The Shipboard Meteorological Satellite Receiving-processing System (SMSRPS) is specially developed for the navigation meteorological safeguard of the Antarctic exploration ship over the sea ice area of the forth Ocean...The Shipboard Meteorological Satellite Receiving-processing System (SMSRPS) is specially developed for the navigation meteorological safeguard of the Antarctic exploration ship over the sea ice area of the forth Ocean. This system can suit to the climate environment of very high temperature high moisture and very low temperature - supersaturation; it has a self-protection ability to against the hurricane - force wind over force 12 and the strong vibration during icebreaking, as well as strong magnetic disturbance. It has two sets of receiving-imagery processing systems for polar orbit low-resolution and quasi-stationary high-solution satellites. The key creation Points of this system are as follows: 1. the active gyro-control stabilization platform and a mixed mounting system of three rotating a - B and x -- y axes are used. It solved the tracing difficulties both in the low elevation angle and very high elevation angle of polar-orbit satellite, even in the status of ship moving with continuously changing its poition, direction and ship roll and pitch. 2. Imagery processing subsystem. The newest BORLAND-- DELPHI language and PASCAL language pro gramming software are used under WINDOWS 95 environment. It has a dynamic positioning nested-grid system and electric mapping grid data system. It can show the latitude-longitude of any point on the map, and marks any object such as ship, station or island, and draws the route. It can monitor cloud and temperature, forest fire, anomalous change of ocean and land. It can output satellite cloud maps of 24 bit with very high clarity. This system is very advanced in technique for the whole structure with the features of small volume, light weight and very low cost. It suits to very bad climate and ocean environment. Its imagery process ing system has complete functions with high resolution and being very easy to operate. It is not only suit to land use, but also and specially to all kinds of ship over the sea. It can be extended to domestic and international use. This system played a very important role in the 14th Chinese Antarctic Exploration Navigation, and was introduced a broad attention paid by Chinese newspapers and TV Stations.展开更多
The neutron count rate fluctuation reaches six orders of magnitude between the ohmic plasma scenario and high power of auxiliary heating on an experimental advanced superconducting tokamak(EAST).The measurement result...The neutron count rate fluctuation reaches six orders of magnitude between the ohmic plasma scenario and high power of auxiliary heating on an experimental advanced superconducting tokamak(EAST).The measurement result of neutron flux monitoring(NFM)is a significant feedback parameter related to the acquisition of radiation protection-related information and rapid fluctuations in neutron emission induced by plasma magnetohydrodynamic activity.Therefore,a wide range and high time resolution are required for the NFM system on EAST.To satisfy these requirements,a digital pulse signal acquisition and processing system with a wide dynamic range and fast response time was developed.The present study was conducted using a field-programmable gate array(FPGA)and peripheral component interconnect extension for instrument express(PXIe)platform.The digital dual measurement modes,which are composed of the pulse-counting mode and AC coupled square integral's Campbelling mode,were designed to expand the measurement range of the signal acquisition and processing system.The time resolution of the signal acquisition and processing system was improved from 10 to 1 ms owing to utilizing highspeed analog-to-digital converters(ADCs),a high-speed PXIe communication with a direct memory access(DMA)mode,and online data preprocessing technology of FPGA.The signal acquisition and processing system was tested experimentally in the EAST radiation field.The test results showed that the time resolution of NFM was improved to 1 ms,and the dynamic range of the neutron counts rate was expanded to more than 10^(6) counts per second.The Campbelling mode was calibrated using a multipoint average linear fitting method;subsequently,the fitting coefficient reached 0.9911.Therefore,the newly developed pulse signal acquisition and processing system ensures that the NFM system meets the requirements of high-parameter experiments conducted on EAST more effectively.展开更多
The new type of embedded signal processing system based on the packet switched network is achieved. According to the application field and the-characteristics of signal processing system, the RapidIO protocol is used ...The new type of embedded signal processing system based on the packet switched network is achieved. According to the application field and the-characteristics of signal processing system, the RapidIO protocol is used to solve the high-speed interconnection of multi-digital signal processor (DSP). Based on this protocol, a kind of crossbar switch module which is used to interconnect multi-DSP in the system is introduced. A route strategy, some flow control rules and error control rules, which adapt to different RapidIO network topology are also introduced. Crossbar switch performance is analyzed in detail by the probability module. By researching the technique of crossbar switch and analyzing the system performance, it has a significant meaning for building the general signal processing system.展开更多
