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Tongwen Chen - One of the best experts on this subject based on the ideXlab platform.

  • generalized moving variance filters for industrial Alarm Systems
    Journal of Process Control, 2020
    Co-Authors: Mohammad Hossein Roohi, Tongwen Chen
    Abstract:

    Abstract Accurate and rapid detection of variation changes in process variables is of paramount importance to the safety and proficiency of process industries. Moving variance filters detect such variation changes by tracking the variance of the last N samples of a process variable. However, no explicit formulation is available for performance analysis, and design of these filters. We extend these filters by considering the ‘generalized variance’, which is the same as the conventional variance, but the filter terms are weighted differently. Next, we propose an analytical framework to analyze the filter performance. We prove that the conventional filter indeed is the optimal configuration if only the detection accuracy is considered. But in the case study, via a counter-example, we show that this statement does not hold if we also take the detection delay index into account. In this case, our result gives a straightforward and intuitive measure to obtain the filter accuracy as a function of filter coefficients. This can also be used as a part of the cost function when designing these filters considering multiple criteria. Through a case study on the Tennessee Eastman process, we show that compared to conventional filters, generalized filters make it possible to detect abnormality faster for the same degree of accuracy.

  • ℋ 2 controller synthesis with an Alarm performance constraint
    International Symposium on Industrial Electronics, 2019
    Co-Authors: Mohammad Hossein Roohi, Tongwen Chen, Iman Izadi
    Abstract:

    Alarms are essential part of industrial plants which inform process operators about abnormal situations or the happening of faults. Ideally, for each abnormality one and only one Alarm should be raised. But in reality, many Alarms can be missed and there are also many false Alarms. So it is crucial to utilize Alarms properly. Effectiveness of Alarm Systems is also related to the behavior of the controller. In this paper, we study the effect of proportional-integral-derivative (PID) controller parameters on the Alarm performance. The performance of an Alarm system is measured based on the false Alarm rate (FAR) and missed Alarm rate (MAR). However, these indices are difficult to be exploited in the controller synthesis problem. Thus, we introduce a new index to quantify the performance of Alarm Systems. Then we introduce a new approach to design a controller which guarantees a bound for the control performance of as well the Alarm performance. We also show that there is a trade-off between control and Alarm performances.

  • analysis and design of time deadbands for univariate Alarm Systems
    Control Engineering Practice, 2018
    Co-Authors: Muhammad Shahzad Afzal, Tongwen Chen, Ali Bandehkhoda, Iman Izadi
    Abstract:

    Abstract Time-deadbands (or Alarm latches) are popular Alarm configuration methods used in industry to improve the Alarm system performance. In this paper, time-deadband based configurations for the case of univariate Alarm Systems are analyzed. Mathematical models are developed based on Markov processes, and analytical expressions for performance indices (the false Alarm rate, missed Alarm rate, and expected detection delay) are derived. Systematic design procedures are also proposed, and the utility of the methods is illustrated through design examples.

  • a method to remove chattering Alarms using median filters
    Isa Transactions, 2017
    Co-Authors: Wen Tan, Yongkui Sun, Tongwen Chen
    Abstract:

    Chattering Alarms are the most found nuisance Alarms that will probably reduce the usability and result in a confidence crisis of Alarm Systems for industrial plants. This paper addresses the chattering Alarm reduction using median filters. Two rules are formulated to design the window size of median filters. If the Alarm probability is estimated using process data, one rule is based on the probability of Alarms to satisfy some requirements on the false Alarm rate, or missed Alarm rate. If there are only historical Alarm data available, the other rule is based on percentage reduction of chattering Alarms using Alarm duration distribution. Experimental results for industrial cases testify that the proposed method is effective.

  • design of univariate Alarm Systems via rank order filters
    Control Engineering Practice, 2017
    Co-Authors: Wen Tan, Yongkui Sun, Ishtiza Ibne Azad, Tongwen Chen
    Abstract:

    Abstract Filtering is one of the techniques used in Alarm system design to improve the performance of an Alarm system. Due to the fact that the filtered data is no longer independent, computation of the performance indexes (false Alarm rate (FAR), missed Alarm rate (MAR) and expected detection delay (EDD)) is hard for filters. In this paper, rank order filters are applied in Alarm system design. The output of rank order filters is restricted to one of the input samples, thus the probability density function (PDF) of the filtered data can be computed directly from the PDF of the raw data. This feature makes it possible to compute FAR and MAR for rank order filters directly. Further, a method to compute the expected detection delay is proposed for rank order filters despite the dependence of the filtered data. Simulation results shows that the order of rank order filters provide another degree-of-freedom in Alarm system design besides the window size, which can be used to improve the Alarm performance.

