As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery...As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.展开更多
Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become...Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment （BPA） approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach.展开更多
To overcome the shortcomings of 1 D and 2 D Otsu’s thresholding techniques, the 3 D Otsu method has been developed.Among all Otsu’s methods, 3 D Otsu technique provides the best threshold values for the multi-level ...To overcome the shortcomings of 1 D and 2 D Otsu’s thresholding techniques, the 3 D Otsu method has been developed.Among all Otsu’s methods, 3 D Otsu technique provides the best threshold values for the multi-level thresholding processes. In this paper, to improve the quality of segmented images, a simple and effective multilevel thresholding method is introduced. The proposed approach focuses on preserving edge detail by computing the 3 D Otsu along the fusion phenomena. The advantages of the presented scheme include higher quality outcomes, better preservation of tiny details and boundaries and reduced execution time with rising threshold levels. The fusion approach depends upon the differences between pixel intensity values within a small local space of an image;it aims to improve localized information after the thresholding process. The fusion of images based on local contrast can improve image segmentation performance by minimizing the loss of local contrast, loss of details and gray-level distributions. Results show that the proposed method yields more promising segmentation results when compared to conventional1 D Otsu, 2 D Otsu and 3 D Otsu methods, as evident from the objective and subjective evaluations.展开更多
Background: cervical spondylotic myelopathy is a common health problem that neurosurgeons face in Egypt. The aim of this study is to evaluate the efficacy of PEEK cage only in 4 levels anterior cervical discectomy as ...Background: cervical spondylotic myelopathy is a common health problem that neurosurgeons face in Egypt. The aim of this study is to evaluate the efficacy of PEEK cage only in 4 levels anterior cervical discectomy as one of surgical option other than anterior cervical corpectomy, fixation by plat or posterior approach for cervical laminectomy, and assessment of post spinal surgery pain. Methods: this prospective study on 28 patients with cervical spondylotic myelopathy (CSM) over a period of 3 years (between April 2012 and April 2015) with mean period of follow up 30 months. We have done anterior cervical discectomy with fixation by cage only for all cases with perioperative assessment and scoring clinically and radiologically (Japanese Orthopaedic Association [JOA] scores, Visual Analogue Scale [VAS] scores for assessment of neck and arm pain, perioperative parameters (hospital stay, blood loss, operative time), the European Myelopathy Scoring (EMS) and Odom’s criteria, and the incidence of complication,post spinal surgery pain assessment). Results: clinical outcome was excellent (28.55), good (50%) and fair (21.5) according to Odom criteria. The European Myelopathy Scoring (EMS), improved from 10 to 16. The mean JOA score improved from 10.1 ± 2.1 to 14.2 ± 2.3. Fusion failure had been seen in 4 patients in one level for each secondary to anterior displacement of the cage with no other major complications. Conclusion: 4 levels anterior cervical discectomy with PEEK cage only is an effective, save and less costly with less post operative complication and hospital stay and less post spinal surgery pain.展开更多
随着6G移动通信技术的发展,通信与感知一体化(integrated sensing and communication,ISAC)成为未来无线网络的重要方向。在大规模分布式场景中,高精度定位仍面临计算和通信开销过大、参数不可靠等挑战。为此,提出一种多级融合的ISAC定...随着6G移动通信技术的发展,通信与感知一体化(integrated sensing and communication,ISAC)成为未来无线网络的重要方向。在大规模分布式场景中,高精度定位仍面临计算和通信开销过大、参数不可靠等挑战。为此,提出一种多级融合的ISAC定位架构:在接入点(access point,AP)级对感知信号进行预处理,并将结果上传至边缘分布式单元(edge distributed unit,EDU);EDU级利用神经网络将信噪比映射为时延参数的权重,并结合几何精度因子(geometric dilution of precision,GDOP)策略进行加权最小二乘局部定位;中央处理单元(central processing unit,CPU)级则在全局视角下对EDU上传的可靠参数进行二次动态筛选与最终定位。仿真结果表明,该架构能显著降低整体区域内的定位误差,通信和计算开销均优于集中式方案,具有良好的系统可扩展性。展开更多
针对断路器机械特性异常诊断中的多源信号采集与分析问题,设计出一套分合闸线圈电流和触头行程信号的采集系统,并提出了相应的异常模拟方案。通过引入分段滤波和循环差分判别进行特征提取,机器学习算法采用CatBoost模型进行单源信号的...针对断路器机械特性异常诊断中的多源信号采集与分析问题,设计出一套分合闸线圈电流和触头行程信号的采集系统,并提出了相应的异常模拟方案。通过引入分段滤波和循环差分判别进行特征提取,机器学习算法采用CatBoost模型进行单源信号的异常诊断,结合遗传算法(genetic algorithm,GA)进行参数优化,实现了基于线圈电流和触头行程的高准确率诊断。同时,利用线性判别分析(linear discriminant analysis,LDA)方法进行特征融合,提升了异常诊断效果。此外,对多种融合方法的诊断结果进行对比分析。结果表明,LDA-GA-CatBoost的特征级融合方法与基于改进的D-S证据理论(dempster-shafer theory of evidence,DST)的决策级融合方法的异常诊断率最高,均为95.82%,但LDA-GA-CatBoost的模型训练时间仅为改进的D-S证据理论的一半,更具有应用优势。展开更多
无人船环境感知是无人船智能航行的关键技术之一,目前主要依赖于可获取目标空间位置的激光雷达和提供目标类别信息的光学设备。为获得复杂海上环境下目标多维感知信息,提出一种无人船载激光雷达-相机的融合感知方法,融合PR-YOLOv8视觉...无人船环境感知是无人船智能航行的关键技术之一,目前主要依赖于可获取目标空间位置的激光雷达和提供目标类别信息的光学设备。为获得复杂海上环境下目标多维感知信息,提出一种无人船载激光雷达-相机的融合感知方法,融合PR-YOLOv8视觉检测结果和激光雷达三维点云,实现了海上目标高精度识别和空间定位。首先,利用标定板进行激光雷达和相机联合标定,构建了两传感器间的投影关系。随后,对于雷达分支,对目标点云聚类拟合,提取目标的特征信息并投影至图像;对于相机分支,基于YOLOv8提出PR-YOLOv8目标检测模型,获得高识别精度的目标检测边界框。最后,结合两分支检测结果,提出一种新的代价构建因子DSIoU(Distance-Scale Intersection over Union)关联目标,并结合贝叶斯理论,实现了多源感知信息的融合。采用青岛近海和内湖船只感知实验,验证了所提出方法的可行性和有效性。展开更多
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z433)Hunan Provincial Natural Science Foundation of China (Grant No. 09JJ8005)Scientific Research Foundation of Graduate School of Beijing University of Chemical and Technology,China (Grant No. 10Me002)
文摘As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.
基金co-supported by Grant for State Key Program for Basic Research of China(No.2013CB329405)National Natural Science Foundation of China(Nos.61104214,61203222)+3 种基金Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.61221063)Specialized Research Fund for the Doctoral Program of Higher Education(No.20120201120036)China Postdoctoral Science Foundation(No.20100481337),China Postdoctoral Science Foundation-Special fund(No.201104670)Fundamental Research Funds for the Central Universities
文摘Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment （BPA） approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach.
