The industrial sector is the primary source of carbon emissions in China.In pursuit of meeting its carbon reduction targets,China aims to promote resource consumption sustainability,reduce energy consumption,and achie...The industrial sector is the primary source of carbon emissions in China.In pursuit of meeting its carbon reduction targets,China aims to promote resource consumption sustainability,reduce energy consumption,and achieve carbon neutrality within its processing industries.An effective strategy to promote energy savings and carbon reduction throughout the life cycle of materials is by applying life cycle engineering technology.This strategy aims to attain an optimal solution for material performance,resource consumption,and environmental impact.In this study,five types of technologies were considered:raw material replacement,process reengineering,fuel replacement,energy recycling and reutilization,and material recycling and reutilization.The meaning,methodology,and development status of life cycle engineering technology abroad and domestically are discussed in detail.A multidimensional analysis of ecological design was conducted from the perspectives of resource and energy consumption,carbon emissions,product performance,and recycling of secondary resources in a manufacturing process.This coupled with an integrated method to analyze carbon emissions in the entire life cycle of a material process industry was applied to the nonferrous industry,as an example.The results provide effective ideas and solutions for achieving low or zero carbon emission production in the Chinese industry as recycled aluminum and primary aluminum based on advanced technologies had reduced resource consumption and emissions as compared to primary aluminum production.展开更多
Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the pro...Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is proposed.This paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process enterprises.Based on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system.Finally,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.展开更多
Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety...Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.展开更多
The process industry plays a crucial role in national economic development and national defense construction.However,as a typical energy-intensive industry,it is at the forefront of efforts to reduce carbon emissions....The process industry plays a crucial role in national economic development and national defense construction.However,as a typical energy-intensive industry,it is at the forefront of efforts to reduce carbon emissions.Information and communications technology(ICT)is an important means of achieving low-carbon operation in the process industry by strengthening the regulation of carbon flow in the production process.This paper first introduces the relevant research on low-carbon operation of industrial processes,and analyzes and summarizes the current research status and bottleneck.Then,the challenging problems faced by ICT in achieving low-carbon operation in the process industry are analyzed from four aspects:carbon emission sensing,carbon transfer modeling,carbon migration control,as well as low-carbon operation optimization throughout the entire process.Finally,the overall framework and vision for implementing low-carbon operation in the process industry through ICT are presented,and future research directions are proposed in conjunction with industrial artificial intelligence.展开更多
Fault diagnosis in industrial process is essential for ensuring production safety and efficiency.However,existing methods exhibit limited capability in recognizing hard samples and struggle to maintain consistency in ...Fault diagnosis in industrial process is essential for ensuring production safety and efficiency.However,existing methods exhibit limited capability in recognizing hard samples and struggle to maintain consistency in feature distributions across domains,resulting in suboptimal performance and robustness.Therefore,this paper proposes a fault diagnosis neural network for hard sample mining and domain adaptive(SmdaNet).First,the method uses deep belief networks(DBN)to build a diagnostic model.Hard samples are mined based on the loss values,dividing the data set into hard and easy samples.Second,elastic weight consolidation(EWC)is used to train the model on hard samples,effectively preventing information forgetting.Finally,the feature space domain adaptation is introduced to optimize the feature space by minimizing the Kullback–Leibler divergence of the feature distributions.Experimental results show that the proposed SmdaNet method outperforms existing approaches in terms of classification accuracy,robustness and interpretability on the penicillin simulation and Tennessee Eastman process datasets.展开更多
Recently,the implementation of Industry 4.0 has become a new tendency,and it brings both opportunities and challenges to worldwide manufacturing companies.Thus,many manufacturing companies are attempting to find advan...Recently,the implementation of Industry 4.0 has become a new tendency,and it brings both opportunities and challenges to worldwide manufacturing companies.Thus,many manufacturing companies are attempting to find advanced technologies to launch intelligent manufacturing transformation.In this study,we propose a new model to measure the intelligent manufacturing readiness for the process industry,which aims to guide companies in recognizing their current stage and short slabs when carrying out intelligent manufacturing transformation.Although some models have already been reported to measure Industry 4.0 readiness and maturity,there are no models that are aimed at the process industry.This newly proposed model has six levels to describe different development stages for intelligent manufacturing.In addition,the model consists of four races,nine species,and 25 domains that are relevant to the essential businesses of companies’daily operation and capability requirements of intelligent manufacturing.Furthermore,these 25 domains are divided into 249 characteristic items to evaluate the manufacturing readiness in detail.A questionnaire is also designed based on the proposed model to help process-industry companies easily carry out self-diagnosis.Using the new method,a case including 196 real-world process-industry companies is evaluated to introduce the method of how to use the proposed model.Overall,the proposed model provides a new way to assess the degree of intelligent manufacturing readiness for process-industry companies.展开更多
