Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken a...Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.展开更多
An integrated monitoring system for running parameters of key mining equipmenton the basis of condition monitoring technology and modern communication networktechnology was developed.The system consists of a client co...An integrated monitoring system for running parameters of key mining equipmenton the basis of condition monitoring technology and modern communication networktechnology was developed.The system consists of a client computer with functions ofsignal acquisition and processing, and a host computer in the central control room.Thesignal acquisition module of the client computer can collect the running parameters fromvarious monitoring terminals in real-time.The DSP high-speed data processing system ofthe main control module can quickly achieve the numerical calculation for the collectedsignal.The signal modulation and signal demodulation are completed by the frequencyshift keying circuit and phase-locked loop frequency circuit, respectively.Finally, the signalis sent to the host computer for logic estimation and diagnostic analysis using the networkcommunication technology, which is helpful for technicians and managers to control therunning state of equipment.展开更多
Millimeter range signals have been widely used in biology and medicine over the 20-30 years of the last century.At this time in Ukraine have been developed and implemented treatment technologies,the main ones are mill...Millimeter range signals have been widely used in biology and medicine over the 20-30 years of the last century.At this time in Ukraine have been developed and implemented treatment technologies,the main ones are millimeter therapy(MMT),microwave resonance therapy(MRT),information-wave therapy(IWT).The features of this technologies are the use of signals in the frequency band 40-78 GHz with extremely low signal levels-10-9-10-11 W/cm2,the parameters are immanent to own communication signals of the human body.The author of the article attempts to conduct a combined analysis of hardware and software of these treatment technologies with mm-band signals.Thus the specialized equipment used for the treatment,technologies and the statistical results of its use for various diseases are considered.The problems of metrological support and measuring the weak signals of the mm range are proposed to solve by creating highly sensitive radiometric systems.The results of measurements of microwave signals of natural objects that can be used for physiotherapy and physical bodies that are in contact with or in human environment are submitted.Promising areas of the using the highly sensitive radiometric measurement equipment for research in biology and medicine are presented.展开更多
The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train ...The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train operation, numerous text-based onboard logs are recorded by on-board computers. Machine learning methods can help technicians make a correct judgment of fault types using the on-board log reasonably. Therefore, a fault classification model of on-board equipment based on attention capsule networks is proposed. This paper presents an empirical exploration of the application of a capsule network with dynamic routing in fault classification. A capsule network can encode the internal spatial part-whole relationship between various entities to identify the fault types. As the importance of each word in the on-board log and the dependencies between them have a significant impact on fault classification, an attention mechanism is incorporated into the capsule network to distill important information. Considering the imbalanced distribution of normal data and fault data in the on-board log, the focal loss function is introduced into the model to adjust the imbalanced data. The experiments are conducted on the on-board log of a railway bureau and compared with other baseline models. The experimental results demonstrate that our model outperforms the compared baseline methods, proving the superiority and competitiveness of our model.展开更多
With the development of high-speed railway and heavy-haul rail transport in China,a large number of new types of electric locomotives and electric multiple units have been put into operation,improving the efficiency a...With the development of high-speed railway and heavy-haul rail transport in China,a large number of new types of electric locomotives and electric multiple units have been put into operation,improving the efficiency and equipment quality of railway transportation.However,harmonics emitted from the traction system and locomotives often interfere with the railway signalling equipment,which can lead to critical malfunction of the equipment.Based on field test data,this paper analyses the interference coupling mechanism and magnitude of traction harmonics to the signalling equipment using a three-element method of interference.It examines the three essential elements of electromagnetic interference,studies harmonic mitigation measures and proposes to solve the problem of inteference with signalling equipment by installing a passive high-pass filter in the coupling path.After comparing the effects of several types of filters using simulation tests,this paper verified the validity of the method and concluded that a second-order passive filter is the optimal solution for harmonic interference mitigation.展开更多
基金Gansu Province Higher Education Innovation Fund Project(No.2020B-104)“Innovation Star”Project for Outstanding Postgraduates of Gansu Province(No.2021CXZX-606)。
文摘Rapid and precise location of the faults of on-board equipment of train control system is a significant factor to ensure reliable train operation.Text data of the fault tracking table of on-board equipment are taken as samples,and an on-board equipment fault diagnosis model is designed based on the combination of convolutional neural network(CNN)and particle swarm optimization-support vector machines(PSO-SVM).Due to the characteristics of high dimensionality and sparseness of fault text data,CNN is used to achieve feature extraction.In order to decrease the influence of the imbalance of the fault sample data category on the classification accuracy,the PSO-SVM algorithm is introduced.The fully connected classification part of CNN is replaced by PSO-SVM,the extracted features are classified precisely,and the intelligent diagnosis of on-board equipment fault is implemented.According to the test analysis of the fault text data of on-board equipment recorded by a railway bureau and comparison with other models,the experimental results indicate that this model can obviously upgrade the evaluation indexes and can be used as an effective model for fault diagnosis for on-board equipment.
