城市轨道交通作为一种城市内交通运输方式,因其快速高效、低碳环保、运力强大等优点得到了国家产业政策的大力支持,近几年来,我国城市轨道交通发展迅速、列车速度不断提高,其安全问题愈发重要。列车长时间的运行,由于震动、碰撞、老化...城市轨道交通作为一种城市内交通运输方式,因其快速高效、低碳环保、运力强大等优点得到了国家产业政策的大力支持,近几年来,我国城市轨道交通发展迅速、列车速度不断提高,其安全问题愈发重要。列车长时间的运行,由于震动、碰撞、老化等问题,列车底部的紧固螺栓会出现松动、甚至掉落丢失的情况,存在发生重大安全事故的风险。而现阶段采取的人工巡检的方法存在效率低、漏检多、标准不一等诸多限制。为了避免造成人员伤亡和财产损失,亟需研究出一种快速、准确的螺栓故障检测方法。本文采用智能列检机器人采集列车车底螺栓图像,合成点云数据,通过ICP算法与模版数据点云配准、RANSAC平面分割消除异常点,计算螺栓表面点云的数量与平面距离判断列车车底螺栓是否正常,实验表明,该方法可以有效的识别出列车车底螺栓丢失和3 mm以上松动故障,真实故障识别率为100%。对减少人工成本、排除列车安全隐患、保障人民生命财产安全具有重要意义。Urban rail transit, as an intra-city transportation mode, has been strongly supported by the national industrial policy due to its advantages of high speed, high efficiency, low carbon and environmental protection, and strong transportation capacity. Its security issues are becoming more and more important. When the train runs for a long time, due to vibration, collision, aging and other problems, the fastening bolts at the bottom of the train will be loose, or even lost, and there is a risk of major safety accidents. However, the manual inspection method adopted at this stage has many limitations, such as low efficiency, many missed inspections, and different standards. In order to avoid casualties and property losses, it is urgent to develop a fast and accurate bolt fault detection method. In this paper, the intelligent train inspection robot is used to collect the images of the bolts on the bottom of the train, synthesize the point cloud data, and use the ICP algorithm to register the point cloud with the template data, RANSAC plane segmentation to eliminate abnormal points, and calculate the number of point clouds on the bolt surface and the plane distance to judge the train bottom. Whether the bolts are normal or not, the experiment shows that this method can effectively identify the loss of the bolts on the bottom of the train and the loose faults of more than 3mm, and the real fault recognition rate is 100%. It is of great significance to reduce labor costs, eliminate hidden dangers of train safety, and ensure the safety of people’s lives and properties.展开更多
早起的货车故障诊断主要依靠列检人员的眼看、耳听、手摸、敲打等方式,该方法不仅劳动强度大、检测效率低,且易受气候、职工疲劳程度与素质等因素影响,已不能满足当前铁路交通高速发展的需要。基于此种情况产生了货车运行故障动态图像...早起的货车故障诊断主要依靠列检人员的眼看、耳听、手摸、敲打等方式,该方法不仅劳动强度大、检测效率低,且易受气候、职工疲劳程度与素质等因素影响,已不能满足当前铁路交通高速发展的需要。基于此种情况产生了货车运行故障动态图像检测系统(英文全称Trouble of moving Freight car Detection System,简称TFDS),该系统采用轨边高速摄像技术,拍摄经过列车的制动梁梁体、固定杠杆、移动杠杆、交叉杆、制动梁支柱、中拉杆等关键部位的图像,然后将拍摄图像传输到列检所,由计算机图像自动识别方法进行货车关键部位是否有故障的检测,同时将结果传递给室外检测员,以此保障列车的运输安全。本文就列车制动梁中梁体夹扣螺栓丢失故障诊断的方法进行研究。展开更多
Based on the analysis of the failure characteristics and backfilling effect of the compound roof at 1801 backfilling workface in Taiyuan coal mine, China, we propose a method of controlling the pre- subsidence of a co...Based on the analysis of the failure characteristics and backfilling effect of the compound roof at 1801 backfilling workface in Taiyuan coal mine, China, we propose a method of controlling the pre- subsidence of a compound roof by using pre-stressed bolts to improve the backfilling ratio of the work- face so as to maintain the global stability of the stope roof. In addition, PHASE simulation software was employed to analyze the influence law of pre-stressing force, length, and interval on roof subsidence at the workface. On the basis of the numerical simulation results, a model for calculating the pre-stressing force and length of the bolts, the interval between the bolts, as well as roof subsidence at the workface, was established by using SPSS regression analysis software. Moreover, the research results were applied successfully to the 1801 filling workface. According to the monitoring data of roof closure, it was found that the final subsidence value for the goal roof was 350 mm and the filling ratio at the workface was 86%, which could fully meet the demand for safety production at the workface. The safe and effective control of the stope roof was therefore realized, which achieves the goal of safe and efficient backfilling mining under a compound roof.展开更多
In order to investigate the effects of different geometrical parameters and pretightening loads on failure mode and bearing strength,a large number of single-bolted T300/QY8911 composite laminates were tested under st...In order to investigate the effects of different geometrical parameters and pretightening loads on failure mode and bearing strength,a large number of single-bolted T300/QY8911 composite laminates were tested under static tension load.Box-plot was used to extract the singular testing values of bearing strength and effective statistical values were obtained.T-test method of independent samples was used to study how much pretightening loads influence bearing strength.The results show that the geometrical parameters,such as ratios of width to hole diameter(w/d) and edge distance to hole diameter(e/d),remarkably influence failure mode and bearing strength.Net-section failure will occur when w/d is smaller than 4,and shear-out failure will occur when e/d is smaller than 2.Bearing failure or bearing and shear-out combined failure will occur when w/d is greater than 4 and e/d is greater than 2.There is an optimal combination of geometrical parameters to achieve the highest bearing strength.For most of specimens,pretightening loads do not explicitly influence bearing strength.展开更多
