大型车辆底盘测功机测试软件系统的开发研究

大型底盘测功机是在室内完成汽车经济性试验、动力性试验、排放性能评价与分析、可靠性试验以及与车辆传动系有关的专项试验等所必需的大型设备。为了充分发挥底盘测功机的巨大作用,保证各项性能试验的正确性、可靠性、快速及方便,该文以自行开发的大型汽车底盘测功机为基础,以国家的有关法规标准为依据开发了用于各种试验的测试控制软件系统,并通过试验进行了验证,为有效利用底盘测功机奠定了基础。     

苹果－瓦楞纸板缓冲跌落动力学模型

基于瓦楞纸板受冲击压缩变形的特征,提出-表征其非线性冲击力-变形模型,结合其跌落冲击试验结果表征模型参数.在此基础上,建立"富士"苹果-瓦楞纸板缓冲跌落动力学模型方程,进行不同高度下的苹果缓冲跌落冲击响应的理论分析,并与试验结果进行比较.结果表明,试验结果与理论模型结果吻合性好,所提出苹果-瓦楞纸板缓冲跌落冲击模型能合理地表征苹果缓冲跌落冲击动力学特征,瓦楞纸板能显著降低苹果跌落的冲击加速度.研究结果为果品缓冲包装设计提供了理论基础.     

基于视触觉与深度学习的猕猴桃无损硬度检测方法

硬度是确定猕猴桃成熟度的重要指标之一,对其贮藏周期与销售节点均具有重要指导意义。针对现阶段缺乏使用简易、成本低且精度高的猕猴桃无损硬度检测方法的问题,提出了一种基于视触觉与深度学习的猕猴桃硬度检测方法,通过分析柔性触觉传感层与猕猴桃接触时的形变,获取猕猴桃的动态触觉信息,并据此推断其硬度。以树莓派开发板为机电控制平台,制作了猕猴桃视触觉序列图像采集装置,并对装置按压猕猴桃间隔3h后接触面果肉与非接触面果肉的CIELAB颜色分量平均数进行差异显著性检验,随后采集了猕猴桃视触觉序列图像数据集600组,分别搭建了CNN网络、CNN-LSTM迁移学习网络、CNN-LSTM联合学习网络对视触觉序列图像进行分析及硬度预测。研究结果表明,接触面果肉与非接触面果肉颜色L*、a*、b*三通道分量下平均值无显著差异;深度学习模型LSTM引入长时和短时信息可以动态关联CNN提取的单帧图像特征,从而有效推断猕猴桃硬度,其中CNN-LSTM联合学习模型预测效果最优,其均方根误差(RMSE)、平均绝对误差(MAE)、决定系数R2分别为 1.611N、1.360N、0.856,优于现阶段光谱技术检测猕猴桃硬度的结果,随后将模型嵌入树莓派中制作了猕猴桃硬度自动检测装置,可实现短时间内猕猴桃硬度的较为准确检测。因此,结合视触觉传感方法与联合学习模型可以实现对单个猕猴桃硬度的准确无损测量。     

基于EIT的土壤中油菜根茎检测

主要应用EIT技术检测土壤中油菜的根茎。搭建16电极数据采集系统,采用相邻法激励测量模式获得成像数据并应用基于MatLab的MNR算法进行图像重建。结果表明:本实验方法能实现油菜根茎的无损检测,可以检测出油菜根茎的位置和大小信息;对干枯的油菜根茎检测效果比新鲜根茎差,而对于腐烂的根茎,不能检测出来。据此,可以对土壤中油菜根茎进行可视化观察,了解其根系生长情况。     

乳酸聚丙烯酰胺凝胶电泳在辣椒种子纯度检验中的应用

提取辣椒种子的盐溶蛋白,在乳酸缓冲系统下电冰,通过对凝胶系统的调整,得出一套可以很好地显示辣椒各上子蛋白差异的电泳方法。上坷以很好地区分一些辣椒品种的父本、母本以及杂种一代。可以用作一些辣椒品种的纯度检验。     

Real-Time Soil CO2 Respiration Rate Determination and the Comparison between the Infrared Gas Analyzer and Microrespirometer (MicroRes®) Methods

