Machining accuracy improvement for a dual-spindle ultra-precision drum roll lathe based on geometric error analysis and calibration

This paper performs a comprehensive analysis and calibration on the geometric error of the ultra-precision drum roll lathe with dual-spindle symmetrical structure and cross slider layout. Firstly, the volumetric error model which contains all geometric errors of the dual-spindle ultra-precision drum roll lathe (DSUPDRL) is developed based on the combination of the homogenous transfer matrix (HTM) and multi-body system (MBS) theory. Secondly, sensitivity analysis for the volumetric error model is conducted to identify the sensitive geometric error components of the DSUPDRL using an improved Sobol method based on the quasi-Monte Carlo algorithm. The result of sensitivity analysis laid the foundation for the subsequent geometric error calibration. Then, some sensitive error components along the X and Z directions are calibrated using a laser interferometer and a pair of inductance displacement probes. Besides the volumetric error model, the concentricity error caused by dual-spindle symmetrical structure is proposed and calibrated by the on-machine measurement using a classic reversal method. Finally, a large-scale roller mold with a diameter of 250 mm and a length of 600 mm is machined using the DSUPDRL after calibration. The experimental result shows that 1.4 μm/600 mm generatrix accuracy is obtained, which validate the effectiveness of the geometric error analysis and calibration.     

Genetic algorithm to simultaneously optimise stope sequencing and equipment dispatching in underground short-term mine planning under time uncertainty

ABSTRACT

The main issue in short-term planning optimisation for underground mining is organising the mining process with limited resources in the form of equipment and materials to satisfy production targets and stable feed grade requirements. In this paper, an integrated optimisation model is proposed based on an individual generation algorithm and an improved Genetic Algorithm to simultaneously optimise stope extraction sequencing and timing, extracted ore grade and equipment dispatching. The model objectives are to shorten the time gap between the stope mining processes and the overall working time. When the uncertainty of equipment working time is taken into account in a short-term scheduling model, the Monte Carlo simulation is applied to evaluate the risk of not meeting the production target. A modification strategy is defined to evaluate equipment failure. Consequently, any available equipment is automatically reassigned to the mining site to replace the broken-down equipment. A case study is used to validate the model in the Sanshandao gold mine of China to formulate an optimal monthly schedule. Compared with the conventional approach, the new model could reduce the variance of ore tonnage and feed grade and improve the equipment allocation efficiency. Discussions are presented to address the uncertainty.     

高斯混合模型结合加权似然的目标跟踪算法

鉴于高斯混合模型对背景变化快时无法精确检测出目标和目标跟踪的适应性差等瑕疵，提出了基于加权似然跟踪器来改进高斯混合模型实现运动目标跟踪算法。主要引入了自适应高斯混合模型来实时检测运动目标，然后空间加权似然来进行视频中的目标定位，引入加权似然期望值来改进高斯混合模型处理视频中的多尺度、多角度变化的目标跟踪不精准问题。通过VOT 2014 dataset对比实验结果表明提出的基于加权似然跟踪（Weighted Likelihood Tracking，WLT）和改进高斯混合模型（Improved Gaussian Mixture Model，IGMM）的目标跟踪算法较传统高斯混合模型跟踪算法在跟踪的精度有较大提高。在应对多尺度、多角度变化的目标跟踪表现出了较大的优势。     

镁改性活性炭强化活性污泥处理混合污水研究

基于序批式活性污泥法(SBR)工艺,将镁盐改性活性炭(MgO-PAC)与传统活性炭(PAC)混合而成MPAC材料,用于处理生活与工业混合污水。通过连续30 d的运行实验,探讨了MPAC材料对生活与工业混合污水中COD、NH4^+-N和TP的去除效果以及对污泥的比耗氧速率、沉降性能和微生物多样性的影响。结果表明,投加MPAC材料对污水中COD的去除率提升了12.7百分点,对TP的去除率提升了17.5百分点,对NH4^+-N的去除率超过86.4%。投加MPAC后处理效果更好的重要原因,在于MPAC使得活性污泥的沉降性能和比耗氧速率得到明显改善,也提升了污泥的微生物丰度。MPAC对活性污泥处理生活与工业混合污水具有强化作用。     

