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Fault Diagnosis Using Bond Graphs in an Expert System
Zhuoran Zhou, Zhanguo Ma, Yingying Jiang, Minjun Peng
February 27, 2023 (v1)
Keywords: bond graph, expert system, fault diagnosis, reactor coolant system
A fault diagnosis method using bond graphs in an expert system is proposed for a reactor coolant system. Firstly, the time causality graph and the variable relationship graph are derived from the bond graph. Secondly, the fault signature matrix is obtained by combining the change relationship of fault parameters. Finally, the fault signature matrix is used as the rule of the inference engine design in the expert system for fault diagnosis. In this paper, the key equipment of the reactor coolant system is used to verify the fault diagnosis method of the bond graph expert system, and the path reasoning relationship between alarms is obtained, which can accurately obtain the deep knowledge required by the operators. A new idea for fault diagnosis in a nuclear power plant’s expert system is provided by this method.
DC Component Suppression of Grid-Connected Z-Source Inverter Based on Disturbance Observer
Guofeng He, Junfang Lin, Guojiao Li, Yanfei Dong, Wenjie Zhang
February 27, 2023 (v1)
Keywords: DC current injection, disturbance observer, split capacitor, ZSI
Regarding the problems of resonance and direct current (DC) components when the Z-source inverter (ZSI) without an isolation transformer is connected to the grid through an LCL filter, this paper proposes a novel DC component suppression strategy for a grid-connected ZSI based on the split capacitor method of disturbance observer (DOB). The split capacitor method is utilized to convert a third-order LCL filter into a first-order one to eliminate the resonance problem. The DC component of the inverter output voltage is regarded as an external disturbance, and the employed DOB is used to observe it, which is fed forward to suppress the DC disturbance component. Various comparison results of the simulation and experiment show that the proposed control strategy can effectively reduce grid-connected DC components injected into the grid at less than 0.5%, which decreases the DC component from 1.8% to 0.1%.
Comparison of AC Losses in the Winding of Electrical Machines with Fixed Strands Positions, Fixed Conductor Shapes and Random Winding
Anuvav Bardalai, David Gerada, Tianjie Zou, Michele Degano, Chengming Zhang, Chris Gerada
February 27, 2023 (v1)
Keywords: AC copper loss, circulating currents, permanent magnet machines, proximity effect, windings
In high performance electric machines, the increase of fundamental frequency leads to additional losses in the winding due to parasitic effects such as the associated skin and proximity effects. In the first part, this paper presents an investigation into accurate modelling of AC losses in the winding using numerical methods and their experimental verification. Then, using experimental motorette setups, this research provides a comparative study between fixed strand positioning and fixed conductor shapes on the AC losses in the winding. It is shown that the exact position of strands in the conductor is not a critical factor; however, it is very important to control the conductor shape inside the slot. In the final section of this paper, an investigation into the relationship between AC losses in the winding and copper filling factor is presented. It is shown experimentally that counter-intuitive design choices such as using a lower copper fill factor and thicker strand diameters may be... [more]
Measuring Pollution Control and Environmental Sustainable Development in China Based on Parallel DEA Method
Ying Feng, Chih-Yu Yang, Ching-Cheng Lu, Pao-Yu Tang
February 27, 2023 (v1)
Subject: Environment
Keywords: DDF, TGR, treatment funds, waste gas, Wastewater, Yellow River
