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Prediction of dissolved oxygen in a fishery pond based on gated recurrent unit (GRU)

Information Processing in Agriculture 2021年第1期8卷 185-193页

作者： Wuyan Li Hao Wu Nanyang Zhu Yongnian Jiang Jinglu Tan Ya Guo Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of Internet of Things EngineeringJiangnan UniversityWuxi 214122China Jiangsu Internet Agricultural Development Center Nanjing 210017China Jiangsu Zhongnong IoT Technology Co. LTDYixing 214200China University of Missouri ColumbiaMO 65211USA

Dissolved oxygen(DO),an important water quality indicator in aquaculture,affects the survival rate of aquatic creatures and the yield of aquatic ***,it is important to predict DO in fishery ponds for applying artificial aeration with low energy and ***,deep learning models,such as recurrent neural network(RNN),long short-term memory(LSTM),and gated recurrent unit(GRU),are often used to predict the trend of time series,but it is unclear which one of them is more suitable for prediction of DO in fishery *** this work,the RNN model,LSTM model,and GRU model were used to build three DO predicting *** performance of the three models were compared by mean absolute error(MAE),mean square error(MSE),mean absolute percentage error(MAPE),and the coefficient of determination(R2).The performance of RNN is worse result than LSTM and *** four evaluation indicators of GRU are 0.450 mg/L,0.411,0.054,and 0.994,and the four indicators of LSTM are 0.407 mg/L,0.294,0.059,and 0.970,which shows that the performance of GRU is similar to LSTM,but the time cost and number of parameters used for GRU is much lower than *** is concluded that the GRU has overall better performance and can be applied to practical applications.

关键词： Dissolved oxygen RNN model LSTM model GRU model

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Condition-Based Maintenance for Performance Degradation Under Nonperiodic Unreliable Inspections

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 709-721页

作者： Li, Yang Shi, Yan Zhang, Zhiyao Lu, Ningyun Wang, Xiuli Zio, Enrico Nanjing University of Aeronautics and Astronautics College of Automation Engineering Key Laboratory of Internet of Things and Control Technologies Nanjing211106 China Politechnico di Milano Energy Department Milan20156 Italy Northwestern Polytechnical University School of Aeronautics Xi'an710072 China Chongqing University State Key Laboratory of Mechanical Transmission Chongqing400044 China Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China Politecnico di Milano Energy Department Milan20156 Italy Aramis Srl Milano20121 Italy Kyung Hee University Department of Nuclear Engineering College of Engineering Seoul02447 Korea Republic of

With the development of monitoring technology, increasing attention has been paid to condition-based maintenance (CBM). Also, if condition information for maintenance can be obtained with fewer inspections, the cost of the entire maintenance process could be reduced. However, in application, the monitoring equipment cannot maintain always a reliable operating state, for example, due to various uncertain factors, such as sensor errors, component tolerances, and environment disturbances, the inspections from the sensors are often unreliable. Motivated by these simple observations, we propose a nonperiodic CBM policy under unreliable inspections. The time interval of the nonperiodic inspections is obtained via an inspection scheduling function. The unknown parameters of the component degradation process are updated by GD, while simultaneously the maintenance decision variables are adjusted. A catastrophe strategy-based particle swarm optimization is used to set the optimal decision variables by minimizing the long-run cost rate. Application to laser degradation data illustrates the effectiveness of the proposed method. © 2020 IEEE.

关键词： Condition based maintenance

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An Adaptive Fault Compensation Scheme for Formation control of Spacecraft Formation Flying

An Adaptive Fault Compensation Scheme for Formation Control ...

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第33届中国控制与决策会议

作者： Zongxing Zhang Yajie Ma Bin Jiang Yuxi Liu College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Key Laboratory of Internet of Things and Control Technologies

The relative position model is established to meet the requirement of the leader-follower spacecraft *** this model,we consider the follower spacecraft actuator fault which the fault model is combined with loss of effectiveness and constant deviation *** adaptive controller is designed to solve the uncertainty caused by the actuator *** on the Lyapunov theory,it is proved that the relative position error and velocity error can converged to zero under the *** result proves the effectiveness of this method.

关键词： Adaptive fault-tolerant control Formation control Spacecraft formation flying

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Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions

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Journal of Systems Engineering and Electronics 2020年第4期31卷 841-851页

作者： CHEN Chuang LU Ningyun JIANG Bin XING Yin College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China Jiangsu Key Laboratory of Internet of Things and Control Technologies Nanjing University of Aeronautics and AstronauticsNanjing 211106China School of Earth Sciences and Engineering Hohai UniversityNanjing 211100China

Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance *** maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.

