Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture

Agricultural robots rely on semantic segmentation for distinguishing between crops and weeds to perform selective treatments and increase yield and crop health while reducing the amount of chemicals used. Deep‐learning approaches have recently achieved both excellent classification performance and real‐time execution. However, these techniques also rely on a large amount of training data, requiring a substantial labeling effort, both of which are scarce in precision agriculture. Additional design efforts are required to achieve commercially viable performance levels under varying environmental conditions and crop growth stages. In this paper, we explore the role of knowledge transfer between deep‐learning‐based classifiers for different crop types, with the goal of reducing the retraining time and labeling efforts required for a new crop. We examine the classification performance on three datasets with different crop types and containing a variety of weeds and compare the performance and retraining efforts required when using data labeled at pixel level with partially labeled data obtained through a less time‐consuming procedure of annotating the segmentation output. We show that transfer learning between different crop types is possible and reduces training times for up to 80%. Furthermore, we show that even when the data used for retraining are imperfectly annotated, the classification performance is within 2% of that of networks trained with laboriously annotated pixel‐precision data.     

Dairy farmers with larger herd sizes adopt more precision dairy technologies

An increase in the average herd size on Australian dairy farms has also increased the labor and animal management pressure on farmers, thus potentially encouraging the adoption of precision technologies for enhanced management control. A survey was undertaken in 2015 in Australia to identify the relationship between herd size, current precision technology adoption, and perception of the future of precision technologies. Additionally, differences between farmers and service providers in relation to perception of future precision technology adoption were also investigated. Responses from 199 dairy farmers, and 102 service providers, were collected between May and August 2015 via an anonymous Internet-based questionnaire. Of the 199 dairy farmer responses, 10.4% corresponded to farms that had fewer than 150 cows, 37.7% had 151 to 300 cows, 35.5% had 301 to 500 cows; 6.0% had 501 to 700 cows, and 10.4% had more than 701 cows. The results showed that farmers with more than 500 cows adopted between 2 and 5 times more specific precision technologies, such as automatic cup removers, automatic milk plant wash systems, electronic cow identification systems and herd management software, when compared with smaller farms. Only minor differences were detected in perception of the future of precision technologies between either herd size or farmers and service providers. In particular, service providers expected a higher adoption of automatic milking and walk over weighing systems than farmers. Currently, the adoption of precision technology has mostly been of the type that reduces labor needs; however, respondents indicated that by 2025 adoption of data capturing technology for monitoring farm system parameters would be increased.     

Top-down技术精密度法评定饮用水中氯酸钾含量的不确定度

目的使用Top-down技术精密度法评定饮用水中氯酸盐含量的不确定度。方法按照GB/T5750.10-2006《生活饮用水标准检验方法消毒副产物指标》规定的分析方法,通过对质控样品和能力验证样品的测定,基于Top-down精密度法的原理对数据进行检验和分析。结果通过偏移和精密度核查,在证明分析系统受控的情况下,计算得到不确定的结果U=0.056 mg/L。结论 Top-down技术用于化学分析不确定评估将不确定评估与实验室内部质量控制工作结合,减少了工作量,具有广泛的应用前景。     

精密磨床转台静压轴承的强健化设计

针对精密磨床转台静压轴承性能仿真数据与其回转精度实测数据不一致的问题，为提高转台静压轴承的设计水平，提出了静压轴承的强健化设计方法。该方法考虑了轴承结构参数在轴承全生命周期内的变化，分析了半径间隙、油腔尺寸、节流比及润滑油黏度在设计、加工、装配和服役4个阶段的变化规律，重点研究了半径间隙在各阶段对轴承性能造成的影响，给出了转台静压轴承的强健化设计流程。通过一个径向轴承的设计实例对该强健化设计方法进行了说明，并将设计结果与传统设计进行了对比。对比的指标是轴承在4个阶段的刚度、承载力和温升，这3个指标对轴承回转精度有直接影响。研究表明：进行强健化设计后，在生命周期内静压轴承的刚度和承载力的变化量为10%~27%，温度的变化量为0.5%~1.6%，较传统设计更能保证转台回转精度的稳定。     

高精度多环片自动装配控制技术

为了实现对微小环片零件的自动化装配,搭建了自动装配系统.通过4根直线导向轴与4个直线轴承来提高系统的导向精度和刚度.采用直线导轨进行各装配作业模块之间的切换,保证了微小环片零件的自动装配与取出.在环片的装配方向上,螺旋升降机和光栅尺实现环片的位置精度控制.在Lab VIEW编程环境中,采用分层软件架构和模块化控制思想,避免了不必要的数据循环检测与丢失,能够达到环片组件的装配精度要求.控制系统分为系统初始化模块、参数设置模块、装配模块和取出模块,自动装配系统通过各个模块间的相互交流配合完成装配任务.采用本文中自动装配系统装配环片的实验结果表明,环片零件装配的最大位置误差为26μm,垂直度误差为17μm,平均装配时间为75 s/片,可满足环片组件所需的精度要求.     