The purpose of this study is to explore the impact of pollution control on industrial production efficiency in 31 provinces and cities in the Yellow River and Non-Yellow River basins in China from 2013 to 2017, using the methods of the directional distance function (hereinafter referred to as DDF) and the technology gap ratio (hereinafter referred to as TGR) in parallel, while taking the industrial production sector (labor force, total capital formation, energy consumption and industrial water consumption) and the pollution control sector (wastewater treatment funds and waste gas treatment funds) as input variables. Undesirable outputs (total wastewater discharge, lead, SO2 and smoke and dust in wastewater) and an ideal output variable (industrial output value) are taken as output variables. It is found that the total efficiency of DDF in the Non-Yellow River Basin is 0.9793, which is slightly better than 0.9688 in the Yellow River Basin. Among the 17 provinces and cities with a total... [more]
Optimisation of Induced Steam Residual Moisture Content in a Clothing Conditioner Based on a Genetic Algorithm
Arslan Saleem, Muhammad Saeed, Man-Hoe Kim
February 27, 2023 (v1)
Keywords: clothes-conditioning unit, Genetic Algorithm, heat and mass transfer, numerical analysis, thermal management
This paper presents the modelling of heat and moisture transfer in a clothes-conditioning unit with the aim of improving the moisture content distribution to the clothes. A multicomponent, non-reacting, two-phase Eulerian−Eulerian model was utilised to solve the computational model. The clothes inside the conditioning unit were modeled as retangular towels (porous medium) of uniform thickness. Mass flow distribution of air and steam through the clothes was studied by systematically varying the steam nozzle angle (30° to 75°) and air inflow grill angle (45° to 105°). The simulation results were studied to identify the impact of design parameters on the mass flow distribution inside the clothes-conditioning unit. The mass flow of steam and the air−steam mixture were calculated through each towel in the forward and reverse direction. Response surface analysis was conducted to correlate the total mass flow rate and steam mass flow rate through each towel with the design variables. Moreover... [more]
An Improved Extended State Observer-Based Composite Nonlinear Control for Permanent Magnet Synchronous Motor Speed Regulation Systems
Zhiyuan Che, Haitao Yu, Saleh Mobayen, Murad Ali, Chunyu Yang, Andrzej Bartoszewicz
February 27, 2023 (v1)
Keywords: composite nonlinear control, extended state observer (ESO), nonlinear proportional feedback (NPF), permanent magnet synchronous motors (PMSMs), speed regulation systems, tracking differentiator (TD)
This paper addresses the problems of an improved extended state observer (ESO)-based composite nonlinear control for the permanent magnet synchronous motor (PMSM) speed regulation systems, which is primarily constituted by a linear ESO-based feedforward compensation and nonlinear proportional feedback (NPF) control law. Firstly, by taking the parametric perturbations and external disturbances into account, a novel linear ESO is designed and analyzed to estimate the lumped disturbance, such that the system anti-disturbance performance is preserved. Meanwhile, the estimation of system state is also performed. Then, an optimal control synthesis function-based tracking differentiator (TD) is developed to arrange the transition dynamic for the reference velocity value, while its high quality differential signal is facilitated. Furthermore, an adaptive proportional control law is proposed, resulting in the eventual composite nonlinear strategy by incorporating the estimate values into the de... [more]
Big-Data Analysis and Machine Learning Based on Oil Pollution Remediation Cases from CERCLA Database
Hangyu Li, Ze Zhou, Tao Long, Yao Wei, Jianchun Xu, Shuyang Liu, Xiaopu Wang
February 27, 2023 (v1)
Subject: Environment
Keywords: CERCLA, Machine Learning, oil-contaminated soil, soil remediation
The U.S. Environmental Protection Agency’s (EPA) Superfund—the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) database—has collected and built an open-source database based on nearly 2000 US soil remediation cases since 1980, providing detailed information and references for researchers worldwide to carry out remediation work. However, the cases were relatively independent to each other, so the whole database lacks systematicness and instructiveness to some extent. In this study, the basic features of all 144 soil remediation projects in four major oil-producing states (California, Texas, Oklahoma and Alaska) were extracted from the CERCLA database and the correlations among the pollutant species, pollutant site characteristics and selection of remediation methods were analyzed using traditional and machine learning techniques. The Decision Tree Classifier was selected as the machine learning model. The results showed that the growth of new contaminated... [more]