A low-power complementary metal oxide semiconductor(CMOS) operational amplifier (op-amp) for real-time signal processing of micro air vehicle (MAV) is designed in this paper.Traditional folded cascode architectu...A low-power complementary metal oxide semiconductor(CMOS) operational amplifier (op-amp) for real-time signal processing of micro air vehicle (MAV) is designed in this paper.Traditional folded cascode architecture with positive channel metal oxide semiconductor(PMOS) differential input transistors and sub-threshold technology are applied under the low supply voltage.Simulation results show that this amplifier has significantly low power,while maintaining almost the same gain,bandwidth and other key performances.The power required is only 0.12 mW,which is applicable to low-power and low-voltage real-time signal acquisition and processing system.展开更多
Implementation of artificial neural network(ANN)is very important to theoretical studyand applications of ANN.On the basis of studying existing methods,this paper concentrateson the DSP-based virtual implementation of...Implementation of artificial neural network(ANN)is very important to theoretical studyand applications of ANN.On the basis of studying existing methods,this paper concentrateson the DSP-based virtual implementation of ANN.A parallel processing system composed ofTMS320C30 has been designed and configured,which ean provide a peak speed as high as100 MFLOPS and a parallel efficiency of 90%(during the forward phase of BP),and can heused for sonar signal processing.Scalability of the system is also studied.展开更多
In the era of Big Data, typical architecture of distributed real-time stream processing systems is the combination of Flume, Kafka, and Storm. As a kind of distributed message system, Kafka has the characteristics of ...In the era of Big Data, typical architecture of distributed real-time stream processing systems is the combination of Flume, Kafka, and Storm. As a kind of distributed message system, Kafka has the characteristics of horizontal scalability and high throughput, which is manly deployed in many areas in order to address the problem of speed mismatch between message producers and consumers. When using Kafka, we need to quickly receive data sent by producers. In addition, we need to send data to consumers quickly. Therefore, the performance of Kafka is of critical importance to the performance of the whole stream processing system. In this paper, we propose the improved design of real-time stream processing systems, and focus on improving the Kafka's data loading process.We use Kafka cat to transfer data from the source to Kafka topic directly, which can reduce the network transmission. We also utilize the memory file system to accelerate the process of data loading, which can address the bottleneck and performance problems caused by disk I/O. Extensive experiments are conducted to evaluate the performance, which show the superiority of our improved design.展开更多
Research for detecting or obtaining radionuclide by gamma energy spectrum data acquisition and process system is one of the key issues about intelligent measurement of gamma-ray spectrum. For this reason, a software a...Research for detecting or obtaining radionuclide by gamma energy spectrum data acquisition and process system is one of the key issues about intelligent measurement of gamma-ray spectrum. For this reason, a software and hardware implementation schematic design based on ARM ( Advanced RISC Machines) + DSP ( Digital Signal Processor) architecture for gamma energy spectrum data acquisition and processing system is proposed. The paper discusses in detail some key technologies such as communication interface design between microcontroller ARM and digital signal processor DSP,distribution scheduling under multi-task in the ARM-Linux,DSP handling procedures for multi-channel A / D high-speed sample. At the same time,because the traditional Gaussian fitting to determine the boundary of peak is not ideal,it puts forward a weighting factor of Gaussian function least squares fitting realize boundary determined. Finally gamma-spectrum data from sodium iodide NaI( TI) scintillation detector is tested and processed in the new system. The results show that gamma energy spectrum data acquisition and process system is perfect functionality, stable and convergence in unimodal. Compared with data from conventional energy spectrometers,the system can keep better energy resolution in a wide range of pulse pass rate.展开更多
