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6th International Conference on Industrial Engineering, ICIE 2020

作者： Gots, A.N. 87 Gorky Street Vladimir600000 Russia

ISBN: (纸本)9783030548131

The paper presents the free oscillation analysis of the reduced torsional system in the crankshaft of a six-cylinder piston internal combustion engine with a liquid or rubber (internal friction) damper mounted on the toe. Installing a torsional vibration damper on the sock of the crankshaft changes the frequency of free oscillations, and in addition, when installing a rubber damper, another mass of the torsional system is added with the coefficient of rigidity of the rubber layer and the moment of inertia of the damper flywheel. At the same time, for liquid torsional vibration damper, the flywheel which has no direct connection with the toe of the crankshaft, for the calculation of free oscillations to the moment of inertia of the sock it is necessary to add a half the moment of inertia of the flywheel. The order of selection of optimal damping coefficients, namely the moments of inertia of the damper flywheel and damping coefficients of silicone fluid, is considered. For the rubber (internal friction) damper, the necessary parameters include the moment of inertia of the flywheel, the stiffness coefficient of the rubber layer and the damping coefficient. The free oscillations are considered in a complex form, which allows obtaining a function after the transition to real values that can be taken as a function of optimizing the parameters of the liquid or rubber damper. In this case, at the optimum damping or maximum energy dissipated in the damper, the amplitude of torsional oscillations of the crankshaft toe is reduced as much as possible. Using this approach allows for a significant reduction in the number of calculations with different damping coefficients and chooses the most optimal results. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Damping coefficient Flywheel moment of inertia optimization optimization function Torsional oscillations Torsional vibration damper

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Operating Strategies and Disturbance Characterization for DC Microgrids

Operating Strategies and Disturbance Characterization for DC...

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作者： Leonard-Albert, Miles University of South Carolina

学位级别：M.S., Master of Science/Master of Surgery

The present state of the electrical grid is unable to meet the demands of transmission. Digital twin technology provides a promising solution to this problem by allowing for analysis and control of distributed energy resources. This thesis presents initial work towards development of a digital twin for a DC power system. Two versions of the DC power system are created and evaluated against randomly generated load profiles. System performance is evaluated on the basis of the quantity of the load that is unserviced by the generation and energy storage. Energy storage operating strategies that modify the model to prioritize different aspects of the system are introduced, along with a discussion of the effects of the modifications. A preliminary optimization function is discussed that will be used to control the system. From this optimization function, key information that is needed for the digital twin can be determined. This work also introduces two additional works that will require adjustments as the digital twin is developed. The first measures the ability of the system to withstand disturbances. The second presents a decision matrix to examine the trade-off between the number of pulses that the system is capable of producing and the magnitude of those pulses.

关键词： DC microgrids Digital twin technology optimization function

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Depth-aware total variation regularization for underwater image dehazing

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2021年 98卷 116408-116408页

作者： Ding, Xueyan Liang, Zheng Wang, Yafei Fu, Xianping Dalian Maritime Univ Informat Sci & Technol Sch Dalian 116026 Peoples R China Pengcheng Lab Shenzhen 518055 Guangdong Peoples R China

Underwater images often show severe quality degradation due to the light absorption and scattering effects in water medium. This paper introduces a scene depth regularized underwater image dehazing method to obtain high-quality underwater images. Unlike previous underwater image dehazing methods that usually calculate a transmission map or a scene depth map using priors, we construct an exponential relationship between transmission map and normalized scene depth map. An initial scene depth is first estimated by the difference between color channels. Then it is refined by total variation regularization to keep structures while smoothing excessive details. An alternating direction algorithm is given to solve the optimization problem. Extensive experiments demonstrate that the proposed method can effectively improve the visual quality of degraded underwater images, and yields high-quality results comparative to the state-of-the-art underwater image enhancement methods quantitatively and qualitatively.

关键词： Underwater image dehazing optimization function Normalized scene depth

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Adaptive drilling application uses AI to enhance on-bottom drilling performance

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JPT, Journal of Petroleum Technology 2020年第8期72卷 45-47页

作者： Jeffery, Christopher Creegan, Andrew NOV

Ever since the first commercial well was spudded, operators have looked for ways to drill wells faster without sacrificing safety or incurring huge costs. While saving time and money through efficient drilling is not a new concept, the more recent adoption of drilling optimization and automation services has certainly become one of the biggest drivers to achieving those *** the current downturn has shown limited signs of recovery, it has continued to evolve in ways never imagined, and the effects are taking their toll in every facet of the oil and gas industry. While rigs and drilling equipment can be set aside to ride out the storm, what about the drilling teams who are working on the rigs and in remote operation centers? As these teams are being removed from the field, the expectation is that many of them won’t return for a myriad of reasons. So, what happens when that experience is lost?The exodus of seasoned crews, otherwise known as the “great crew change,” has been discussed for several years, but recent conditions could expedite the process. Considering the recent shutdown of rigs and the loss of personnel, the question remains whether we will see a noticeable gap in knowledge and experience once crews return to the drilling rigs in full *** lack of individual skills can be offset over time with hands-on experience, but a drilling crew needs to operate at the highest level possible, preferably with few to no gaps in experience. To assist the drilling process, NOV’s M/D Totco division recently launched its KAIZEN intelligent drilling optimization application, which performs as an adaptive autodriller. The system features continuous learning capabilities, enabling it to provide proactive drilling dysfunction mitigation while maximizing rate of penetration (ROP) and optimizing mechanical specific energy. It also reduces human dependence in the drilling process, lowering the risk of slow or incorrect responses to drilling dysfunction. In turn, the syst