Unified Strategy for Fault-Tolerant Operation of MMC with Multiple SMs Failure Based on SMs Grouping Management
Zhihong Bai, Yifei Li
February 27, 2023 (v1)
Keywords: fault tolerance, modular multilevel converter (MMC), post-fault operation, space vector modulation (SVM)
Modular multilevel converter (MMC) is distinguished by its modularity. In order to improve its reliability and avoid unscheduled maintenance, it requires the MMC to continue operating even though some of its submodules (SMs) have failed. In this paper, a grouping management method of SMs in MMC is first presented where every six SMs are conceptually grouped into a virtual subunit (SU), and on this basis, a simplified space vector modulation (SVM) implementation is developed. Then, the fault-tolerant solutions are proposed by investigating the post-fault operation of the MMC based on the virtual SU concept. It is analyzed that the SU failures can be categorized into three basic types, according to the phase where the failed SMs are located, and also multiple SM failures can be decomposed into one or multiple basic fault types. In this way, the fault-tolerant solutions are unified regardless of the number of faulty SMs. Further, the sorting capacitor voltage control is combined into the... [more]
Transport Preferences of City Residents in the Context of Urban Mobility and Sustainable Development
Anna Eliza Wolnowska, Lech Kasyk
February 27, 2023 (v1)
Subject: Environment
Keywords: preferences in individual and collective urban transport, sustainable development, urban mobility
The article focuses on the transport preferences of the inhabitants of a medium-sized city in the context of changing urban mobility and sustainable development. It fills the gap in the literature researching the changing communication behavior of the inhabitants of a given city. The main purpose of this article is to identify and analyze the preferred means of movement for inhabitants of a medium-sized city in Central and Eastern Europe. The research area was the city of Szczecin, Poland. The research was carried out using the following research methods: literature review, analysis of legal acts and documents, case study. The research material was collected using an anonymous questionnaire based on a proprietary survey made available to the inhabitants of the largest city of north-western Poland, Szczecin, in the GOOGLE browser in the period 17 May 2019−1 April 2021. The multiple-response contingency tables, chi-square test of independence and non-parametric U Mann−Whitney and Kruskal... [more]
A Novel Measurement-Based Method for Assessing Global Warming Mitigation via High-Albedo Solutions
Federico Rossi, Mirko Filipponi, Beatrice Castellani, Stefania Bonafoni, Chaouki Ghenai
February 27, 2023 (v1)
Keywords: albedo, emission credit, global warming, radiative forcing meter
Global warming mitigation via terrestrial albedo increase has been widely investigated in literature; the proposed methodologies relate CO2 compensation to albedo increase generally via the concept of Radiative Forcing (RF). However, literature methods calculate RF by averaged input data, without considering RF variation due to many local and temporal phenomena. For instance, an average value of compensated effect of albedo change (Δα = 0.01) is 3 kg CO2eq/m2, which has been introduced no matter the position and climatic condition of the site. In our study, we propose a novel procedure to measure RF continuous time history by means of ground measurements, astronomical equations, and satellite calibration. The procedure is called RF-meter. In this way, a more accurate assessment of compensated CO2 may be achieved. A test facility is also designed and proposed to double check the procedure, and preliminary results are reported in order to show and test the calibration procedure. It is ex... [more]
Correction: Kim et al. Optimal Operation Strategy of ESS for EV Charging Infrastructure for Voltage Stabilization in a Secondary Feeder of a Distribution System. Energies 2020, 13, 179
Dae-Jin Kim, Kyung-Sang Ryu, Hee-Sang Ko, Byungki Kim
February 27, 2023 (v1)
The authors wish to make the following correction to their paper [...]