抽采孔液态CO2预裂效果显微CT实验研究

为研究液态CO2预裂爆破后,煤体内裂隙发育情况,采用高精度微焦点显微CT系统,对预裂后不同区域的煤样进行CT扫描,并利用Photoshop进行孔裂隙占比统计学分析。研究结果显示,距预裂孔4 m处的煤体裂隙发育明显,孔裂隙占比增加了一倍,而在5 m处的煤体裂隙则发育较弱。表明抽采孔内采取液态C2预裂技术后,4 m范围内的煤体裂隙得到了充分发育,为瓦斯抽采提供了有利条件。     

压电精密驱动柔性微夹钳设计

为了实现对微纳尺度下物件的精密夹持,建立了柔性微夹钳系统。并对该系统柔性夹钳设计、运动学、动力学和控制方法等进行研究。首先,利用柔性铰链设计方法设计了柔性微夹钳,利用伪刚体法建立了机械的伪刚体模型。接着,以伪刚体模型法建立了系统的运动学模型,即机械放大比和输入刚度等数学模型。然后,利用拉格朗日方法建立了系统的动力学方程,得出系统的自然振动频率。最后,通过ANSYS有限元方法对系统建立的模型进行了仿真分析和验证,此外,利用PID控制算法对微夹钳系统进行实验控制。实验结果表明:跟踪控制结果误差为2.4%;放大比为9.12倍。基本满足微纳尺度下的微夹持工作,其工作精度可达微米级别甚至纳米级别,符合设计要求。     

圆盘类精锻件顺序转向输送方法的研究及应用

针对圆盘类精锻件输送问题,提出了一种圆盘类精锻件顺序转向输送方法,对圆盘类精锻件多排变单排的输送形式及多排布局方案进行研究。输送过程分为两个阶段:第1阶段,第1输送装置进行多排输送;第2阶段,经自动落料装置按顺序依次落料至第2输送装置,实现了转向、单排输送。其中,第1输送装置的多排布局分别为由远及近、由近及远两种形式,第2输送装置的输送速度分别设置为ΔL/P、2ΔL/P、3ΔL/P、4ΔL/P,通过对以上8种组合的位置仿真分析得到了合理方案。研究及应用表明,若第2输送装置输送速度设置为4ΔL/P,则由近及远多排布局方案的布局形式满足了顺序转向的输送要求。     

基于敏感度分析的机床关键几何误差元素辨识与评定

为了正确识别和判定机床关键几何误差元素对机床精度设计的影响,以PCV-620立式加工中心为研究对象,采用多体系统理论建立机床空间误差模型,从而得到机床几何误差元素与机床精度之间的关联函数。对空间误差模型进行灵敏度分析,获得机床各运动方向的局部灵敏度系数,完成机床关键几何误差元素的初步辨识。以局部灵敏度系数为基础,提出一种与局部灵敏度系数和工作空间中任意位置处的几何误差元素值相关的全局灵敏度系数计算方法,将其作为机床关键几何误差元素的辨识和评定标准,分析得到PCV-620立式加工中心的关键几何误差元素包含3项定位误差、3项垂直度误差和5项直线度误差。     

波前传感器电铸镍层应力实时检测精度评估

目的 搭建电铸应力实时检测平台，评估其测量精度，并探明电化学沉积过程中镍层平均内应力的变化规律。方法 采用横向剪切波前传感器搭建电铸应力实时检测平台，通过测量在铸层应力作用下电铸基底弯曲的曲率半径，利用Stoney公式计算铸层平均应力。采用参考球面反射镜评估横向剪切波前传感器曲率半径的测量精度，并在0.5 A/dm2电流密度下进行电铸应力实时检测实验，对铸层平均应力测量极限进行评估，同时对检测误差进行分析。结果 横向波前传感器曲率半径测量精度为99.22%，在0.5 A/dm2电流密度下，所搭建的铸层应力实时检测平台可测量的最小厚度为5.1 μm，由曲率测量波动带来的应力检测误差为1.3 MPa。实验测得铸层平均应力随铸层厚度的增加而变大，当铸层厚度达到30 μm左右，铸层平均应力趋于稳定，应力大小为79.7 MPa。同时发现，当铸层厚度小于30 μm时，沿电铸基底长度方向的铸层平均应力明显大于宽度方向铸层平均应力，随铸层厚度的增加，两个方向的应力大小趋于等值。结论 采用横向剪切波前传感器搭建的电铸应力检测平台，能有效对铸层应力进行高精度的实时测量，为精密电铸过程中应力变化规律的研究提供了检测技术基础。