关键词： condition-based maintenance(CBM) imperfect maintenance maintenance cost availability constraint optimization

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Joint-Comb-Acquisition for High-Accelerating Doppler-Shift in Space Communications

Joint-Comb-Acquisition for High-Accelerating Doppler-Shift i...

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IEEE International Conference on Communications (ICC)

作者： Zhaowei Zhang Lin Liu Hui Liu Jun Yin Ruirui Chen Su Pan Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and Telecommunications Nanjing China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China School of Software Engineering Jinling Institute of Technology Nanjing China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

In space communications, the signal suffers a long-distance transmission and a high dynamic movement. The long-distance transmission causes a very low signal-to-noise ratio (SNR) and the high dynamic movement causes a high-accelerating Doppler-shift. To address the low SNR, the conventional strategy is long-time accumulation. However, during the long-time accumulation period, the high-accelerating Doppler-shift brings about the serious energy dispersion problem. In this paper, we propose one joint-comb-acquisition (JCA) scheme to address the energy dispersion problem. The proposed JCA scheme, which uses multiple accumulation periods to jointly construct a narrower comb-search-range, excludes most noise elements. Also, the theoretical analysis derives the closed-form expression for acquisition probability. Moreover, the simulation results demonstrate the significant increase of acquisition probability varies from 4.6 to 47.2 percents, as compared with the existing schemes.

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Test Selection Design with Unreliable Tests Based on Bayesian Network and SA-GA

Test Selection Design with Unreliable Tests Based on Bayesia...

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第35届中国控制与决策会议

作者： Yang Li Dandan Huang Ningyun Lu Li Jia Bin Jiang Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation (Shanghai University) Academic Affairs Office (Nanjing University of Aeronautics and Astronautics) the Key Laboratory of Internet of Things and Control Technologies College of Automation Engineering (Nanjing University of Aeronautics and Astronautics)

Testability is a crucial issue in the field of fault detection and diagnosis(FDD).Testing every parameter of a system is an unacceptable option in practice,because it often generates an overwhelming amount of data with sparse value density and costs a lot of time and resource *** test selection design is essential for effectively performing FDD *** paper focuses on the unreliable test problem in testability to minimize the test cost subjected to lower constraints on fault detection,and fault ***-maximization and Bayesian network are applied to solve the missed detection *** avoid the local optimum phenomenon,a combination of simulated annealing algorithm and genetic algorithm method is adopted to search the optimal test *** proposed optimal test selection design scheme under unreliable tests is implemented on the Automatic Gauge control(AGC) simulation platform in Baosteel Co.,Ltd.,Shanghai,*** results show that the obtained optimal test sequence can greatly reduce the test cost,and ensure good fault detection and isolation performance.

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An Improved RAIM Algorithm for Multiple Satellite Faults Detection and Exclusion

An Improved RAIM Algorithm for Multiple Satellite Faults Det...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Wang, Mengchen Li, Zhimin Lai, Jizhou Lv, Pin Huang, Kai Navigation Research Center College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Key Laboratory of Internet of Things and Control Technology in Jiangsu Province Nanjing University of Aeronautics and Astronautics Nanjing211106 China Shanxi Baocheng Aviation Instrument Co. Ltd. AVIC Baoji721006 China

ISBN: (纸本)9789811581540

Satellite fault detection and exclusion (FDE) is an important guarantee for Global Navigation Satellite System (GNSS) to provide standard services. With the great investment of GNSS construction in many countries, multi-constellation positioning needs higher multi-fault detection performance of Receiver Autonomous Integrity Monitoring (RAIM) algorithm. In this paper, an improved RAIM algorithm with decoupling parity vectors (DPV) is proposed for multi-satellite FDE. By means of decoupling of traditional parity vector, multiple fault observations are isolated at one time. To eliminate the interference of large faults and multiple faults, positioning with fault-free satellite set by iterative detection is adopted. The simulations show that the fault test rate of the algorithm in this paper is more than 99%. The 99% corresponds to faults which is less than 8 fault observations with more than 11 × σ bias (1σ = 10.5 m). The experiment results proved that DPV is effective in multiple faults scenario. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fault detection

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Multi-vehicle Collaborative Navigation Method Based on Datalink Relative Distance in GNSS Denied Environment