Novel Magnetic Suspension Platform with Three Types of Magnetic Bearings for Mass Transfer
Shinan Cao, Pingjuan Niu, Wei Wang, Tiantian Zhao, Qiang Liu, Jie Bai, Sha Sheng
February 27, 2023 (v1)
Keywords: electromagnetic suspension bearing, Lorentz force-type magnetic bearings, magnetic suspension platform, mass transfer, passive magnetic bearing
For ultra-precision, large stroke, and high start/stop acceleration, a novel magnetic suspension platform with three types of magnetic bearings is proposed. The structure and working principle of the novel platform are introduced. The passive magnetic bearings are used to compensate for the weight of the actuator. The repulsive force of the passive magnetic bearing model is established and analyzed. The Lorentz force-type magnetic bearings are used to provide driving force and rotational torque in the XY-plane. The driving force model and rotational torque model are established. The electromagnetic suspension bearing is used to provide driving force in the Z-axis and rotational torque along the X-axis and Y-axis. A novel Halbach magnetic array is designed to improve the magnetic flux density in the air gap. The finite element method is used to validate the force model, torque model, and magnetic flux density in the air gap. The results show that the maximum force of the passive magneti... [more]
Modeling and Design of Split-Pi Converter
Geethanjali Subramaniyan, Vijayakumar Krishnasamy, Jagabar Sathik Mohammed
February 27, 2023 (v1)
Keywords: compensator, dual way converter, electric vehicles, power train, small-signal modeling, split-pi converter
High-power bidirectional dc−dc converters are being widely employed in renewable energy interfacing, energy storage, electric vehicle charging, military, aerospace, and marine applications. Among various bidirectional topologies documented in the literature for dc−dc power conversion, the split-pi converter invites special attention with regard to applications involving multi-phase systems requiring high-power density. This paper endeavors to present the small-signal modeling of the split-pi converter in its various operating modes. Subsequently, the dynamic characteristics of the converter are studied, and appropriate control design is presented for stable operation of the converter. Frequency response plots are illustrated, and a hardware prototype model of the converter is designed and implemented.
Multidisciplinary Geophysical Investigations over Deep Coal-Bearing Strata: A Case Study in Yangjiazhangzi, Northeast China
Kun Wang, Xinbo Ge, Jianguo Ning, Jing Li, Xueyu Zhao
February 27, 2023 (v1)
Keywords: aeromagnetic survey, coal-bearing strata exploration, controlled-source audio magnetotellurics, magnetotellurics, multidisciplinary geophysical investigations
With the majority of coal mines in uncovered and semi-covered coal strata now explored and developed, most of the undiscovered coal-bearing strata are concealed. Compared with expensive drilling, deep targets such as concealed coal-bearing strata can be more efficiently and cost-effectively discovered through geophysical methods. We designed an integrated geophysical exploration approach to detect coal-bearing strata in the Yangjiazhangzi (YJZZ) area. Large-scale magnetotellurics (MT) is used to describe the geological structure along with its profile through the YJZZ area. An aeromagnetic survey was used to delineate the spatial distribution characteristics of the YJZZ syncline, a coal-bearing prospect tectonic unit. Localized exploration with controlled-source audio magnetotellurics (CSAMT) and MT reveals coal-bearing targets for drilling. Drilling results verified the targets identified through the integrated geophysical approach. Coal-bearing strata in the Benxi formation, the Taiy... [more]
On the Water-Oil Relative Permeabilities of Southern Algerian Sandstone Rock Samples
Sami Yahyaoui, Rezki Akkal, Mohammed Khodja, Toudert Ahmed Zaid
February 27, 2023 (v1)
Keywords: capillary pressure, oil recovery, relative permeability, wettability
The water−oil relative permeability behavior of different plugs from the Hassi Messaoud reservoir in south Algeria has been investigated to understand the fundamental processes of two-phase flow taking place within the macro-structure of rock samples. The experiments were conducted on cylindrical reservoir samples (plugs) using the unsteady-state method to measure the oil−water relative permeabilities due to operational simplicity. The impact of factors such as wettability, overburden pressure and rock characteristics based on the relative permeability curves have been carefully assessed. During this test, temperature was kept in the range of 95 to 100 °C and pressure was maintained at 100 bar. Large variations in relative permeability curve trends have been experimentally observed for different rock samples under investigation, which can be explained by the heterogeneous nature of the studied reservoir. Results showed an intermediate alteration of wettability and for all studied sampl... [more]
