A new concept is suggested on tectonomagnetic research about the noise in simultaneous geomagnetic difference data caused by the effect of Sq local-time variation, together with the method of theoretical calculation. ...A new concept is suggested on tectonomagnetic research about the noise in simultaneous geomagnetic difference data caused by the effect of Sq local-time variation, together with the method of theoretical calculation. The level of the noise and its contribution to the total noises of the differences data are analyzed. The result indicates that the noise increases linearly with the increase of the distance between the two stations in the range of 40° longitude-difference, and its increasing rate is about 0.4 nT/（°）at latitude 40°N. The example calculated at a pair of sites with longitude-difference 0.357°, shows that the noise is about one fifth of the total noises of the difference data on geomagnetic quiet-day.展开更多
In this study,we use observations from the Sounding of the Atmosphere using Broadband Emission Radiometry(SABER)instrument onboard the Thermosphere–Ionosphere–Mesosphere Energetics and Dynamics(TIMED)satellite to de...In this study,we use observations from the Sounding of the Atmosphere using Broadband Emission Radiometry(SABER)instrument onboard the Thermosphere–Ionosphere–Mesosphere Energetics and Dynamics(TIMED)satellite to develop and apply a new local-time binning method to investigate the long-term evolution of mesospheric water vapor at high latitudes.The proposed method accounts for the gradual local-time drift of the SABER orbit by aligning seasonal observation windows and selecting samples observed at similar local times.This approach minimizes tidal aliasing and ensures more consistent sampling,yielding more reliable estimates of long-term water vapor trends at high latitudes.The results show that drying signals primarily appear in the polar regions.However,in the southern hemisphere,a drying trend is observed only in autumn,whereas winter and summer mainly show moistening trends.In contrast,the northern hemisphere exhibits drying signals in the polar regions during all seasons,showing a clear seasonal asymmetry.Additionally,the water vapor trend in the northern hemisphere is particularly pronounced in February(late winter),with moistening reaching up to+2.0 ppmv.The winter in the southern hemisphere(July–August)also shows moistening,but the trend is still weaker than in the northern hemisphere.These differences highlight the strong moistening trend in the northern hemisphere during winter and underscore the significant asymmetry in seasonal water vapor changes between the two hemispheres.These findings emphasize the limitations of water vapor trend estimates across different seasons and latitudes.Moreover,they provide new insights into the spatiotemporal variability associated with tidal structures,underscoring the importance of optimizing local-time sampling strategies for reliable long-term trend detection.展开更多
当今主流地图构建系统由于定位精度不高、重投影误差较大等问题,限制了稠密地图的生成。尤其在动态场景中,系统的实时性和地图的高精度之间无法共存,以及物体的往复移动为后续地图精度的提升带来了额外的困难。针对上述问题,提出了一种...当今主流地图构建系统由于定位精度不高、重投影误差较大等问题,限制了稠密地图的生成。尤其在动态场景中,系统的实时性和地图的高精度之间无法共存,以及物体的往复移动为后续地图精度的提升带来了额外的困难。针对上述问题,提出了一种基于闭环检测和自适应降采样的视觉SLAM点云地图构建方法(Visual SLAM point cloud map construction method based on closed-loop detection and adaptive downsampling,PCL-LCAD)。上述方法从视觉SLAM系统建图的角度出发,加入3D点云技术,构建一个闭环检测优化模型,扩大生成地图的面积,再建立一个点云自适应降采样模型,利用KD-tree算法对其体素滤波进行改进。实验结果表明,PCL-LCAD方法能在保障准确性和实时性的同时,降低地图占用空间并且提高地图稠密度。展开更多
提升绳是矿井、电梯等系统的关键承载部件,其安全性至关重要。针对传统检测方法实时性差、误报率高的问题,构建了基于图像识别的提升绳缺陷识别-定位-联动系统。该系统通过结构先验设定ROI(Region of Interest,感兴趣区域),采用多尺度...提升绳是矿井、电梯等系统的关键承载部件,其安全性至关重要。针对传统检测方法实时性差、误报率高的问题,构建了基于图像识别的提升绳缺陷识别-定位-联动系统。该系统通过结构先验设定ROI(Region of Interest,感兴趣区域),采用多尺度融合模型提升识别精度,结合绳体几何映射与时序跟踪实现动态捕捉与稳定复核,并在控制层实现分级联动。现场验证表明,该系统识别准确率高、误报率低,具备良好的工程适应性。展开更多