关键词： drilling equipment digital wellsite portfolio control mode artificial intelligence drilling process optimization function machine learning drilling operation adaptive drilling application control system Artificial intelligence Drilling Equipment Drilling Operations Drilling optimization Information Management and Systems

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Spam message detection using Danger theory and Krill herd optimization

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COMPUTER NETWORKS 2021年 199卷 108453-108453页

作者： Sharaff, Aakanksha Kamal, Chandramani Porwal, Siddhartha Bhatia, Surbhi Kaur, Kuljeet Hassan, Mohammad Mehendi Natl Inst Technol Dept Comp Sci & Engn Raipur Madhya Pradesh India Manav Rachna Int Inst Res & Studies Faridabad India Univ Quebec Ecole Technol Super Montreal PQ Canada King Saud Univ Coll Comp & Informat Sci Dept Informat Syst Riyadh Saudi Arabia King Saud Univ Res Chair Smart Technol Riyadh Saudi Arabia

Due to proliferation of online posts and rise in the active social media users, fraudulent activities related with spam messages have taken a spike drift. Spam is an activity by which hackers use electronic messaging system to unsolicited messages in mass content to unknown users. It can be also taken as one of the major attraction of attackers in the form of short message service (SMS) messages. Spam messages can be categorized in different categories such as business opportunity spam, trending topic spam, banking services spam etc. These problems can be tackled by confirming to the actions taken by users towards these messages. There is an urgent explicit need of practical medium in order to assist the users against these spam messages. This paper proposes a novel SMS spam filtering model based on Danger theory of Artificial Immune System (AIS). Several feature extraction and selection techniques have been applied for optimizing the algorithm and claiming an admissible accuracy. This paper uses a biologically inspired algorithm named Krill herd optimization (KHO) for the task of feature selection and various optimization functions like Quing function, Sumsquare function, Levy function etc. are applied for enhancing its performance. The Dendritic Cell Algorithm (DCA) is also incorporated with KHA as an added advantage towards achieving efficiency. Comparative results between Dendritic Cell Algorithm (DCA) with KHA and other spam filtering models have been shown in comparison with several state-of-the-art machine learning classifiers. The algorithms have been experimented by using varied optimization functions illustrated using visualization tools and results have been validated in the paper. The obtained results demonstrate an admissible accuracy of 96% that is calculated using different information retrieval metrics using recall, F -measure and precision.

关键词： Danger theory Dendritic cells Krill herd optimization (KHO) Antigen Mature context antigen value (MCAV) Co-stimulated molecules (CSM) Semi mature dendritic cells (smDC) Mature dendritic cells (mDC) Pathogen associated molecular patterns (PAMP) Neighboring motion Foraging motion Physical diffusion Crossover Mutation optimization function

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The Problem of Steel Cutting in the Steel Manufacturing Industry

International Core Journal of Engineering

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International Core Journal of Engineering 2021年第8期7卷 172-177页

作者： Yongyuan Wang Hangyu Meng Linqing Fei Xiaoran Liu Feiteng Li

With the continuous improvement of social productivity, steel production is increasing day by day. The consumption of raw materials is increasing, and the impact on the environment is also getting worse. The sharp rise in steel prices has led to a sharp increase in production costs and a decline in profits for all steel companies in the world. Some companies even suffered losses. Therefore, improving the utilization rate of steel plate raw materials is an urgent problem that steel companies need to solve. In the steel plate cutting problem, a perfect cutting plan can greatly increase the utilization rate of the steel plate. This method can reduce the waste of raw materials, which not only saves costs, but also helps protect the environment. According to the steel plate cutting problem encountered at this stage, this paper establishes a dynamic programming discrete set mathematical model. While considering the cost of lossy steel plate and cutting cost, we establish an optimized layout function. This function can provide a high-quality layout plan and reduce product costs.

关键词： Dynamic Programming Discrete Set Permutation and Combination optimization function

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Model Predictive Control of Unmanned Mine Vehicle Trajectory Tracking

Model Predictive Control of Unmanned Mine Vehicle Trajectory...