Tram System as a Challenge for Smart and Sustainable Urban Public Transport: Effects of Applying Bi-Directional Trams
Krystian Pietrzak, Oliwia Pietrzak
February 27, 2023 (v1)
Keywords: bi-directional tram, electric vehicles, electromobility, public transport, smart city, sustainable transport, tram, tram infrastructure, zero-emission vehicles
Smart and sustainable urban public transport is a considerable challenge for contemporary cities. Society’s ever-increasing transport needs require the search for solutions to increase the attractiveness of public transport. In view of the above, the main objective of this article was to determine what effects can ensue from applying bi-directional trams in the context of the smart and sustainable city concept. To attain the said objective, the research process involved desk research as well as primary research using the Delphi method, a case study, and the participant observation method. The research area covered by the study was the city of Szczecin, Poland. The completed research made it possible to identify the limitations of tram systems and the effects of applying bi-directional trams in cities, as well as to develop some practical applications for the city in question. The research study showed that application of bi-directional trams may contribute to improved functionality of... [more]
A Comparative Study on Wind Energy Assessment Distribution Models: A Case Study on Weibull Distribution
Hanifa Teimourian, Mahmoud Abubakar, Melih Yildiz, Amir Teimourian
February 27, 2023 (v1)
Keywords: empirical method, energy pattern factor, maximum likelihood method, parameter estimation, Weibull distribution
Wind power generation highly depends on the determination of wind power potential, which drives the design and feasibility of the wind energy production investment. This gives an important role to wind power estimation, which creates the need for an accurate wind data analysis and wind energy potential assessments for a given location. Such assessments require the implementation of an accurate and suitable wind distribution model. Therefore, in the quest for a well-fitted model, eight methods for estimating the Weibull parameters are investigated in this paper. The methods were then investigated by employing statistical tools, and their performances have been discussed in terms of various error indicators such as root mean squared error (RMSE), regression error (R2), chi-square (X2), and mean absolute error (MAE). Meteorological data for diverse terrain from 14 provinces with 30 sites scattered across Iran were employed to examine the performance of the investigated methods. The result... [more]
Battery-Supercapacitor Energy Storage Systems for Electrical Vehicles: A Review
Diana Lemian, Florin Bode
February 27, 2023 (v1)
Keywords: electrical vehicles, electrified vehicle energy management, hybrid energy storage systems, supercapacitors, vehicle batteries
The current worldwide energy directives are oriented toward reducing energy consumption and lowering greenhouse gas emissions. The exponential increase in the production of electrified vehicles in the last decade are an important part of meeting global goals on the climate change. However, while no greenhouse gas emissions directly come from the operations of the electrical vehicles, the electrical vehicle production process results in much higher energy consumption and greenhouse gas emissions than in the case of a classical internal combustion vehicle; thus, to reduce the environment impact of electrified vehicles, they should be used for as long as possible. Using only batteries for electric vehicles can lead to a shorter battery life for certain applications, such as in the case of those with many stops and starts but not only in these cases. To increase the lifespan of the batteries, couplings between the batteries and the supercapacitors for the new electrical vehicles in the for... [more]
FTCN: A Reservoir Parameter Prediction Method Based on a Fusional Temporal Convolutional Network
Hongxia Zhang, Kaijie Fu, Zhihao Lv, Zhe Wang, Jiqiang Shi, Huawei Yu, Xinmin Ge
February 27, 2023 (v1)
Keywords: permeability, porosity, reservoir parameter prediction, temporal convolutional network, water saturation
