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.     

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。     

土壤中硫的形态分析及其测定方法研究进展

本文对土壤中硫的形态分析与测定方法,从无机硫,有机硫,总硫,以及硫的系统分析方法,硫的检测几个方面进行了综述,对各种方法进行了客观的评价,指出了尚待于解决的问题,并对今后的研究进行了展望。     

畜禽养殖中沙门氏菌污染的PCR快速检测

针对畜禽养殖是造成农村水环境生物性污染的主要原因,指出用常规生化检测技术耗时长、效率低,不能满足环境管理的要求：应用PCR技术检测沙门氏菌,特异性高、敏感性强、耗时短,与常规分离鉴定方法比较,完全符合实验证明,PCR技术可很好的应用于沙门氏菌污染的调查与监测。     

空气阴极微生物燃料电池的构型优化及其快速测定BOD的性能评价

设计了一种新型双室空气阴极微生物燃料电池(MFC)并将其作为生物传感器,与传统双室空气阴极MFC进行对比,考察其电化学性能及用于快速检测BOD的性能。结果表明：新型空气阴极MFC可有效提高功率密度并降低内阻,其功率密度最高为897 mW·m⁻²,而内阻最低为92 Ω;该MFC可用于直接快速检测高浓度有机物的BOD,对醋酸钠底物的线性检测限为1 280 mg·L⁻¹,在此底物浓度下MFC的检测时间为31.2~66 h,线性可决系数R²为0.97~0.99;对于GGA底物的线性检测限为1 250 mg·L⁻¹,在此底物浓度下MFC的检测时间为33~67 h,线性可决系数R²为0.98。本研究可为MFC型BOD检测传感器的性能优化提供参考。     

PVC电缆火灾早期特征气体的组成分析和传感器探测

利用气体传感器对电缆绝缘过热释放的气体进行监测有望实现电气火灾早期预警,目前该技术的发展由于特征气体未得到确认而受到限制。分析了聚氯乙烯(PVC)电缆绝缘层在不同温度下释放的气体组成,并对其主要成分进行传感器测试。TG-IR和GC-MS分析表明PVC电缆绝缘层在200℃前已出现微小失重,释放出以邻苯二甲酸二辛酯(DOP)等塑化剂为主的气体。气敏测试中,商用半导体气体传感器对DOP和电缆蒸气产生较好、相似的响应性能。因此,DOP可以作为PVC电缆火灾早期的特征气体。     

尾矿库上覆排土场工程危险源辨识及安全评估技术研究

随着我国对尾砂及尾矿库场地综合利用的更高要求,尾矿库上覆排土场工程的数量不断增多。尾矿库上覆排土场工程是金属非金属矿山高危、典型并涵盖许多关键安全科学问题的特殊工程。提出了“尾矿库上覆排土场工程”的定义,总结了尾矿库上覆排土场工程的结构特点,具备隐蔽工程复杂、尾矿库固结程度难以判断、排土场变形趋势复杂等特点,提出了尾矿库上覆排土场工程危险有害因素的辨识方法;研究了工程中尾矿库固结程度、排土场结构的探测技术和方法,利用图像处理技术分析了尾矿库上修建排土场工程的隐蔽工程质量。基于上述分析结果,提出了尾矿库上覆排土场工程的灾害防治措施。上述成果可为今后在闭库尾矿库上修建排土场的安全鉴定提供重要依据。     

Fault detection and diagnostics of a three-phase separator

A high demand of oil products on daily basis requires oil processing plants to work with maximum efficiency. Oil, water and gas separation in a three-phase separator is one of the first operations that are performed after crude oil is extracted from an oil well. Failure of the components of the separator introduces the potential hazard of flammable materials being released into the environment. This can escalate to a fire or explosion. Such failures can also cause downtime for the oil processing plant since the separation process is essential to oil production. Fault detection and diagnostics techniques used in the oil and gas industry are typically threshold based alarm techniques. Observing the sensor readings solely allows only a late detection of faults on the separator which is a big deficiency of such a technique, since it causes the oil and gas processing plants to shut down.A fault detection and diagnostics methodology for three-phase separators based on Bayesian Belief Networks (BBN) is presented in this paper. The BBN models the propagation of oil, water and gas through the different sections of the separator and the interactions between component failure modes and process variables, such as level or flow monitored by sensors installed on the separator. The paper will report on the results of the study, when the BBNs are used to detect single and multiple failures, using sensor readings from a simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the separator.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.