False monitoring information is a major problem in process production system and several ineffective methods have been proposed to identify false monitoring information in the production system. In this paper, a new m...False monitoring information is a major problem in process production system and several ineffective methods have been proposed to identify false monitoring information in the production system. In this paper, a new method is proposed to identify false monitoring information based on system coupling analysis and collision detection from the perspective of data analysis. Coupling multifractal features are extracted to reflect the changes in coupling relationship by utilizing the multifractal detrended cross-correlation analysis (MF-DXA). Each monitoring variable in process production system has more than one coupled variable, which can be regarded as multi-source. To achieve low redundancy in features and uniform description of coupling relationship, the feature level information fusion is studied based on modified Mahalanobis Taguchi system (MTS). False alarms are identified when the coupling relationships among the coupled monitoring variables collide. Analysis results of coupled R?ssler and Henon datasets indicate the feasibility of this method for selecting the effective coupling feature and uniform description of coupling relationship. The compressor system case of Coal Chemical Ltd. Group is studied and false monitoring information is identified.展开更多
Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have b...Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.展开更多
This paper selected the corn processing industry technology innovation alliance in Heilongjiang Province as the research object, evaluated the operational performance of the alliance by using analytic hierarchy proces...This paper selected the corn processing industry technology innovation alliance in Heilongjiang Province as the research object, evaluated the operational performance of the alliance by using analytic hierarchy process(AHP) and fuzzy comprehensive evaluation methods. AHP empirical results showed that the satisfaction of information communication and the satisfaction of the management process were the weakest. And the order from high to low on the level of indicators of the impact for the alliance was the result of alliance operations and the process of alliance operations, the behavioral attitude of alliance members. Besides, the results of fuzzy comprehensive evaluation showed that the operational performance of the corn processing industry technology innovation alliance in Heilongjiang Province was in the general level.展开更多
With the development of society and economy and increasing awareness of people's diet and health care,the demand for waxy corn and its processed products has been rising. At present,the planting of waxy corn in Ch...With the development of society and economy and increasing awareness of people's diet and health care,the demand for waxy corn and its processed products has been rising. At present,the planting of waxy corn in Chongqing is taking shape,but the waxy corn processing is still in the initial stage with smaller enterprise scale and fewer processing product variety. Based on the analysis of the development advantages and disadvantages of waxy corn processing industry in Chongqing,this paper brings forward the development ideas and strategies of Chongqing waxy corn processing industry from three aspects of production,processing and policy.展开更多
This paper establishes 13 evaluation indicators for the competitiveness of agri-food processing industry,uses factor analysis to evaluate the competitiveness of agri-food processing industry in 31 provinces(cities,aut...This paper establishes 13 evaluation indicators for the competitiveness of agri-food processing industry,uses factor analysis to evaluate the competitiveness of agri-food processing industry in 31 provinces(cities,autonomous regions)of China,and does cluster analysis to divide these regions into several categories according to the difference in competitiveness,in order to understand the level of competitiveness of agri-food processing industry in China.展开更多
From the beginning of the 21^(st)century to 2013,the economic income of main business of agricultural products processing enterprises in China had maintained above double digits for a long time.The current traditional...From the beginning of the 21^(st)century to 2013,the economic income of main business of agricultural products processing enterprises in China had maintained above double digits for a long time.The current traditional high-speed growth will be transformed to high-quality,mediumhigh-speed development,and the development trend is in line with economic laws and macro situation characteristics.With the acceleration of spa-tial distribution and cluster development of agricultural processing industry,the late-mover advantages in the central and western regions of China are gradually emerging.With the support of Internet+and e-commerce online shopping platforms,the integrative development with related industries has been deepened.Led by the new concept of green development,the demand of processing industry of green,healthy,specific functional food(such as diabetes,hypertension and other specific groups)is booming.In the aspect of development strategy,it is appropriate to build multivariate information service platform,improve the technical cooperation platform,and provide software and hardware facilities for further development of agricultural product processing industry.Combined with local economic development advantages,resource advantages and industrial advantages and other factors,the way of differentiation,regionalization and characterization should be taken according to local conditions and following the law,so as to energize the rural revitalization.展开更多
