When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ...When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.展开更多
Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this iss...Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.展开更多
The development of 3D geological models involves the integration of large amounts of geological data,as well as additional accessible proprietary lithological, structural,geochemical,geophysical,and borehole data.Luan...The development of 3D geological models involves the integration of large amounts of geological data,as well as additional accessible proprietary lithological, structural,geochemical,geophysical,and borehole data.Luanchuan,the case study area,southwestern Henan Province,is an important molybdenum-tungsten -lead-zinc polymetallic belt in China.展开更多
Shockwaves from fuel-air explosive(FAE)cloud explosions may cause significant casualties.The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves.In this paper,a finite elemen...Shockwaves from fuel-air explosive(FAE)cloud explosions may cause significant casualties.The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves.In this paper,a finite element model of multi-sources FAE explosion is established to simulate the process of multiple shockwaves propagation and interaction.The model is verified with the experimental data of a fourfoldsource FAE explosion,with the total fuel mass of 340 kg.Simulation results show that the overpressure fields of multi-sources FAE explosions are different from that of the single-source.In the case of multisources,the overpressure fields are influenced significantly by source scattering distance and source number.Subsequently,damage ranges of overpressure under three different levels are calculated.Within a suitable source scattering distance,the damage range of multi-sources situation is greater than that of the single-source,under the same amount of total fuel mass.This research provides a basis for personnel shockwave protection from multi-sources FAE explosion.展开更多
The planetary reducer is a common type of transmission mechanism,which can provide high transmission accuracy and has been widely used,and it is usually required with high reliability of transmission characteristics i...The planetary reducer is a common type of transmission mechanism,which can provide high transmission accuracy and has been widely used,and it is usually required with high reliability of transmission characteristics in practice.During the manufacturing and usage stages of planetary reducers,uncertainties are ubiquitous and wear is inevitable,which affect the transmission characteristics and the reliability of planetary reducers.In this paper,belief reliability modeling and analysis considering multi-uncertainties and wear are proposed for planetary reducers.Firstly,based on the functional principle and the influence of wear,the performance margin degradation model is established using the hysteresis error as the key performance parameter,where the degradation is mainly caused by the accumulated wear.After that,multi-source uncertainties are analyzed and quantified separately,including manufacturing errors,uncertainties in operational and environmental conditions,and uncertainties in performance thresholds.Finally,the belief reliability model is established based on the performance margin degradation model.A case study of a planetary reducer is applied and the reliability sensitivity analysis is implemented to show the practicability of the proposed method.The results show that the proposed method can provide some suggestions to the design and manufacturing phases of the planetary reducer.展开更多
The components of urban surface cover are diversified,and component temperature has greater physical significance and application values in the studies on urban thermal environment.Although the multi-angle retrieval a...The components of urban surface cover are diversified,and component temperature has greater physical significance and application values in the studies on urban thermal environment.Although the multi-angle retrieval algorithm of component temperature has been matured gradually,its application in the studies on urban thermal environment is restricted due to the difficulty in acquiring urban-scale multi-angle thermal infrared data.Therefore,based on the existing multi-source multi-band remote sensing data,access to appropriate urban-scale component temperature is an urgent issue to be solved in current studies on urban thermal infrared remote sensing.Then,a retrieval algorithm of urban component temperature by multi-source multi-band remote sensing data on the basis of MODIS and Landsat TM images was proposed with expectations achieved in this work,which was finally validated by the experiment on urban images of Changsha,China.The results show that：1） Mean temperatures of impervious surface components and vegetation components are the maximum and minimum,respectively,which are in accordance with the distribution laws of actual surface temperature; 2） High-accuracy retrieval results are obtained in vegetation component temperature.Moreover,through a contrast between retrieval results and measured data,it is found that the retrieval temperature of impervious surface component has the maximum deviation from measured temperature and its deviation is greater than 1 ℃,while the deviation in vegetation component temperature is relatively low at 0.5 ℃.展开更多
日志主要记录软硬件的运行信息,通过查看系统日志,可以找到系统出现的问题及原因,确保系统的稳定性和正常运行。日志解析的目的是将半结构化的原始日志解析为可阅读的日志模板,现有解析方法往往只注重于对原始日志的解析,而忽略了后期...日志主要记录软硬件的运行信息,通过查看系统日志,可以找到系统出现的问题及原因,确保系统的稳定性和正常运行。日志解析的目的是将半结构化的原始日志解析为可阅读的日志模板,现有解析方法往往只注重于对原始日志的解析,而忽略了后期模板处理,导致结果的精度不能进一步提高。自此,提出了一种日志解析方法FMLogs(logs parsing based on frequency and MinHash algorithm)。该方法通过设计正则表达式和调节阈值参数以获得最佳性能,同时采用了字符级频率统计和MinHash方法对长度相同和不同的日志模板进行合并。FMLogs在七个真实数据集上进行了广泛的实验,取得了0.924的平均解析准确率和0.983的F 1-Score。实验结果表明,FMLogs是一种有效的日志解析方法,在解析日志的同时具有较高的准确性和效率,并能保证性能的稳定。展开更多
文摘When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.
