The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the...The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the equipment.In engineering scenarios,co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify,and existing intelligent methods require more hardware conditions and are exclusively time-consuming.Therefore,Lightweight-convolutional neural networks(LW-CNN)algorithm is proposed in this paper to achieve real-time fault diagnosis.The critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation method.Based on LW-CNN and data augmentation,the real-time intelligent diagnosis of co-frequency is realized.Moreover,a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault diagnosis.It is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.展开更多
Intelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health management.To deal with co-frequency vibration faults,a type of typical fault in rotating machinery,this pa...Intelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health management.To deal with co-frequency vibration faults,a type of typical fault in rotating machinery,this paper proposes a fault diagnosis method based on the stacked autoencoder(SAE)and ensembled ResNet-SVM.Furthermore,the time-and frequency-domain features of several co-frequency vibration faults are summarized based on the mechanism analysis and calculated using actual vibration data.To realize and validate the high-precision diagnosis method of rotating equipment with co-frequency faults proposed in this study,the following three criteria are required:First,to improve the effectiveness and robustness of the ensembled model and the sliding window using data augmentation,adding noise,autoencoder(AE)and SAE methods are analyzed in terms of principle and practical effects.Second,ResNet is used as the feature extractor for the ensembled ResNet-SVM model.Feature extraction is carried out twice,and the extracted co-frequency fault features are more comprehensive.Finally,the data augmentation method and ensemble ResNet-SVM are combined for fault diagnosis and compared with other methods.The experimental results show that the accuracy of the proposed method can exceed 99.9%.展开更多
In recent years,as giant satellite constellations grow rapidly worldwide,the co-existence between constellations has been widely concerned.In this paper,we overview the co-frequency interference(CFI)among the giant no...In recent years,as giant satellite constellations grow rapidly worldwide,the co-existence between constellations has been widely concerned.In this paper,we overview the co-frequency interference(CFI)among the giant non-geostationary orbit(NGSO)constellations.Specifically,we first summarize the CFI scenario and evaluation index among different NGSO constellations.Based on statistics about NGSO constellation plans,we analyse the challenges in mitigation and analysis of CFI.Next,the CFI calculation methods and research progress are systematically sorted out from the aspects of interference risk analysis framework,numerical calculation and link construction.Then,the feasibility of interference mitigation technologies based on space,frequency domain isolation,power control,and interference alignment mitigation in the NGSO mega-constellation CFI scenario are further sorted out.Finally,we present promising directions for future research in CFI analysis and CFI avoidance.展开更多
By employing a radio frequency(RF) feedback chain, the self-interference can be canceled efficiently in co-time co-frequency full duplex(CCFD). However, the evitable signal crosstalk which is caused by the imperfect R...By employing a radio frequency(RF) feedback chain, the self-interference can be canceled efficiently in co-time co-frequency full duplex(CCFD). However, the evitable signal crosstalk which is caused by the imperfect RF feedback chain isolation usually damages the self-interference cancelation(SIC) performance. To deal with this problem, firstly, we analyze the impact of RF feedback chain isolation on SIC performance. Then a digital preprocessing scheme with RF feedback chain is proposed in the multiple-antenna CCFD architecture. Using both analytical and experimental methods, we find that the proposed scheme achieves a better performance on SIC.展开更多
The performance of three wireless local-area network(WLAN) media access control(MAC) protocols is investigated and compared in the context of simulcast radioover-fiber-based distributed antenna systems(RoF-DASs) where...The performance of three wireless local-area network(WLAN) media access control(MAC) protocols is investigated and compared in the context of simulcast radioover-fiber-based distributed antenna systems(RoF-DASs) where multiple remote antenna units(RAUs) are connected to one access point(AP) with different-length fiber links.The three WLAN MAC protocols under investigation are distributed coordination function(DCF) in basic access mode,DCF in request/clear to send(RTS/CTS) exchange mode,and point coordination function(PCF).In the analysis,the inter-RAU hidden nodes problems and fiber-length difference effect are both taken into account.Results show that adaptive PCF mechanism has better throughput performances than the other two DCF modes,especially when the inserted fiber length is short.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51875031,52242507)Beijing Municipal Natural Science Foundation of China(Grant No.3212010)Beijing Municipal Youth Backbone Personal Project of China(Grant No.2017000020124 G018).