The agricultural product processing industry is the inevitable choice for the agriculture to realize the industrialization, integration and modernization. Although the agricultural product processing industry has beco...The agricultural product processing industry is the inevitable choice for the agriculture to realize the industrialization, integration and modernization. Although the agricultural product processing industry has become the bright point in Chinese economy development, the whole development level falls behind the developed countries. The thesis brings up that the inherent reasons that Chinese agricultural product processing industry falls behind is that Chinese agricultural product processing industry has not an integrated industrial innovation system and has not a proper innovation strategy. So this thesis deeply discusses how to construct innovation system of Chinese agricultural product processing industry and puts forward the innovation strategy in order to improve the technology innovation capability and the development level.展开更多
The construction industry is one of the important industries supporting China's economic development, which has made a great contribution to the rise of China's overall economic level. At present, with the adv...The construction industry is one of the important industries supporting China's economic development, which has made a great contribution to the rise of China's overall economic level. At present, with the advent of the information technology era and the rapid renewal and iteration of construction technology, the industry is facing the urgent need of internal intelligent construction. At the same time, there are still many disadvantages in the development process, which urgently needs the breakthrough and innovation of new technology, which requires the construction unit to closely follow the development direction of the current era, actively explore new paths and directions of scientific and technological development, and promote the sustainable development of its own industry. Based on this, this paper mainly discusses the industrialization process of the construction industry and the development of intelligent construction, and realizes the industrialization and intelligent reform of the construction industry according to its development principles.展开更多
Various post-harvest processes of rice are commonly employed,especially during the off-season,to ensure its consumption feasibility,which often affect the grain quality.Different forms of drying,storage and processing...Various post-harvest processes of rice are commonly employed,especially during the off-season,to ensure its consumption feasibility,which often affect the grain quality.Different forms of drying,storage and processing of rice are evaluated to identify their effects on grain quality.Microwave drying has emerged as an alternative to the widely-used intermittent-drying and fixed-bed-dryer methods of drying paddy rice.Control of drying-air temperatures(between 40℃ and 60℃)according to the rice variety can improve quality,especially for exotic varieties.Keeping stored grain in hygroscopic balance,with water content between 11%to 15%,at temperatures between 16℃ and 20℃ and with intergranular relative humidity near 60%,allows 12 months of storage in a controlled environment without significant deterioration.Other innovations,notably the application of artificial refrigeration to grain stored in bulk in vertical cylindrical silos and the use of impermeable packaging for storage,ensure the conservation of grain mass.The different stages and equipments used to obtain polished,brown and parboiled rice result in significant changes in the nutritional value of rice because of the removal of the outermost layers of the grains.Polishing reduces the nutritional value and physical homogeneity of rice.Brown rice retains more bioactive compounds and nutrients because it does not lose the outer layer of the grains in the polishing processes.Parboiled rice,although less nutritious than brown rice,has better grain integrity and milling yield and less loss of nutrients than white rice.展开更多
In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate tim...In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.展开更多
In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data be...In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data benchmark(HIS)has garnered the most attention due to its practicality and effectiveness.However,existing CPM reviews usually focus on the theoretical benchmark,and there is a lack of an in-depth review that thoroughly explores HIS-based methods.In this article,a comprehensive overview of HIS-based CPM is provided.First,we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo:static and dynamic properties.The static property portrays time-independent variability in system output,and the dynamic property describes temporal behavior driven by closed-loop feedback.Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two perspectives.Specifically,two mainstream solutions for CPM methods are summarized,including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior.Furthermore,this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.展开更多
