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Optimization of sensor deployment sequences for hazardous gas leakage monitoring and source term estimation

Chinese Journal of Chemical Engineering 2023年第4期56卷 169-179页

作者： Jikai Dong Bing Wang Xinjie Wang Chenxi Cao Shikuan Chen Wenli Du key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Nowadays, chemical safety has attracted considerable attention, and chemical gas leakage monitoring and source term estimation(STE) have become hot spots. However, few studies have focused on sensor layouts in scenarios with multiple potential leakage sources and wind conditions, and studies on the risk information(RI) detection and prioritization order of sensors have not been performed. In this work, the monitoring area of a chemical factory is divided into multiple rectangles with a uniform mesh. The RI value of each grid node is calculated on the basis of the occurrence probability and normalized concentrations of each leakage scenario. A high RI value indicates that a sensor at a grid node has a high chance of detecting gas concentrations in different leakage scenarios. This situation is beneficial for leakage monitoring and STE. The methods of similarity redundancy detection and the maximization of sensor RI detection are applied to determine the sequence of sensor locations. This study reveals that the RI detection of the optimal sensor layout with eight sensors exceeds that of the typical layout with 12 sensors. In addition, STE with the optimized placement sequence of the sensor layout is numerically simulated. The statistical results of each scenario with various numbers of sensors reveal that STE is affected by sensor number and scenarios(leakage locations and winds). In most scenarios, appropriate STE results can be retained under the optimal sensor layout even with four sensors. Eight or more sensors are advised to improve the performance of STE in all scenarios. Moreover, the reliability of the STE results in each scenario can be known in advance with a specific number of sensors. Such information thus provides a reference for emergency rescue.

关键词： Gas leakage Source term estimation Sensor layout Risk information Numerical simulation Optimization

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A stochastic reconstruction strategy based on a stratified library of structural descriptors and its application in the molecular reconstruction of naphtha

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Chinese Journal of Chemical Engineering 2022年第11期51卷 153-167页

作者： Guangyao Zhao Minglei Yang Wenli Du Feifei Shen Feng Qian key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Molecular reconstruction is a rapid and reliable way to provide molecular detail of petroleum fractions,which is required in the kinetic modeling of petroleum conversation processes at the molecular level.In the typical stochastic reconstruction method,the estimation of properties of pseudo molecules that are generated by Monte Carlo sampling depends on the building of predefined molecular libraries,which is expensive and inaccessible for certain petroleum fractions.In this paper,a novel stochastic reconstruction strategy is proposed,which is based on a stratified library of structural descriptors.Properties of pseudo molecules generated in the novel strategy can be directly estimated by group contribution method in the condition of lacking predefined molecular libraries.In this strategy,the molecular building diagram comprises two steps.First,the ring structure is configured by determining the number of rings.Different from the length of chain adopted in the traditional stochastic reconstruction method,in the second step,number of structural descriptors(SDs)for binding site and chain were determined sequentially for the configuration of binding site and saturated acyclic hydrocarbon chain.These structural descriptors for binding site and chain were selected from group contribution methods.To count the number of partial overlapping sections between structural descriptors for chain,two supplementary structural descriptors were created.All possible saturated structures of hydrocarbon chains can be represented by structural descriptors at the scale of property estimation.This strategy separates the building of a predefined molecule library from the stochastic reconstruction process.The exact structures of pseudo molecules represented by structural descriptors in this work can be determined with sufficient chemical knowledge.Fifty naphtha samples are tested independently to demonstrate the performance of the proposed strategy and the results show that the estimated properties were close enough to the experimental val

关键词： Novel stochastic reconstruction strategy Stratified library of structural descriptors Group contribution method

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A Local Quadratic Embedding Learning Algorithm and Applications for Soft Sensing

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Engineering 2022年第11期18卷 186-196页

作者： Yaoyao Bao Yuanming Zhu Feng Qian key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Inspired by the tremendous achievements of meta-learning in various fields,this paper proposes the local quadratic embedding learning(LQEL)algorithm for regression problems based on metric learning and neural networks(NNs).First,Mahalanobis metric learning is improved by optimizing the global consistency of the metrics between instances in the input and output space.Then,we further prove that the improved metric learning problem is equivalent to a convex programming problem by relaxing the constraints.Based on the hypothesis of local quadratic interpolation,the algorithm introduces two lightweight NNs;one is used to learn the coefficient matrix in the local quadratic model,and the other is implemented for weight assignment for the prediction results obtained from different local neighbors.Finally,the two sub-mod els are embedded in a unified regression framework,and the parameters are learned by means of a stochastic gradient descent(SGD)algorithm.The proposed algorithm can make full use of the information implied in target labels to find more reliable reference instances.Moreover,it prevents the model degradation caused by sensor drift and unmeasurable variables by modeling variable differences with the LQEL algorithm.Simulation results on multiple benchmark datasets and two practical industrial applications show that the proposed method outperforms several popular regression methods.

关键词： Local quadratic embedding Metric learning Regression machine Soft sensor

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流程工业智能制造的未来

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Engineering 2023年第3期22卷 20-22页

作者：钱峰 key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

manufacturing processes in the process industry comprise a process branch that uses petroleum,natural gas,coal,ore,biomass,and other resources as key raw materials;provides bulk raw materials for national economic construction;and provides high-end electronic chemicals,polymers,and alloy steels for strategic emerging industries,such as the integrated circuit industry and aerospace industry,and for key technologies,such as 5G technology and high-end equipment.These manufacturing processes involve physical and chemical reactions,gas–liquid–solid multiphase coexistence,and continuous complex material-conversion processes.process industries include the petrochemical,chemical,steel,nonferrous metal,building-material,biomedicine,and other industries,whose industry chain is shown in Fig.1.

