基于直方图相似度度量的中央空调风管附尘度检测

对于主从控制中央空调清洁机器人,操作人员依据视频很容易就可判断出风管是否清扫干净。在机器人自主清洗中央空调风管时,为了能够使机器人识别管道内灰尘附着程度,文章采用了直方图相似度作为清洁机器人自动判断管道附尘度和清洁与否的标准。文章给出了相关的原理和算法,并进行了试验验证,结果表明该方法具有快速性、实时性和准确性等特点。     

Effect of nozzle type on pulse-jet cleaning performance of ceramic filter tube

The dust-cleaning efficiency of the ceramic filter tube is the key factor to determine the long-term stable operation of the dust removal system, and the type of nozzle significantly influences the performance. In this study, four types of nozzles (injection hole, sudden enlargement nozzle, tubular nozzle, and induction nozzle) are used to conduct comparative experimental study on the dust-cleaning effect of the ceramic filter tube. Using the schlieren technique find that the tubular and induction nozzles can improve the deviation angle of pulse-jet airflow. The injection parameters were set as an injection pressure of 200 kPa, an injection distance of 120 mm and a pulse width of 80 ms in the experiment. Using the sidewall pressure measurement system indicates that the integrated pressure of the sudden enlargement nozzle is the largest, but the uniformity is poor. The comprehensive pressure of the sudden enlargement nozzle is increased by 64.86 %, and the non-uniformity is reduced by 28.62 % compared with those of the induction nozzle. Using the visualization filtration cycle test system implies that the degree of damage and stripping state of the dust layer are directly proportional to the sidewall pressure. Moreover, it is found that the residual pressure drop changes exponentially with the dust removal quality under different nozzle types. These conclusions can help explain the mechanism of dust stripping and provide a basis for the selection of nozzles.     

Dust source identification using MODIS: A comparison of techniques applied to the Lake Eyre Basin, Australia

The impact of mineral aerosol (dust) in the Earth's system depends on particle characteristics which are initially determined by the terrestrial sources from which the sediments are entrained. Remote sensing is an established method for the detection and mapping of dust events, and has recently been used to identify dust source locations with varying degrees of success. This paper compares and evaluates five principal methods, using MODIS Level 1B and MODIS Level 2 aerosol data, to: (a) differentiate dust (mineral aerosol) from non-dust, and (2) determine the extent to which they enable the source of the dust to be discerned. The five MODIS L1B methods used here are: (1) un-processed false colour composite (FCC), (2) brightness temperature difference, (3) Ackerman's (1997: J.Geophys. Res., 102, 17069-17080) procedure, (4) Miller's (2003:Geophys. Res. Lett. 30, 20, art.no.2071) dust enhancement algorithm and (5) Roskovensky and Liou's (2005: Geophys. Res. Lett. 32, L12809) dust differentiation algorithm; the aerosol product is MODIS Deep Blue (Hsu et al., 2004: IEEE Trans. Geosci. Rem. Sensing, 42, 557-569), which is optimised for use over bright surfaces (i.e. deserts). These are applied to four significant dust events from the Lake Eyre Basin, Australia. OMI AI was also examined for each event to provide an independent assessment of dust presence and plume location. All of the techniques were successful in detecting dust when compared to FCCs, but the most effective technique for source determination varied from event to event depending on factors such as cloud cover, dust plume mineralogy and surface reflectance. Significantly, to optimise dust detection using the MODIS L1B approaches, the recommended dust/non-dust thresholds had to be considerably adjusted on an event by event basis. MODIS L2 aerosol data retrievals were also found to vary in quality significantly between events; being affected in particular by cloud masking difficulties. In general, we find that OMI AI and MODIS AQUA L1B and L2 data are complementary; the former are ideal for initial dust detection, the latter can be used to both identify plumes and sources at high spatial resolution. Overall, approaches using brightness temperature difference (BT10-11) are the most consistently reliable technique for dust source identification in the Lake Eyre Basin. One reason for this is that this enclosed basin contains multiple dust sources with contrasting geochemical signatures. In this instance, BTD data are not affected significantly by perturbations in dust mineralogy. However, the other algorithms tested (including MODIS Deep Blue) were all influenced by ground surface reflectance or dust mineralogy; making it impossible to use one single MODIS L1B or L2 data type for all events (or even for a single multiple-plume event). There is, however, considerable potential to exploit this anomaly, and to use dust detection algorithms to obtain information about dust mineralogy.     

