Visual FoxPro中错误处理技术

论述了Visual FoxPro程序设计过程中经常出现的错误,分析问题产生的原因并给出相应的解决办法.     

Validation of a small-area method for estimating the spatial distribution of the degree of tree damage

This article presents a validation of a method, proposed in Podlaski (2003), for estimating the degree of tree damage. This method belongs to a group of small-area methods. To estimate the degree of tree damage in individual P₃ sub-blocks of the SINUS system of information on the natural environment, a classification based on the degree of defoliation was used. Spatial distribution of the degree of tree damage was estimated through unrestricted simple random sampling. The maximum total estimation error for proportions of fir and beech with a damage degree of zero, and also with second and third degrees jointly, reached a maximum of 35.6% for fir, and 33.8% for beech. P₃ sub-blocks characterised by the highest proportion of the healthiest trees (at least 15% being undamaged trees) occurred in patches in the case of fir, and in larger, compact areas in the case of beech. Because spatial diversification in the health of fir, and to a smaller degree in the case of beech, occurs at small scales, small-area methods for estimating tree condition are necessary. An analogous scheme, combining small-area with large-area methods (utilising sub-blocks of the network of large-area systems in a small-area inventory, and establishing a common database), could be used on a wider scale; for example, by supplementing the program of estimating tree health carried out by the United Nations Economic Commission for Europe (Lorenz et al. 2002) with local inventories.     

林分平均胸径100倍圆法测定每公顷断面积的理论初探(之二)--误差分析与修正系数

通过对100Dg圆公式含义的分析,对影响林分断面积精度的2个主要因子:样地株数密度与林分平均胸径估测值进行了误差分析与探讨,提出了样地株数密度估计林分株数密度采用典型选样,林分平均胸径估测值采用目测法等相应解决办法。其中,当目测值有偏差时采用修正系数可使100Dg圆的可靠性进行了理论上的探讨。     

Accounting for unknown foster dams in the genetic evaluation of embryo transfer progeny

Animals born by embryo transfer (ET) are usually not included in the genetic evaluation of beef cattle for preweaning growth if the recipient dam is unknown. This is primarily to avoid potential bias in the estimation of the unknown age of dam. We present a method that allows including records of calves with unknown age of dam. Assumptions are as follows: (i) foster cows belong to the same breed being evaluated, (ii) there is no correlation between the breeding value (BV) of the calf and the maternal BV of the recipient cow, and (iii) cows of all ages are used as recipients. We examine the issue of bias for the fixed level of unknown age of dam (AOD) and propose an estimator of the effect based on classical measurement error theory (MEM) and a Bayesian approach. Using stochastic simulation under random mating or selection, the MEM estimating equations were compared with BLUP in two situations as follows: (i) full information (FI); (ii) missing AOD information on some dams. Predictions of breeding value (PBV) from the FI situation had the smallest empirical average bias followed by PBV obtained without taking measurement error into account. In turn, MEM displayed the highest bias, although the differences were small. On the other hand, MEM showed the smallest MSEP, for either random mating or selection, followed by FI, whereas ignoring measurement error produced the largest MSEP. As a consequence from the smallest MSEP with a relatively small bias, empirical accuracies of PBV were larger for MEM than those for full information, which in turn showed larger accuracies than the situation ignoring measurement error. It is concluded that MEM equations are a useful alternative for analysing weaning weight data when recipient cows are unknown, as it mitigates the effects of bias in AOD by decreasing MSEP.     

旋转式多比例分样方法对作物籽粒分样效果的研究

为验证旋转式多比例分样方法的可行性,探究旋转式多比例分样方法对作物籽粒的分样效果,以谷子、绿豆、大豆和玉米籽粒材料制备成混合样品,在不同转速(0~30.0 r/min)处理和不同进样时间(60、90、120 s)内比较旋转式多比例分样方法获得1/2、1/4、1/8和1/16子样的代表性和缩分比误差。结果表明,在转速0~30.0 r/min和进样时间60~120 s的情况下,旋转式多比例分样方法获得子样的分样误差和均无显著差异,且均不高于四分法(CK)。但是,除不旋转(0 r/min)处理的1/8四盒和1/16单盒及30 r/min处理的1/16单盒子样的缩分比误差显著高于对照外,旋转处理(转速≥7.5 r/min)的单盒、双盒或四盒子样的缩分比误差不高于四分法对照。因此,在进行样品前处理的分样工作中应用旋转式多比例分样方法是可行的,应设置转速≥7.5 r/min,取相对2个扇盒或十字相对4个扇盒形成的子样。     