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第40届中国控制会议

作者： Peng Xin Zhiwen Wang Hongtao Sun Bin Zhang School of Electrical Engineering and Information Engineering Lanzhou University of Technology Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology College of Engineering Qufu Normal University

Unmanned mine vehicle driving technology is a significant part of smart mining research. This paper proposes a model predictive control strategy for the planning path trajectory tracking problem of unmanned mine vehicles during mining and transportation. Firstly, we construct an optimized function with soft constraints. Secondly, the terminal equation constraint is introduced to design model predictive control optimization problem, thereby transforming the trajectory tracking problem of the unmanned mine vehicle into the solution of the optimization problem. Then the unmanned mine vehicle trajectory tracking model predictive controller is designed, and the stability of the closed loop system through the Lyapunov stability theory is proved. Finally, a simulation example is used to verify that the terminal equation constraint model predictive controller proposed in this paper has a good tracking effect in the process of unmanned mine vehicle trajectory tracking. The control strategy proposed in this paper has improved the effect of unmanned mine vehicle planning path tracking, and its the following speed and stability are enhanced.

关键词： Unmanned Mine Vehicle Driving Technology optimization function Model Predictive Control Trajectory Tracking

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Reliability-based calibration of partial factors for the design of membrane structures

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ENGINEERING STRUCTURES 2020年 214卷 110632-110632页

作者： De Smedt, Elien Mollaert, Marijke Caspeele, Robby Botte, Wouter Pyl, Lincy Vrije Univ Brussel Pleinlaan 2 B-1050 Brussels Belgium Univ Ghent Technol Pk Zwijnaarde 60 B-9052 Ghent Belgium

Membrane structures are widely used because of their lightweight properties and expressive architectural shapes. However, there does not yet exist a unified design approach for membrane structures as is available for conventional buildings. Because of their flexibility, membrane structures exhibit a different structural behaviour than conventional buildings. Membrane structures are doubly curved, prestressed and the prestress contributes to the stiffness. The structural response of these structures is non-linear, and the hanging and arching directions interact. A probabilistic framework for tensioned membrane structures is developed herein. Using this tool, partial factors are calibrated for a representative tensioned hypar membrane structure made of PVC-coated polyester fabric. Reliability analyses are performed using a First Order Reliability Method in combination with Latin Hypercube Sampling. The approach is illustrated for two load cases, i.e. considering snow load and wind uplift load, respectively. Three hypars are investigated, each with a different rise to span ratio. The partial factors are determined through a minimisation process. As a result of the performed process, the recommended partial factor for prestress is 1.0, for snow load is 2.0 and for wind uplift load is 2.0 for the investigated membrane structure. In this study, the hanging direction under snow load proves to be decisive for the calibration of the partial factors. The obtained partial factors are not in line with the partial factors found in the Eurocode (1.5 for variable loads). Alternatively, when considering a partial factor for snow load and wind uplift load of 1.5, partial factor for prestress should be increased to 1.2 for the structural type which have been investigated. The application of Latin Hypercube Sampling in combination with the structural analysis of membrane structures enables to perform the reliability analysis calculations in a more computationally efficient way. Moreov

关键词： Membrane structures Reliability analysis optimization function First order reliability method Latin hyper cube sampling

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The calibration of the partial factors for the design of a typical hypar membrane structure 60

The calibration of the partial factors for the design of a t...

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60th Anniversary Symposium of the International-Association-for-Shell-and-Spatial-Structures (IASS SYMPOSIUM) / 9th International Conference on Textile Composites and Inflatable Structures (STRUCTURAL MEMBRANES)

作者： De Smedt, Elien Mollaert, Marijke Caspeele, Robby Pyl, Lincy Vrije Univ Brussel Pl Laan 2 B-1040 Etterbeek Belgium Univ Ghent Ghent Belgium

ISBN: (纸本)9788412110104

Membrane structures are widely used for various functions, although there does not exist a unified design approach as there exists for conventional buildings (partial factor framework, Eurocode). Specific for most membrane structures is that they have doubly curved shapes, they are pre-tensioned and exhibit a non-linear structural behaviour. The current article investigates an existing calibration method to obtain the partial factors to be used for the design of a typical hypar membrane structure. The reliability analysis is performed using a First Order Second Moment method in combination with Latin Hypercube Sampling. The study is performed for the load cases snow load and wind uplift load.

关键词： hypar membrane structure reliability index optimization function Latin Hypercube Sampling

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optimization of Grid Dynamic Resource Scheduling Algorithm Based on Response Time 11

Optimization of Grid Dynamic Resource Scheduling Algorithm B...

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11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Guo Wei-wei Liu Feng Wang Hui Heilongjiang Univ Technol Jixi 158100 Peoples R China

ISBN: (纸本)9781728121659

In order to improve the utilization of grid resources and the efficiency of task execution, this paper compares and analyzes the scheduling problems existing in genetic algorithm, Min-Min algorithm and hierarchical scheduling algorithm, and proposes a dynamic resource scheduling algorithm based on corresponding time. The parameters of resource change, weight coefficient and optimization function are introduced into the algorithm. Through the simulation experiment results, the scheduling algorithm proposed in this paper effectively improves the utilization of grid resources and the efficiency of task execution.

关键词： resource management task scheduling optimization function

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