Predicting reservoir parameters accurately is of great significance in petroleum exploration and development. In this paper, we propose a reservoir parameter prediction method named a fusional temporal convolutional network (FTCN). Specifically, we first analyze the relationship between logging curves and reservoir parameters. Then, we build a temporal convolutional network and design a fusion module to improve the prediction results in curve inflection points, which integrates characteristics of the shallow convolution layer and the deep temporal convolution network. Finally, we conduct experiments on real logging datasets. The results indicate that compared with the baseline method, the mean square errors of FTCN are reduced by 0.23, 0.24 and 0.25 in predicting porosity, permeability, and water saturation, respectively, which shows that our method is more consistent with the actual reservoir geological conditions. Our innovation is that we propose a new reservoir parameter prediction... [more]
Numerical Investigation of Heat Transfer Performance and Structural Optimization of Fan-Shaped Finned Tube Heat Exchanger
Qianjun Mao, Xinlei Hu, Yuanyuan Zhu
February 27, 2023 (v1)
Subject: Optimization
Keywords: Energy Efficiency, fan-shaped fin, Latent Heat Storage, structure optimization
Latent heat storage technology is widely used in solar power generation. Aiming to enhance the energy utilization rate to a greater extent, an innovative fan-shaped structure has been proposed to construct the metal fins of the shell-and-tube thermal storage device. The enthalpy method is used to simulate the heat storage process and focuses on the influence of inlet conditions on heat transfer. The influence of the fin structure on the melting properties of phase change material has been studied. The results show that increasing inlet temperature and inlet flow rate is a convenient and effective way to improve energy efficiency. As the inlet temperature is increased from 343 K to 358 K, the total heat storage and energy efficiency are improved by 13.4% and 10.2%, respectively, and the melting time is reduced by 36.2%. As the flow rate is increased from 3 L/min to 9 L/min, the complete melting time is reduced by 33.4%. Energy efficiency peaks at a flow rate of 5 L/min. Reasonable optim... [more]
Air-Type Vacuum-Tube Solar Collector Design and Heat Collection Performance Test
Chuanhui Zhu, Xiaodong Dong, Shubin Yan, Yang Cui, Quanquan Luo
February 27, 2023 (v1)
Subject: Materials
Keywords: ammonium aluminum sulfate dodecahydrate/stearic acid composite material, heat-storage rod, hot-water storage tank, phase-change heat storage, solar collector
With the continuous development and utilization of clean energy, the thermal utilization of solar energy is an important research direction. In view of the problems of the low utilization rate of solar heat in alpine regions of solar energy, an air-type vacuum-tube solar collector (AVSC) with air as the heat-exchange medium was designed. The vacuum tube of the solar heat collector adopted a double-pass spiral direct-current structure, and the vacuum tube had a built-in heat-storage rod. In order to test the heat collection performance of the designed air evacuated-tube solar collector, a heat collection performance test of the collector was conducted. The results showed that the average heat collection efficiency of the vacuum tube solar collector without phase-change heat-storage rods was 38%. The evacuated-tube solar collector using water as the heat transfer medium had an average heat collection efficiency of 58%. The average equivalent heat collection efficiency of the AVSC with a... [more]
On the Organisation of Translation—An Inter- and Transdisciplinary Approach to Developing Design Options for CO2 Storage Monitoring Systems
Danny Otto, Marit Sprenkeling, Ruben Peuchen, Åsta Dyrnes Nordø, Dimitrios Mendrinos, Spyridon Karytsas, Siri Veland, Olympia Polyzou, Martha Lien, Yngve Heggelund, Matthias Gross, Pim Piek, Hanneke Puts
February 27, 2023 (v1)
Keywords: carbon capture and storage, CCS, CO2 storage monitoring, interdisciplinary research, transdisciplinary research
Interdisciplinary and transdisciplinary collaboration has become a common practice in technology development projects. Rarely, however, the integration (and translation) of knowledge from different disciplines and different societal contexts is reported in detail. In this article, we address this gap and present the inter- and transdisciplinary technology development in the international research project “DigiMon—Digital Monitoring of CO2 Storage Projects” that aims to develop a human-centered monitoring system. Based on interviews, surveys and stakeholder workshops in Norway, Greece, Germany and The Netherlands, we identify characteristics of CO2 storage monitoring systems that reflect the concerns and expectations of publics and stakeholders. We document the translation of social scientific findings into technical expertise for the design of a monitoring system. We discuss how the interdisciplinary and transdisciplinary process has affected the technology development. In outlining ho... [more]
