Identification and characterization of extracted microplastics from agricultural soil near industrial area: FTIR and X-ray diffraction method

Microplastics have been found in large quantities in agricultural soil and now become a major global issue. Different types of microplastic have adverse effects on agricultural soil. The most widely used method for the extraction of microplastics in agricultural soil is the density floatation method by using saturated NaCl solution. This method includes the pre-digestion of soil samples with H₂O₂ to remove all the organic matter present in the soil. Different types of microplastic particles were extracted and identified by using ATR-FTIR viz polypropylene, polybutylene tetrapthalate, polyethylene, polystyrene, and polyethylene tetrapthalate. The crystalline nature of extracted microplastic was checked by employing XRD analytical technique. Floatation with higher density saturated sodium chloride (NaCl) solution recovered approximately 80% MPs from soil. Floatation methods were found to be effective for extracting microplastics from soils.     

井下光谱多参数分析系统开发

本系统基于气体浓度光学分析方法理论朗伯-比尔(Lambert-Beer)定律、光谱气体检测技术开发,实现了对煤矿火灾与瓦斯灾害超前预警、灾害产生的有毒有害气体实时监测和煤矿环境气体爆炸危险性辨识,对于煤矿灾害防治、救灾过程中杜绝次生灾害,保障煤矿工人及救护队员的生命安全,促进煤矿安全生产具有重要意义。     

PLS-based EWMA fault detection strategy for process monitoring

Fault detection (FD) and diagnosis in industrial processes is essential to ensure process safety and maintain product quality. Partial least squares (PLS) has been used successfully in process monitoring because it can effectively deal with highly correlated process variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T² and the Q statistics are ill suited to detect small faults because they only use information from the most recent observations. Other univariate statistical monitoring methods, such as the exponentially weighted moving average (EWMA) control scheme, has shown better abilities to detect small faults. However, EWMA can only be used to monitor single variables. Therefore, the main objective of this paper is to combine the advantages of the univariate EWMA and PLS methods to enhance their performances and widen their applicability in practice. The performance of the proposed PLS-based EWMA FD method was compared with that of the conventional PLS FD method through two simulated examples, one using synthetic data and the other using simulated distillation column data. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS, especially in the presence of faults with small magnitudes.     

环境空气自动监测方法检出限相关问题探讨

探讨了环境空气自动监测中实际评估方法检出限的意义,详细介绍了常规气态污染物自动监测方法检出限的评估方法。并以EC 9850型SO2分析仪为例,说明了环境空气自动监测的测定步骤和方法检出限的计算。     

两种吹扫捕集浓缩仪在测定土壤VOCs时的性能比较

从仪器精密度、方法检出限、准确度等角度对吹扫捕集浓缩仪Stratum PTC与Eclipse 4660的性能进行比较。结果表明,大部分分析物用Stratum PTC的方法检出限略高于Eclipse 4660,但精密度比Eclipse 4660稍差;Eclipse 4660用于分析极性的、水溶性物质的效果比Stratum PTC好,回收率更高。两种吹扫捕集仪的测试结果均满足《土壤和沉积物挥发性有机物的测定吹扫捕集/气相色谱-质谱法》(HJ 605-2011)标准方法的指标要求。     

基于BP神经网络的受限空间火灾联合探测方法

针对航空受限空间火灾探测高误报的问题，在现有技术成果基础上对多种火灾探测方式进行研讨，并提出1种基于BP神经网络技术的飞机机身内部受限空间火灾联合探测报警方法。该方法结合现有烟雾感应、气体传感器探测等常用火灾探测技术，以红外热成像探测为辅助手段，采用神经网络实现数据融合，对模拟实验舱火灾烟雾进行联合探测，在单一火灾探测方式基础上提高了探测准确率。     

Improving pedestrian safety using combined HOG and Haar partial detection in mobile systems

Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.

Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.

Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.

Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian.     

THOR dummy chest deflection response in oblique and lateral far-side sled tests

Abstract

Objective: The focus of this study is side impact. Though occupant injury assessment and protection in nearside impacts has received considerable attention and safety standards have been promulgated, field studies show that a majority of far-side occupant injuries are focused on the head and thorax. The 50th percentile male Test Device for Human Occupant Restraint (THOR) has been used in oblique and lateral far-side impact sled tests, and regional body accelerations and forces and moments recorded by load cells have been previously reported. The aim of this study is to evaluate the chestband-based deflection responses from these tests.

Methods: The 3-point belt–restrained 50th percentile male THOR dummy was seated upright in a buck consisting of a rigid flat seat, simulated center console, dashboard, far-side side door structure, and armrest. It was designed to conduct pure lateral and oblique impacts. The center console, dashboard, simulated door structure, and armrest were covered with energy-absorbing materials. A center-mounted airbag was mounted to the right side of the seat. Two 59-gage chestbands were routed on the circumference of the thorax, with the upper and lower chestbands at the level of the third and sixth ribs, respectively, following the rib geometry. Oblique and pure lateral far-side impact tests with and without airbags were conducted at 8.3 m/s. Maximum chest deflections were computed by processing temporal contours using custom software and 3 methods: Procedures paralleling human cadaver studies, using the actual anchor point location and actual alignment of the InfraRed Telescoping Rods for the Assessment of Chest Compression (IR-TRACC) in the dummy on each aspect—that is, right or left,—and using the same anchor location of the internal sensor but determining the location of the peak chest deflection on the contour confined to the aspect of the sensor; these were termed the SD, ID, and TD metrics, respectively.

Results: All deformation contours at the upper and lower thorax levels and associated peak deflections are given for all tests. Briefly, the ID metrics were the lowest in magnitude for both pure lateral and oblique modes, regardless of the presence or absence of an airbag. This was followed by the TD metric, and the SD metric produced the greatest deflections.

Conclusion: The chestbands provide a unique opportunity to compute peak deflections that parallel current IR-TRACC-type deflections and allow computation of peak deflections independent of the initial point of attachment to the rib. The differing locations of the peak deflection vectors along the rib contours for different test conditions suggest that a priori attachment is less effective. Further, varying magnitudes of the differences between ID and TD metrics underscore the difficulty in extrapolating ID outputs under different conditions: Pure lateral versus oblique, airbag presence, and thoracic levels. Deflection measurements should, therefore, not be limited to an instrument that can only track from a fixed point. For improved predictions, these results suggest the need to investigate alternative techniques, such as optical methods to improve chest deflection measurements for far-side occupant injury assessment and mitigation.     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.     

煤矿岗前人员不安全状态智能检测系统研究*—以红柳林煤矿为例

为从根本上降低煤矿从业人员实施不安全行为的概率,在充分考虑煤矿从业人员不安全个体状态是诱发其不安全行为的主要原因的基础上,设计开发一套矿工不安全状态智能检测系统。首先,对2007—2022年期间各高危行业安全事故调查报告和专家研究进行归纳,总结得出煤矿从业人员不安全状态的影响因素,构建包括生理状态、心理状态以及个体能力状态在内的3个一级指标和15个二级指标体系;其次,通过相应的表征模型对不安全状态影响因素进行深入剖析;最后,基于构建的从业人员不安全状态倾向数据库,建立煤矿岗前不安全状态智能检测系统。研究结果表明:在下井工作前对从业人员个体状态进行智能检测,能够实现矿工不安全状态“早发现、早干预”,能够有效地降低人因事故发生率,研究结果对煤炭行业安全管理具有重要的参考价值。