遥感技术在水生态环境管理的应用与前景

随着遥感数据源的不断丰富,遥感技术不断提高,可以解决越来越多的水环境问题。指出了当前水生态环境管理方面的主要需求,结合目前遥感技术的发展,对国内外的水环境遥感研究进展进行综述。以湖泊富营养化监测与评估、核电站温排水遥感监测及城市黑臭水体遥感监测为案例,具体阐述遥感在水环境管理中的应用方法及成效。未来水生态环境管理发展趋势将以水污染防治为主向水污染防治和水生态修复与保护并重发展。基于此趋势,提出遥感在水生态修复的应用潜力,利于更多地方部门积极有效应用遥感技术,解决水生态环境问题。     

基于BIM的装配式建筑并行施工作业空间冲突识别

为识别装配式建筑施工并行作业之间的空间冲突，分析装配式建筑施工项目现场各类作业空间占用需求，利用BIM技术模拟作业空间占用，引入混合轴向包围盒（AABB）与有向包围盒（OBB）算法，建立施工现场并行作业空间冲突检测模型。结果表明:所建立的模型可有效预测施工现场并行作业之间的空间冲突，为进一步的空间资源优化与项目安全管理提供支撑。     

基于BERT-BILSTM-CRF模型的电力行业事故文本智能分析*

为解决电力行业事故报告文本较长、语义复杂,难以进行有效文本识别问题,提出1种以BERT作为底层的预训练模型,并设计1种双重注意力机制编码器,结合BILSTM-CRF深度挖掘事故文本语义特征,从而实现文本智能分析。首先构建电力词典,通过对BERT预训练,进行BIO标注,然后引入BILSTM-CRF模型实现对文本标签智能分类,最后将该模型与现行其他4种深度学习模型进行对比。研究结果表明:该模型智能识别精确率、召回率及F1值(查准率)均达到约97%,较其他4种模型中效果最好的模型分别提高0.02,0.03,0.02。研究结果可为电力行业事故报告文本分析提供1种新思路。     

饮用水源地的水华对人体健康风险评价

饮用水源地的水华现象近年来在世界各地不断爆发,给人类饮水安全造成极大的威胁。本文通过检测微囊藻毒素和三卤甲烷类物质,利用急性暴露安全阈值（浓度）计算模型,计算出了各自的急性暴露安全阅值,并对健康风险进行了评价。     

Beyond hypoxia：Occurrence and characteristics of black blooms due to the decomposition of the submerged plant Potamogeton crispus in a shallow lake

Organic matter-induced black blooms(hypoxia and an offensive odor) are a serious ecosystem disasters that have occurred in some large eutrophic shallow lakes in China. In this study, we investigated two separate black blooms that were induced by Potamogeton crispus in Lake Taihu, China. The main physical and chemical characteristics, including color- and odor-related substances, of the black blooms were analyzed. The black blooms were characterized by low dissolved oxygen concentration(close to 0 mg/L), low oxidation-reduction potential, and relatively low pH of overlying water. Notably higher Fe2+and∑S2-were found in the black-bloom waters than in waters not affected by black blooms. The black color of the water may be attributable to the high concentration of these elements, as black FeS was considered to be the main substance causing the black color of blooms in freshwater lakes. Volatile organic sulfur compounds, including dimethyl sulfide, dimethyl disulfide, and dimethyl trisulfide, were very abundant in the black-bloom waters. The massive anoxic degradation of dead Potamogeton crispus plants released dimethyl sulfide, dimethyl disulfide, and dimethyl trisulfide, which were the main odor-causing compounds in the black blooms. The black blooms also induced an increase in ammonium nitrogen and soluble reactive phosphorus levels in the overlying waters. This extreme phenomenon not only heavily influenced the original lake ecosystem but also greatly changed the cycling of Fe, S, and nutrients in the water column.     

颗粒直链藻水华生消对婆罗异剑水蚤（桡足类）种群动态的影响

近年来,国内外学者对湖库型水华的发生机理和生态效应都做了大量研究,但有关水华生消对浮游动物群落结构影响的研究还很少.因此,本研究利用两个室外水泥池在中等尺度上考察了颗粒直链藻水华生消过程对婆罗异剑水蚤(桡足类)种群动态的影响,以及后者摄食对水华生消的下行调控作用.结果发现,颗粒直链藻水华发展迅速,仅5 d时间叶绿素浓度就从(21.24±0.75)μg·L-1上升到(240.34±11.00)μg·L-1;随后水华进入快速消退期,3 d后叶绿素a浓度下降到(53.63±0.47)μg·L-1.婆罗异剑水蚤的摄食压力对颗粒直链藻水华具有明显的抑制作用,水华生消期间含有婆罗异剑水蚤的藻液叶绿素a浓度比对照组低20μg·L-1左右,最大差异为26.08μg·L-1.期间婆罗异剑水蚤的丰度也由接入时的(56.50±4.32)ind·L-1增加到(142.11±6.35)ind·L-1,增加了1.5倍.该研究结果表明,在无鱼类摄食压力情况下,颗粒直链水华的爆发和消亡对婆罗异剑水蚤的生长和繁殖没有负面影响,反而促进了其种群数量的增加,这可能是由于水华期间为其提供了充足的饵料供应.     