Soil carbon dioxide (CO₂) respiration is one of the important soil health parameters that provides a general assessment of soil microbial activity and soil quality. Soil respiration rates, however, have not been widely applied in soil testing protocols mainly because the traditional methods are either inconvenient, technically cumbersome or too expensive. Currently, only two methods are available for a true real-time soil respiration rate determination (<2 h): the infrared gas analyzer (IRGA) and the microrespirometer (MR or MicroRes^®) methods. We analyzed the real-time soil respiration rates of 20 soil samples from fifteen states after various periods of incubation using the IRGA method and the MR method. The measured soil respiration rates ranged from 0.4 µL CO₂/h/g to 9.0 µL CO₂/h/g. Both methods show precision in soil respiration determinations (CV = 12.7% and 11.9%, respectively). Comparison of the results between the IRGA and MR methods indicates high degrees of agreement (r² = 0.914). This study shows that the MR method is a simpler and more cost-effective alternative for real-time soil respiration rate determinations.     

苹果外部缺陷全表面在线检测分选装置研发

中国是水果消费大国,但在水果产后检测装备方面相对滞后。针对目前在线检测装置无法采集苹果全表面图像信息且无法精确计算缺陷面积的问题,该研究以表面缺陷面积的快速检测为主要目标,提出苹果全表面图像合成算法,设计了一套苹果外部品质在线检测及分级装置。该研究以苹果为例,基于球模型提出苹果全表面图像合成算法、缺陷面积校正算法精确计算苹果的表面缺陷面积。通过试验验证,对苹果表面图像进行分割合成后,整体的图像的漏检率为0。提出缺陷面积校正算法,可以计算图像中位于任意位置的苹果缺陷真实面积,选取了120个样本进行验证,其中擦伤样本、碰伤样本、痘斑病样本、表面腐败样本各30个。4种表面损伤面积的预测值和真实值的决定系数R²均在0.97以上,均方根误差(Root Mean Squared Error, RMSE)在4 mm²以下。在偏角试验中,4种表面损伤面积的预测值和真实值的决定系数R²均在0.974 2以上,RMSE在6.304 4 mm²以下。装置检测苹果的速度为2个/s,评级准确率为95%。研究结果表明,检测与苹...     

The determination of hot‐water‐soluble boron in some acid Oregon soils using a modified azomethine‐H procedure

Abstract

A method is proposed for determination of hot‐water‐soluble boron in acid soils from western Oregon. The soil sample is boiled in 0.02 M CaCl₂, filtered, and B determined using azomethine‐H. Soils extracted in this way yielded extracts with little color in them and the predicted error due to this color was 0.00–0.07 ppm B. The use of charcoal as a decolorizing agent resulted in comparatively high predicted errors.

Inductively‐coupled plasma emission spectroscopic (ICP) analysis of distilled water and 0.02 M CaCl₂ extracts indicated that the extractable B level was not affected by the presence of CaCl₂. Azomethine‐H yielded comparable values to ICP but the curcumin method tended to give high values for hot‐water‐soluble B.     

Portable soil test laboratory results compared to standard soil test values

Abstract

Results from a commercially available portable soil test laboratory were compared to standard soil test procedures used by a public soil testing laboratory. Standard soil tests examined were water extracted NO₃‐N, pH, Acid‐P, NaHCO₃‐P, and ammonium acetate extracted K. Approximately 35 to 55 different soils were used to compare methods for each soil test. Linear regression equations between the portable laboratory soil test values and those from the standard procedures were developed. The r² values for NO₃‐N, pH, Acid‐P, NaHCO₃‐P, and K were 0.970, 0.891, 0.734, 0.742, and 0.887, respectively. The coefficient of variability values for NO₃‐N, pH, Acid‐P, NaHCO₃‐P, and K were 10, 1, 13, 15, and 6%, respectively for the portable laboratory, and 9, 2, 8, 9, and 5%, respectively for the public soil testing laboratory. Multiple regression was used to relate soil properties to soil test results. The R2 values for NO3‐N, pH, Acid‐P, NaHCO₃‐P, and K were 0.970, 0.911, 0.860, 0.940, and 0.936, respectively.