An air classifier is used in the recycling process of covered electric wire in the recycling factories, in which the covered electric wires are crushed, sieved, and classified by the air classifier, which generates wa...An air classifier is used in the recycling process of covered electric wire in the recycling factories, in which the covered electric wires are crushed, sieved, and classified by the air classifier, which generates wastes. In these factories, operators manually adjust the air flow rate while checking the wastes discharged from the separator outlet. However, the adjustments are basically done by trial and error, and it is difficult to do them appropriately. In this study, we tried to develop the image processing system that calculates the ratio of copper (Cu) product and polyvinyl chloride (PVC) in the wastes as a substitute for the operator’s eyes. Six colors of PVC (white, gray, green, blue, black, and red) were used in the present work. An image consists of foreground and background. An image’s regions of interest are objects (Cu particles) in its foreground. However, the particles having a color similar to the background color are buried in the background. Using the difference of two color backgrounds, we separated particles and background without dependent of background. The Otsu’ thresholding was employed to choose the threshold to maximize the degree of separation of the particles and background. The ratio of Cu to PVC pixels from mixed image was calculated by linear discriminant analysis. The error of PVC pixels resulted in zero, whereas the error of Cu pixels arose to 4.19%. Comparing the numbers of Cu and PVC pixels within the contour, the minority of the object were corrected to the majority of the object. The error of Cu pixels discriminated as PVC incorrectly became zero percent through this correction.展开更多
Sonar image processing system is an important intelligent system of Autonomous Un-derwater Vehicle.Based on TMS320C30 high speed DSP,it is used to realize sonar imagecompression and underwater object detections includ...Sonar image processing system is an important intelligent system of Autonomous Un-derwater Vehicle.Based on TMS320C30 high speed DSP,it is used to realize sonar imagecompression and underwater object detections including obstacle recognition in real time.Inthis paper,the software and hardware designs of this system are introduced and the experi-mental results are given.展开更多
A robot flexible processing system of shipbuilding profile steel was developed. The system consists of computer integrated control and robot. An off line programming robot was used for marking and cutting of shipbuil...A robot flexible processing system of shipbuilding profile steel was developed. The system consists of computer integrated control and robot. An off line programming robot was used for marking and cutting of shipbuilding profile steel. In the system the deformation and position error of profile steel can be detected by precise sensors, and figure position coordinate error resulted from profile steel deformation can be compensated by modifying traveling track of robotic arm online. The practical operation results show that the system performance can meet the needs of profile steel processing.展开更多
Based on the analysis results of the dust size distribution of flue gas from Baosteel's short-flow (BSSF) slag processing system and the mechanism of the wet scrubber,a wet scrubber system was designed and installe...Based on the analysis results of the dust size distribution of flue gas from Baosteel's short-flow (BSSF) slag processing system and the mechanism of the wet scrubber,a wet scrubber system was designed and installed in the No. 1 BSSF slag processing system at Baosteel. The results show that the dust removal efficiency of the previous system that had conventional water nozzles was only 69% with a liquid-gas ratio of 0.79 L/m^3 ,while the dust removal efficiency reached 94% when three sets of high-efficiency dual phase spray guns were installed inside both the flue and the chimney. For the latter system,the liquid-gas ratio was 0. 84 L/m^3 ,and the dust concentration in the cleaned emissions reduced to less than 40 mg/m^3.展开更多
This paper analyzes the current difficulties encountered in on-line inspection systems of strip surface quality, specifically relating to problems with real-time processing of huge amounts of data. To address this nee...This paper analyzes the current difficulties encountered in on-line inspection systems of strip surface quality, specifically relating to problems with real-time processing of huge amounts of data. To address this need, this paper describes an FPGA-based high-speed image processing module with both hardware and software aspects. Improving these two aspects together will help the system achieve real-time processing of massive image data, and simplifies the architecture of the strip surface quality on-line inspection system.展开更多
A distributed processing system (DPS) contains many autonomous nodes, which contribute their own computing power. DPS is considered a unified logical structure, operating in a distributed manner;the processing tasks a...A distributed processing system (DPS) contains many autonomous nodes, which contribute their own computing power. DPS is considered a unified logical structure, operating in a distributed manner;the processing tasks are divided into fragments and assigned to various nodes for processing. That type of operation requires and involves a great deal of communication. We propose to use the decentralized approach, based on a distributed hash table, to reduce the communication overhead and remove the server unit, thus avoiding having a single point of failure in the system. This paper proposes a mathematical model and algorithms that are implemented in a dedicated experimental system. Using the decentralized approach, this study demonstrates the efficient operation of a decentralized system which results in a reduced energy emission.展开更多