Sludge,the massive by-product of the sewage system,became a major challenge for the wastewater treatment industry.Yet,conventional methods often face challenges like low efficiency,high energy consumption,and environm...Sludge,the massive by-product of the sewage system,became a major challenge for the wastewater treatment industry.Yet,conventional methods often face challenges like low efficiency,high energy consumption,and environmental pollution.Especially,the improper treatment and disposal of toxic sludge generated from different industrial processes or specific wastewater treatment operations exerted significant pressure and threat to hydrosphere,pedosphere,atmosphere and even biosphere.展开更多
As an important pillar of China's industrialization process,the coal industry has not only made contributions to economic growth,but also left a large number of coal mine sites bearing historical memories.These si...As an important pillar of China's industrialization process,the coal industry has not only made contributions to economic growth,but also left a large number of coal mine sites bearing historical memories.These sites are not only the witness of the industrial civilization,but also the potential resources for urban renewal and industrial transformation.展开更多
Global climate change has become one of the most pressing challenges of the 21st century.As anthropogenic CO_(2) emissions from fossil fuel consumption and industrial processes continue to disrupt Earth’s carbon cycl...Global climate change has become one of the most pressing challenges of the 21st century.As anthropogenic CO_(2) emissions from fossil fuel consumption and industrial processes continue to disrupt Earth’s carbon cycle,atmospheric CO_(2) concentrations have reached unprecedented levels-exceeding 420 parts per million(ppm)in 2023 compared to pre-industrial 280 ppm.This rapid accumulation of greenhouse gases has resulted in measurable con-sequences including rising global temperatures,ocean acidifica-tion,and increased frequency of extreme weather events.展开更多
基金supported by the National Key Research and Development Programs(2021YFB3704201 and 2021YFB3700902).
文摘The industrial sector is the primary source of carbon emissions in China.In pursuit of meeting its carbon reduction targets,China aims to promote resource consumption sustainability,reduce energy consumption,and achieve carbon neutrality within its processing industries.An effective strategy to promote energy savings and carbon reduction throughout the life cycle of materials is by applying life cycle engineering technology.This strategy aims to attain an optimal solution for material performance,resource consumption,and environmental impact.In this study,five types of technologies were considered:raw material replacement,process reengineering,fuel replacement,energy recycling and reutilization,and material recycling and reutilization.The meaning,methodology,and development status of life cycle engineering technology abroad and domestically are discussed in detail.A multidimensional analysis of ecological design was conducted from the perspectives of resource and energy consumption,carbon emissions,product performance,and recycling of secondary resources in a manufacturing process.This coupled with an integrated method to analyze carbon emissions in the entire life cycle of a material process industry was applied to the nonferrous industry,as an example.The results provide effective ideas and solutions for achieving low or zero carbon emission production in the Chinese industry as recycled aluminum and primary aluminum based on advanced technologies had reduced resource consumption and emissions as compared to primary aluminum production.
基金This research was supported by the National Natural Science Foundation of China(61991400,61991403,and 61991404)China Institute of Engineering Consulting Research Project(2019-ZD-12)the 2020 Science and Technology Major Project of Liaoning Province(2020JH1/10100008),China.
文摘Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is proposed.This paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process enterprises.Based on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system.Finally,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.
文摘Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.
基金supported in part by the National Key R&D Program of China(2022YFB3304900)in part by the National Natural Science Foundation of China(62394340,62073340,61860206014)+1 种基金in part by China Engineering Science and Technology Development Strategy Jiangxi Research Institute Consulting Research Project(2023-02JXZD-02)in part by the 111 Project,China(B17048).
文摘The process industry plays a crucial role in national economic development and national defense construction.However,as a typical energy-intensive industry,it is at the forefront of efforts to reduce carbon emissions.Information and communications technology(ICT)is an important means of achieving low-carbon operation in the process industry by strengthening the regulation of carbon flow in the production process.This paper first introduces the relevant research on low-carbon operation of industrial processes,and analyzes and summarizes the current research status and bottleneck.Then,the challenging problems faced by ICT in achieving low-carbon operation in the process industry are analyzed from four aspects:carbon emission sensing,carbon transfer modeling,carbon migration control,as well as low-carbon operation optimization throughout the entire process.Finally,the overall framework and vision for implementing low-carbon operation in the process industry through ICT are presented,and future research directions are proposed in conjunction with industrial artificial intelligence.