200MW乏气送粉机组主蒸汽温度控制优化方案

本文在常规火电厂主蒸汽温度自动控制方案的基础上,对200MW乏气送粉机组的特性进行了分析,结合锅炉主要参数与主蒸汽温度自动控制的相互关系,以及相关的工艺要求,提出了一种新的优化方案。     

DCS在焦炉地面除尘系统中的应用

以和利时DCS系统在某100万t捣固焦炉地面除尘站系统中的应用为例,介绍了袋式除尘系统的工艺流程、工艺联锁与控制要求,并依此制订了基于和利时MACSV系统的详细实现方案。系统具有免维护、除尘效果良好等特点。系统投运后,不仅减少了工人劳动强度,改善了工厂周边环境,并且取得了良好的经济效益和社会效益。     

An upgraded high-velocity dust particle accelerator at Concordia College in Moorhead, Minnesota

In 1975, Concordia College in Moorhead, Minnesota acquired a 2 MeV dust particle accelerator from NASA/GSFC that was used to test the lunar ejecta and micrometeorite (LEAM) experiment flown on Apollo 17. This high-speed dust particle accelerator is still fully functional and is currently being upgraded. Improvements to the electronic detection system have been undertaken including a computer-based, data acquisition system and new particle detection sensor electronics. These sensors have additional amplifiers that extend the range of charge detection to 1×10⁻¹² C allowing for the detection of larger particles. Improvements to the vacuum system have also been made. The accelerator beam line is now pumped with an oil-free, turbomolecular pump reducing possible problems with hydrocarbon contamination. In this work, we describe the facility, and outline some of the recent improvements to the dust particle accelerator and discuss its capabilities and limitations. We also summarize some of the recent experiments conducted using the facility.     

除尘器智能控制器的开发

针对市场上传统的脉冲袋式除尘器控制器在实际应用中存在的灵活性差、可靠性低等问题，借助于高性能的单片机开发了一种功能完善的通用型控制器。具体介绍了系统的组成和工作原理，详细讨论了通用控制器的硬件组成和软件设计，阐述了系统的性能指标和功能特点，在设计中采用光电耦合器将外部负载驱动电路和控制电路隔离，同时结合看门狗技术提高整个系统的可靠性。     

拆除爆破粉尘控制研究现状与前景

综述了爆破粉尘控制的研究现状,分析了爆破粉尘的特点,对拆除爆破粉尘的控制方法进行了探讨,预测了拆除爆破粉尘控制的发展趋势。文中提出了采用清除积尘、预湿建筑物、爆炸水雾、局部建筑单元蓄水、喷淋等综合除尘方法降低城市控制爆破过程中的粉尘,以减轻和消除爆破粉尘对环境的污染。     

Semi‐volatile organic compounds in the air and dust of 30 French schools: a pilot study

The contamination of indoor environments with chemical compounds released by materials and furniture, such as semi‐volatile organic compounds (SVOCs), is less documented in schools than in dwellings—yet children spend 16% of their time in schools, where they can also be exposed. This study is one of the first to describe the contamination of the air and dust of 90 classrooms from 30 nursery and primary schools by 55 SVOCs, including pesticides, phosphoric esters, musks, polycyclic aromatic hydrocarbons (PAHs), polychlorobiphenyls (PCBs), phthalates, and polybromodiphenylethers (PBDEs). Air samples were collected using an active sampling method, and dust samples were collected via two sampling methods (wiping and vacuum cleaning). In air, the highest concentrations (median >100 ng/m³) were measured for diisobutyl phthalate (DiBP), dibutyl phthalate (DBP), diethyl phthalate (DEP), bis(2‐ethylhexyl) phthalate (DEHP), and galaxolide. In dust, the highest concentrations (median >30 μg/g) were found for DEHP, diisononyl phthalate (DiNP), DiBP, and DBP. An attempt to compare two floor dust sampling methods using a single unit (ng/m²) was carried out. SVOC concentrations were higher in wiped dust, but frequencies of quantification were greater in vacuumed dust.     

Predicting dust emissions – Experimental study compared to coupled DEM/CFD simulations using a reference test bulk material

The awareness of dust emissions is crucial regarding safe industrial processes, environmental protection and health care. For this purpose, closely linked experimental and numerical investigations are performed. This work presents the results of an experimental study which is used for the calibration of a modelling framework based on the Discrete Element Method (DEM) coupled with Computational Fluid Dynamics (CFD) and applied for the calculation of dust emissions for predictive purposes. The key objective of the approach is to come up with a dust source term which enables to describe and to quantify the release of particle emissions. For the presented experimental study, a wind tunnel and a rotating drum setup, which cover various handling types of bulk materials, are used in order to gain data about parameters having an impact on the dust release. The special feature of the investigations is the use of a reference test bulk material which represents a bulk material in its generally main fractions, the fine and the coarse material, keeping the discrepancy between experiments and simulations low. With the help of the experimental results the calibration of the simulation model was carried out and followed by a comparison.