【目的】在“双碳”战略的驱动下,精准量化水务行业碳排放是其低碳转型的基础。现有水处理系统碳足迹核算普遍存在排放因子普适性过强、动态更新机制缺乏以及系统性整合不足等问题。【方法】本文构建了水处理系统本地化碳足迹动态测算...【目的】在“双碳”战略的驱动下,精准量化水务行业碳排放是其低碳转型的基础。现有水处理系统碳足迹核算普遍存在排放因子普适性过强、动态更新机制缺乏以及系统性整合不足等问题。【方法】本文构建了水处理系统本地化碳足迹动态测算方法及集成系统,提出“动态因子库-实时数据流-生命周期模型”三位一体的核算框架:电力因子通过应用程序接口(API)对接电网实现年度、季度、实时三级动态获取;药剂因子基于供应商环境产品声明(EPD)实现标准化与本地化;运输因子依据全球定位系统(GPS)轨迹动态计算;针对监测困难的一氧化二氮(N_(2)O)过程排放,开发了融合机理模型与机器学习[极端梯度提升-长短期记忆网络(XGBoost-LSTM)]混合预测模型,支持每日自适应更新。系统采用4层架构,集成多源数据采集、混合数据库(PostgreSQL+InfluxDB)、参数化生命周期模型(OpenLCA)及人工智能(AI)诊断功能,形成从精准核算到优化调控的闭环管理。【结果】本文以上海某20万t/d厌氧-缺氧-好氧污水处理厂为例,2024年上半年动态核算得总碳排放量为18450 t CO_(2)-eq,碳排放强度为0.51 kg CO_(2)-eq/m^(3)。排放结构:电力占比为62.3%、药剂占比为18.5%、生化过程占比为15.2%、运输占比为4.0%,碳排放强度呈现显著日波动(0.42~0.68 kg CO_(2)-eq/m^(3))。相较传统静态法,本方法总排放估算偏差降低3.5%,过程排放占比识别精度提升35.7%(从11.2%提高至15.2%),不确定性由±18.5%降至±8.3%,时间分辨率提升至小时级。AI诊断识别出曝气优化、药剂投加调整与沼气回收3项关键减排措施,预计可实现年减排13.8%(年碳减排量为520 t CO_(2)-eq)。【结论】该方法通过时空双重本地化的动态因子库与实时数据融合,有效克服了传统核算的静态滞后与本地化不足的问题,为水务行业从宏观合规核算向微观实时优化的精细化管理转型提供了可行的技术方案。展开更多
基金Joint Seismological Science Foundation of China (198009).
文摘A new concept is suggested on tectonomagnetic research about the noise in simultaneous geomagnetic difference data caused by the effect of Sq local-time variation, together with the method of theoretical calculation. The level of the noise and its contribution to the total noises of the differences data are analyzed. The result indicates that the noise increases linearly with the increase of the distance between the two stations in the range of 40° longitude-difference, and its increasing rate is about 0.4 nT/（°）at latitude 40°N. The example calculated at a pair of sites with longitude-difference 0.357°, shows that the noise is about one fifth of the total noises of the difference data on geomagnetic quiet-day.
基金supported by the National Key R&D Program of China(Grant No.2022YFF0503703)the National Natural Science Foundation of China(Grant Nos.42130203,42275133,and 42241135).
文摘In this study,we use observations from the Sounding of the Atmosphere using Broadband Emission Radiometry(SABER)instrument onboard the Thermosphere–Ionosphere–Mesosphere Energetics and Dynamics(TIMED)satellite to develop and apply a new local-time binning method to investigate the long-term evolution of mesospheric water vapor at high latitudes.The proposed method accounts for the gradual local-time drift of the SABER orbit by aligning seasonal observation windows and selecting samples observed at similar local times.This approach minimizes tidal aliasing and ensures more consistent sampling,yielding more reliable estimates of long-term water vapor trends at high latitudes.The results show that drying signals primarily appear in the polar regions.However,in the southern hemisphere,a drying trend is observed only in autumn,whereas winter and summer mainly show moistening trends.In contrast,the northern hemisphere exhibits drying signals in the polar regions during all seasons,showing a clear seasonal asymmetry.Additionally,the water vapor trend in the northern hemisphere is particularly pronounced in February(late winter),with moistening reaching up to+2.0 ppmv.The winter in the southern hemisphere(July–August)also shows moistening,but the trend is still weaker than in the northern hemisphere.These differences highlight the strong moistening trend in the northern hemisphere during winter and underscore the significant asymmetry in seasonal water vapor changes between the two hemispheres.These findings emphasize the limitations of water vapor trend estimates across different seasons and latitudes.Moreover,they provide new insights into the spatiotemporal variability associated with tidal structures,underscoring the importance of optimizing local-time sampling strategies for reliable long-term trend detection.