基金support from the following foundations:the National Natural Science Foundation of China(62322309,62433004)Shanghai Science and Technology Innovation Action Plan(23S41900500)Shanghai Pilot Program for Basic Research(22TQ1400100-16).
文摘Fault diagnosis in industrial process is essential for ensuring production safety and efficiency.However,existing methods exhibit limited capability in recognizing hard samples and struggle to maintain consistency in feature distributions across domains,resulting in suboptimal performance and robustness.Therefore,this paper proposes a fault diagnosis neural network for hard sample mining and domain adaptive(SmdaNet).First,the method uses deep belief networks(DBN)to build a diagnostic model.Hard samples are mined based on the loss values,dividing the data set into hard and easy samples.Second,elastic weight consolidation(EWC)is used to train the model on hard samples,effectively preventing information forgetting.Finally,the feature space domain adaptation is introduced to optimize the feature space by minimizing the Kullback–Leibler divergence of the feature distributions.Experimental results show that the proposed SmdaNet method outperforms existing approaches in terms of classification accuracy,robustness and interpretability on the penicillin simulation and Tennessee Eastman process datasets.
基金Project supported by the National Key Research and Development Program of China(No.2019YFB1705004)。
文摘Recently,the implementation of Industry 4.0 has become a new tendency,and it brings both opportunities and challenges to worldwide manufacturing companies.Thus,many manufacturing companies are attempting to find advanced technologies to launch intelligent manufacturing transformation.In this study,we propose a new model to measure the intelligent manufacturing readiness for the process industry,which aims to guide companies in recognizing their current stage and short slabs when carrying out intelligent manufacturing transformation.Although some models have already been reported to measure Industry 4.0 readiness and maturity,there are no models that are aimed at the process industry.This newly proposed model has six levels to describe different development stages for intelligent manufacturing.In addition,the model consists of four races,nine species,and 25 domains that are relevant to the essential businesses of companies’daily operation and capability requirements of intelligent manufacturing.Furthermore,these 25 domains are divided into 249 characteristic items to evaluate the manufacturing readiness in detail.A questionnaire is also designed based on the proposed model to help process-industry companies easily carry out self-diagnosis.Using the new method,a case including 196 real-world process-industry companies is evaluated to introduce the method of how to use the proposed model.Overall,the proposed model provides a new way to assess the degree of intelligent manufacturing readiness for process-industry companies.
基金supported by the National Natural Science Foundation of China (Grant No. 51375375)
文摘False monitoring information is a major problem in process production system and several ineffective methods have been proposed to identify false monitoring information in the production system. In this paper, a new method is proposed to identify false monitoring information based on system coupling analysis and collision detection from the perspective of data analysis. Coupling multifractal features are extracted to reflect the changes in coupling relationship by utilizing the multifractal detrended cross-correlation analysis (MF-DXA). Each monitoring variable in process production system has more than one coupled variable, which can be regarded as multi-source. To achieve low redundancy in features and uniform description of coupling relationship, the feature level information fusion is studied based on modified Mahalanobis Taguchi system (MTS). False alarms are identified when the coupling relationships among the coupled monitoring variables collide. Analysis results of coupled R?ssler and Henon datasets indicate the feasibility of this method for selecting the effective coupling feature and uniform description of coupling relationship. The compressor system case of Coal Chemical Ltd. Group is studied and false monitoring information is identified.
基金the National Natural Science Foundation of China(62003298,62163036)the Major Project of Science and Technology of Yunnan Province(202202AD080005,202202AH080009)the Yunnan University Professional Degree Graduate Practice Innovation Fund Project(ZC-22222770)。
文摘Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.