In this paper, we present an optimized design method for high-speed embedded image processing system using 32 bit floating-point Digital Signal Processor (DSP) and Complex Programmable Logic Device (CPLD). The DSP...In this paper, we present an optimized design method for high-speed embedded image processing system using 32 bit floating-point Digital Signal Processor (DSP) and Complex Programmable Logic Device (CPLD). The DSP acts as the main processor of the system: executes digital image processing algorithms and operates other devices such as image sensor and CPLD. The CPLD is used to acquire images and achieve complex logic control of the whole system. Some key technologies are introduced to enhance the performance of our system. In particular, the use of DSP/BIOS tool to develop DSP applications makes our program run much more efficiently. As a result, this system can provide an excellent computing platform not only for executing complex image processing algorithms, but also for other digital signal processing or multi-channel data collection by choosing different sensors or Analog-to-Digital (A/D) converters.展开更多
DNA-based nanostructure allows the construction of molecular devices useful in biological computing and information processing.Herein,an addressable and editable DNA information processing system established on a fluo...DNA-based nanostructure allows the construction of molecular devices useful in biological computing and information processing.Herein,an addressable and editable DNA information processing system established on a fluorescence intensity signal detection platform to save and encrypt information is proposed.The system operates by encoding information into distinct and changeable units of the trigger strands decoding by fluorescence intensity signal detection.Through toehold-mediated strand displacement reactions,the trigger strand can be precisely added to and removed from the memorizer and reporter to implement the function of editing,encrypting,and decrypting.Our strategy is simple to implement,requiring only two mixing steps at room temperature for each operation and fluorescence intensity signal detection to read the data.And the system can realize accurate retrieval of specific individual information,eliminating all unnecessary redundant readouts.Because of its point-to-point accurate readout and programmability,the system is expected to become a powerful tool for the future development of information storage and sensing of biological molecules.展开更多
Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of predic...Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.展开更多
The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart devices.It plays an important role in industrial models...The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart devices.It plays an important role in industrial models such as speech understanding,emotion detection,home automation,and so on.If an image needs to be captioned,then the objects in that image,its actions and connections,and any silent feature that remains under-projected or missing from the images should be identified.The aim of the image captioning process is to generate a caption for image.In next step,the image should be provided with one of the most significant and detailed descriptions that is syntactically as well as semantically correct.In this scenario,computer vision model is used to identify the objects and NLP approaches are followed to describe the image.The current study develops aNatural Language Processing with Optimal Deep Learning Enabled Intelligent Image Captioning System(NLPODL-IICS).The aim of the presented NLPODL-IICS model is to produce a proper description for input image.To attain this,the proposed NLPODL-IICS follows two stages such as encoding and decoding processes.Initially,at the encoding side,the proposed NLPODL-IICS model makes use of Hunger Games Search(HGS)with Neural Search Architecture Network(NASNet)model.This model represents the input data appropriately by inserting it into a predefined length vector.Besides,during decoding phase,Chimp Optimization Algorithm(COA)with deeper Long Short Term Memory(LSTM)approach is followed to concatenate the description sentences 4436 CMC,2023,vol.74,no.2 produced by the method.The application of HGS and COA algorithms helps in accomplishing proper parameter tuning for NASNet and LSTM models respectively.The proposed NLPODL-IICS model was experimentally validated with the help of two benchmark datasets.Awidespread comparative analysis confirmed the superior performance of NLPODL-IICS model over other models.展开更多
Depression has become one of the most common mental illnesses in the world.For better prediction and diagnosis,methods of automatic depression recognition based on speech signal are constantly proposed and updated,wit...Depression has become one of the most common mental illnesses in the world.For better prediction and diagnosis,methods of automatic depression recognition based on speech signal are constantly proposed and updated,with a transition from the early traditional methods based on hand‐crafted features to the application of architectures of deep learning.This paper systematically and precisely outlines the most prominent and up‐to‐date research of automatic depression recognition by intelligent speech signal processing so far.Furthermore,methods for acoustic feature extraction,algorithms for classification and regression,as well as end to end deep models are investigated and analysed.Finally,general trends are summarised and key unresolved issues are identified to be considered in future studies of automatic speech depression recognition.展开更多