Prediction Model for the Internal Temperature of a Greenhouse with a Water-to-Water Heat Pump Using a Pellet Boiler as a Heat Source Using Building Energy Simulation
Chung-Geon Lee, La-Hoon Cho, Seok-Jun Kim, Sun-Yong Park, Dae-Hyun Kim
February 27, 2023 (v1)
Keywords: economic analysis, greenhouse heating, heat pump, pellet boiler, TRNSYS
Although smart farms are considered an alternative to traditional agriculture, they require large amounts of energy and high investment costs, hindering their efficient implementation. In the Republic of Korea, the energy supply is primarily for heating rather than cooling, necessitating the accurate prediction of the greenhouse internal temperature to determine the feasibility of agricultural management while using renewable energy. This study developed a model (TRNSYS) for predicting the internal temperature of a greenhouse using building energy simulation. A greenhouse heating experiment was conducted using a hybrid heating system simulated by TRNSYS to analyze the prediction model. The regression analysis of the experimental and simulation results revealed an R2 and RMSE of 0.8834 and 3.61, respectively. A comparative analysis was conducted with the existing hot air heating system to evaluate the heating performance and economic feasibility of the hybrid system. Overall, the heatin... [more]
Organizational Factors of Commitment to Innovation vs. Innovative Behavior in Smes in the Renewable Energy Sources (RES) Industry
Joanna Dzieńdziora, Małgorzata Smolarek, Dawid Żebrak, Elwira Gross-Gołacka
February 27, 2023 (v1)
Keywords: innovative behaviors, internal relationships, organizational factors of commitment to innovation, RES, small and medium-sized enterprises (SMEs)
Innovation is one of the successful and competitive advantage factors for SMEs in the dynamically changing environment of the RES industry. For SMEs, innovation is driven by a number of factors, such as the size of the enterprise, the scope of activity, innovation capability, strategy, and environmental conditions. Organizations’ commitment to innovation is another important factor. This is especially true for SMEs with strong social bonds, meaning that every employee of the company is, to some extent, involved in the innovation process and influences the organization’s opinion. The goal of the paper is to assess the impact of organizational determinants of commitment to innovation on innovative behavior in SMEs in the RES industry. The paper is both theoretical and empirical. The theoretical part explains the relevance of organizational determinants of commitment to innovation and how they translate to innovative behavior in SMEs. The empirical part presents an analysis of the results... [more]
Abnormal Detection for Running State of Linear Motor Feeding System Based on Deep Neural Networks
Zeqing Yang, Wenbo Zhang, Wei Cui, Lingxiao Gao, Yingshu Chen, Qiang Wei, Libing Liu
February 27, 2023 (v1)
Keywords: anomaly detection, deep neural network, lack of abnormal samples, linear motor feeding system, long short-term memory (LSTM) network, semi-supervised anomaly detection generative adversarial network (GANomaly)
Because the linear motor feeding system always runs in complex working conditions for a long time, its performance and state transition have great randomness. Therefore, abnormal detection is particularly significant for predictive maintenance to promptly discover the running state degradation trend. Aiming at the problem that the abnormal samples of linear motor feed system are few and the samples have time-series features, a method of abnormal operation state detection of a linear motor feed system based on normal sample training was proposed, named GANomaly-LSTM. The method constructs an encoding-decoding-reconstructed encoding network model. Firstly, the time-series features of vibration, current and composite data samples are extracted by the long short-term memory (LSTM) network; Secondly, the three-layer fully connected layer is employed to extract potential feature vectors; Finally, anomaly detection of the system is completed by comparing the potential feature vectors of the t... [more]
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