{"title":"优化多元报警系统:利用线性规划技术研究联合误报率和联合漏报率","authors":"","doi":"10.1016/j.psep.2024.09.078","DOIUrl":null,"url":null,"abstract":"<div><div>In modern complex industrial systems, multiple process variables interact with one another. The role of alarm systems in ensuring the safety of these systems is of utmost importance. Consequently, there is an increasing value placed on the assessment of the performance of multivariate alarm systems. As the dimensions of the system and the number of variables grow, designing optimal parameters for the multivariate alarm system using traditional approaches such as probability density function estimation becomes increasingly convoluted. In this paper, an approximate method is proposed for calculating two indices known as the Joint False Alarm Rate (JFAR) and Joint Missed Alarm Rate (JMAR), which are used to evaluate the performance of multivariate alarm systems. These indices are computed using the multivariate Markov chain method. The Markov chain is constructed by solving an optimal Linear Programming (LP) problem. Subsequently, joint indices are defined based on steady state estimations of a multivariate Markov chain. To validate the theoretical results obtained on the JFAR and JMAR and to demonstrate the proposed performance assessment and alarm system design procedures, numerical example and an industrial case study are provided.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing multivariate alarm systems: A study on joint false alarm rate, and joint missed alarm rate using linear programming technique\",\"authors\":\"\",\"doi\":\"10.1016/j.psep.2024.09.078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In modern complex industrial systems, multiple process variables interact with one another. The role of alarm systems in ensuring the safety of these systems is of utmost importance. Consequently, there is an increasing value placed on the assessment of the performance of multivariate alarm systems. As the dimensions of the system and the number of variables grow, designing optimal parameters for the multivariate alarm system using traditional approaches such as probability density function estimation becomes increasingly convoluted. In this paper, an approximate method is proposed for calculating two indices known as the Joint False Alarm Rate (JFAR) and Joint Missed Alarm Rate (JMAR), which are used to evaluate the performance of multivariate alarm systems. These indices are computed using the multivariate Markov chain method. The Markov chain is constructed by solving an optimal Linear Programming (LP) problem. Subsequently, joint indices are defined based on steady state estimations of a multivariate Markov chain. To validate the theoretical results obtained on the JFAR and JMAR and to demonstrate the proposed performance assessment and alarm system design procedures, numerical example and an industrial case study are provided.</div></div>\",\"PeriodicalId\":20743,\"journal\":{\"name\":\"Process Safety and Environmental Protection\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Process Safety and Environmental Protection\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0957582024012199\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Process Safety and Environmental Protection","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957582024012199","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Optimizing multivariate alarm systems: A study on joint false alarm rate, and joint missed alarm rate using linear programming technique
In modern complex industrial systems, multiple process variables interact with one another. The role of alarm systems in ensuring the safety of these systems is of utmost importance. Consequently, there is an increasing value placed on the assessment of the performance of multivariate alarm systems. As the dimensions of the system and the number of variables grow, designing optimal parameters for the multivariate alarm system using traditional approaches such as probability density function estimation becomes increasingly convoluted. In this paper, an approximate method is proposed for calculating two indices known as the Joint False Alarm Rate (JFAR) and Joint Missed Alarm Rate (JMAR), which are used to evaluate the performance of multivariate alarm systems. These indices are computed using the multivariate Markov chain method. The Markov chain is constructed by solving an optimal Linear Programming (LP) problem. Subsequently, joint indices are defined based on steady state estimations of a multivariate Markov chain. To validate the theoretical results obtained on the JFAR and JMAR and to demonstrate the proposed performance assessment and alarm system design procedures, numerical example and an industrial case study are provided.
期刊介绍:
The Process Safety and Environmental Protection (PSEP) journal is a leading international publication that focuses on the publication of high-quality, original research papers in the field of engineering, specifically those related to the safety of industrial processes and environmental protection. The journal encourages submissions that present new developments in safety and environmental aspects, particularly those that show how research findings can be applied in process engineering design and practice.
PSEP is particularly interested in research that brings fresh perspectives to established engineering principles, identifies unsolved problems, or suggests directions for future research. The journal also values contributions that push the boundaries of traditional engineering and welcomes multidisciplinary papers.
PSEP's articles are abstracted and indexed by a range of databases and services, which helps to ensure that the journal's research is accessible and recognized in the academic and professional communities. These databases include ANTE, Chemical Abstracts, Chemical Hazards in Industry, Current Contents, Elsevier Engineering Information database, Pascal Francis, Web of Science, Scopus, Engineering Information Database EnCompass LIT (Elsevier), and INSPEC. This wide coverage facilitates the dissemination of the journal's content to a global audience interested in process safety and environmental engineering.