Multi-vehicle Collaborative Navigation Method Based on Datal...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Zhou, Zihan Lyu, Pin Lai, Jizhou Zhu, Xudong Huang, Kai Navigation Research Center College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211100 China Key Laboratory of Internet of Things and Control Technology in Jiangsu Province Nanjing University of Aeronautics and Astronautics Nanjing211100 China Shanxi Baocheng Aviation Instrument Co. Ltd. AVIC Baoji721006 China

ISBN: (纸本)9789811581540

Multi-vehicle collaborative position improves the position accuracy of the entire fleet through the information interaction between vehicles. Traditional methods are mostly based on satellite navigation systems, and navigation accuracy is difficult to guarantee in GNSS denied environment. This paper presents a ranging datalink based collaborative navigation method for multi-vehicles. On each vehicle, this paper establishes the odometry, inertial navigation system (INS) and datalink system to obtain the absolute navigation information and relative navigation information of the vehicle. The relative distance between each vehicle is attainted by the datalink system. A four vehicles scene is considered. This paper establishes the speed and angle measurement model of sensors and the ranging model of datalink, and derives the state equation and measurement equation of the cooperative system as a whole. The simulation verification shows that the assistance of the datalink system can improve the absolute position and relative position accuracy of each vehicle. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Inertial navigation systems

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Explainable Fault Diagnosis Using Invertible Neural Networks-Part I: A Left Manifold-based Solution

TechRxiv

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TechRxiv 2023年

作者： Chen, Hongtian Huang, Biao Sun, Wenxin Zhang, Weidong Jiang, Bin Ding, Steven X. The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The School of the Internet of Things Engineering Jiangnan University Wuxi214122 China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Jiangsu Key Laboratory of Internet of Things and Control Technologies China University of Duisburg-Essen Duisburg47057 Germany The Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 1H9 Canada

The series includes two parts, articulating the two novel avenues of research on intelligent fault diagnosis (FD) for nonlinear feedback control systems. In Part I of the series, we design a novel FD paradigm by elaborating an invertible neural network (INN) for feedback control systems. With the aid of a left manifold, the core idea behind the INN-based FD scheme is (i) formulation of residual generator used for FD as a projection of system data onto the null space that has the same dimension as system outputs, (ii) in a topological space, elaboration of a homeomorphism that delivers an invertible relationship between system outputs and residual signals when the system input is given, (iii) skillful introduction of both the master and slave objective functions to achieve system/parameter identification with information loseless property. Comparing with the existing FD approaches, the three superior strengths of the proposed FD scheme deserving mentation are: 1) it specializes in nonlinear feedback control systems, 2) it can effectively avoid the overfitting problem when approximating or learning nonlinear system dynamics, and 3) control theory guides the whole design, ensuring the interpretability of the learning process. Finally, two studies on nonlinear systems demonstrate the feasibility of the invertible left manifold (ILM)-based FD strategy. Part I would contribute to the future development of machine learning (ML)based system identification and explainable FD approaches, and also benefits the right manifold-based FD designs in the Part II. © 2023, CC BY.

关键词： Failure analysis

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Test Selection Design with Unreliable Tests Based on Bayesian Network and SA-GA

Test Selection Design with Unreliable Tests Based on Bayesia...

引用

Chinese control and Decision Conference, CCDC

作者： Yang Li Dandan Huang Ningyun Lu Li Jia Bin Jiang Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation (Shanghai University) Shanghai China Academic Affairs Office (Nanjing University of Aeronautics and Astronautics) Nanjing China The Key Laboratory of Internet of Things and Control Technologies College of Automation Engineering (Nanjing University of Aeronautics and Astronautics) Nanjing China

Testability is a crucial issue in the field of fault detection and diagnosis (FDD). Testing every parameter of a system is an unacceptable option in practice, because it often generates an overwhelming amount of data with sparse value density and costs a lot of time and resource consumption. Optimal test selection design is essential for effectively performing FDD strategies. This paper focuses on the unreliable test problem in testability to minimize the test cost subjected to lower constraints on fault detection, and fault isolation. Expectation-maximization and Bayesian network are applied to solve the missed detection issue. To avoid the local optimum phenomenon, a combination of simulated annealing algorithm and genetic algorithm method is adopted to search the optimal test sequence. The proposed optimal test selection design scheme under unreliable tests is implemented on the Automatic Gauge control (AGC) simulation platform in Baosteel Co., Ltd., Shanghai, China. The results show that the obtained optimal test sequence can greatly reduce the test cost, and ensure good fault detection and isolation performance.

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