基于视觉测量的挖掘机工作装置姿态测量系统

提出了一种基于视觉测量的挖掘机工作装置姿态测量方法。使用工业相机获取工作装置侧视图像,采用鞍点检测方法快速捕捉工作臂上的人工靶标;将靶标间的固定几何尺寸关系作为约束条件筛选出靶标中的鞍点并计算相应工作臂的姿态角;通过预判靶标的运动范围以缩小图像检测区域,提高算法处理速度。试验表明,与挖掘机上原有的拉线传感器测量系统相比较,动臂和斗杆姿态角动态测量偏差分别小于1°和2°,处理每帧工作装置运动图像平均用时在100 ms以内,验证了该方法对挖掘机工作装置姿态测量的可行性。     

地下凿岩设备的发展历程和趋势

论述了地下凿岩设备的发展历史、应用效果和发展趋势。     

动态图像处理技术在农业工程中的应用

近年来图像处理技术的应用已越来越广泛，如何将动态图像处理技术应用到农业工程对农业的自动化研究具有着重要意义：本文主要讨论了动态图像处理技术及其在农业丁程中的应用概况与未来展望，并对应用中存在的问题提出了几点思考与建议。     

农机制造企业供应链管理中的需求预测

随着经济全球化和知识经济时代的到来,我国农机企业所面临的市场竞争更为残酷。本文从建立和加强供应链管理角度出发,探讨了农机企业供应链管理中的需求预测问题,包括预测在供应链管理中的重要性和特点,影响预测的因素及预测方法分类,农机企业供应链需求预测的基本方法。     

计算机辅助声强测量法识别车辆主要噪声源

描述了计算机辅助声强测量原理，并利用计算机声强测试系统及声强分析择小客车进行了声强测量和声场分析，给出了小客车车外声的三维声强图、等声强图及其频谱图，方便地识别出了小客车主要噪声原。为这种喾车车外噪声控制提供了依据。     

应用声强测试技术对发动机噪声源识别的研究

通过对一台增压柴油机的噪声进行声强测试,将测试得到的数据用STARAcoustics声强软件进行处理和分析,得出发动机各个包络面的等声强分布、声强矢量分布和声功率的计算结果;利用这些结果着重分析和识别了该发动机的主要噪声源,确定了其噪声源的位置、主要噪声频率成分和声功率的贡献,为降低发动机噪声提供了改进依据.结果表明,通过与9点法试验结果的定性比较,能够更准确地判断噪声源的位置及其频率分布.     

明渠测流及量水槽精度的鉴定

水的逐步商品化要求供水计量精度得到保证，特别是大流量的农业灌溉或工业供水尤显重要。大水港灌溉工程高干渠渠首无喉道量水槽的量水精度，采用明渠测流法进行精度鉴定，并在定量定性的基础上，评定量水槽的适用性。     

Using the RUSLE to identify factors controlling erosion rates of mine soils

Observable differences in particle size, smoothness and compaction between cap site (slope 2·8 per cent) and batter site (slope 20·7 per cent) surfaces on the waste rock dump at Ranger Uranium Mine were quantified in terms of revised universal soil loss equation (RUSLE) parameter values. Cap site surface material had a K_m (erodibility corrected for sediment density) of 0·030 and batter site surface material had a K_m of 0·0056. Using these K_m values (derived from particle size distributions), slope length and steepness (LS) factors of 0·36 for the cap site and 3·66 for the batter site, and a cover (C) factor of 0·45 for the cap site and 0·16 for the batter site, the RUSLE predicts an erosion rate from the cap site that is 1·9 times greater than erosion from the much steeper batter site. The RUSLE indicates that the finer particle size and blocky soil structure of the cap site (D₅₀ = 0·91 mm) compared with the looser granular structure of the batter site (D₅₀ = 1·74 mm) strongly influence erosion. The predictions are similar to observed soil losses from erosion plots on these sites under rainfall simulation events, for which the measured erosion rate from the cap site was approximately twice that from the batter site. For the RUSLE to predict the observed erosion rates, the support practice (P) factor for the cap site would have to be approximately 30 per cent greater than the P factor for the batter site. The higher cap site P factor probably results from smoothing and compaction caused by vehicle movement across the surface. Compaction is considered to have greatly reduced infiltration capacity, thus increasing the erodibility of the cap site. Vehicles probably also crushed the surface material at the cap site, creating the observed finer particle size distribution and further increasing the erodibility. Compaction, through its effects on erodibility (K_m) and surface roughness (P), is concluded to be the major cause of higher erosion from the cap site, even though the slope steepness is 10 times less. Parameterisation of the RUSLE quantifies the differences between sites and explains the unexpected erosion rates observed. The results highlight the need for careful management of rehabilitated sites to avoid increases in erosion which may arise from compaction by machinery.