The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its...The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .展开更多
基金the State Oceanic Administration "95" Principal Project "9501" National Antarctic"95" Principal
文摘The Shipboard Meteorological Satellite Receiving-processing System (SMSRPS) is specially developed for the navigation meteorological safeguard of the Antarctic exploration ship over the sea ice area of the forth Ocean. This system can suit to the climate environment of very high temperature high moisture and very low temperature - supersaturation; it has a self-protection ability to against the hurricane - force wind over force 12 and the strong vibration during icebreaking, as well as strong magnetic disturbance. It has two sets of receiving-imagery processing systems for polar orbit low-resolution and quasi-stationary high-solution satellites. The key creation Points of this system are as follows: 1. the active gyro-control stabilization platform and a mixed mounting system of three rotating a - B and x -- y axes are used. It solved the tracing difficulties both in the low elevation angle and very high elevation angle of polar-orbit satellite, even in the status of ship moving with continuously changing its poition, direction and ship roll and pitch. 2. Imagery processing subsystem. The newest BORLAND-- DELPHI language and PASCAL language pro gramming software are used under WINDOWS 95 environment. It has a dynamic positioning nested-grid system and electric mapping grid data system. It can show the latitude-longitude of any point on the map, and marks any object such as ship, station or island, and draws the route. It can monitor cloud and temperature, forest fire, anomalous change of ocean and land. It can output satellite cloud maps of 24 bit with very high clarity. This system is very advanced in technique for the whole structure with the features of small volume, light weight and very low cost. It suits to very bad climate and ocean environment. Its imagery process ing system has complete functions with high resolution and being very easy to operate. It is not only suit to land use, but also and specially to all kinds of ship over the sea. It can be extended to domestic and international use. This system played a very important role in the 14th Chinese Antarctic Exploration Navigation, and was introduced a broad attention paid by Chinese newspapers and TV Stations.
基金supported by the Users with Excellence Program of the Hefei Science Center CAS (No. 2020HSC-UE012)
文摘The neutron count rate fluctuation reaches six orders of magnitude between the ohmic plasma scenario and high power of auxiliary heating on an experimental advanced superconducting tokamak(EAST).The measurement result of neutron flux monitoring(NFM)is a significant feedback parameter related to the acquisition of radiation protection-related information and rapid fluctuations in neutron emission induced by plasma magnetohydrodynamic activity.Therefore,a wide range and high time resolution are required for the NFM system on EAST.To satisfy these requirements,a digital pulse signal acquisition and processing system with a wide dynamic range and fast response time was developed.The present study was conducted using a field-programmable gate array(FPGA)and peripheral component interconnect extension for instrument express(PXIe)platform.The digital dual measurement modes,which are composed of the pulse-counting mode and AC coupled square integral's Campbelling mode,were designed to expand the measurement range of the signal acquisition and processing system.The time resolution of the signal acquisition and processing system was improved from 10 to 1 ms owing to utilizing highspeed analog-to-digital converters(ADCs),a high-speed PXIe communication with a direct memory access(DMA)mode,and online data preprocessing technology of FPGA.The signal acquisition and processing system was tested experimentally in the EAST radiation field.The test results showed that the time resolution of NFM was improved to 1 ms,and the dynamic range of the neutron counts rate was expanded to more than 10^(6) counts per second.The Campbelling mode was calibrated using a multipoint average linear fitting method;subsequently,the fitting coefficient reached 0.9911.Therefore,the newly developed pulse signal acquisition and processing system ensures that the NFM system meets the requirements of high-parameter experiments conducted on EAST more effectively.
文摘The new type of embedded signal processing system based on the packet switched network is achieved. According to the application field and the-characteristics of signal processing system, the RapidIO protocol is used to solve the high-speed interconnection of multi-digital signal processor (DSP). Based on this protocol, a kind of crossbar switch module which is used to interconnect multi-DSP in the system is introduced. A route strategy, some flow control rules and error control rules, which adapt to different RapidIO network topology are also introduced. Crossbar switch performance is analyzed in detail by the probability module. By researching the technique of crossbar switch and analyzing the system performance, it has a significant meaning for building the general signal processing system.
