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SSRN 2022年

作者： Zuo, Yi Shao, Yanjun Sun, Yiyue Li, Wenxiang Wang, Junwei An, Ying Jiang, Lu-Man Zhou, Zhen Shanghai Engineering Research Center of Energy - Saving in Heat Exchange Systems College of Environmental and Chemical Engineering Shanghai University of Electric Power Shanghai200090 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

Membrane fouling is the major obstacle for membrane bioreactors (MBRs) operated at a long sludge retention time (SRT) to reduce sludge production. In this study, a sludge process reduction (SPR) module, consisting of a microaerobic tank and a settler, was inserted before an anoxic/oxic MBR (AO-MBR) to achieve dual objectives of fouling alleviation and sludge reduction. Three SPR-MBRs were operated to investigate influences of sludge recirculation ratios from the SPR settler to the microaerobic tank (RSPR) on process performance. Compared to AO-MBR, the SPR-MBRs reduced sludge production by 43.1 - 56.4% by maintaining SRTs above 175 d, and decreased foulant layer resistance and pore clogging resistance. Inserting SPR reduced the accumulation of dissolved organic matters and extracellular polymeric substances (EPS), enlarged sludge flocs, and decreased sludge viscoelasticity. However, increasing RSPR stimulated outward diffusion of EPS and increased sludge viscosity. SPR-MBRs achieved effective sludge reduction by enriching hydrolytic (Trichococcus and Aeromonas) and fermentative genera (Lactococcus, Paludibacter, Macellibacteroides, and Acinetobacter) in the SPR, and alleviated membrane fouling by prohibiting the growth of EPS-secreting bacteria and enriching filamentous bacteria to enlarge particle size. The results revealed that the SPR-MBR maximized sludge reduction with a very long SRT, and alleviated membrane fouling synchronously. © 2022, The Authors. All rights reserved.

关键词： Bioreactors

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Sludge Decay Kinetics and Metagenomic Analysis Uncover Discrepant Metabolic Mechanisms in Two Different Sludge in Situ Reduction systems

SSRN

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SSRN 2022年

作者： Shao, Yanjun Zhou, Zhen Zuo, Yi Jiang, Jie Sun, Yiyue He, Junli Qiu, Ji An, Ying Jiang, Lu-Man Shanghai Engineering Research Center of Energy - Saving in Heat Exchange Systems College of Environmental and Chemical Engineering Shanghai University of Electric Power Shanghai200090 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China

A comparative study of one- and two-sludge systems for sludge in situ reduction (SIR), with an anaerobic side-stream reactor (ASSR) process and a sludge process reduction (SPR) activated sludge (SPRAS) process as representative configurations, was undertaken to determine the appropriate SIR configuration and reveal crucial metabolic mechanisms governing sludge reduction. Three pilot-scale anoxic/oxic membrane bioreactors (AO-MBRs) were operated in parallel, with one as a control and two others inserted with an ASSR (ASSR-MBR) and a mainstream SPR module consisting of a microaerobic reactor and a settler (SPR-MBR). All three pilot-scale systems were efficient in removing chemical oxygen demand (>94.8%) and ammonium nitrogen (>99.3%), and the ASSR-MBR had significantly higher total nitrogen removal. ASSR- and SPR-MBR reduced sludge production by 27.9% and 62.3%, respectively, compared to the AO-MBR. The highest rate coefficients of sludge decay, heterotroph lysis and hydrolysis of particulate organic matter, were 0.106, 0.219 and 0.054 d-1 in the SPR module, followed by rate coefficients of 0.060, 0.135 and 0.047 d-1, respectively, in the ASSR. The SPR module achieved an 81.9% higher sludge decay mass with a 32.8% smaller volume compared to the ASSR module. The SPR module preferentially enriched hydrolytic/fermentative and slow-growing bacteria with relative abundances much higher (4.36 - 5.09 times) than the AO-MBR, while only a slight increase (1.45 - 2.26 times) was observed with the ASSR module. Metagenomic sequencing analysis revealed that SPR strengthened the key hydrolytic enzymes and L-lactate dehydrogenase in the glycolysis pathways and weakened the citrate cycle, inducing metabolic uncoupling due to the reduced biosynthesis of ATP. ASSR-MBR inhibited the citrate cycle but enhanced acetate-CoA ligase in glycolysis, indicating that inserting ASSR only altered the ATP biosynthesis pathway, but the maintenance metabolism was dominant for sludge reduction in ASSR