基于注意力机制的时空卷积数控机床热误差模型研究

为了提高数控机床热误差模型的精度与泛化性,提出了基于注意力机制的长短时记忆卷积神经网络(Long short term memory convolutional neural network based on attention mechanism, AM-CNN-LSTM)热误差模型。利用卷积神经网络提取高维数据空间状态特征的能力和长短时记忆网络提取长时间序列状态特征的能力,构建具有2个支路的热误差模型,分别提取特征后输入到注意力机制中进行特征重要性重构,建立原始数据与热误差的特征映射,最后通过全连接层进行热误差预测。采用G460L型数控机床进行实验数据采集,将不同季节采集到的温度数据和热误差作为模型输入,采用循环学习率与正则化优化方法对模型进行训练。与LSTM、ConvLSTM和CNN-LSTM热误差模型对比,结果表明,AM-CNN-LSTM模型对特征还原能力最强,残差波动范围最小,其残差范围较最大值下降62.09%,模型预测精度在2.4μm以内。     

刚柔耦合串联机械臂末端位置误差分析与补偿

机械臂连杆柔性、关节柔性等非线性变形的综合影响,导致其末端位置发生偏离而产生误差。本文以IRB1410型串联机械臂为研究对象,采用理论分析、仿真分析与实验验证相结合的方式,对机械臂末端位置误差进行分析与补偿研究。首先,建立机械臂刚柔耦合理论误差模型,并运用Newmarkβ法进行数值仿真分析;联合ANSYS和ADAMS进行刚柔耦合机械臂末端位置运动误差仿真;为了实现快速补偿,提出基于BP神经网络的伪目标点法对位置误差进行补偿,补偿后其位置误差均方根减小了68.3%,说明该方法具有较好的补偿效果;最后,自主设计并搭建了测量实验平台,采用所提算法进行了误差补偿实验,对比补偿前后距离误差,补偿后误差均方根减小了77.01%,验证了伪目标点法对柔性误差补偿的有效性。     

大空间运动3-RRRU并联机器人运动学标定与误差分析

并联机器人具有高速、高刚度和大负载等明显优势,被广泛应用到农业和工业领域,但多关节导致该类机器人控制精度不高。针对大空间运动3-RRRU并联机器人的运动学建模和误差标定方法展开了系统、深入研究。综合应用DH法和空间矢量法建立了机器人的运动学模型,在此基础上,借助偏微分理论推导并建立机器人的误差模型;应用激光跟踪仪进行不同轨迹下机器人的空间位置数据采集,对一般遗传算法进行改进,以等步距搜索策略实现主要遗传算子的优化,并通过全局数值寻优获取机器人的误差补偿数据,完成标定和补偿工作。实验表明：基于直线标定方式,补偿后直线轨迹跟踪误差控制在0.14～1.34mm,但不适用于曲线轨迹补偿,其实测补偿后的最大误差高达5.08mm。曲线轨迹标定精度高于直线轨迹标定,补偿后将直线和曲线两种路径下的最大误差分别降低至1.18mm和1.56mm。该标定方法自动化程度高,适用于含有大量关节并联机器人的误差标定工作。     

精准网络通信理念在智能作物收获机中的应用

为进一步提高作物收获机的智能通信水平,从精准网络理念角度出发对其通信系统展开研究。全面理解智能收获机一站式的集中收获作业机理,考虑车辆运动的非线性特点及收获执行部件(摘辊系统及相连接组件等)运动参数与作物收获破损关系,搭建该类型智能化作物收获机的精准网络通信控制模型,运用数据传感融合核心算法,针对通信系统硬件配置及软件控制驱动进行设计,并进行通信系统应用试验。试验结果表明:收获机速度、高度设定数值与通信装置监测传输误差分别为5.33%、2.12%,执行部件转速、位置设定与通信系统监测传输误差分别为2.57%、7.27%,均控制在7.5%之内,满足收获机的控制与通信精度要求。