{"title":"Adaptive design of delay timers for non-stationary process variables based on change detection and Bayesian estimation","authors":"Shuo Shi, Jiandong Wang","doi":"10.1016/j.jprocont.2025.103410","DOIUrl":null,"url":null,"abstract":"<div><div>In industrial alarm systems, delay timers are embedded modules to deal with nuisance alarms. However, most existing approaches for the design of delay timers make an assumption that process variables are stationary distributed, so that designed delay timers may not achieve the desired performance on false alarm rates (FAR) and missed alarm rates (MAR) for non-stationary process variables. Motivated by such a problem, this paper proposes an adaptive approach that updates delay timer parameters to control the number of nuisance alarms. Two main technical issues are addressed. For the first issue of whether delay timer parameters need to be updated, three cases of updating delay timer parameters are formulated according to the changes in alarm durations or intervals and the conditions of process variables. For the second issue of determining time instants to update delay timer parameters, the Bayesian estimation technique is exploited based on confidence intervals of FAR or MAR to be achieved. The proposed approach is illustrated by industrial and numerical examples, showing its necessity via a comparison with conventional delay timers whose parameters are fixed.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"149 ","pages":"Article 103410"},"PeriodicalIF":3.3000,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Process Control","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959152425000381","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In industrial alarm systems, delay timers are embedded modules to deal with nuisance alarms. However, most existing approaches for the design of delay timers make an assumption that process variables are stationary distributed, so that designed delay timers may not achieve the desired performance on false alarm rates (FAR) and missed alarm rates (MAR) for non-stationary process variables. Motivated by such a problem, this paper proposes an adaptive approach that updates delay timer parameters to control the number of nuisance alarms. Two main technical issues are addressed. For the first issue of whether delay timer parameters need to be updated, three cases of updating delay timer parameters are formulated according to the changes in alarm durations or intervals and the conditions of process variables. For the second issue of determining time instants to update delay timer parameters, the Bayesian estimation technique is exploited based on confidence intervals of FAR or MAR to be achieved. The proposed approach is illustrated by industrial and numerical examples, showing its necessity via a comparison with conventional delay timers whose parameters are fixed.
在工业报警系统中,延迟计时器是处理骚扰报警的嵌入式模块。然而,现有的大多数延迟计时器设计方法都假设过程变量是静态分布的,因此设计的延迟计时器在非静态过程变量的误报率(FAR)和漏报率(MAR)方面可能达不到预期的性能。受这一问题的启发,本文提出了一种更新延迟计时器参数以控制误报数量的自适应方法。本文主要解决了两个技术问题。第一个问题是延迟计时器参数是否需要更新,根据报警持续时间或间隔的变化以及过程变量的条件,提出了三种更新延迟计时器参数的情况。对于第二个问题,即确定更新延迟计时器参数的时间,利用了基于 FAR 或 MAR 置信区间的贝叶斯估计技术。通过与参数固定的传统延迟计时器进行比较,以工业和数值实例说明了所提出方法的必要性。
期刊介绍:
This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others.
Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques.
Topics covered include:
• Control applications• Process monitoring• Plant-wide control• Process control systems• Control techniques and algorithms• Process modelling and simulation• Design methods
Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.