针对当今工业对钢铁产品能够实现在线检测、实时处理以及提高检测精度和速度的要求越来越迫切,设计双线圈传感器,结合电磁层析成像(Electromagnetic Tomography,EMT)技术,搭建一套基于数字信号处理器(Digital Signal Processor,DSP)TMS3...针对当今工业对钢铁产品能够实现在线检测、实时处理以及提高检测精度和速度的要求越来越迫切,设计双线圈传感器,结合电磁层析成像(Electromagnetic Tomography,EMT)技术,搭建一套基于数字信号处理器(Digital Signal Processor,DSP)TMS320F2812的电磁探伤系统.通过实验验证传感器结构和系统的可行性.实验结果表明,系统可以较好地对金属表面缺陷进行快速检测和定位.该系统可为工业金属缺陷检测提供一种新的检测依据.展开更多
Feedforward symbol timing recovery techniques are particularly important for initial acquisition in burst modems. However, these techniques either have large calculation burden or sensitive to frequency offsets. In th...Feedforward symbol timing recovery techniques are particularly important for initial acquisition in burst modems. However, these techniques either have large calculation burden or sensitive to frequency offsets. In this paper, we proposed an efficient symbol timing recovery algorithm of MPSK signals named OMQ(Ordered Maximum power using Quadratic approximation partially) algorithm which is based on the Quadratic Approximation(QA) algorithm. We used ordered statistic sorting method to reduce the computational complexity further, meanwhile maximum mean power principle was used to decrease frequency offset sensitivity. The proposed algorithm adopts estimation-down sampling structure which is suitable for small packet size transmission. The results show that, while comparing with the QA algorithm, the computational complexity is reduced by 75% at most when 8 samples per symbol are used. The proposed algorithm shows better performance in terms of the jitter variance and sensitivity to frequency offsets.展开更多
The clustering of trajectories over huge volumes of streaming data has been rec- ognized as critical for many modem applica- tions. In this work, we propose a continuous clustering of trajectories of moving objects ov...The clustering of trajectories over huge volumes of streaming data has been rec- ognized as critical for many modem applica- tions. In this work, we propose a continuous clustering of trajectories of moving objects over high speed data streams, which updates online trajectory clusters on basis of incremental line- segment clustering. The proposed clustering algorithm obtains trajectory clusters efficiently and stores all closed trajectory clusters in a bi- tree index with efficient search capability. Next, we present two query processing methods by utilising three proposed pruning strategies to fast handle two continuous spatio-temporal queries, threshold-based trajectory clustering queries and threshold-based trajectory outlier detections. Finally, the comprehensive experi- mental studies demonstrate that our algorithm achieves excellent effectiveness and high effi- ciency for continuous clustering on both syn- thetic and real streaming data, and the propo- sed query processing methods utilise average 90% less time than the naive query methods.展开更多
文摘针对当今工业对钢铁产品能够实现在线检测、实时处理以及提高检测精度和速度的要求越来越迫切,设计双线圈传感器,结合电磁层析成像(Electromagnetic Tomography,EMT)技术,搭建一套基于数字信号处理器(Digital Signal Processor,DSP)TMS320F2812的电磁探伤系统.通过实验验证传感器结构和系统的可行性.实验结果表明,系统可以较好地对金属表面缺陷进行快速检测和定位.该系统可为工业金属缺陷检测提供一种新的检测依据.
基金supported by the National Natural Science Foundation of China(NSFC.NO.61303253)
文摘Feedforward symbol timing recovery techniques are particularly important for initial acquisition in burst modems. However, these techniques either have large calculation burden or sensitive to frequency offsets. In this paper, we proposed an efficient symbol timing recovery algorithm of MPSK signals named OMQ(Ordered Maximum power using Quadratic approximation partially) algorithm which is based on the Quadratic Approximation(QA) algorithm. We used ordered statistic sorting method to reduce the computational complexity further, meanwhile maximum mean power principle was used to decrease frequency offset sensitivity. The proposed algorithm adopts estimation-down sampling structure which is suitable for small packet size transmission. The results show that, while comparing with the QA algorithm, the computational complexity is reduced by 75% at most when 8 samples per symbol are used. The proposed algorithm shows better performance in terms of the jitter variance and sensitivity to frequency offsets.
基金supported by the National Natural Science Foundation of China under Grants No.61172049,No.61003251the National High Technology Research and Development Program of China(863 Program)under Grant No.2011AA040101the Doctoral Fund of Ministry of Education of Chinaunder Grant No.20100006110015
文摘The clustering of trajectories over huge volumes of streaming data has been rec- ognized as critical for many modem applica- tions. In this work, we propose a continuous clustering of trajectories of moving objects over high speed data streams, which updates online trajectory clusters on basis of incremental line- segment clustering. The proposed clustering algorithm obtains trajectory clusters efficiently and stores all closed trajectory clusters in a bi- tree index with efficient search capability. Next, we present two query processing methods by utilising three proposed pruning strategies to fast handle two continuous spatio-temporal queries, threshold-based trajectory clustering queries and threshold-based trajectory outlier detections. Finally, the comprehensive experi- mental studies demonstrate that our algorithm achieves excellent effectiveness and high effi- ciency for continuous clustering on both syn- thetic and real streaming data, and the propo- sed query processing methods utilise average 90% less time than the naive query methods.