基金Supported by Technology Research and Development Project of Heilongjiang Province(GB14D202)
文摘This paper selected the corn processing industry technology innovation alliance in Heilongjiang Province as the research object, evaluated the operational performance of the alliance by using analytic hierarchy process(AHP) and fuzzy comprehensive evaluation methods. AHP empirical results showed that the satisfaction of information communication and the satisfaction of the management process were the weakest. And the order from high to low on the level of indicators of the impact for the alliance was the result of alliance operations and the process of alliance operations, the behavioral attitude of alliance members. Besides, the results of fuzzy comprehensive evaluation showed that the operational performance of the corn processing industry technology innovation alliance in Heilongjiang Province was in the general level.
基金Supported by Science and Technology Service Platform Project of Chongqing Science and Technology Commission(cstc2015ptfw-ggfw80001)Agricultural Development Project of Chongqing Academy of Agricultural Sciences(Research and Demonstration of the Key Technology in Adjusting Corn Planting Structure)Soft Science Project of Jiulongpo District Science and Technology Commission in Chongqing Municipality(Study on the Industrialization Layout and Development Strategy of Grain Reform in Chongqing)
文摘With the development of society and economy and increasing awareness of people's diet and health care,the demand for waxy corn and its processed products has been rising. At present,the planting of waxy corn in Chongqing is taking shape,but the waxy corn processing is still in the initial stage with smaller enterprise scale and fewer processing product variety. Based on the analysis of the development advantages and disadvantages of waxy corn processing industry in Chongqing,this paper brings forward the development ideas and strategies of Chongqing waxy corn processing industry from three aspects of production,processing and policy.
基金Supported by Humanities and Social Sciences Project of Hubei Provincial Department of Education(14Q033)
文摘This paper establishes 13 evaluation indicators for the competitiveness of agri-food processing industry,uses factor analysis to evaluate the competitiveness of agri-food processing industry in 31 provinces(cities,autonomous regions)of China,and does cluster analysis to divide these regions into several categories according to the difference in competitiveness,in order to understand the level of competitiveness of agri-food processing industry in China.
文摘From the beginning of the 21^(st)century to 2013,the economic income of main business of agricultural products processing enterprises in China had maintained above double digits for a long time.The current traditional high-speed growth will be transformed to high-quality,mediumhigh-speed development,and the development trend is in line with economic laws and macro situation characteristics.With the acceleration of spa-tial distribution and cluster development of agricultural processing industry,the late-mover advantages in the central and western regions of China are gradually emerging.With the support of Internet+and e-commerce online shopping platforms,the integrative development with related industries has been deepened.Led by the new concept of green development,the demand of processing industry of green,healthy,specific functional food(such as diabetes,hypertension and other specific groups)is booming.In the aspect of development strategy,it is appropriate to build multivariate information service platform,improve the technical cooperation platform,and provide software and hardware facilities for further development of agricultural product processing industry.Combined with local economic development advantages,resource advantages and industrial advantages and other factors,the way of differentiation,regionalization and characterization should be taken according to local conditions and following the law,so as to energize the rural revitalization.
文摘The agricultural product processing industry is the inevitable choice for the agriculture to realize the industrialization, integration and modernization. Although the agricultural product processing industry has become the bright point in Chinese economy development, the whole development level falls behind the developed countries. The thesis brings up that the inherent reasons that Chinese agricultural product processing industry falls behind is that Chinese agricultural product processing industry has not an integrated industrial innovation system and has not a proper innovation strategy. So this thesis deeply discusses how to construct innovation system of Chinese agricultural product processing industry and puts forward the innovation strategy in order to improve the technology innovation capability and the development level.
文摘The construction industry is one of the important industries supporting China's economic development, which has made a great contribution to the rise of China's overall economic level. At present, with the advent of the information technology era and the rapid renewal and iteration of construction technology, the industry is facing the urgent need of internal intelligent construction. At the same time, there are still many disadvantages in the development process, which urgently needs the breakthrough and innovation of new technology, which requires the construction unit to closely follow the development direction of the current era, actively explore new paths and directions of scientific and technological development, and promote the sustainable development of its own industry. Based on this, this paper mainly discusses the industrialization process of the construction industry and the development of intelligent construction, and realizes the industrialization and intelligent reform of the construction industry according to its development principles.
