Framework and models for an event-based early warning system design

基于事件的预警系统设计的框架和模型

• 批准号: RGPIN-2014-05812
• 负责人: Ahmed, Salim
• 金额: $ 1.46万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588634
• 关键词: Framework; models; event; based; early

I have proposed a five-year research program that aims to develop an event-based approach to the design and management of warning systems used in process industries. The special features and novelty of the proposed approach are in the allocation of warnings to specific events, the use of risk as a basis for alarm annunciation and categorization, and the use of prediction for warnings. The challenges in the design of such a warning system are tied to identification of events, selection of their associated variable sets, and continuous estimation of the risk of corresponding events. Moreover, the use of prediction will require the development of identification schemes to estimate models with the ability to predict variables around safety limits. My experience with the development of novel system identification algorithms and our recent works in the field of alarm system design will be valuable tools to overcome the above challenges. My record of contributions, previous and current HQP training performance, and detailed plan for HQP training will ensure the success of the program. The outcome of the program will be a novel warning system design framework and models, corresponding intellectual properties, and a group of highly qualified personnel. This program will also help to establish the applicant as a leading contributor to this field of significant industrial importance. Warning systems for industrial operations, including alerts and both process and safety alarms, play a key role in monitoring process safety. These systems warn operators of abnormal operating conditions, and seek the attention of an operator when intervention is required. Timely action, based on real warnings, is needed to help enhance plant safety and minimize costs through the effective prevention, control and mitigation of abnormal situations. In industrial plants, however, misleading warnings are a regular occurrence. Moreover, when flooded with spurious alarms, the warning system may itself contribute to abnormal situations and to plant accidents. A root cause of the ineffectiveness of existing warning systems is the large number of warnings that result from the use of single-variable settings. The number of warnings in a plant needs to be significantly reduced. Warnings should be made informative, actionable and clear indicators of the risk associated with the current state of process/system variables. Plant operators should not need to monitor the trend of individual variables; instead, the risk profiles of a plant should be monitored, with warnings that have predictive capabilities. To achieve adoption of this novel approach, a paradigm shift in the overall design of the warning systems is needed. To overcome the problems associated with existing warning systems (use of single variables, alarm flooding), the proposed research program will develop an event-based approach to warning system design and management that will improve the ability of plant operators to identify potential problems, make timely decisions and take any necessary actions. By assigning warnings to events, the number of warnings will be significantly reduced, as will the number of false warnings. Incorporation of risk in the methodology for annunciation will make it possible to accommodate the importance of the process variables and the criticality of an abnormal situation. Thus it will be possible to categorize warnings using a well-defined metric. Finally, the use of prediction will provide operators with extra time to take necessary measures. The new warning system will be a valuable addition to the arsenal of plant operators in their management of abnormal situations, the prevention of plant accidents, and improve process safety.

我提出了一项为期五年的研究计划，旨在开发一种基于事件的方法来设计和管理过程行业中使用的警告系统。所提出方法的特殊特征和新颖性在于将警告分配给特定事件，风险用作警报通知和分类的基础以及对警告的预测使用。这种警告系统设计中的挑战与事件的识别，其相关变量集的选择以及对相应事件风险的持续估算有关。此外，预测的使用将需要开发识别方案来估计模型，并能够预测围绕安全限制的变量。 我在开发新型系统识别算法以及我们在警报系统设计领域的最新作品方面的经验将是克服上述挑战的宝贵工具。我的贡献记录，以前和当前的HQP培训表现以及HQP培训的详细计划将确保该计划的成功。该计划的结果将是一个新颖的警告系统设计框架和模型，相应的知识属性以及一组高素质的人员。该计划还将有助于将申请人确立为这一重要工业重要性领域的主要贡献者。 用于工业操作的警告系统，包括警报以及过程和安全警报，在监视过程安全中起着关键作用。这些系统警告操作员异常操作条件，并在需要干预时寻求操作员的注意。基于实际警告，需要及时采取行动，以帮助提高植物安全，并通过有效的预防，控制和缓解异常情况来最大程度地降低成本。但是，在工业工厂中，误导性警告是经常发生的。此外，当被虚假警报淹没时，警告系统本身可能导致异常情况并发生事故。现有警告系统无效的根本原因是使用单变量设置引起的大量警告。 需要大大减少工厂的警告数量。警告应成为与当前的过程/系统变量相关的风险的信息，可行和明确的指标。植物运营商不需要监视单个变量的趋势；取而代之的是，应监控工厂的风险概况，并具有具有预测能力的警告。为了采用这种新颖的方法，需要对警告系统的总体设计进行范式转变。 为了克服与现有警告系统相关的问题（使用单个变量，警报洪水），拟议的研究计划将开发一种基于事件的警告系统设计和管理方法，以提高植物运营商确定潜在问题的能力，做出及时的决策并采取任何必要的行动。通过向事件分配警告，警告的数量将大大减少，虚假警告的数量也将大大减少。将风险纳入通告方法中将使可以适应过程变量的重要性和异常情况的关键。因此，可以使用明确定义的度量标准对警告进行分类。最后，预测的使用将为操作员提供额外的时间来采取必要的措施。新的警告系统将是植物运营商武器库的宝贵补充，以管理异常情况，预防植物事故并提高过程安全性。