某型柴油机水泵、机油泵间隙调整工装的应用

为了方便某柴油机前端水泵和机油泵齿轮间隙的调整,改变以前传统的调整方法,通过长期在装配现场的观察和了解,设计出某柴油机前端水泵和机油泵齿轮间调整工作,经现场使用验证;该工装安全、小巧轻便精度高,改善了装配的劳动强度和装配质量。     

基于参数预标定的长行程PMLSM无传感器控制

为了解决长行程定子不连续永磁直线同步电机存在的因无法全程安装位置传感器和不同动子和定子之间的电磁参数不固定所造成的控制性能下降的难题,提出一种在每一段定子内先进行参数标定,再进行速度控制的控制系统设计。首先,在动子进入过程中,对电机进行电磁参数标定,根据标定参数对控制器参数进行调整,以达到更好的控制效果。然后,使用无位置传感器控制系统使动子快速达到设定速度值并稳定运行。实验结果表明:动子进入过程参数标定精度分别为0.002Wb和0.000 4H;无位置传感器控制中位置估计精度为0.63mm,速度收敛时间为0.45s,稳态误差为0.02m/s。基本满足永磁直线同步电机用于长行程运输的控制快速性、稳定性等要求。     

奥钢联板坯铸机驱动力报警问题的分析及改进

浇铸过程中，驱动力报警会导致紧急停浇甚至滞坯事故发生。为防止事故发生，通常采用降速、强冷等措施，但降速造成成本浪费，强冷又产生裂纹等质量缺陷，两者都难以满足生产需要。通过对铸机的各项参数对比分析，找到影响驱动力报警的主要原因为辊缝异常，轻压下模型参数、冷却工艺设置不合理等，通过调整二冷工艺、优化模型参数、加强轻压下区域扇形段辊缝维护，可以达到明显降低驱动力、消除报警的目的，从而保证连铸生产稳定。     

光核桃仁油和蛋白质同步提取工艺优化及油脂品质分析

以西藏光核桃为原料,采用水剂法提取结合酶法破乳技术分离其中的油脂和蛋白质,优化了光核桃仁油脂与蛋白质水剂法同步提取的工艺条件,并分析了油脂的主要理化指标及脂肪酸组成。结果表明:西藏光核桃仁油与蛋白质同步提取最优工艺为物料粒径150目、液料比8:1 (mL/g)、pH 10、浸提温度50℃、提取时间5h、搅拌速度80r/min,该工艺条件下核桃仁油提取率为(67.79±2.97)%,蛋白质提取率为(78.13±1.53)%。光核桃仁油脂具有优良的理化性质,并检测出12种脂肪酸组分,主要由顺式油酸(57.32%)、亚油酸(31.65%)、棕榈酸(6.49%)和硬脂酸(2.29%)组成,其中饱和脂肪酸7种,单不饱和脂肪酸3种,多不饱和脂肪酸2种;油脂以不饱和脂肪酸为主,相对百分含量为89.43%,其中多不饱和脂肪酸相对百分含量为31.76%,单不饱和脂肪酸相对百分含量为57.67%。     

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。     

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.     

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。     

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。     

Physics‐based spectral sharpening through filter‐chart calibration

The spectral overlap of color‐sampling filters increases errors when using a diagonal matrix transform, for color correction and reduces color distinction. Spectral sharpening is a transformation of colors that was introduced to reduce color‐constancy errors when the colors are collected through spectrally overlapping filters. The earlier color‐constancy methods improved color precision when the illuminant color is changed, but they overlooked the color distinction. In this article, we introduce a new spectral sharpening technique that has a good compromise of color precision and distinction, based on real physical constraints. The spectral overlap is measured through observing a gray reference chart with a set of real and spectrally disjoint filters selected by the user. The new sharpening method enables to sharpen colors obtained by a sensor without knowing the camera response functions. Experiments with real images showed that the colors sharpened by the new method have good levels of color precision and distinction as well. The color‐constancy performance is compared with the data‐based sharpening method in terms of both precision and distinction. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 564–576, 2015