六都寨水库夏季富营养化状况与浮游植物分布特征研究

六都寨水库是湖南省邵阳市重要的备用水源地,本文在2012年夏季对六都寨水库水体理化指标和浮游植物群落结构进行调查,评价水库富营养化状况.结果显示六都寨水库氮、磷浓度较高,TN和TP平均值分别为0.88和0.04 mg·L-1,部分点位超过Ⅲ类水标准.调查期间库区浮游植物总细胞密度变化范围为3.68×106~5.84×106cells·L-1,水库中心区域以绿藻为主,靠近坝首处则以蓝藻为主.各点位Shannon-Wiener多样性指数(H')介于2.19~3.17之间,Chl.a浓度范围为3.64~20.24μg·L-1,综合营养状态指数(TLI)为38.51~48.11,六都寨水库水体已处于中营养状态.要从根本上控制六都寨水库水体富营养化进程,防范蓝藻水华风险,需通过长期科学监控和综合防治.     

寒区水体中溶藻铜绿假单胞菌的分离和性质研究

我国北方,尤其是东北地区的一些水体由于富营养化导致的水华现象呈增加趋势,成为急需解决的水环境问题.溶藻菌可从生态调控的角度来控制水华的爆发,因此,在富营养化水体治理方面逐渐得到重视.本文从寒区水华爆发水体中分离获得了一株溶藻细菌JM1,系统发育分析表明,菌株JM1与铜绿假单胞菌的同源性最高.VITEK系统鉴定表明,菌株JM1与铜绿假单胞菌的相似度为98%.菌株JM1在不同的碳源和氮源培养基中可产生不同颜色和p H值的代谢产物,而以葡萄糖和蛋白胨分别为碳源和氮源时发酵液的溶藻效果明显好于其它培养基.菌株JM1的溶藻效果随藻细胞初始密度的降低而增强,随发酵液添加量的增加而增加;当菌体细胞的密度达到1011CFU·m L-1时,可单一抑制藻细胞的生长;当菌体细胞的密度大于105CFU·m L-1时,菌体细胞可促进发酵液的溶藻作用.发酵液作用于藻细胞6 h时可明显影响其恢复能力,当暴露时间达18 h时,藻细胞彻底丧失了恢复能力.菌株JM1发酵液在中性和偏碱性的藻液中的溶藻效果最强,并且经过酸化、碱化和高温处理后,仍然保持较高的溶藻活性.本研究可为基于微生物作用过程的水华控制提供优势的土著菌种及其应用上的技术支持.     

A dual-sensor-based method to recognize pipeline leakage and interference signals

During the detection of pipeline leakages, false alarms of leak detection could be markedly reduced if the interference signals resulting from pressure regulating, pump regulating or valve movements could be accurately distinguished. A digital recognition method for interference signals and leakage signals based on a dual-sensor system is proposed in this paper. It is demonstrated that the direction of the signal can be recognized by a cross-correlation calculation between two signals from the dual-sensor, one of which undergoes forward linear interpolation and backward linear interpolation. Based on this theory, the interference signal and the leak signal can be discriminated exactly, and the distance between the two sensors in the dual-sensor system can be considerably reduced without needing to increase the sampling frequency. The monotonicity of the cross-correlation function is demonstrated, and a fast discrimination algorithm based on a binary extreme search method, which decreases the computational load and maintains global optimization, is also proposed. A pre-processing method of the actual signal is proposed to decrease the identity requirement for the two sensors in a dual-sensor system. In the experiment based on artificial signals, the proposed discrimination algorithm could achieve accurate recognition of the abnormal signal, and as such, the theory and application of pipeline leak detection based on dual-sensor systems are extended.     

基于FTA-SVM的车辆发动机故障识别方法

发动机结构日益复杂,其故障具有多样性和频发性的特点,收集大量故障样本存在很多实施障碍。为了提高车辆发动机的故障识别的效率和准确性,提出了一种新的结合故障树(FTA)和支持向量机(SVM)各自特点,从故障模式分析到故障类型识别的FTA-SVM故障识别方法。首先利用故障树在复杂系统故障模式分析中的优势,找出系统的故障模式,建立故障树模型,通过对故障树模型中各故障事件的分析,采集与故障事件状态相关的数据,建立数据与故障树底事件的映射模型,最后利用支持向量机在小样本数据处理中的优势,进行故障类型的识别。以发动机的失火故障为例建立了发动机失火故障树模型及故障数据与故障模式映射模型,验证了FTA-SVM方法的有效性和适用性。