基金supported by the National Natural Science Foundation of China(61903305,62073267)the Fundamental Research Funds for the Central Universities(HXGJXM202214).
文摘Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.
文摘The development of 3D geological models involves the integration of large amounts of geological data,as well as additional accessible proprietary lithological, structural,geochemical,geophysical,and borehole data.Luanchuan,the case study area,southwestern Henan Province,is an important molybdenum-tungsten -lead-zinc polymetallic belt in China.
基金The authors would like to acknowledge the China Postdoctoral Science Foundation(Grant No.2019M660488)to provide fund for this work.
文摘Shockwaves from fuel-air explosive(FAE)cloud explosions may cause significant casualties.The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves.In this paper,a finite element model of multi-sources FAE explosion is established to simulate the process of multiple shockwaves propagation and interaction.The model is verified with the experimental data of a fourfoldsource FAE explosion,with the total fuel mass of 340 kg.Simulation results show that the overpressure fields of multi-sources FAE explosions are different from that of the single-source.In the case of multisources,the overpressure fields are influenced significantly by source scattering distance and source number.Subsequently,damage ranges of overpressure under three different levels are calculated.Within a suitable source scattering distance,the damage range of multi-sources situation is greater than that of the single-source,under the same amount of total fuel mass.This research provides a basis for personnel shockwave protection from multi-sources FAE explosion.
基金This work was supported by the National Natural Science Foundation of China(51775020,51875019)the Fundamental Research Funds for the Central Universities(YWF-20-BJ-J-515).
文摘The planetary reducer is a common type of transmission mechanism,which can provide high transmission accuracy and has been widely used,and it is usually required with high reliability of transmission characteristics in practice.During the manufacturing and usage stages of planetary reducers,uncertainties are ubiquitous and wear is inevitable,which affect the transmission characteristics and the reliability of planetary reducers.In this paper,belief reliability modeling and analysis considering multi-uncertainties and wear are proposed for planetary reducers.Firstly,based on the functional principle and the influence of wear,the performance margin degradation model is established using the hysteresis error as the key performance parameter,where the degradation is mainly caused by the accumulated wear.After that,multi-source uncertainties are analyzed and quantified separately,including manufacturing errors,uncertainties in operational and environmental conditions,and uncertainties in performance thresholds.Finally,the belief reliability model is established based on the performance margin degradation model.A case study of a planetary reducer is applied and the reliability sensitivity analysis is implemented to show the practicability of the proposed method.The results show that the proposed method can provide some suggestions to the design and manufacturing phases of the planetary reducer.
基金Projects(41171326,40771198)supported by the National Natural Science Foundation of ChinaProject(08JJ6023)supported by the Natural Science Foundation of Hunan Province,China
文摘The components of urban surface cover are diversified,and component temperature has greater physical significance and application values in the studies on urban thermal environment.Although the multi-angle retrieval algorithm of component temperature has been matured gradually,its application in the studies on urban thermal environment is restricted due to the difficulty in acquiring urban-scale multi-angle thermal infrared data.Therefore,based on the existing multi-source multi-band remote sensing data,access to appropriate urban-scale component temperature is an urgent issue to be solved in current studies on urban thermal infrared remote sensing.Then,a retrieval algorithm of urban component temperature by multi-source multi-band remote sensing data on the basis of MODIS and Landsat TM images was proposed with expectations achieved in this work,which was finally validated by the experiment on urban images of Changsha,China.The results show that：1） Mean temperatures of impervious surface components and vegetation components are the maximum and minimum,respectively,which are in accordance with the distribution laws of actual surface temperature; 2） High-accuracy retrieval results are obtained in vegetation component temperature.Moreover,through a contrast between retrieval results and measured data,it is found that the retrieval temperature of impervious surface component has the maximum deviation from measured temperature and its deviation is greater than 1 ℃,while the deviation in vegetation component temperature is relatively low at 0.5 ℃.
文摘日志主要记录软硬件的运行信息,通过查看系统日志,可以找到系统出现的问题及原因,确保系统的稳定性和正常运行。日志解析的目的是将半结构化的原始日志解析为可阅读的日志模板,现有解析方法往往只注重于对原始日志的解析,而忽略了后期模板处理,导致结果的精度不能进一步提高。自此,提出了一种日志解析方法FMLogs(logs parsing based on frequency and MinHash algorithm)。该方法通过设计正则表达式和调节阈值参数以获得最佳性能,同时采用了字符级频率统计和MinHash方法对长度相同和不同的日志模板进行合并。FMLogs在七个真实数据集上进行了广泛的实验,取得了0.924的平均解析准确率和0.983的F 1-Score。实验结果表明,FMLogs是一种有效的日志解析方法,在解析日志的同时具有较高的准确性和效率,并能保证性能的稳定。