基金Sponsored by the National Natural Science Foundation of China (60843005)the Basic Research Foundation of Beijing Institute of Technology(20070142018)
文摘A low-power complementary metal oxide semiconductor(CMOS) operational amplifier (op-amp) for real-time signal processing of micro air vehicle (MAV) is designed in this paper.Traditional folded cascode architecture with positive channel metal oxide semiconductor(PMOS) differential input transistors and sub-threshold technology are applied under the low supply voltage.Simulation results show that this amplifier has significantly low power,while maintaining almost the same gain,bandwidth and other key performances.The power required is only 0.12 mW,which is applicable to low-power and low-voltage real-time signal acquisition and processing system.
文摘Implementation of artificial neural network(ANN)is very important to theoretical studyand applications of ANN.On the basis of studying existing methods,this paper concentrateson the DSP-based virtual implementation of ANN.A parallel processing system composed ofTMS320C30 has been designed and configured,which ean provide a peak speed as high as100 MFLOPS and a parallel efficiency of 90%(during the forward phase of BP),and can heused for sonar signal processing.Scalability of the system is also studied.
基金supported by the Research Fund of National Key Laboratory of Computer Architecture under Grant No.CARCH201501the Open Project Program of the State Key Laboratory of Mathematical Engineering and Advanced Computing under Grant No.2016A09
文摘In the era of Big Data, typical architecture of distributed real-time stream processing systems is the combination of Flume, Kafka, and Storm. As a kind of distributed message system, Kafka has the characteristics of horizontal scalability and high throughput, which is manly deployed in many areas in order to address the problem of speed mismatch between message producers and consumers. When using Kafka, we need to quickly receive data sent by producers. In addition, we need to send data to consumers quickly. Therefore, the performance of Kafka is of critical importance to the performance of the whole stream processing system. In this paper, we propose the improved design of real-time stream processing systems, and focus on improving the Kafka's data loading process.We use Kafka cat to transfer data from the source to Kafka topic directly, which can reduce the network transmission. We also utilize the memory file system to accelerate the process of data loading, which can address the bottleneck and performance problems caused by disk I/O. Extensive experiments are conducted to evaluate the performance, which show the superiority of our improved design.
基金Sponsored by the Natural Science Fundation of Jiangxi Province(Grant No.20114BAB211026 and No.20122BA-B201028)Open Science Fund from Key Laboratory of Radioactive Geology and Exploration Technology Fundamental Science for National Defense,East China Institute of Technology(Grant No.2010RGET11)
文摘Research for detecting or obtaining radionuclide by gamma energy spectrum data acquisition and process system is one of the key issues about intelligent measurement of gamma-ray spectrum. For this reason, a software and hardware implementation schematic design based on ARM ( Advanced RISC Machines) + DSP ( Digital Signal Processor) architecture for gamma energy spectrum data acquisition and processing system is proposed. The paper discusses in detail some key technologies such as communication interface design between microcontroller ARM and digital signal processor DSP,distribution scheduling under multi-task in the ARM-Linux,DSP handling procedures for multi-channel A / D high-speed sample. At the same time,because the traditional Gaussian fitting to determine the boundary of peak is not ideal,it puts forward a weighting factor of Gaussian function least squares fitting realize boundary determined. Finally gamma-spectrum data from sodium iodide NaI( TI) scintillation detector is tested and processed in the new system. The results show that gamma energy spectrum data acquisition and process system is perfect functionality, stable and convergence in unimodal. Compared with data from conventional energy spectrometers,the system can keep better energy resolution in a wide range of pulse pass rate.