关键词： Wastewater treatment

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Frequent Event Pattern Extraction of Drilling Time Series Using Change Point Detection and Event Sequence Generation

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IFAC-PapersOnLine 2023年第2期56卷 6168-6173页

作者： Yupeng Li Wenkai Hu Weihua Cao R. Bhushan Gopaluni Liang Cao Chao Gan Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Department of Chemical and Biological Engineering University of British Columbia Vancouver BC V6T 1Z3 Canada

In drilling processes, non-stationary phases corresponding to shifts between operating conditions and changes in downhole formations typically lead to false alarms. Extracting these frequent event patterns is critical to build drilling process monitoring and fault diagnosis models. This study aims to extract the frequent event patterns associated with non-stationary phases in drilling time series. In this way, diversified information related to signal changes under normal conditions can be obtained, which is beneficial for suppressing false alarms and improving fault detection performance. The main contributions of this study are twofold: 1) a non-stationary phase detection method is proposed to extract drilling frequent event patterns based on t -distributed stochastic neighbor embedding and relative unconstrained least-squares importance fitting; 2) an event sequence generation method is proposed to express drilling frequent event patterns with a group of symbols. The effectiveness of the proposed method is demonstrated by data from a real drilling project.

关键词： Drilling processes pattern extraction change point detection event sequence generation frequent event pattern

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Safe Exploration and Escape Local Minima with Model Predictive control under Partially Unknown Constraints

arXiv

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arXiv 2022年

作者： Soloperto, Raffaele Mesbah, Ali Allgöwer, Frank Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 Stuttgart70569 Germany Department of Chemical and Biomolecular Engineering University of California BerkeleyCA94720 United States

In this paper, we propose a novel model predictive control (MPC) framework for output tracking that deals with partially unknown constraints. The MPC scheme optimizes over a learning and a backup trajectory. The learning trajectory aims to explore unknown and potentially unsafe areas, if and only if this might lead to a potential performance improvement. On the contrary, the backup trajectory lies in the known space, and is intended to ensure safety and convergence. The cost function for the learning trajectory is divided into a tracking and an offset cost, while the cost function for the backup trajectory is only marginally considered and only penalizes the offset cost. We show that the proposed MPC scheme is not only able to safely explore the unknown constraints, but also escape from local minima that may arise from the presence of obstacles. Moreover, we provide formal guarantees for convergence and recursive feasibility of the MPC scheme, as well as closed-loop constraint satisfaction. Finally, the proposed MPC scheme is demonstrated in simulations using an example of autonomous vehicle driving in a partially unknown environment where unknown obstacles are present. Copyright © 2022, The Authors. All rights reserved.

关键词： Model predictive control

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Enhancing soil quality and maize growth while reducing Cd accumulation with biochar and humic acid in northwestern China

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Journal of Environmental chemical engineering 2025年第2期13卷

作者： Li, Ziyi Ma, Xiangbang Zhang, Shuangting Chen, Geng Lu, Yineng Tan, Rong Proshad, Ram Zhang, Xifeng Cheng, Xiuwen Zhao, Zhuanjun State Key Laboratory of Mountain Hazards and Engineering Safety Institute of Mountain Hazards and Environment Chinese Academy of Sciences Sichuan Chengdu610041 China College of Chemical Engineering Jiuquan Vocationl and Technical College Jiuquan735000 China College of Earth and Environmental Sciences Lanzhou University Lanzhou730000 China Key Laboratory of Western China's Environmental Systems Lanzhou730000 China Key Laboratory for Environmental Pollution Prediction and Control Gansu Province China University of Chinese Academy of Sciences Beijing100049 China