Jiandong Wang - One of the best experts on this subject based on the ideXlab platform.

  • practices of detecting and removing nuisance Alarms for Alarm overloading in thermal power plants
    Control Engineering Practice, 2017
    Co-Authors: Jiandong Wang, Zijiang Yang, Kuang Chen, Donghua Zhou
    Abstract:

    Abstract Alarm overloading refers to the most noticeable phenomenon in existing Alarm Systems: there are far too many Alarms to be promptly handled by industrial plant operators. A large number of occurred Alarms are nuisance Alarms that are not associated with any actual abnormalities and are extremely detrimental to important roles of industrial Alarm Systems. This paper presents long-term industrial applications of three techniques on detecting and removing nuisance Alarms to a thermal power generation unit. By deploying these techniques, the severity of Alarm overloading phenomenon has been significantly alleviated. The average number of Alarm occurrences per day has been reduced from 18,280 to 359 in the year of 2015, so that about 98% Alarm occurrences have been removed without affecting true Alarms.

  • abnormal data detection for multivariate Alarm Systems based on correlation directions
    Journal of Loss Prevention in The Process Industries, 2017
    Co-Authors: Di Zhu, Jiandong Wang, Yan Zhao
    Abstract:

    Abstract This paper proposes a method to detect abnormal data segments from historical multivariate time series, which are common prerequisites for rationalization of industrial Alarm Systems. Correlation directions among process variables are taken as the features to detect abnormal conditions. To find time instants of changing correlation directions, key turning points (KTPs) are determined by a piecewise linear representation of multivariate time series. Correlation directions in each data segment between adjacent KTPs are calculated from Spearman's rank correlation coefficients and associated hypothesis tests. Data segments are classified into normal or abnormal ones by comparing the calculated correlation directions with their counterparts in normal conditions obtained from process knowledge. Numerical and industrial examples are provided to illustrate the proposed method.

  • an overview of industrial Alarm Systems main causes for Alarm overloading research status and open problems
    IEEE Transactions on Automation Science and Engineering, 2016
    Co-Authors: Jiandong Wang, Tongwen Chen, Fan Yang, Sirish L. Shah
    Abstract:

    Alarm Systems play critically important roles for the safe and efficient operation of modern industrial plants. However, most existing industrial Alarm Systems suffer from poor performance, noticeably having too many Alarms to be handled by operators in control rooms. Such Alarm overloading is extremely detrimental to the important role played by Alarm Systems. This paper provides an overview of industrial Alarm Systems. Four main causes are identified as the culprits for Alarm overloading, namely, chattering Alarms due to noise and disturbance, Alarm variables incorrectly configured, Alarm design isolated from related variables, and abnormality propagation owing to physical connections. Industrial examples from a large-scale thermal power plant are provided as supportive evidences. The current research status for industrial Alarm Systems is summarized by focusing on existing studies related to these main causes. Eight fundamental research problems to be solved are formulated for the complete lifecycle of Alarm variables including Alarm configuration, Alarm design, and Alarm removal.

  • performance assessment and design for univariate Alarm Systems based on far mar and aad
    IEEE Transactions on Automation Science and Engineering, 2012
    Co-Authors: Jiandong Wang, Iman Izadi, Tongwen Chen
    Abstract:

    The performance of a univariate Alarm system can be assessed in many cases by three indices, namely, the false Alarm rate (FAR), missed Alarm rate (MAR), and averaged Alarm delay (AAD). First, this paper studies the definition and computation of the FAR, MAR, and AAD for the basic mechanism of Alarm generation solely based on a trip point, and for the advanced mechanism of Alarm generation by exploiting Alarm on/off delays. Second, a systematic design of Alarm Systems is investigated based on the three performance indices and the tradeoffs among them. The computation of FAR, MAR, and AAD and the design of Alarm Systems require the probability density functions (PDFs) of the univariate process variable in the normal and abnormal conditions. Thus, a new method based on mean change detection is proposed to estimate the two PDFs. Numerical examples and an industrial case study are provided to validate the obtained theoretical results on the FAR, MAR and AAD, and to illustrate the proposed performance assessment and Alarm system design procedures.

