具有变频器的矿井低压漏电保护研究

为了解决移动变电站低压侧为变频器供电时漏电保护装置误动的问题，提出了基于傅式算法的附加直流原理漏电保护新方法。通过理论分析和MATLAB/Simulink仿真，研究了具有变频器的矿井低压供电系统附加直流原理漏电保护，提出由傅式算法分解出采样电压直流分量以反映电缆绝缘水平的保护方法；同时分析了其他因素对直流分量的影响。研究结果表明:变频器对传统附加直流保护整定值有较大影响，易造成漏电保护装置误动且无法实现电缆的在线绝缘监测；所提出的直流分量法能准确测量电缆对地绝缘电阻，且可消除电缆分布电容、变频器载波频率、变频器输出频率等其他因素的干扰；采用该漏电保护方法，可承受变频器投入时对采样电压造成的较大冲击，不必在启动期间解除漏电保护装置，能够消除在此期间存在的人身触电安全隐患。     

基于遗传神经网络的除湿机故障诊断与寿命预测

目的识别除湿机的性能状态和预测吸附剂的剩余寿命。方法针对除湿机故障过程缓变的特点,提出一种基于数据驱动的遗传神经网络模型。首先,为解决设备失效程度划分模糊的问题,由5个热力参数组成反映吸附剂劣化程度的特征向量,关联分析得到除湿机的5类故障模式。其次,利用遗传神经网络建立状态参数和故障模式的映射关系。最后,对表征设备吸附能力的主参数进行外推预测。结果训练好的诊断网络可准确地识别出设备的劣化程度及其演变过程,预测网络的预测精度非常高。结论该方法可有效地实现对除湿机的故障诊断与预测。。     

ABC算法优化SVR的磨损故障预测模型

目的为了提高故障预测的精度,针对支持向量回归SVR(Support vector machine for regression,SVR)参数选择困难的问题,提出一种采用人工蜂群(artificial bee colony,ABC)算法优化支持向量回归(SVR)的故障预测模型(ABC-SVR)。方法该模型先对样本数据进行重构,然后将故障预测误差(适应度)作为优化目标,通过ABC算法寻优找到最优的SVR参数,建立故障预测模型。最后通过实例仿真验证模型的优越性。结果采用ABC算法优化的SVR故障预测模型进行时间序列预测,能够较好地跟踪发动机滑油金属元素浓度的变化过程,并且能够提前2个取样时间预测异常情况的出现。结论 ABC-SVR模型有效解决了SVR参数选择难题,能够更加准确地表现故障变化规律,提高了故障预测精度。     

西藏自治区措勤县德能铜多金属矿床地质特征及成因分析

通过对西藏自治区措勤县德能铜多金属矿的研究发现,矿区内共6条达到工业品位的铜矿体,并伴生有铅、锌、金、银等多种有益组分,成矿地质条件较好。矿体主要赋存于燕山期石英闪长玢岩岩体外接触带及构造破碎带中,其中Cu4矿体规模最大,经深部钻孔工程及地表槽探验证,矿体品位和厚度沿走向和倾向变化系数较小。燕山晚期第一阶段第一次石英闪长玢岩侵入体是主要成矿物质来源,后期北西西向断裂构造是主要导矿和容矿构造。     

模糊控制技术在污水处理中的应用

针对污水处理过程中采用传统的流量程序控制和时间程序控制的不足,提出了一种基于单片机的模糊控制方法。该方法以污水流量、溶解氧(DO)浓度和污泥回流比为主要被控对象,以DO浓度为主要控制参数,通过离散计算和在线查表的模糊推理方法可得到最佳的风机转速,使污水处理生化池内DO浓度保持在最佳状态,同时还通过控制曲线展示了当输入污水流量发生扰动时对DO浓度的控制精度,使污水处理质量保持稳定。通过实际应用表明,该控制方法不但能确保出口净化水水质达标,还可以节约15%的电能。     

焦化废水对蚕豆和大麦毒性的影响

以COD作为主要参照指标,研究了焦化废水在符合GB 13456-92<钢铁工业水污染物排放标准>焦化一级、二级排放标准限值要求时,对蚕豆和大麦幼根生长、根尖细胞遗传毒性的影响.结果表明:在实验周期内,焦化废水对蚕豆幼根根长、根重和有丝分裂指数的影响不大;对大麦幼根根重无明显影响,而对大麦根长和有丝分裂指数有促进作用.焦...     

路面径流水环境下交通承载力分析

为了对路面径流水容许污染总量控制下的交通承载力问题进行探讨,利用神经网络具有的非线性映射能力和遗传算法具有的全局随机搜索能力,结合公路路面径流水质检测数据,提出了一种基于遗传神经网络进行公路交通环境承载力反计算的分析方法,应用该方法可根据路面径流水质污染数据反演出路段交通量大小,并可据此进行交通量与路而径流水质污染的关...     

Fast increasing of surface ozone concentrations in Pearl River Delta characterized by a regional air quality monitoring network during 2006-2011

Based on the observation by a Regional Air Quality Monitoring Network including 16 monitoring stations, temporal and spatial variations of ozone(O3), NO2and total oxidant(Ox) were analyzed by both linear regression and cluster analysis. A fast increase of regional O3concentrations of 0.86 ppbV/yr was found for the annual averaged values from 2006 to 2011 in Guangdong, China. Such fast O3increase is accompanied by a correspondingly fast NOx reduction as indicated by a fast NO2 reduction rate of 0.61 ppbV/yr. Based on a cluster analysis, the monitoring stations were classified into two major categories – rural stations(non-urban) and suburban/urban stations. The O3concentrations at rural stations were relatively conserved while those at suburban/urban stations showed a fast increase rate of 2.0 ppbV/yr accompanied by a NO2 reduction rate of 1.2 ppbV/yr. Moreover, a rapid increase of the averaged O3 concentrations in springtime(13%/yr referred to 2006 level) was observed, which may result from the increase of solar duration, reduction of precipitation in Guangdong and transport from Eastern Central China. Application of smog production algorithm showed that the photochemical O3production is mainly volatile organic compounds(VOC)-controlled. However, the photochemical O3production is sensitive to both NOx and VOC for O3pollution episode. Accordingly, it is expected that a combined NOx and VOC reduction will be helpful for the reduction of the O3 pollution episodes in Pearl River Delta while stringent VOC emission control is in general required for the regional O3 pollution control.     

Human Influence and Classical Biogeographic Predictors of Rare Species Occurrence

Biogeographic theory predicts that rare species occur more often in larger, less‐isolated habitat patches and suggests that patch size and connectivity are positive predictors of patch quality for conservation. However, in areas substantially modified by humans, rare species may be relegated to the most isolated patches. We used data from plant surveys of 81 meadow patches in the Georgia Basin of Canada and the United States to show that presence of threatened and endangered plants was positively predicted for patches that were isolated on small islands surrounded by ocean and for patches that were isolated by surrounding forest. Neither patch size nor connectivity were positive predictors of rare species occurrence. Thus, in our study area, human influence, presumably due to disturbance or introduction of competitive non‐native species, appears to have overwhelmed classical predictors of rare species distribution, such that greater patch isolation appeared to favor presence of rare species. We suggest conservation planners consider the potential advantages of protecting geographically isolated patches in human‐modified landscapes because such patches may represent the only habitats in which rare species are likely to persist. Influencia Humana y Predictores Biogeográficos Clásicos de la Ocurrencia de Especies Raras