基于机器视觉的运煤车车号识别技术研究

在铁路运煤装车过程中为了快速、准确地识别车号,提出一种基于机器视觉的运煤车车号识别技术。将连通区域提取与投影分割法结合,实现车号的粗定位、细分割,并对图像中的断裂字符进行二次分割,构建了基于BP神经网络的分类模型进行车号识别,提升了煤炭装车的效率和精度。     

Quantitative analysis of semiconductor supply chain contracts with order flexibility under demand uncertainty: A case study

The evidence base for the configuration of rolling horizon flexibility (RHF) contracts (a type of quantity flexibility contract) used in the semiconductor industry to coordinate production and demand remains meagre, more art than science. Informed by the characteristics of actual clauses and demand behaviors drawn from a company’s experience, a discrete-event simulation model is developed to represent the company’s supply chain. It comprises of three parties: a customer, a supplier (semiconductor manufacturer), and a capacity provider. Through analysis of customer forecasted demand the paper characterizes forecast demand as being under, over or unbiased. Models of these forecasted demands drives both long and short term planning. In long term planning, which is given twelve months before an order is delivered, capacity at the capacity provider is booked. Short term planning is also driven by this forecast which, within a binding period, is governed by an RHF contract. Results from the model report inventory levels, and delivery compliance, namely Delivery Performance (DP) and Delivery Reliability (DR), measures widely used in this sector. It is concluded from this work that on the balance of performance measures RHF contracts with asymmetrical flexibility bounds are substantially better than those with symmetrical boundaries, and that this conclusion is robust with regard to both over-planning and under-planning behaviors. This robustness is a critical attribute with respect to the endemic medium-term vacillation between both states experienced in practice in this sector.     

Quantitative relationship between time margin and human reliability

Operator reliability in complex systems is influenced by various performance shaping factors (PSFs). Time is a particularly important PSF; however, empirical studies of human reliability analysis (HRA) are rarely focused on modeling the effect of time PSF on human error probability (HEP). This study contributes to HRA literature by investigating the empirical relationship between time margin and HEP. Time margin is defined as the difference between the time available to complete a task and the time required to successfully complete the task, divided by the required time. We investigate and compare two models (logistic and linear) to explain HEP based on time margin. The empirical HEP data for model testing were extracted from a microworld simulator (Study 1) and a full-scope simulator (Study 2) in two existing studies relevant to procedural tasks in nuclear power plants. For Study 1, both models exhibited an acceptable, equivalent explanatory power; for Study 2, although both models exhibited an acceptable explanatory ability, the logistic model explained more variance in HEP. Our findings indicate the potential of the logistic model in explaining and predicting HEP based on time margin in time-critical tasks.     

大气次声源定位算法及误差分析

逐步多通道相关方法是定位次声源的主要方法。该方法会忽略阵元的海拔高度差,从而引入误差。文章分析了基于广义互相关的时间延迟估计算法,讨论了基于时延的平面波入射角定位方法。着重研究了逐步多通道相关方法的误差来源,确定了基于时延的定位方法是产生误差的主要原因,明确了大气次声源定位误差来源于忽略了阵元间的海拔高度差。基于最小二乘法推导了在不考虑阵元高度的情况下计算次声波入射角的方法。对存在高度差的4元中心三角阵型进行了误差仿真实验,在忽略阵元海拔高度差的条件下,各方向入射的次声波角度定位误差最大达到4°,特定阵型的阵元最大海拔高度差与入射角度计算误差成线性关系,并探讨了入射角度计算误差对主要参数和后续定位的影响。     

里程计辅助的高精度车载GNSS/INS组合导航系统

针对城市隧道、偏远山区等复杂路况下,卫星导航系统信号被遮挡较严重或无卫星导航系统信号的场景中,车载GNSS/INS组合导航系统精度下降的问题,提出一种里程计辅助的高精度车载GNSS/INS组合导航方法。该方法中的组合滤波模式可根据载车环境变化在GNSS/INS组合模式和DR/INS组合模式间实现自适应切换,该组合导航方法将三维里程计航位推算位置误差作为状态量扩充到常规组合导航滤波器中,里程计的标度因数误差、安装角误差可通过里程计误差标定方法离线精确得到,后续使用只需将里程计误差参数装订到组合导航系统中即可。车载试验表明,7 km的信号遮挡场景下组合导航系统单个方向上的位置误差最大值也不大于8 m,整个跑车过程中位置误差在3 m以内,进一步保证了车载GNSS/INS组合导航系统复杂路况下的高精度定位。     

动圈仪表的温度附加误差及其补偿方法

本文对动圈仪表产生温度附加误差的各种因素作了一定的理论分析,并提出了相应的补偿措施。文章以多幅图、表及实例作了论述。     

尘埃粒子计数器校准结果及其应用探讨

本文对尘埃粒子计数器粒子浓度示值误差校准结果的计算进行了讨论,并以制药行业中尘埃粒子计数器的使用为例对尘埃粒子计数器校准结果的应用进行了探讨。     

一种基于多用户协同的网络定位性能评估方法

常见的网络定位技术主要有GNSS定位、基站定位、WiFi定位三种,每种定位技术都有其应用的场景和优缺点。现有的定位性能评估方法因涉及较专业的实验室设备,存在设备采购和维护成本高、场景覆盖较少等问题。本文提出了一种基于多用户协同的网络定位性能评估方法,该方法通过多用户手机协同机制采集大量高精度的GNSS基准位置评估基站或WiFi等粗精度网络定位性能,文章分析了该方法的实现流程,并通过试验场景和数据分析对比,最终给出了评价。     

基于物联网的智能室内定位送水系统设计

随着物联网技术的发展,机器人已广泛应用于生产和生活之中。自动送水机器人作为一种智能饮水系统,可应用于办公区域、医院、家庭等多种场所,智能化地为人类提供饮水服务。本文设计了一款智能室内定位送水系统,可以实现水杯定位、转向前行、自动添注水等功能。系统以UP Squared处理器为设计平台,扩展了UWB定位、Zigbee无线传输、陀螺仪、机械臂等功能模块。采用MPU6050 模块进行旋转角度感知,PID算法控制机器人旋转；基于电流磁效应和电磁感应定律感知水杯位置；采用超声波模块对出水口上升的高度和水杯中水位进行检测。通过实验测试了系统的定位、方向调整、测距、功耗等多项参数以及送水全过程,结果表明,系统具有定位准确、转向快速平稳和功耗低等特点,达到实际应用于室内智能定位送水的技术要求。     

面向自动化精密装配的视觉定位引导系统

针对总装生产线精密装配现状,项目设计开发了一种机器视觉定位引导系统,主要实现工业机器人在运动过程中完成在线采集不规则工件图像、视觉定位、角度补偿及精密装配作业。该系统首先采集实时工件图像,利用改进优化的九点标定算法对机器人进行视觉标定可以提高算法的精度;通过预处理操作获取质量较好的图像,按顺序创建卡尺工具,采用加权最小二乘法拟合工件亚像素边缘,再根据相关二维测量算法获取工件中心坐标。最终将得到的位姿数据传送给6轴机器人进行精密装配任务。实验结果表明,该视觉定位引导系统具有现场环境下的高精度定位检测功能,自动化装配定位精度在X方向最大定位误差为0.0281mm、Y方向最大定位误差为0.026mm,足以达到自动化装配生产线的技术要求,具有较好的应用前景和参考价值。