文摘当今主流地图构建系统由于定位精度不高、重投影误差较大等问题,限制了稠密地图的生成。尤其在动态场景中,系统的实时性和地图的高精度之间无法共存,以及物体的往复移动为后续地图精度的提升带来了额外的困难。针对上述问题,提出了一种基于闭环检测和自适应降采样的视觉SLAM点云地图构建方法(Visual SLAM point cloud map construction method based on closed-loop detection and adaptive downsampling,PCL-LCAD)。上述方法从视觉SLAM系统建图的角度出发,加入3D点云技术,构建一个闭环检测优化模型,扩大生成地图的面积,再建立一个点云自适应降采样模型,利用KD-tree算法对其体素滤波进行改进。实验结果表明,PCL-LCAD方法能在保障准确性和实时性的同时,降低地图占用空间并且提高地图稠密度。
文摘提升绳是矿井、电梯等系统的关键承载部件,其安全性至关重要。针对传统检测方法实时性差、误报率高的问题,构建了基于图像识别的提升绳缺陷识别-定位-联动系统。该系统通过结构先验设定ROI(Region of Interest,感兴趣区域),采用多尺度融合模型提升识别精度,结合绳体几何映射与时序跟踪实现动态捕捉与稳定复核,并在控制层实现分级联动。现场验证表明,该系统识别准确率高、误报率低,具备良好的工程适应性。
文摘【目的】在“双碳”战略的驱动下,精准量化水务行业碳排放是其低碳转型的基础。现有水处理系统碳足迹核算普遍存在排放因子普适性过强、动态更新机制缺乏以及系统性整合不足等问题。【方法】本文构建了水处理系统本地化碳足迹动态测算方法及集成系统,提出“动态因子库-实时数据流-生命周期模型”三位一体的核算框架:电力因子通过应用程序接口(API)对接电网实现年度、季度、实时三级动态获取;药剂因子基于供应商环境产品声明(EPD)实现标准化与本地化;运输因子依据全球定位系统(GPS)轨迹动态计算;针对监测困难的一氧化二氮(N_(2)O)过程排放,开发了融合机理模型与机器学习[极端梯度提升-长短期记忆网络(XGBoost-LSTM)]混合预测模型,支持每日自适应更新。系统采用4层架构,集成多源数据采集、混合数据库(PostgreSQL+InfluxDB)、参数化生命周期模型(OpenLCA)及人工智能(AI)诊断功能,形成从精准核算到优化调控的闭环管理。【结果】本文以上海某20万t/d厌氧-缺氧-好氧污水处理厂为例,2024年上半年动态核算得总碳排放量为18450 t CO_(2)-eq,碳排放强度为0.51 kg CO_(2)-eq/m^(3)。排放结构:电力占比为62.3%、药剂占比为18.5%、生化过程占比为15.2%、运输占比为4.0%,碳排放强度呈现显著日波动(0.42~0.68 kg CO_(2)-eq/m^(3))。相较传统静态法,本方法总排放估算偏差降低3.5%,过程排放占比识别精度提升35.7%(从11.2%提高至15.2%),不确定性由±18.5%降至±8.3%,时间分辨率提升至小时级。AI诊断识别出曝气优化、药剂投加调整与沼气回收3项关键减排措施,预计可实现年减排13.8%(年碳减排量为520 t CO_(2)-eq)。【结论】该方法通过时空双重本地化的动态因子库与实时数据融合,有效克服了传统核算的静态滞后与本地化不足的问题,为水务行业从宏观合规核算向微观实时优化的精细化管理转型提供了可行的技术方案。