基金CAPES(Coordination for the Improvement of Higher Education Personnel)(Financial Code 001)CNPq(National Council for Scientific Technological Development)+1 种基金FAPERGS-RS(Research Support Foundation of the State of Rio Grande do Sul)UFSM(Federal University of Santa Maria)-Research Group at Postharvest Innovation:Technology,Quality and Sustainability,for their financial contributions。
文摘Various post-harvest processes of rice are commonly employed,especially during the off-season,to ensure its consumption feasibility,which often affect the grain quality.Different forms of drying,storage and processing of rice are evaluated to identify their effects on grain quality.Microwave drying has emerged as an alternative to the widely-used intermittent-drying and fixed-bed-dryer methods of drying paddy rice.Control of drying-air temperatures(between 40℃ and 60℃)according to the rice variety can improve quality,especially for exotic varieties.Keeping stored grain in hygroscopic balance,with water content between 11%to 15%,at temperatures between 16℃ and 20℃ and with intergranular relative humidity near 60%,allows 12 months of storage in a controlled environment without significant deterioration.Other innovations,notably the application of artificial refrigeration to grain stored in bulk in vertical cylindrical silos and the use of impermeable packaging for storage,ensure the conservation of grain mass.The different stages and equipments used to obtain polished,brown and parboiled rice result in significant changes in the nutritional value of rice because of the removal of the outermost layers of the grains.Polishing reduces the nutritional value and physical homogeneity of rice.Brown rice retains more bioactive compounds and nutrients because it does not lose the outer layer of the grains in the polishing processes.Parboiled rice,although less nutritious than brown rice,has better grain integrity and milling yield and less loss of nutrients than white rice.
基金Project(61025015) supported by the National Natural Science Funds for Distinguished Young Scholars of ChinaProject(21106036) supported by the National Natural Science Foundation of China+2 种基金Project(200805331103) supported by Research Fund for the Doctoral Program of Higher Education of ChinaProject(NCET-08-0576) supported by Program for New Century Excellent Talents in Universities of ChinaProject(11B038) supported by Scientific Research Fund for the Excellent Youth Scholars of Hunan Provincial Education Department,China
文摘In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.
基金supported in part by the National Natural Science Foundation of China(62125306)Zhejiang Key Research and Development Project(2024C01163)the State Key Laboratory of Industrial Control Technology,China(ICT2024A06)
文摘In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data benchmark(HIS)has garnered the most attention due to its practicality and effectiveness.However,existing CPM reviews usually focus on the theoretical benchmark,and there is a lack of an in-depth review that thoroughly explores HIS-based methods.In this article,a comprehensive overview of HIS-based CPM is provided.First,we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo:static and dynamic properties.The static property portrays time-independent variability in system output,and the dynamic property describes temporal behavior driven by closed-loop feedback.Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two perspectives.Specifically,two mainstream solutions for CPM methods are summarized,including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior.Furthermore,this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.
基金supported by National Natural Science Foundation of China(Nos.52370025,22176012)BUCEA Post Graduate Innovation Project(No.PG2024086)。
文摘Sludge,the massive by-product of the sewage system,became a major challenge for the wastewater treatment industry.Yet,conventional methods often face challenges like low efficiency,high energy consumption,and environmental pollution.Especially,the improper treatment and disposal of toxic sludge generated from different industrial processes or specific wastewater treatment operations exerted significant pressure and threat to hydrosphere,pedosphere,atmosphere and even biosphere.
文摘As an important pillar of China's industrialization process,the coal industry has not only made contributions to economic growth,but also left a large number of coal mine sites bearing historical memories.These sites are not only the witness of the industrial civilization,but also the potential resources for urban renewal and industrial transformation.
文摘Global climate change has become one of the most pressing challenges of the 21st century.As anthropogenic CO_(2) emissions from fossil fuel consumption and industrial processes continue to disrupt Earth’s carbon cycle,atmospheric CO_(2) concentrations have reached unprecedented levels-exceeding 420 parts per million(ppm)in 2023 compared to pre-industrial 280 ppm.This rapid accumulation of greenhouse gases has resulted in measurable con-sequences including rising global temperatures,ocean acidifica-tion,and increased frequency of extreme weather events.