文摘An air classifier is used in the recycling process of covered electric wire in the recycling factories, in which the covered electric wires are crushed, sieved, and classified by the air classifier, which generates wastes. In these factories, operators manually adjust the air flow rate while checking the wastes discharged from the separator outlet. However, the adjustments are basically done by trial and error, and it is difficult to do them appropriately. In this study, we tried to develop the image processing system that calculates the ratio of copper (Cu) product and polyvinyl chloride (PVC) in the wastes as a substitute for the operator’s eyes. Six colors of PVC (white, gray, green, blue, black, and red) were used in the present work. An image consists of foreground and background. An image’s regions of interest are objects (Cu particles) in its foreground. However, the particles having a color similar to the background color are buried in the background. Using the difference of two color backgrounds, we separated particles and background without dependent of background. The Otsu’ thresholding was employed to choose the threshold to maximize the degree of separation of the particles and background. The ratio of Cu to PVC pixels from mixed image was calculated by linear discriminant analysis. The error of PVC pixels resulted in zero, whereas the error of Cu pixels arose to 4.19%. Comparing the numbers of Cu and PVC pixels within the contour, the minority of the object were corrected to the majority of the object. The error of Cu pixels discriminated as PVC incorrectly became zero percent through this correction.
基金the High Technology Research and Development Programme of china.
文摘Sonar image processing system is an important intelligent system of Autonomous Un-derwater Vehicle.Based on TMS320C30 high speed DSP,it is used to realize sonar imagecompression and underwater object detections including obstacle recognition in real time.Inthis paper,the software and hardware designs of this system are introduced and the experi-mental results are given.
文摘A robot flexible processing system of shipbuilding profile steel was developed. The system consists of computer integrated control and robot. An off line programming robot was used for marking and cutting of shipbuilding profile steel. In the system the deformation and position error of profile steel can be detected by precise sensors, and figure position coordinate error resulted from profile steel deformation can be compensated by modifying traveling track of robotic arm online. The practical operation results show that the system performance can meet the needs of profile steel processing.
文摘Based on the analysis results of the dust size distribution of flue gas from Baosteel's short-flow (BSSF) slag processing system and the mechanism of the wet scrubber,a wet scrubber system was designed and installed in the No. 1 BSSF slag processing system at Baosteel. The results show that the dust removal efficiency of the previous system that had conventional water nozzles was only 69% with a liquid-gas ratio of 0.79 L/m^3 ,while the dust removal efficiency reached 94% when three sets of high-efficiency dual phase spray guns were installed inside both the flue and the chimney. For the latter system,the liquid-gas ratio was 0. 84 L/m^3 ,and the dust concentration in the cleaned emissions reduced to less than 40 mg/m^3.
文摘This paper analyzes the current difficulties encountered in on-line inspection systems of strip surface quality, specifically relating to problems with real-time processing of huge amounts of data. To address this need, this paper describes an FPGA-based high-speed image processing module with both hardware and software aspects. Improving these two aspects together will help the system achieve real-time processing of massive image data, and simplifies the architecture of the strip surface quality on-line inspection system.
文摘A distributed processing system (DPS) contains many autonomous nodes, which contribute their own computing power. DPS is considered a unified logical structure, operating in a distributed manner;the processing tasks are divided into fragments and assigned to various nodes for processing. That type of operation requires and involves a great deal of communication. We propose to use the decentralized approach, based on a distributed hash table, to reduce the communication overhead and remove the server unit, thus avoiding having a single point of failure in the system. This paper proposes a mathematical model and algorithms that are implemented in a dedicated experimental system. Using the decentralized approach, this study demonstrates the efficient operation of a decentralized system which results in a reduced energy emission.
基金Supported by the National Natural Science Foundation of China (No.60472046)
文摘In this paper, we present an optimized design method for high-speed embedded image processing system using 32 bit floating-point Digital Signal Processor (DSP) and Complex Programmable Logic Device (CPLD). The DSP acts as the main processor of the system: executes digital image processing algorithms and operates other devices such as image sensor and CPLD. The CPLD is used to acquire images and achieve complex logic control of the whole system. Some key technologies are introduced to enhance the performance of our system. In particular, the use of DSP/BIOS tool to develop DSP applications makes our program run much more efficiently. As a result, this system can provide an excellent computing platform not only for executing complex image processing algorithms, but also for other digital signal processing or multi-channel data collection by choosing different sensors or Analog-to-Digital (A/D) converters.
基金This work was supported by the National Natural Science Foundation of China(Nos.82172372 and 21904045).