  • averaged Alarm delay and systematic design for Alarm Systems
    Conference on Decision and Control, 2010
    Co-Authors: Jiandong Wang
    Abstract:

    The performance of a univariate Alarm system can be assessed in many cases by three indices, namely, the false Alarm rate (FAR), missed Alarm rate (MAR) and averaged Alarm delay (AAD). By contrast to the FAR and MAR, the AAD seemingly has been received litter attention. This paper firstly studies the definition and computation of the AAD for the basic mechanism of Alarm generation solely based on a trip point, and for the advanced mechanism of Alarm generation by exploiting Alarm on-delays and moving average filters. Secondly, a systematic design for Alarm Systems is proposed based on the three performance indices. The trade-offs among FAR, MAR and AAD are investigated. Numerical examples are provided to validate the obtained theoretical results on the AAD and to illustrate the proposed Alarm system design procedure.

Iman Izadi - One of the best experts on this subject based on the ideXlab platform.

  • ℋ 2 controller synthesis with an Alarm performance constraint
    International Symposium on Industrial Electronics, 2019
    Co-Authors: Mohammad Hossein Roohi, Tongwen Chen, Iman Izadi
    Abstract:

    Alarms are essential part of industrial plants which inform process operators about abnormal situations or the happening of faults. Ideally, for each abnormality one and only one Alarm should be raised. But in reality, many Alarms can be missed and there are also many false Alarms. So it is crucial to utilize Alarms properly. Effectiveness of Alarm Systems is also related to the behavior of the controller. In this paper, we study the effect of proportional-integral-derivative (PID) controller parameters on the Alarm performance. The performance of an Alarm system is measured based on the false Alarm rate (FAR) and missed Alarm rate (MAR). However, these indices are difficult to be exploited in the controller synthesis problem. Thus, we introduce a new index to quantify the performance of Alarm Systems. Then we introduce a new approach to design a controller which guarantees a bound for the control performance of as well the Alarm performance. We also show that there is a trade-off between control and Alarm performances.

  • analysis and design of time deadbands for univariate Alarm Systems
    Control Engineering Practice, 2018
    Co-Authors: Muhammad Shahzad Afzal, Tongwen Chen, Ali Bandehkhoda, Iman Izadi
    Abstract:

    Abstract Time-deadbands (or Alarm latches) are popular Alarm configuration methods used in industry to improve the Alarm system performance. In this paper, time-deadband based configurations for the case of univariate Alarm Systems are analyzed. Mathematical models are developed based on Markov processes, and analytical expressions for performance indices (the false Alarm rate, missed Alarm rate, and expected detection delay) are derived. Systematic design procedures are also proposed, and the utility of the methods is illustrated through design examples.

  • graphical tools for routine assessment of industrial Alarm Systems
    Computers & Chemical Engineering, 2012
    Co-Authors: Sandeep R Kondaveeti, Sirish L. Shah, Iman Izadi, Tim Black, Tongwen Chen
    Abstract:

    Alarms are important for safe and reliable operation in process industries. Periodic Alarm assessment is a crucial step in Alarm management lifecycle that provides valuable feedback for fine tuning the Alarm system. In this perspective tutorial, Alarm data is represented using binary sequences and subsequently, two novel Alarm data visualization tools are presented: (1) The High Density Alarm Plot (HDAP) charts top Alarms over a given time period and (2) Alarm Similarity Color Map (ASCM) highlights related and redundant Alarms in a convenient manner. The proposed graphical tools are instrumental in performance assessment of industrial Alarm Systems in terms of effectively identifying nuisance Alarms such as chattering and related Alarms based on routinely collected Alarm event data. The special features and advantages of the proposed graphical tools are illustrated by successful application to two large scale industrial case studies, each involving over half a million observations for top fifty Alarm tags.

  • performance assessment and design for univariate Alarm Systems based on far mar and aad
    IEEE Transactions on Automation Science and Engineering, 2012
    Co-Authors: Jiandong Wang, Iman Izadi, Tongwen Chen
    Abstract:

    The performance of a univariate Alarm system can be assessed in many cases by three indices, namely, the false Alarm rate (FAR), missed Alarm rate (MAR), and averaged Alarm delay (AAD). First, this paper studies the definition and computation of the FAR, MAR, and AAD for the basic mechanism of Alarm generation solely based on a trip point, and for the advanced mechanism of Alarm generation by exploiting Alarm on/off delays. Second, a systematic design of Alarm Systems is investigated based on the three performance indices and the tradeoffs among them. The computation of FAR, MAR, and AAD and the design of Alarm Systems require the probability density functions (PDFs) of the univariate process variable in the normal and abnormal conditions. Thus, a new method based on mean change detection is proposed to estimate the two PDFs. Numerical examples and an industrial case study are provided to validate the obtained theoretical results on the FAR, MAR and AAD, and to illustrate the proposed performance assessment and Alarm system design procedures.