Heavy metal (HM) contamination of soil has posed an international risk to food safety. Biochar (BC) and humic acid (HA) are commonly employed to mitigate HM pollution. Both BC and HA can potentially influence the availability of cadmium (Cd) in soil. However, further investigation is required to understand their impacts and the mechanisms affecting Cd bioavailability and soil quality, particularly in the arid and semi-arid regions of northwestern China. Rice husk biochar (RBC) and HA were used on the actual polluted cropland soil in this investigation to reduce Cd pollution, improve soil quality, and promote maize plant growth. Results revealed that RBC, HA, and their combined application had significant effects on regulating the soil nutrient levels and Cd mobility and uptake by maize plants. The soil CEC and SOM levels rose the most in the T4 treatment (with 0.5 % RBC and 0.5 % HA added), by 13.10 % and 45.31 %, respectively, compared to the control. It was the T1 treatment (with 0.5 % RBC added) that reduced soil DTPA-Cd by 19.01 %, which was the most significant amount. Grain and root Cd levels decreased from 23.84 % to 44.27 % and from 25.03 % to 35.35 %, respectively. Average maize yields increased from 26.31 % to 51.74 %. Furthermore, the results of X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy indicated that the oxygen-containing functional groups (such as -OH and -COOH) present in RBC and RBC-HA could be considered as the primary mechanism of Cd adsorption. This research showed that RBC and HA can improve the quality of heavy metal-contaminated farmland, stop plants from taking in Cd, and raise maize yields. © 2025 Elsevier Ltd

关键词： Fourier transform infrared spectroscopy

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An Efficient Defect Detection System for Printed Circuit Boards with Edge-Cloud Fusion Computing 3

An Efficient Defect Detection System for Printed Circuit Boa...

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3rd International Conference on Industrial Artificial Intelligence, IAI 2021

作者： Wu, Yi Wang, Jing Chen, Yang-Quan Beijing University of Chemical Technology College of Information Science and Technology Beijing China University of Technology School of Electrical and Control Engineering Beijing China University of California Mechatronics Embedded Systems and Automation Lab MercedCA95343 United States

ISBN: (纸本)9781665435178

Many intelligent methods have been proposed and applied in the field of autonomous manufacturing inspection. These advanced algorithms with high requirements on computing power and network may lead to time delay, high cost and energy consumption in practical applications with massive data to be processed. We carry out an efficient defect detection system in an end-edge-cloud architecture with the concept of edge computing to process the big data quickly and effectively. A branchy deep learning model with early exit capability of inference is proposed to detect the category and location of the defect in printed circuit boards. We offload part of the computing tasks to the edge nodes by segmenting and deploying the DL model. Therefore, our system has high detection efficiency and makes real-time defect detection possible. © 2021 IEEE.

关键词： Printed circuit boards

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3D Vision Based Lamination Gap Detection of Carbon Fiber Composite

3D Vision Based Lamination Gap Detection of Carbon Fiber Com...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Yuanye Xu Libiao Yuan Wei Liang Yutuo Yang Shuai Liu Ziming Zeng Yinlong Zhang Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China College of Information Engineering Shenyang University of Chemical Technology Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Automotive and Transportation Engineering Shenzhen Polytechnic Shenzhen China

The paper presents a machine learning approach to detect laminate gaps and to classify them as open or closed. Compared with the traditional detection methods, which suffer from low precision of point cloud segmentation and poor effect of gap extraction in traditional gap detection, this paper proposes a gap detection algorithm based on 3D Vision. First, an improved undirected graph point cloud segmentation algorithm is used to overcome the under-segmentation of the target region. Second, an adaptive vector for angle discriminant model is proposed to solve the problem of poor extraction effect of the gap edge points. Finally, the B-spline curve-fitting model is used to describe the 3D points on the lamination edges. The proposed algorithm has been evaluated in a visual quality detection platform for carbon fiber composite laminates. The results show that the proposed approach is able to accurately detect and classify laminate gaps in carbon fiber composite structures, providing a reliable tool for quality control in industrial manufacturing processes.

