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

我提出了一个为期五年的研究计划，旨在开发一个基于事件的方法来设计和管理过程工业中使用的预警系统。所提出的方法的特点和新奇是在分配的警告，以特定的事件，使用的风险作为报警和分类的基础，并使用预测的警告。设计这样一个预警系统的挑战是与事件的识别，选择其相关的变量集，并连续估计相应事件的风险。此外，预测的使用将需要开发识别方案，以估计具有预测安全限值附近变量能力的模型。我在开发新的系统识别算法方面的经验以及我们最近在报警系统设计领域的工作将是克服上述挑战的宝贵工具。我的贡献记录，以前和现在的HQP培训表现，以及详细的HQP培训计划将确保该计划的成功。该计划的成果将是一个新颖的预警系统设计框架和模型，相应的知识产权，以及一批高素质的人才。该计划还将有助于将申请人确立为这一具有重要工业重要性的领域的主要贡献者。用于工业操作的警报系统，包括警报以及过程和安全警报，在监控过程安全方面发挥着关键作用。这些系统警告操作员异常操作条件，并在需要干预时引起操作员的注意。需要根据真实的警告及时采取行动，通过有效预防、控制和缓解异常情况，帮助提高工厂安全并最大限度地降低成本。然而，在工厂中，误导性的警告经常发生。此外，当充斥着虚假警报时，警报系统本身可能导致异常情况和工厂事故。现有警告系统无效的根本原因是使用单变量设置导致的大量警告。工厂中的警告数量需要大幅减少。应使风险评估成为与过程/系统变量的当前状态相关的风险的信息性、可操作性和明确的指标。工厂操作员不需要监控单个变量的趋势;相反，应该监控工厂的风险状况，并发出具有预测能力的警告。为了实现采用这种新的方法，需要在警报系统的整体设计的范式转变。为了克服与现有的报警系统（使用单变量，报警洪水）相关的问题，拟议的研究计划将开发一个基于事件的方法来报警系统的设计和管理，将提高工厂运营商的能力，以识别潜在的问题，及时作出决定，并采取任何必要的行动。通过将警告分配给事件，警告的数量将显著减少，错误警告的数量也将显著减少。在通知方法中纳入风险将使其能够适应过程变量的重要性和异常情况的关键性。因此，可以使用定义明确的度量标准对警告进行分类。最后，预测的使用将为运营商提供额外的时间来采取必要的措施。新的报警系统将是一个有价值的除了武器库的工厂操作员在他们的管理异常情况，防止工厂事故，并提高过程安全。

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.