  • on expected detection delays for Alarm Systems with deadbands and delay timers
    Journal of Process Control, 2011
    Co-Authors: Naseeb Ahmed Adnan, Iman Izadi, Tongwen Chen
    Abstract:

    Abstract False and nuisance Alarms are major problems in the process industry. Techniques like deadbands, delay-timers, and filtering can significantly reduce these false and nuisance Alarms. The down-side, however, is that using these techniques introduces some delay in raising the Alarm (detection delay). The detection delay is not often considered in the design of Alarm Systems. In this paper, detection delays are calculated using Markov processes for deadbands and delay-timers. A design procedure is then proposed that compromises between detection delay, false Alarm rate (Type I error) and missed Alarm rate (Type II error) for an optimal configuration. Inclusion of the detection delay in the Alarm design makes the design more reliable and provides better insight to the consequences.

Ali Cinar - One of the best experts on this subject based on the ideXlab platform.

  • hypoglycemia early Alarm Systems based on multivariable models
    Industrial & Engineering Chemistry Research, 2013
    Co-Authors: Kamuran Turksoy, Elif S Bayrak, Lauretta Quinn, Elizabeth Littlejohn, Derrick K Rollins, Ali Cinar
    Abstract:

    Hypoglycemia is a major challenge of artificial pancreas Systems and a source of concern for potential users and parents of young children with Type 1 diabetes (T1D). Early Alarms to warn the potential of hypoglycemia are essential and should provide enough time to take action to avoid hypoglycemia. Many Alarm Systems proposed in the literature are based on interpretation of recent trends in glucose values. In the present study, subject-specific recursive linear time series models are introduced as a better alternative to capture glucose variations and predict future blood glucose concentrations. These models are then used in hypoglycemia early Alarm Systems that notify patients to take action to prevent hypoglycemia before it happens. The models developed and the hypoglycemia Alarm system are tested retrospectively using T1D subject data. A Savitzky-Golay filter and a Kalman filter are used to reduce noise in patient data. The hypoglycemia Alarm algorithm is developed by using predictions of future glucose concentrations from recursive models. The modeling algorithm enables the dynamic adaptation of models to inter-/intra-subject variation and glycemic disturbances and provides satisfactory glucose concentration prediction with relatively small error. The Alarm Systems demonstrate good performance in prediction of hypoglycemia and ultimately in prevention of its occurrence.

  • hypoglycemia early Alarm Systems based on multivariable models
    Industrial & Engineering Chemistry Research, 2013
    Co-Authors: Kamuran Turksoy, Elif S Bayrak, Lauretta Quinn, Elizabeth Littlejohn, Derrick K Rollins, Ali Cinar
    Abstract:

    Hypoglycemia is a major challenge of artificial pancreas Systems and a source of concern for potential users and parents of young children with Type 1 diabetes (T1D). Early Alarms to warn of the potential of hypoglycemia are essential and should provide enough time to take action to avoid hypoglycemia. Many Alarm Systems proposed in the literature are based on interpretation of recent trends in glucose values. In the present study, subject-specific recursive linear time series models are introduced as a better alternative to capture glucose variations and predict future blood glucose concentrations. These models are then used in hypoglycemia early Alarm Systems that notify patients to take action to prevent hypoglycemia before it happens. The models developed and the hypoglycemia Alarm system are tested retrospectively using T1D subject data. A Savitzky-Golay filter and a Kalman filter are used to reduce noise in patient data. The hypoglycemia Alarm algorithm is developed by using predictions of future gl...

  • hypoglycemia early Alarm Systems based on recursive autoregressive partial least squares models
    Journal of diabetes science and technology, 2013
    Co-Authors: Elif S Bayrak, Kamuran Turksoy, Lauretta Quinn, Elizabeth Littlejohn, Ali Cinar, Derrick K Rollins
    Abstract:

    Background: Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas Systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas Systems. Many of the proposed Alarm Systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early Alarm Systems of potential hypoglycemia. Method: A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia Alarm Systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia Alarm algorithm using these models is proposed and evaluated. Results: Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early Alarm Systems based on RARPLS shows good performance. A sensitivity of 86% and a false Alarm rate of 0.42 false positive/day are obtained for the early Alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions:

Wang Jiandong - One of the best experts on this subject based on the ideXlab platform.