Influence of doped platinum nanoparticles on photocatalytic performance of CuO–SiO2 for degradation of Acridine orange dye

Preparation of cupric oxide-silicon dioxide nanoparticles was carried out using a sol-gel method. Cupric oxide-silicon dioxide nanoparticles were decorated by different weight percent of platinum (0.5, 1.0, 3.0 and 5.0 wt %) using method of photoassisted deposition. XRD remarks revealed that XRD patterns for all samples are composed of cupric oxide. Therefore, silicon dioxide is amorphous and decoration of cupric oxide-silicon dioxide nanoparticles by platinum has no effect on the formed phase. Also, due to low percent of platinum there are no peaks for platinum oxide or platinum. Cupric oxide has bandgap energy absorb in visible region but has high e-h recombination rate. Decoration of cupric oxide-silicon dioxide nanoparticles by platinum was decreased bandgap energy from 2.38 to 1.91 eV and also decrease rate of e-h recombination rate. The photocatalytic activity of platinum decorated cupric oxide-silicon dioxide nanoparticles was measured under visible light for Acridine orange dye degradation. 100% of Acridine orange dye can be degraded using 3.0 wt % of platinum decorated cupric oxide-silicon dioxide photocatalyst, 1.2 g/L dose of platinum decorated cupric oxide-silicon dioxide photocatalyst and 30 min reaction time. 3.0 wt % of platinum decorated cupric oxide-silicon dioxide photocatalyst has photocatalytic stability for five times.     

SBR处理村镇生活污水试验研究

研究了用SBR处理系统在不同水力停留时间,不同污泥龄(SRT),不同温度条件下对村镇生活污水的去除有机物、脱氮除磷效果。结果表明,考虑到脱氮除磷效果并兼顾经济的原则,水力停留时间采用6h比较合理,SBR反应器的最适SRT为20d;温度SBR反应器的除磷效果影响较小,SBR反应器更适合处理低温污水。     

Improved average consensus algorithm based distributed cost optimization for loading shedding of autonomous microgrids

This paper addresses a new distributed cost optimization (DCO) method for load shedding (LS) of an islanded microgrid considering cost. A two-layer improved average consensus algorithm (IACA) of multi-agent system (MAS) is proposed, and the consensus characteristic of which is analyzed in detail. With the global information discovered in the first layer of the IACA, the DCO of LS can be solved by using the synchronization processing of the IACA in the second layer. PSCAD/EMTDC-based simulation models are built to study the value settings of consensus constants and the performances of the proposed DCO method. Simulation results verified the convergence improvement of the IACA and the effectiveness of the proposed DCO.     

Ascorbic acid-assisted hydrothermal route to create mesopores in polymeric carbon nitride for increased photocatalytic hydrogen generation

The facile synthesis of mesoporous polymeric carbon nitride (PCN) can enlarge the surface area and provide mass transport channels, which thus potentially boosts its photocatalytic H₂ generation. However, the formation of mesopores in PCN are mainly relying on the hard and soft templates with tedious operations, and it remains a grand challenge in preparing mesoporous PCN without the assistance of templates. Herein we report on an ascorbic acid-assisted hydrothermal route to effectively create the mesoporous in bulk PCN. The mesopores thus formed a typical IV isotherm with an H3 hysteresis loop, and have a pore size distribution of ∼3.8 nm. Moreover, the crystallinity of mesoporous PCN was improved with ascorbic acid-assisted hydrothermal treatment. Meanwhile, ascorbic acid can be converted to carbon materials under hydrothermal conditions. As a result, an increased photocatalytic H₂ generation was realized under visible light exposure. The highest H₂ generation rate is up to 26.8 μmol h⁻¹ for Pt/CN-A10%, near 10 times higher than that of Pt/PCN (2.7 μmol h⁻¹). This work highlights the effectiveness of organic acid-assisted hydrothermal treatment for synthesizing mesoporous PCN for increased photocatalytic performance.