文摘To overcome the shortcomings of 1 D and 2 D Otsu’s thresholding techniques, the 3 D Otsu method has been developed.Among all Otsu’s methods, 3 D Otsu technique provides the best threshold values for the multi-level thresholding processes. In this paper, to improve the quality of segmented images, a simple and effective multilevel thresholding method is introduced. The proposed approach focuses on preserving edge detail by computing the 3 D Otsu along the fusion phenomena. The advantages of the presented scheme include higher quality outcomes, better preservation of tiny details and boundaries and reduced execution time with rising threshold levels. The fusion approach depends upon the differences between pixel intensity values within a small local space of an image;it aims to improve localized information after the thresholding process. The fusion of images based on local contrast can improve image segmentation performance by minimizing the loss of local contrast, loss of details and gray-level distributions. Results show that the proposed method yields more promising segmentation results when compared to conventional1 D Otsu, 2 D Otsu and 3 D Otsu methods, as evident from the objective and subjective evaluations.
文摘Background: cervical spondylotic myelopathy is a common health problem that neurosurgeons face in Egypt. The aim of this study is to evaluate the efficacy of PEEK cage only in 4 levels anterior cervical discectomy as one of surgical option other than anterior cervical corpectomy, fixation by plat or posterior approach for cervical laminectomy, and assessment of post spinal surgery pain. Methods: this prospective study on 28 patients with cervical spondylotic myelopathy (CSM) over a period of 3 years (between April 2012 and April 2015) with mean period of follow up 30 months. We have done anterior cervical discectomy with fixation by cage only for all cases with perioperative assessment and scoring clinically and radiologically (Japanese Orthopaedic Association [JOA] scores, Visual Analogue Scale [VAS] scores for assessment of neck and arm pain, perioperative parameters (hospital stay, blood loss, operative time), the European Myelopathy Scoring (EMS) and Odom’s criteria, and the incidence of complication,post spinal surgery pain assessment). Results: clinical outcome was excellent (28.55), good (50%) and fair (21.5) according to Odom criteria. The European Myelopathy Scoring (EMS), improved from 10 to 16. The mean JOA score improved from 10.1 ± 2.1 to 14.2 ± 2.3. Fusion failure had been seen in 4 patients in one level for each secondary to anterior displacement of the cage with no other major complications. Conclusion: 4 levels anterior cervical discectomy with PEEK cage only is an effective, save and less costly with less post operative complication and hospital stay and less post spinal surgery pain.
文摘针对断路器机械特性异常诊断中的多源信号采集与分析问题,设计出一套分合闸线圈电流和触头行程信号的采集系统,并提出了相应的异常模拟方案。通过引入分段滤波和循环差分判别进行特征提取,机器学习算法采用CatBoost模型进行单源信号的异常诊断,结合遗传算法(genetic algorithm,GA)进行参数优化,实现了基于线圈电流和触头行程的高准确率诊断。同时,利用线性判别分析(linear discriminant analysis,LDA)方法进行特征融合,提升了异常诊断效果。此外,对多种融合方法的诊断结果进行对比分析。结果表明,LDA-GA-CatBoost的特征级融合方法与基于改进的D-S证据理论(dempster-shafer theory of evidence,DST)的决策级融合方法的异常诊断率最高,均为95.82%,但LDA-GA-CatBoost的模型训练时间仅为改进的D-S证据理论的一半,更具有应用优势。
文摘无人船环境感知是无人船智能航行的关键技术之一,目前主要依赖于可获取目标空间位置的激光雷达和提供目标类别信息的光学设备。为获得复杂海上环境下目标多维感知信息,提出一种无人船载激光雷达-相机的融合感知方法,融合PR-YOLOv8视觉检测结果和激光雷达三维点云,实现了海上目标高精度识别和空间定位。首先,利用标定板进行激光雷达和相机联合标定,构建了两传感器间的投影关系。随后,对于雷达分支,对目标点云聚类拟合,提取目标的特征信息并投影至图像;对于相机分支,基于YOLOv8提出PR-YOLOv8目标检测模型,获得高识别精度的目标检测边界框。最后,结合两分支检测结果,提出一种新的代价构建因子DSIoU(Distance-Scale Intersection over Union)关联目标,并结合贝叶斯理论,实现了多源感知信息的融合。采用青岛近海和内湖船只感知实验,验证了所提出方法的可行性和有效性。