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Diagnostic-free onboard battery health assessment

arXiv

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arXiv 2025年

作者： Che, Yunhong Lam, Vivek N. Rhyu, Jinwook Schaeffer, Joachim Kim, Minsu Bazant, Martin Z. Chueh, William C. Braatz, Richard D. Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering Stanford University StanfordCA94305 United States Applied Energy Division SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Control and Cyber-Physical Systems Laboratory Technical University of Darmstadt 64289 Germany Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Energy Science and Engineering Stanford University StanfordCA94305 United States

Diverse usage patterns induce complex and variable aging behaviors in lithium-ion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery’s current state of health from prior complex aging patterns. However, these same diagnostic cycles alter the battery’s degradation trajectory, are time-intensive, and cannot be practically performed in onboard applications. In this work, we leverage portions of operational measurements in combination with an interpretable machine learning model to enable rapid, onboard battery health diagnostics and prognostics without offline diagnostic testing and the requirement of historical data. We integrate mechanistic constraints within an encoder-decoder architecture to extract electrode states in a physically interpretable latent space and enable improved reconstruction of the degradation path. The health diagnosis model framework can be flexibly applied across diverse application interests with slight fine-tuning. We demonstrate the versatility of this model framework by applying it to three battery-cycling datasets consisting of 422 cells under different operating conditions, highlighting the utility of an interpretable diagnostic-free, onboard battery diagnosis and prognosis model. © 2025, CC BY.

关键词： Electronic health record

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Quick-response protection system against electric shock in distributed generation systems

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Diagnostyka 2021年第3期22卷 59-65页

作者： Shkrabets, Fedir Plaksin, Sergej Ostapchuk, Oleksandr Kuznetsov, Valeriy Tymchenko, Irina Muntian, Antonina Department of Power Engineering Ukrainian State University of Chemical Technology Gagarina 8 Dnipro Ukraine Department of Control Systems Institute of Transport Systems and Technologies of NAS of Ukraine Pisarzhevsky str. 5 Dnipro Ukraine Department of Renewable Energy Igor Sikorsky Kyiv Polytechnic Institute Peremohy ave. 37 Kyiv03056 Ukraine Electric Power Department Railway Research Institute 4 Chlopickiego str. 50 Warsaw Poland Department of Control Systems Institute of Transport Systems and Technologies of NAS of Ukraine Pisarzhevsky str. 5 Dnipro Ukraine Foreign Language Department Dnipro National University of Railway Transport Lazariana 2 Dnipro Ukraine

The peculiarities of the operation of distributed generation systems lead to a change in the requirements for the reliability and safety of the power distribution systems in which they are integrated. To meet the increased requirements, continuous monitoring of the insulation parameters (active resistance and capacitance to ground) is often used with operating artificial non-industrial frequency operational signals introduced into the network. In the case of a sudden touch, such a system is not effective, since the response time of the protection device, which consists of the signal processing time and the operating of the actuator, is crucially important. For the used operational signals with a frequency of 100 and 200 Hz, the processing time using the Fourier transform is 10 ms for 100 Hz and 5 ms for 200 Hz. Considering that the response time of the fastest actuators (based on vacuum switches) is from 3 to 7 ms, this is a rather significant period of time. To develop an effective resolver system, the capabilities of the Matlab environment were used to determine the most successful design of an analog prototype (Butterworth, Bessel, Chebyshev and Cauer of 6th order) for an operational signal with a frequency of 200 Hz. As a result, the processing time was established, which varies widely from 3.5 to 19 ms. Taking into account the known indicators, namely the frequency and number of operational signals, a signal processing system was developed using the vector-matrix analysis method. As a result of modeling the processing characteristics of functional signals (at a sampling rate of 1 kHz), the system quick-response was 3 ms, with the possibility of its further decrease as its productiveness increases. © 2021 Polish Society of Technical Diagnostics. All rights reserved.

关键词： Actuators

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Research on intrusion detection of industrial control system based on improved QPSO-SVM

Research on intrusion detection of industrial control system...

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2022 International Conference on Electronic Information Technology, EIT 2022

作者： Yu, Yajie Liu, Xianda Wei, Weixuan Chen, Hengfei Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China

ISBN: (纸本)9781510655096

Intrusion detection technology can effectively evaluate the security state of the system. However, the accuracy of traditional intrusion detection methods still needs to be improved. Therefore, this paper proposed a SVM model based on improved QPSO. QPSO is used to optimize the hyperparameters of SVM to improve its accuracy. In addition, the shrinkage expansion coefficient in QPSO is improved to make QPSO adaptive. Experiment shows that the proposed algorithm has good performance. © 2022 SPIE. All rights reserved.

关键词： Intrusion detection

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