文摘城市轨道交通作为一种城市内交通运输方式,因其快速高效、低碳环保、运力强大等优点得到了国家产业政策的大力支持,近几年来,我国城市轨道交通发展迅速、列车速度不断提高,其安全问题愈发重要。列车长时间的运行,由于震动、碰撞、老化等问题,列车底部的紧固螺栓会出现松动、甚至掉落丢失的情况,存在发生重大安全事故的风险。而现阶段采取的人工巡检的方法存在效率低、漏检多、标准不一等诸多限制。为了避免造成人员伤亡和财产损失,亟需研究出一种快速、准确的螺栓故障检测方法。本文采用智能列检机器人采集列车车底螺栓图像,合成点云数据,通过ICP算法与模版数据点云配准、RANSAC平面分割消除异常点,计算螺栓表面点云的数量与平面距离判断列车车底螺栓是否正常,实验表明,该方法可以有效的识别出列车车底螺栓丢失和3 mm以上松动故障,真实故障识别率为100%。对减少人工成本、排除列车安全隐患、保障人民生命财产安全具有重要意义。Urban rail transit, as an intra-city transportation mode, has been strongly supported by the national industrial policy due to its advantages of high speed, high efficiency, low carbon and environmental protection, and strong transportation capacity. Its security issues are becoming more and more important. When the train runs for a long time, due to vibration, collision, aging and other problems, the fastening bolts at the bottom of the train will be loose, or even lost, and there is a risk of major safety accidents. However, the manual inspection method adopted at this stage has many limitations, such as low efficiency, many missed inspections, and different standards. In order to avoid casualties and property losses, it is urgent to develop a fast and accurate bolt fault detection method. In this paper, the intelligent train inspection robot is used to collect the images of the bolts on the bottom of the train, synthesize the point cloud data, and use the ICP algorithm to register the point cloud with the template data, RANSAC plane segmentation to eliminate abnormal points, and calculate the number of point clouds on the bolt surface and the plane distance to judge the train bottom. Whether the bolts are normal or not, the experiment shows that this method can effectively identify the loss of the bolts on the bottom of the train and the loose faults of more than 3mm, and the real fault recognition rate is 100%. It is of great significance to reduce labor costs, eliminate hidden dangers of train safety, and ensure the safety of people’s lives and properties.
文摘早起的货车故障诊断主要依靠列检人员的眼看、耳听、手摸、敲打等方式,该方法不仅劳动强度大、检测效率低,且易受气候、职工疲劳程度与素质等因素影响,已不能满足当前铁路交通高速发展的需要。基于此种情况产生了货车运行故障动态图像检测系统(英文全称Trouble of moving Freight car Detection System,简称TFDS),该系统采用轨边高速摄像技术,拍摄经过列车的制动梁梁体、固定杠杆、移动杠杆、交叉杆、制动梁支柱、中拉杆等关键部位的图像,然后将拍摄图像传输到列检所,由计算机图像自动识别方法进行货车关键部位是否有故障的检测,同时将结果传递给室外检测员,以此保障列车的运输安全。本文就列车制动梁中梁体夹扣螺栓丢失故障诊断的方法进行研究。
基金the Qinglan Project,the National Key Basic Research Program of China (No.2013CB227905)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (No.51421003)
文摘Based on the analysis of the failure characteristics and backfilling effect of the compound roof at 1801 backfilling workface in Taiyuan coal mine, China, we propose a method of controlling the pre- subsidence of a compound roof by using pre-stressed bolts to improve the backfilling ratio of the work- face so as to maintain the global stability of the stope roof. In addition, PHASE simulation software was employed to analyze the influence law of pre-stressing force, length, and interval on roof subsidence at the workface. On the basis of the numerical simulation results, a model for calculating the pre-stressing force and length of the bolts, the interval between the bolts, as well as roof subsidence at the workface, was established by using SPSS regression analysis software. Moreover, the research results were applied successfully to the 1801 filling workface. According to the monitoring data of roof closure, it was found that the final subsidence value for the goal roof was 350 mm and the filling ratio at the workface was 86%, which could fully meet the demand for safety production at the workface. The safe and effective control of the stope roof was therefore realized, which achieves the goal of safe and efficient backfilling mining under a compound roof.
基金Project(51175424)supported by the National Natural Science Foundation of ChinaProject(B07050)supported by‘111’Program of ChinaProject(JC20110257)supported by the Basic Research Foundation of Northwestern Polytechnical University,China
文摘In order to investigate the effects of different geometrical parameters and pretightening loads on failure mode and bearing strength,a large number of single-bolted T300/QY8911 composite laminates were tested under static tension load.Box-plot was used to extract the singular testing values of bearing strength and effective statistical values were obtained.T-test method of independent samples was used to study how much pretightening loads influence bearing strength.The results show that the geometrical parameters,such as ratios of width to hole diameter(w/d) and edge distance to hole diameter(e/d),remarkably influence failure mode and bearing strength.Net-section failure will occur when w/d is smaller than 4,and shear-out failure will occur when e/d is smaller than 2.Bearing failure or bearing and shear-out combined failure will occur when w/d is greater than 4 and e/d is greater than 2.There is an optimal combination of geometrical parameters to achieve the highest bearing strength.For most of specimens,pretightening loads do not explicitly influence bearing strength.
