Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI s...Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI segmentation method,which is based on fuzzy c-means(FCM) and DS theory, is proposed. Firstly, the average fusion method is used to reduce the uncertainty and the conflict information in the pictures. Then, the neighborhood information and the different influences of spatial location of neighborhood pixels are taken into consideration to handle the spatial information. Finally, the segmentation and the sensor data fusion are achieved by using the DS theory. The simulated images and the MRI images illustrate that our proposed method is more effective in image segmentation.展开更多
针对目前火车死钩检测无法自动实现的问题,提出了一种自然环境下基于颜色聚类和颜色距离的死钩检测方法。根据死钩和车厢颜色的对应关系,使用CCD(charge-coupled device)相机获取现场车厢图像并提取前景区域和背景区域的颜色特征,通过...针对目前火车死钩检测无法自动实现的问题,提出了一种自然环境下基于颜色聚类和颜色距离的死钩检测方法。根据死钩和车厢颜色的对应关系,使用CCD(charge-coupled device)相机获取现场车厢图像并提取前景区域和背景区域的颜色特征,通过分析该颜色信息的差异来判断车厢之间的连接是否为死钩。首先获取特定区域的颜色信息,然后采用FCM(fuzzy C-mean)聚类算法对颜色信息进行分类得到该区域的单一颜色特征,最后根据HLC(hue,lightness,hromatic)颜色空间和人类颜色视觉的相似关系,计算颜色特征对的NBS(national bureau of standards)颜色距离。利用翻车作业现场火车车厢图像进行检测,实验结果验证了该方法具有对颜色差异的高敏感性和识别的准确性,可以满足实际死钩检测的需要。展开更多
Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of th...Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.展开更多
基金supported by the National Natural Science Foundation of China(6167138461703338)+2 种基金the Natural Science Basic Research Plan in Shaanxi Province of China(2016JM6018)the Project of Science and Technology Foundationthe Fundamental Research Funds for the Central Universities(3102017OQD020)
文摘Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI segmentation method,which is based on fuzzy c-means(FCM) and DS theory, is proposed. Firstly, the average fusion method is used to reduce the uncertainty and the conflict information in the pictures. Then, the neighborhood information and the different influences of spatial location of neighborhood pixels are taken into consideration to handle the spatial information. Finally, the segmentation and the sensor data fusion are achieved by using the DS theory. The simulated images and the MRI images illustrate that our proposed method is more effective in image segmentation.
文摘针对目前火车死钩检测无法自动实现的问题,提出了一种自然环境下基于颜色聚类和颜色距离的死钩检测方法。根据死钩和车厢颜色的对应关系,使用CCD(charge-coupled device)相机获取现场车厢图像并提取前景区域和背景区域的颜色特征,通过分析该颜色信息的差异来判断车厢之间的连接是否为死钩。首先获取特定区域的颜色信息,然后采用FCM(fuzzy C-mean)聚类算法对颜色信息进行分类得到该区域的单一颜色特征,最后根据HLC(hue,lightness,hromatic)颜色空间和人类颜色视觉的相似关系,计算颜色特征对的NBS(national bureau of standards)颜色距离。利用翻车作业现场火车车厢图像进行检测,实验结果验证了该方法具有对颜色差异的高敏感性和识别的准确性,可以满足实际死钩检测的需要。
文摘Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.