文摘DNA-based nanostructure allows the construction of molecular devices useful in biological computing and information processing.Herein,an addressable and editable DNA information processing system established on a fluorescence intensity signal detection platform to save and encrypt information is proposed.The system operates by encoding information into distinct and changeable units of the trigger strands decoding by fluorescence intensity signal detection.Through toehold-mediated strand displacement reactions,the trigger strand can be precisely added to and removed from the memorizer and reporter to implement the function of editing,encrypting,and decrypting.Our strategy is simple to implement,requiring only two mixing steps at room temperature for each operation and fluorescence intensity signal detection to read the data.And the system can realize accurate retrieval of specific individual information,eliminating all unnecessary redundant readouts.Because of its point-to-point accurate readout and programmability,the system is expected to become a powerful tool for the future development of information storage and sensing of biological molecules.
基金financially supported by the National Key Research and Development Program of China(Grant No.2022YFC3004802)the National Natural Science Foundation of China(Grant Nos.52171287,52325107)+3 种基金High Tech Ship Research Project of Ministry of Industry and Information Technology(Grant Nos.2023GXB01-05-004-03,GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province(Grant No.ZR2022JQ25)the Taishan Scholars Project(Grant No.tsqn201909063)the sub project of the major special project of CNOOC Development Technology,“Research on the Integrated Technology of Intrinsic Safety of Offshore Oil Facilities”(Phase I),“Research on Dynamic Quantitative Analysis and Control Technology of Risks in Offshore Production Equipment”(Grant No.HFKJ-2D2X-AQ-2021-03)。
文摘Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R161)PrincessNourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the|Deanship of Scientific Research at Umm Al-Qura University|for supporting this work by Grant Code:(22UQU4310373DSR33).
文摘The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart devices.It plays an important role in industrial models such as speech understanding,emotion detection,home automation,and so on.If an image needs to be captioned,then the objects in that image,its actions and connections,and any silent feature that remains under-projected or missing from the images should be identified.The aim of the image captioning process is to generate a caption for image.In next step,the image should be provided with one of the most significant and detailed descriptions that is syntactically as well as semantically correct.In this scenario,computer vision model is used to identify the objects and NLP approaches are followed to describe the image.The current study develops aNatural Language Processing with Optimal Deep Learning Enabled Intelligent Image Captioning System(NLPODL-IICS).The aim of the presented NLPODL-IICS model is to produce a proper description for input image.To attain this,the proposed NLPODL-IICS follows two stages such as encoding and decoding processes.Initially,at the encoding side,the proposed NLPODL-IICS model makes use of Hunger Games Search(HGS)with Neural Search Architecture Network(NASNet)model.This model represents the input data appropriately by inserting it into a predefined length vector.Besides,during decoding phase,Chimp Optimization Algorithm(COA)with deeper Long Short Term Memory(LSTM)approach is followed to concatenate the description sentences 4436 CMC,2023,vol.74,no.2 produced by the method.The application of HGS and COA algorithms helps in accomplishing proper parameter tuning for NASNet and LSTM models respectively.The proposed NLPODL-IICS model was experimentally validated with the help of two benchmark datasets.Awidespread comparative analysis confirmed the superior performance of NLPODL-IICS model over other models.
基金supported by the National Natural Science Foundation of China(NSFC,no.61701243,71771125)the Major Project of Natural Science Foundation of Jiangsu Education Department(no.19KJA180002).
文摘Depression has become one of the most common mental illnesses in the world.For better prediction and diagnosis,methods of automatic depression recognition based on speech signal are constantly proposed and updated,with a transition from the early traditional methods based on hand‐crafted features to the application of architectures of deep learning.This paper systematically and precisely outlines the most prominent and up‐to‐date research of automatic depression recognition by intelligent speech signal processing so far.Furthermore,methods for acoustic feature extraction,algorithms for classification and regression,as well as end to end deep models are investigated and analysed.Finally,general trends are summarised and key unresolved issues are identified to be considered in future studies of automatic speech depression recognition.
基金This work was supported by Science and Technology Project of State Grid Corporation“Research on Key Technologies of Power Artificial Intelligence Open Platform”(5700-202155260A-0-0-00).
文摘The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .