Outlier mining based abnormal machine detection in intelligent maintenance

Assessing machine’s performance through comparing the same or similar machines is important to implement intelligent maintenance for swarm machine. In this paper, an outlier mining based abnormal machine detection algorithm is proposed for this purpose. Firstly, the outlier mining based on clustering is introduced and the definition of cluster-based global outlier factor (CBGOF) is presented. Then the modified swarm intelligence clustering(MSIC) algorithm is suggested and the outlier mining algorithm based on MSIC is proposed. The algorithm can not only cluster machines according to their performance but also detect possible abnormal machines. Finally, a comparison of mobile soccer robots’ performance proves the algorithm is feasible and effective.     

Diverse traversability mapping using hybrid vision system for lunar rover

Autonomous functions including mapping and path planning are very important to ensure efficient exploration and safe navigation of unmanned rover. Conventional navigation schemes based on equipments such as GPS and magnetic sensors have been proven to be ineffective on lunar surface, while sophisticated dead reckoning approach lacks accuracy in loose soil due to slippage. In this paper, we propose a hybrid vision system (HVS) which consists of one stereo and one omnidirectional vision sensor, attempting to integrate the advantages of diverse vision systems. The hierarchical mapping reconstructs environment through HVS in different resolutions and structures, named qualitative, rough and detailed map. These maps are employed for path planning which navigates the rover towards specified destinations autonomously, avoiding obstacles in its way. The HVS aims at providing more efficient and safe navigation. Simulations and experiments demonstrate the functionality and advantage of our approach.     

遥操作机器人系统主从控制策略

近年来主从式机器人系统被广泛应用在医疗、深海等非结构性环境.在现有研究成果的基础上,研究了主从式机器人系统的控制策略.采用增量式位置控制,易于建立主端与从端的工作空间映射,并增加位置反馈提高系统的控制精度;解决了主从运动比例变化的问题;并通过搭建的主从机器人系统对位置控制策略进行验证,结果表明了系统位置控制策略的准确性和实时性.将主从位置误差引入系统的力反馈控制策略,分析系统的稳定性,并通过MATLAB/Simulink对力反馈策略进行仿真及实验验证,仿真与实验结果验证了所建立控制策略的有效性.     

NIR Hyperspectral Imaging Measurement of Sugar Content in Peach Using PLS Regression

Near infrared (NIR) hyperspectral imaging measurement of sugar content in peach was introduced. NIR spectral images (650～1 000 nm, resolution: 2 nm) of peach samples were captured with developed hyperspectral imaging setup. Partial least square (PLS) regression prediction model was developed to estimate the sugar content in peach; step-wise backward method was utilized to determine optimal wavelength subsets. Experimental results show that the calibration model with optimal wavelength subsets has a correlation coefficient of prediction of 0.97 and a standard error of prediction of 0.19, the prediction accuracy is higher than the calibration model applied over the whole wavelength, which proves that variable selection plays an important role in improving the prediction accuracy of PLS regression model.     

A Machine Vision System for Ball Grid Array Package Inspection

An optical inspection method of the Ball Grid Array package (BGA) was proposed by using a machine vision system. The developed machine vision system could get main critical factors for BGA quality evaluation, such as the height of solder ball, diameter, pitch and coplanarity. The experiment has proved that this system is available for BGA failure detection.