediction method with triple uncertainties is proposed.
System-level health index is constructed by DBN, MI and SOM neural network.
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research-article
Multi-node knowledge graph assisted distributed fault detection for large-scale industrial processes based on graph attention network and bidirectional LSTMs
- Qing Li
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, PR China
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Yangfan Wang
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, PR China
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Chi Zhang
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, University of Science and Technology Beijing, Beijing, 100083, PR China
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing, University of Science and Technology Beijing, Beijing, 100083, PR China
Neural Networks, Volume 173, Issue C•May 2024 • https://doi.org/10.1016/j.neunet.2024.106210
Abstract
Modern industrial processes are characterized by extensive, multiple operation units, and strong coupled correlation of subsystems. Fault detection of large-scale processes is still a challenging problem, especially for tandem plant-wide ...
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Finite-time switching-like sliding mode fault-tolerant control for discrete-time cyber-physical systems under DoS attacks and intermittent faults
- Xinyu Guan
  School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
  ,
- Yanyan Hu
  School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
  Key Laboratory of Intelligent Bionic Unmanned Systems, Ministry of Education, University of Science and Technology Beijing, Beijing 100083, China
  ,
- Kaixiang Peng
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Applied Mathematics and Computation, Volume 469, Issue C•May 2024 • https://doi.org/10.1016/j.amc.2024.128530
Abstract
In this article, the finite-time sliding mode fault-tolerant control problem is addressed for discrete-time cyber-physical systems with intermittent faults and denial-of-service (DoS) attacks. To model the intermittent nature of faults, two ...
Highlights

A switching-like observer is constructed to estimate unknown state and fault information.
The designed reaching law can force the sliding surface function enter quasi-sliding mode domain within a finite time.
An upper bound on the ...
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research-article
A missing manufacturing process data imputation framework for nonlinear dynamic soft sensor modeling and its application
- Liang Ma
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
  ,
- Mengwei Wang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
Expert Systems with Applications: An International Journal, Volume 237, Issue PA•Mar 2024 • https://doi.org/10.1016/j.eswa.2023.121428
Abstract
Data-driven soft sensors have been widely used in manufacturing processes for product quality prediction. However, in engineering practice, traditional linear soft sensors are considered to be insufficient when the manufacturing processes present ...
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research-article
A novel method of neural network model predictive control integrated process monitoring and applications to hot rolling process
- Qingquan Xu
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Xuyan Yang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
Expert Systems with Applications: An International Journal, Volume 237, Issue PB•Mar 2024 • https://doi.org/10.1016/j.eswa.2023.121682
Abstract
The stable control of product quality when abnormal working conditions occur in the industrial production process is essential to improve product quality and economic efficiency. However, the process industry suffers from multivariate, nonlinear, ...
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research-article
Unified Solutions to Optimal Fuzzy Observer-Based Fault Detection for Discrete-Time Nonlinear Systems
- Linlin Li
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China
  ,
- Haili Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China
  ,
- Steven X. Ding
  Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Duisburg, Germany
  ,
- Liang Qiao
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China
  ,
- Xin Peng
  Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, China
IEEE Transactions on Fuzzy Systems, Volume 32, Issue 4•April 2024, pp 1991-2004 • https://doi.org/10.1109/TFUZZ.2023.3339516
This article is concerned with the optimal fault detection issues for discrete-time nonlinear systems with the aid of Takagi–Sugeno fuzzy dynamic modeling technique. To this end, in the first part of this article, the nonlinear system is formulated ...
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Adaptive Fixed-Time Tracking Control for Nonlinear Systems Based on Finite-Time Command-Filtered Backstepping
- Ming Chen
  School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan, China
  ,
- Yingsen Li
  School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan, China
  ,
- Huanqing Wang
  College of Mathematical Sciences, Bohai University, Jinzhou, China
  ,
- Kaixiang Peng
  School of Automation, University of Science and Technology Beijing, Beijing, China
  ,
- Libing Wu
  School of Science, University of Science and Technology Liaoning, Anshan, China
IEEE Transactions on Fuzzy Systems, Volume 31, Issue 5•May 2023, pp 1604-1613 • https://doi.org/10.1109/TFUZZ.2022.3206507
This article takes into account the problem of adaptive fixed-time control for nonlinear systems in a strict form via finite-time command-filtered backstepping. Our presented control scheme gives consideration to rapidity by using fixed-time control and ...
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A comprehensive operating performance assessment framework based on distributed Siamese gated recurrent unit for hot strip mill process
- Chuanfang Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Long Miao
  Hot Rolling Plant, Ansteel Group Chaoyang Iron & Steel Company Limited, Liaoning, 122000, PR China
Applied Soft Computing, Volume 132, Issue C•Jan 2023 • https://doi.org/10.1016/j.asoc.2022.109889
Abstract
For modern industrial processes, the operating performance assessment has a significant role in ensuring high quality and efficiency in production under normal condition. However, with the switching of working conditions, aging of the ...
Highlights

A DSGRU is developed for dealing with the nonlinear and dynamic characteristics in the HSMP.
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KPI-related operating performance assessment based on distributed ImRMR-KOCTA for hot strip mill process
- Chuanfang Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Xueyi Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
Expert Systems with Applications: An International Journal, Volume 209, Issue C•Dec 2022 • https://doi.org/10.1016/j.eswa.2022.118273
Abstract
With the development of modern industrial processes toward integration and complexity, industrial process operation monitoring is of great significance to ensure the plant safety, product quality, and operating efficiency. However, the ...
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A novel distributed detection framework for quality-related faults in industrial plant-wide processes
- Liang Ma
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  ,
- Mengwei Wang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Neurocomputing, Volume 492, Issue C•Jul 2022, pp 126-136 • https://doi.org/10.1016/j.neucom.2022.04.014
Abstract
Quality-related fault detection is crucial for improving system reliability, reducing production costs and ensuring product quality, which has been an emerging area of practical interest. An industrial plant-wide process contains ...
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rapid-communication
An extensible quality-related fault isolation framework based on dual broad partial least squares with application to the hot rolling process
- Chuanfang Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
  National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing, 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China
Expert Systems with Applications: An International Journal, Volume 167, Issue C•Apr 2021 • https://doi.org/10.1016/j.eswa.2020.114166
Abstract
The stability of product quality is a crucial issue in the process industries. Quality-related fault isolation usually assists in the real-time monitoring of process industries, thus allowing for better product quality and higher ...
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A novel plant-wide process monitoring framework based on distributed Gap-SVDD with adaptive radius
- Chuanfang Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
Neurocomputing, Volume 350, Issue C•Jul 2019, pp 1-12 • https://doi.org/10.1016/j.neucom.2019.04.026
Abstract
With the increasing complexity of modern process industries, plant-wide process monitoring has become a challenging issue. In this paper, a novel monitoring framework based on distributed gap support vector data description (Gap-SVDD) with ...
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research-article
Implementing multivariate statistics-based process monitoring: A comparison of basic data modeling approaches
- Kai Zhang
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Kaixiang Peng
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Ruohui Chu
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Jie Dong
  Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
Neurocomputing, Volume 290, Issue C•May 2018, pp 172-184 • https://doi.org/10.1016/j.neucom.2018.02.051
Highlights

Commonly used data modeling methods, including PCA, PLS and CCA, are investigated.
Abstract
The development of large interconnected plants has brought the need for the development of active and accurate performance monitoring methods. The commonly used approach to this problem is implementing the multivariate statistics-based ...
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Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering
- Chunhui Zhao,
- Xiaoling Xue
  School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Zengwang Jin
  School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Yanyan Hu
  School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083 China ustb.edu.cn
  ,
- Kaixiang Peng
  School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
Journal of Control Science and Engineering, Volume 2018•2018 • https://doi.org/10.1155/2018/5205698

A fault detection, isolation, and estimation approach is proposed in this paper based on Interactive Multimodel (IMM) fusion filtering and Strong Tracking Filtering (STF) for asynchronous multisensors dynamic systems. Time-varying fault is ...
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Event-triggered fault detection framework based on subspace identification method for the networked control systems
- Kaixiang Peng
  Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Mengyuan Wang
  Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
  ,
- Jie Dong
  Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, PR China
Neurocomputing, Volume 239, Issue C•May 2017, pp 257-267 • https://doi.org/10.1016/j.neucom.2017.02.027

In this paper, the subspace identification method (SIM) based event-triggered fault detection (FD) is put forward to deal with the process monitoring of networked control systems (NCSs). The core concept is to construct a SIM based event-triggered ...
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An Efficient Quality-Related Fault Diagnosis Method for Real-Time Multimode Industrial Process
- Zhijie Zhou,
- Jie Dong
  Key Laboratory for Advanced Control of Iron and Steel Process Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Kaixiang Peng
  Key Laboratory for Advanced Control of Iron and Steel Process Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Bingzheng Wang
  Key Laboratory for Advanced Control of Iron and Steel Process Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
Journal of Control Science and Engineering, Volume 2017•2017 • https://doi.org/10.1155/2017/9560206

Focusing on quality-related complex industrial process performance monitoring, a novel multimode process monitoring method is proposed in this paper. Firstly, principal component space clustering is implemented under the guidance of quality ...
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Remaining Useful Life Estimation Based on Asynchronous Multisource Monitoring Information Fusion
- Adel Haghani,
- Xiaoling Xue
  Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Shuai Qi
  Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Yanyan Hu
  Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
  ,
- Kaixiang Peng
  Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China ustb.edu.cn
Journal of Control Science and Engineering, Volume 2017•2017 • https://doi.org/10.1155/2017/4139563

An asynchronous RUL fusion estimation algorithm is presented for the hidden degradation process with multiple asynchronous monitoring sensors based on multisource information fusion. Firstly, a state-space type model is established by modeling the ...
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Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
Future Direction: The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.

A direct search interface for Author Profiles will be built.

An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.

It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.

Bibliometrics

The ACM DL is a comprehensive repository of publications from the entire field of computing.

It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.

Average citations per article = The total Citation Count divided by the total Publication Count.
Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)

ACM Author-Izer Service

Summary Description

ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.

Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.

ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.

To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.

How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner

Kaixiang Peng

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