文摘The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the equipment.In engineering scenarios,co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify,and existing intelligent methods require more hardware conditions and are exclusively time-consuming.Therefore,Lightweight-convolutional neural networks(LW-CNN)algorithm is proposed in this paper to achieve real-time fault diagnosis.The critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation method.Based on LW-CNN and data augmentation,the real-time intelligent diagnosis of co-frequency is realized.Moreover,a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault diagnosis.It is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.
基金Supported by National Natural Science Foundation of China (Grant No.51875031)Beijing Municipal Natural Science Foundation (Grant No.3212010)。
文摘Intelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health management.To deal with co-frequency vibration faults,a type of typical fault in rotating machinery,this paper proposes a fault diagnosis method based on the stacked autoencoder(SAE)and ensembled ResNet-SVM.Furthermore,the time-and frequency-domain features of several co-frequency vibration faults are summarized based on the mechanism analysis and calculated using actual vibration data.To realize and validate the high-precision diagnosis method of rotating equipment with co-frequency faults proposed in this study,the following three criteria are required:First,to improve the effectiveness and robustness of the ensembled model and the sliding window using data augmentation,adding noise,autoencoder(AE)and SAE methods are analyzed in terms of principle and practical effects.Second,ResNet is used as the feature extractor for the ensembled ResNet-SVM model.Feature extraction is carried out twice,and the extracted co-frequency fault features are more comprehensive.Finally,the data augmentation method and ensemble ResNet-SVM are combined for fault diagnosis and compared with other methods.The experimental results show that the accuracy of the proposed method can exceed 99.9%.
文摘In recent years,as giant satellite constellations grow rapidly worldwide,the co-existence between constellations has been widely concerned.In this paper,we overview the co-frequency interference(CFI)among the giant non-geostationary orbit(NGSO)constellations.Specifically,we first summarize the CFI scenario and evaluation index among different NGSO constellations.Based on statistics about NGSO constellation plans,we analyse the challenges in mitigation and analysis of CFI.Next,the CFI calculation methods and research progress are systematically sorted out from the aspects of interference risk analysis framework,numerical calculation and link construction.Then,the feasibility of interference mitigation technologies based on space,frequency domain isolation,power control,and interference alignment mitigation in the NGSO mega-constellation CFI scenario are further sorted out.Finally,we present promising directions for future research in CFI analysis and CFI avoidance.
基金supported by the National Natural Science Foundation of China under Grants No.61601064,No.61471108,No.61601065,and No.41404102supported by the Sichuan Youth Science and Technology Foundation under Grant No.2016JQ0012
文摘By employing a radio frequency(RF) feedback chain, the self-interference can be canceled efficiently in co-time co-frequency full duplex(CCFD). However, the evitable signal crosstalk which is caused by the imperfect RF feedback chain isolation usually damages the self-interference cancelation(SIC) performance. To deal with this problem, firstly, we analyze the impact of RF feedback chain isolation on SIC performance. Then a digital preprocessing scheme with RF feedback chain is proposed in the multiple-antenna CCFD architecture. Using both analytical and experimental methods, we find that the proposed scheme achieves a better performance on SIC.
基金supported in part by National 973 Program(2012CB315705)NSFC Program(61302086,61271042,61107058, 61302016,and 61335002)+2 种基金Specialized Research Fund for the Doctoral Program of Higher Education(20130005120007)Program for New Century Excellent Talents in University(NCET-13-0682)Fundamental Research Funds for the Central Universities
文摘The performance of three wireless local-area network(WLAN) media access control(MAC) protocols is investigated and compared in the context of simulcast radioover-fiber-based distributed antenna systems(RoF-DASs) where multiple remote antenna units(RAUs) are connected to one access point(AP) with different-length fiber links.The three WLAN MAC protocols under investigation are distributed coordination function(DCF) in basic access mode,DCF in request/clear to send(RTS/CTS) exchange mode,and point coordination function(PCF).In the analysis,the inter-RAU hidden nodes problems and fiber-length difference effect are both taken into account.Results show that adaptive PCF mechanism has better throughput performances than the other two DCF modes,especially when the inserted fiber length is short.