关键词：智能制造 nonferrous petrochemical

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Event-triggered sliding mode control of linear repetitive processes and its application in metal rolling process

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Science China(Information Sciences) 2024年第3期67卷 167-181页

作者： Xinyu LV Yugang NIU James LAM key laboratory of smart manufacturing in energy Chemical process (East China University of Science and Technology) Ministry of Education Department of Mechanical Engineering The University of Hong Kong

This paper investigates the design problem of a sliding mode controller for linear repetitive processes(LRPs) with a finite pass length on each pass. Under limited communication resources, an eventtriggered mechanism is implemented from the sensors to the controller, whose triggered sequence is consistent with the evolution direction of LRPs. To periodically orchestrate communication between the controller and actuator, a round-robin scheduling mechanism is established based on the pass length. A sliding function involving the state and pass profile is constructed, and the sliding mode controller is designed using triggered states and pass profile signals. Feasible controller gains are attained to ensure the stability of the resultant closed-loop system. Finally, the proposed strategy is implemented for a multi-roll metal rolling process.

关键词： event-triggered mechanism linear repetitive processes metal rolling process round-robin scheduling sliding mode control

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smart process manufacturing toward Carbon Neutrality:Digital Transformation in process manufacturing for Achieving the Goals of Carbon Peak and Carbon Neutrality

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Engineering 2023年第8期27卷 1-2页

作者： Feng Qian key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

At present,the energy-supply and process-manufacturing industries suffer from the outstanding problems of heavy industrial structure,high energy consumption,and high carbonization of the energy supply,with the global demand and consumption of energy continuing to grow.Pollution emissions from high-carbon energy systems are significantly accelerating the global climate crisis.Therefore,there is urgent need for an energy revolution and industrial transformation in these industries.The digitalization of process manufacturing by relying on big data and artificial intelligence can effectively help process-manufacturing companies improve their efficiency and energy conservation.To achieve the goals of a carbon peak and carbon neutrality,innovative digital technology and its application in the fields of pharmaceuticals,chemicals.

关键词： companies Transformation innovative

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A Linear Algorithm for Quantized Event-Triggered Optimization Over Directed Networks

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1095-1098页

作者： Yang Yuan Liyu Shi Wangli He key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China IEEE

Dear Editor,This letter investigates a class of distributed optimization problems with constrained communication.A quantized discrete-time eventtriggered zero-gradient-sum algorithm(QDE-ZGS)is developed to optimize the sum of local functions over weight-balanced directed networks.Based on an encoder-decoder scheme and a zooming-in technique,an event-triggered quantization communication is designed.Theoretical analysis shows that the exact convergence to the global optimal solution is guaranteed when the triggering threshold is bounded and the scaled sequence introduced by the zooming-in technique is quadratic summable.When the scaled sequence is bounded by an exponential decay function,QDE-ZGS converges linearly to the unique global optimal solution.Numerical simulations are conducted to demonstrate the theoretical results.

关键词： solution optimal letter

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Editorial for Special Issue“Artificial Intelligence Energizes process manufacturing”

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Engineering 2021年第9期7卷 1193-1194页

作者： Feng Qian key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

process manufacturing is a pillar of modern economy;it is the dominant mode of production in many industries,including oil and gas,chemicals,nonferrous metals,iron,steel,and more.In order to address the problems of resource constraints,energy efficiency,and environmental protection in process manufacturing,it is necessary to develop systems and methods to make process manufacturing more efficient,greener,and smarter.From another perspective,artificial intelligence has been successfully applied in various fields,such as autonomous vehicles,image analysis,robotic manipulators,real-time assistants,and smart recommendation,and has demonstrated its powerful strengths in knowledge representation,cognitive comprehension,and autonomous learning.Therefore,a deep and tight integration between artificial intelligence and process manufacturing is a promising direction toward“smart process manufacturing.”smart process manufacturing has become a hot research topic in recent years,and various governments have released strategic plans for smart process manufacturing with the aim of upgrading and transforming the process industry.

关键词： steel autonomous artificial

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Data-Driven Fault Compensation Tracking Control for Coupled Wastewater Treatment process

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 294-297页

作者： Peihao Du Weimin Zhong Xin Peng Linlin Li Zhi Li the key laboratory of smart manufacturing in energy Chemical process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China IEEE the key laboratory of Knowledge Automation for Industrial processes of ministry of education the School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China

Dear Editor, This letter is concerned with the data-driven fault compensation tracking control for a coupled wastewater treatment process(WWTP)subject to sensor faults. Invariant set theory is introduced to eliminate the completely bounded and differentiable conditions of coupled non-affine dynamics and to explicitly express the control inputs.An adaptive fault compensation mechanism is constructed to accommodate the effects of sensor faults. By employing a cubic absolutevalue Lyapunov criteria。

关键词： differentiable eliminate absolute

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Tracking performance limitations of MIMO discrete-time networked control systems with multiple constraints

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Science China(Information Sciences) 2023年第8期66卷 267-268页

作者： Xiaowei JIANG Bin ZHANG Xiangyong CHEN Huaicheng YAN School of Automation China University of Geosciences key laboratory of Industrial Internet of Things & Networked Control Ministry of Education Hubei key laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation and Electrical Engineering Linyi University key laboratory of smart manufacturing in energy Chemical process of the ministry of education

Dear editor,Networked control systems(NCSs) have attracted widespread attention in some fields because they offer the advantages of reduced cabling, greater resource sharing,and ease of installation and maintenance [1]. However, in an unreliable network environment, network constraints can significantly limit the performance of NCSs.

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