基金Supported by the National Hi-tech Research and Development Program of China(2007AA04Z415)the Hunan Province and Xiangtan City Natural Science Joint Foundation(09JJ8005)the Torch Program Project of Hunan Province(2008SH044)
文摘An integrated monitoring system for running parameters of key mining equipmenton the basis of condition monitoring technology and modern communication networktechnology was developed.The system consists of a client computer with functions ofsignal acquisition and processing, and a host computer in the central control room.Thesignal acquisition module of the client computer can collect the running parameters fromvarious monitoring terminals in real-time.The DSP high-speed data processing system ofthe main control module can quickly achieve the numerical calculation for the collectedsignal.The signal modulation and signal demodulation are completed by the frequencyshift keying circuit and phase-locked loop frequency circuit, respectively.Finally, the signalis sent to the host computer for logic estimation and diagnostic analysis using the networkcommunication technology, which is helpful for technicians and managers to control therunning state of equipment.
文摘Millimeter range signals have been widely used in biology and medicine over the 20-30 years of the last century.At this time in Ukraine have been developed and implemented treatment technologies,the main ones are millimeter therapy(MMT),microwave resonance therapy(MRT),information-wave therapy(IWT).The features of this technologies are the use of signals in the frequency band 40-78 GHz with extremely low signal levels-10-9-10-11 W/cm2,the parameters are immanent to own communication signals of the human body.The author of the article attempts to conduct a combined analysis of hardware and software of these treatment technologies with mm-band signals.Thus the specialized equipment used for the treatment,technologies and the statistical results of its use for various diseases are considered.The problems of metrological support and measuring the weak signals of the mm range are proposed to solve by creating highly sensitive radiometric systems.The results of measurements of microwave signals of natural objects that can be used for physiotherapy and physical bodies that are in contact with or in human environment are submitted.Promising areas of the using the highly sensitive radiometric measurement equipment for research in biology and medicine are presented.
基金supported by National Natural Science Foundation of China(No.61763025)Gansu Science and Technology Program Project(No.18JR3RA104)+1 种基金Industrial support program for colleges and universities in Gansu Province(No.2020C-19)Lanzhou Science and Technology Project(No.2019-4-49)。
文摘The conventional troubleshooting methods for high-speed railway on-board equipment, with over-reliance on personnel experience, is characterized by one-sidedness and low efficiency. In the process of high-speed train operation, numerous text-based onboard logs are recorded by on-board computers. Machine learning methods can help technicians make a correct judgment of fault types using the on-board log reasonably. Therefore, a fault classification model of on-board equipment based on attention capsule networks is proposed. This paper presents an empirical exploration of the application of a capsule network with dynamic routing in fault classification. A capsule network can encode the internal spatial part-whole relationship between various entities to identify the fault types. As the importance of each word in the on-board log and the dependencies between them have a significant impact on fault classification, an attention mechanism is incorporated into the capsule network to distill important information. Considering the imbalanced distribution of normal data and fault data in the on-board log, the focal loss function is introduced into the model to adjust the imbalanced data. The experiments are conducted on the on-board log of a railway bureau and compared with other baseline models. The experimental results demonstrate that our model outperforms the compared baseline methods, proving the superiority and competitiveness of our model.
文摘With the development of high-speed railway and heavy-haul rail transport in China,a large number of new types of electric locomotives and electric multiple units have been put into operation,improving the efficiency and equipment quality of railway transportation.However,harmonics emitted from the traction system and locomotives often interfere with the railway signalling equipment,which can lead to critical malfunction of the equipment.Based on field test data,this paper analyses the interference coupling mechanism and magnitude of traction harmonics to the signalling equipment using a three-element method of interference.It examines the three essential elements of electromagnetic interference,studies harmonic mitigation measures and proposes to solve the problem of inteference with signalling equipment by installing a passive high-pass filter in the coupling path.After comparing the effects of several types of filters using simulation tests,this paper verified the validity of the method and concluded that a second-order passive filter is the optimal solution for harmonic interference mitigation.
