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Chattering alarms, which repeatedly and rapidly make transitions between alarm and normal states in a short time period, are the most common form of nuisance alarms that severely degrade the performance of alarm systems for industrial plants. One reason for chattering alarms is the presence of oscillation in process signals. The paper proposes an online method to promptly detect the chattering alarms due to oscillation and to effectively reduce the number of chattering alarms. In particular, a revised chattering index is proposed to quantify the level of chattering alarms; the discrete cosine transform-based method is used to detect the presence of oscillation; two mechanisms by adjusting the alarm trippoint and using a delay timer are exploited to reduce the number of chattering alarms. An industrial case study is provided to illustrate the effectiveness of the proposed method. 相似文献
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Chattering and repeating alarms, which repeatedly make transitions between alarm and non-alarm states without operators’ response, are the most common form of nuisance alarms encountered in industrial plants. The paper formulates two novel rules to detect chattering alarms caused by random noise and repeating alarms by regular patterns such as oscillation, and proposes an online method to effectively remove chattering and repeating alarms via the m-sample delay timer. Industrial examples are provided to support the formulated rules and to illustrate the effectiveness of the proposed method. 相似文献
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Sandeep R. Kondaveeti Iman Izadi Sirish L. Shah David S. Shook Ramesh Kadali Tongwen Chen 《Chemical Engineering Research and Design》2013
In the process industry, alarms are configured on the control system to provide indication of abnormal events to the control room operators. In the presence of improper design of alarm generating algorithm or lack of appropriate tuning, alarms are announced more frequently than what is typically sufficient to alert the operator, a condition commonly known as ‘alarm chatter’. Chattering alarms are the most common form of nuisance alarms. The concept of run length is introduced in the alarm management context to study alarm chatter and an index is proposed to quantify the degree of alarm chatter based on run length distributions obtained exclusively from readily available historical alarm data. Chatter index hence plays a crucial role in routine assessment of industrial alarm systems. Prominent features of the proposed chatter index and its variant are demonstrated using industrial data. 相似文献
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Aditya Tulsyan Feras Alrowaie Bhushan Gopaluni 《American Institute of Chemical Engineers》2018,64(1):77-90
In process and manufacturing industries, alarm systems play a critical role in ensuring safe and efficient operations. The objective of a standard industrial alarm system is to detect undesirable deviations in process variables as soon as they occur. Fault detection and diagnosis systems often need to be alerted by an industrial alarm system; however, poorly designed alarms often lead to alarm flooding and other undesirable events. In this article, we consider the problem of industrial alarm design for processes represented by stochastic nonlinear time‐series models. The alarm design for such complex processes faces three important challenges: (1) industrial processes exhibit highly nonlinear behavior; (2) state variables are not precisely known (modeling error); and (3) process signals are not necessarily Gaussian, stationary or uncorrelated. In this article, a procedure for designing a delay timer alarm configuration is proposed for the process states. The proposed design is based on minimization of the rate of false and missed alarm rates—two common performance measures for alarm systems. To ensure the alarm design is robust to any non‐stationary process behavior, an expected‐case and a worst‐case alarm designs are proposed. Finally, the efficacy of the proposed alarm design is illustrated on a non‐stationary chemical reactor problem. © 2017 American Institute of Chemical Engineers AIChE J, 63: 77–90, 2018 相似文献
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Alarm systems play important roles for the safe and efficient operation of modern industrial plants. Critical alarms are configured with a higher priority and are safety related among many other alarms. If critical alarms can be predicted in advance, the operator will have more time to prevent them from happening. In this paper, we present a dynamic alarm prediction algorithm, which is a probabilistic model that utilizes alarm data from distributed control system, to calculate the occurrence probability of critical alarms. It accounts for the local interdependences among the alarms using the n-gram model, which occur because of the nonlinear relationships between variables. Finally, the dynamic alarm prediction algorithm is applied to an industrial case study. 相似文献
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针对复杂工业流程生产单元间变量存在多重时滞且检测困难,提出一种基于趋势相似度分析的多重时滞辨识方法。选取单元间相关性强的关键变量,利用多项式最小二乘拟合后的变量导数数据定义趋势相似度,以经采样时滞平移后的趋势相似度最小,描述多重时滞辨识问题;用L2范数量化趋势相似度向量,将多重时滞辨识问题转化成L2范数最小化问题;并用改进的自适应粒子群算法快速寻优,确定各变量的最优采样时滞。所提方法被应用于加氢裂化流程中,辨识出各变量的实际采样时滞,由此建立了基于局部加权核主元回归的柴油闪点预测模型。实验结果表明:考虑多重时滞的预测模型准确率提高了19.05%,验证了所提时滞辨识方法的有效性。 相似文献
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Joshiba Ariamuthu Venkidasalapathy Costas Kravaris 《American Institute of Chemical Engineers》2021,67(10):e17297