  • Practices of detecting and removing nuisance Alarms for Alarm overloading in thermal power plants
    CONTROL ENGINEERING PRACTICE, 2017
    Co-Authors: Wang Jiandong, Yang Zijiang, Chen Kuang, Zhou Donghua
    Abstract:

    Alarm overloading refers to the most noticeable phenomenon in existing Alarm Systems: there are far too many Alarms to be promptly handled by industrial plant operators. A large number of occurred Alarms are nuisance Alarms that are not associated with any actual abnormalities and are extremely detrimental to important roles of industrial Alarm Systems. This paper presents long-term industrial applications of three techniques on detecting and removing nuisance Alarms to a thermal power generation unit. By deploying these techniques, the severity of Alarm overloading phenomenon has been significantly alleviated. The average number of Alarm occurrences per day has been reduced from 18,280 to 359 in the year of 2015, so that about 98% Alarm occurrences have been removed without affecting true Alarms. (C) 2017 Elsevier Ltd. All rights reserved.National Natural Science Foundation of China [61433001]; Research Fund for the Taishan Scholar Project of Shandong Province of ChinaSCI(E)ARTICLE21-306

  • Main causes of long-standing Alarms and their removal by dynamic state-based Alarm Systems
    JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2016
    Co-Authors: Wang Jiandong, Chen Tongwen
    Abstract:

    Long-standing Alarms are those in the Alarm state continuously for a long period of time. Some long-standing Alarms belong to nuisance Alarms, playing a detrimental role to the performance of industrial Alarm Systems, and hence they should be removed. The paper analyzes the main causes leading to long-standing Alarms as nuisance ones; industrial examples from a large-scale thermal power plant are provided as supportive evidences of the main causes. A dynamic state-based Alarm system is designed to remove long-standing Alarms caused by the inconsistency between the Alarm design and discrete-valued operating states. The design is based on two rules formulated to select state variables and a novel Alarm generation mechanism to generate state-based Alarm variables. Industrial case studies illustrate the effectiveness of the dynamic state-based Alarm system in significantly reducing the severity of long-standing Alarms. (C) 2016 Elsevier Ltd. All rights reserved.National Natural Science Foundation of China [61433001]; Natural Sciences and Engineering Research Council of Canada [CRDPJ-446412-12]SCI(E)EIARTICLEjiandong@pku.edu.cn; tchen@ualberta.ca106-1194

  • Performance Assessment and Design for Univariate Alarm Systems Based on FAR, MAR, and AAD
    ieee transactions on automation science and engineering, 2012
    Co-Authors: Xu Jianwei, Wang Jiandong, Izadi Iman, Chen Tongwen
    Abstract:

    The performance of a univariate Alarm system can be assessed in many cases by three indices, namely, the false Alarm rate (FAR), missed Alarm rate (MAR), and averaged Alarm delay (AAD). First, this paper studies the definition and computation of the FAR, MAR, and AAD for the basic mechanism of Alarm generation solely based on a trip point, and for the advanced mechanism of Alarm generation by exploiting Alarm on/off delays. Second, a systematic design of Alarm Systems is investigated based on the three performance indices and the tradeoffs among them. The computation of FAR, MAR, and AAD and the design of Alarm Systems require the probability density functions (PDFs) of the univariate process variable in the normal and abnormal conditions. Thus, a new method based on mean change detection is proposed to estimate the two PDFs. Numerical examples and an industrial case study are provided to validate the obtained theoretical results on the FAR, MAR and AAD, and to illustrate the proposed performance assessment and Alarm system design procedures. Note to Practitioners-Alarm Systems are critically important to the safety and efficient operation of modern industrial plants, whose operations are monitored by continuous measurements of various signals. However, industrial surveys have shown that operators of industrial plants receive far more Alarms, many of which belong to nuisance Alarms, than they can handle. Relieving this problem is based upon a satisfactory performance of the Alarm system for each univariate signal involved in the operation of industrial plants. This paper studies the performance assessment and design of univariate Alarm Systems for basic mechanism of Alarm generation and for advanced one exploiting Alarm on/off delays. The obtained results are applicable to various industrial plants including power, chemical, and petrochemical plants.Automation & Control SystemsSCI(E)EI4ARTICLE2296-307