When a fault occurs in a process, it slowly propagates within the system and affects the measurements triggering a sequence of alarms in the control room. The operators are required to diagnose the cause of alarms and take necessary corrective measures. The idea of representing the alarm sequence as the fault propagation path and using the propagation path to diagnose the fault is explored. A diagnoser based on hidden Markov model is built to identify the cause of the alarm signals. The proposed approach is applied to an industrial case study: Tennessee Eastman process. The results show that the proposed approach is successful in determining the probable cause of alarms generated with high accuracy. The model was able to identify the cause accurately, even when tested with short alarm sub-sequences. This allows for early identification of faults, providing more time to the operator to restore the system to normal operation. 相似文献
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Alarmflood is one of themain problems in the alarmsystems of industrial process. Alarmroot-cause analysis and alarmprioritization are good for alarmflood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarmpriority and reduce the blindness of alarmhandling. As a case study, the Tennessee Eastman process is utilized to showthe effectiveness and validity of proposed approach. Alarmsystem performance comparison shows that our rationalization methodology can reduce the alarmflood to some extent and improve the performance. 相似文献
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1 INTRODUCTION Normally, operating management experience of in- dustrial process indicates that the probability one ig- nores alarm is 10-4 after handling one alarm signal and the probability one takes no direct action is 10-5 after hearing one alarm. Experiences also indicate that the probability one ignores alarm will increase to 10-3 from 10-4 if one alarm isn't handled within one minute[1]. Therefore, when the second alarm is appearing the probability which it can't be identified is 10… 相似文献
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合理有效的可视化监控技术及工具有助于操作员及时理解报警信息并采取响应措施。针对现有可视化技术存在的缺点及不足, 如资源利用不充分、报警等级划分不明确、报警根源分析不彻底等, 构建了4种新型可视化工具:基于信息融合的解释结构模型(静态和动态)、层次高密度报警图、层次优先级色彩图、性能水平趋势图, 分别实现了过程递阶模型建立、报警根源分析、滋扰报警识别、报警优先级划分、报警系统性能常规评估等目的。以TE仿真模型为例, 阐明了上述可视化技术及工具的实用性和有效性, 不仅可以展示报警全貌原始信息, 还可快速识别报警根源、关键报警、滋扰报警以及报警系统性能水平, 实现了高效监控,从一定程度上解决了报警泛滥问题。 相似文献
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Yajun Mei 《Sequential Analysis》2013,32(4):354-376
Abstract Apart from Bayesian approaches, the average run length (ARL) to false alarm has always been seen as the natural performance criterion for quantifying the propensity of a detection scheme to make false alarms, and no researchers seem to have questioned this on grounds that it does not always apply. In this article, we show that in the change-point problem with mixture prechange models, detection schemes with finite detection delays can have infinite ARLs to false alarm. We also discuss the implication of our results on the change-point problem with either exchangeable prechange models or hidden Markov models. Alternative minimax formulations with different false alarm criteria are proposed. 相似文献
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基于物元分析的过程工业报警优化 总被引:9,自引:4,他引:5
过程工业报警系统设定的报警点多且复杂,给监控生产带来了一定的困难.结合报警系统的特点和物元分析方法,构造各报警参数的物元模型,定义各报警参数与报警级别的关联函数,提出基于关联函数的权重分配改进,计算各报警参数与报警级别的综合关联度.在保证安全生产的前提下,根据综合关联度的大小对各报警参数进行优化选择,形成适合过程工业的报警优化方法.结合精对苯二甲酸溶剂脱水塔报警系统验证了该方法的有效性,基于物元分析的报警优化方法合理地降低了报警系统的报警量和报警频率,为报警管理和操作优化提供了新思路. 相似文献
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Igor V. Nikiforov 《Sequential Analysis》2016,35(3):268-301
The quickest multidecision change detection/isolation problem is the generalization of the quickest changepoint detection problem to the case of M post-change hypotheses. It is necessary to detect the change in distribution as soon as possible and to indicate which hypothesis is true after a change occurs. Both the rate of false alarms and the misidentification (false isolation) rate should be controlled by given levels. Several detection/isolation procedures that asymptotically minimize the tradeoff between the expected detection delay and the false alarm/false isolation rates in the worst-case scenario are discussed. 相似文献
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Abstract. A method for evaluating a predictor-based alarm system is studied in this paper. The predictor is composed of a 'deterministic' component reflecting external information and a statistically based component for the error between the measurements and the external predictor. The aim of the predictor study is twofold:it is a means of interpreting the connections between the alarm and the catastrophe, and it can be used to select suitable alarm levels. As an application, the performance of a water-level predictor as part of a flood warning system has been evaluated. The result of this analysis shows that an alarm system which operates when the predictor reaches a certain level will tend to give either too many alarms or alarms that are out of phase with the catastrophe. 相似文献
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Process safety in chemical industries is considered to be one of the important goals towards sustainable development. This is due to the fact that, major accidents still occur and continue to exert significant reputational and financial impacts on process industries. Alarm systems constitute an indispensable component of automation as they draw the attention of process operators to any abnormal condition in the plant. Therefore, if deployed properly, alarm systems can play a critical role in helping plant operators ensure process safety and profitability. However, in practice, many process plants suffer from poor alarm system configuration which leads to nuisance alarms and alarm floods that compromise safety. A vast amount of research has primarily focused on developing sophisticated alarm management algorithms to address specific issues. In this article, we provide a simple, practical, systematic approach that can be applied by plant engineers(i.e., non-experts) to improve industrial alarm system performance. The proposed approach is demonstrated using an industrial power plant case study. 相似文献
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