Combining FAP,MAP and correlation analysis for multivariate alarm thresholds optimization in industrial process

In the real industrial process, alarm threshold optimization is an important part of alarm system rationalization. If the design of alarm threshold is unreasonable, it would result in nuisance alarms, among which the critical alarms are overwhelmed. In order to alleviate this phenomenon, we propose a method of multivariate alarm thresholds optimization to reduce the nuisance alarms. Firstly, causal relationship between process variables is constructed based on the time delay estimation method, thus we can determine the alarms propagation path and then select the optimized variables. Secondly, in order to guarantee both the process safety and correlation consistency, three factors - false alarm probability (FAP), missed alarm probability (MAP), and the correlation between the alarm information and process information – are combined to establish the objective function of the optimization process for the first time. Then, the optimal thresholds are obtained by the genetic algorithm. Finally, the validity and effectiveness of the developed method are illustrated by the Tennessee Eastman process.     

A risk-based approach to design warning system for processing facilities

Alarm flooding is a major safety issue in today's processing facilities. Important recommendations are available for alarm management; however, they are often violated in practice, especially in the alarm systems implemented through the distributed control system. An effective process alarm prioritization and management system is desired for a safe and effective operation of a process facility.In present work, authors address two main issues related to an alarm system – the reliability and the prioritization of the alarms. The main objective is to deal with the alarm-flooding problem in process facilities. A multi alert voting system based on sensor redundancy approach is proposed to improve the reliability. A quantitative risk-based alarm management approach is proposed to address the flooding issue. In the risk-based approach, an integrated model consisting of the probability (P), the impact (I) of the potential hazards, and the process safety time is proposed to prioritize these raised alarms.The proposed approach is further explained by a reactor system with pressure and temperature variable monitoring and controls, where the hazards associated with two alerts caused by over high pressure and over high temperature are analyzed and integrated with response time for alarms generation and prioritization.     

A data similarity based analysis to consequential alarms of industrial processes

The analysis of consequential alarms is beneficial to avoiding alarm flooding and finding out root alarms in an industrial process. In this context, a novel similarity computation method taking into account of correlation delays between process alarms is introduced firstly. Subsequently, the Granger causality method is suggested to further clarify mutual impacts of similar alarm variables based on process data. Through the combination of alarm data similarity analysis and process data causality analysis, the consequential alarms can be effectively identified along with their evolution paths. An industrial case is employed to illustrate the benefits of the contribution.     

基于数据驱动的石化装置静态报警抑制策略研究

由生产状态变化引起的误报警频发,为解决现有针对基于状态报警的抑制方法缺乏完整性与定量分析的问题,提出了新的报警抑制策略。通过分析报警记录等数据库,对引起报警的生产条件进行结构化整定并量化,利用分类筛选与数据过滤找出基于状态的报警,再结合关联性分析和概率判断,建立了基于数据驱动的静态报警抑制策略。使用现场数据的试验证明了该方法的有效性。     

Comprehensive alarm information processing technology with application in petrochemical plant

During the abnormal plant conditions, too much information is produced due to momentary plant excursions above alarm limits. This flood of information impedes correct interpretation and correction of plant conditions by the operator. Existing techniques for the design of alarm systems mostly have weak ability to handle complex hazard scenarios and increase the probability of larger safety issues. In this paper, a comprehensive alarm information processing (AIP) technology is introduced, called multi-round alarm management system (MRAMS), including several processing strategies: AIP based on single sensor, AIP based on sensor group, root cause diagnosis based on Bayesian network, sensor fault judgment method and false alarm inhibition method. In case studies, both simulation experiment and pilot application on a real petrochemical plant are presented. Results indicate the MRAMS is helpful in improving the accuracy of correctly diagnosing the root causes and hence avoiding false and redundant alarms. By adopting this new technology, the safe and reliable operation of the plant can be achieved, and the economic loss brought by improper alarms can be reduced.     

基于贝叶斯估计的多探测器火警判定方法研究*

为应对感烟探测器的大量误报对消防应急响应带来的挑战,考虑目前以感烟探测器为主的火警设施误报率高且短期内难以全部更换的特点,提出基于贝叶斯估计的多探测器火警判定方法,通过多个探测器的报警时间间隔计算火源位置的后验概率分布,并提出火警真实度概念,为火警判定提供依据。结果表明:使用多探测器耦合模型时每增加1个探测器可将误报率降低约4个数量级,该方法在探测器正常、部分失效、误报的情景下均能有效判别火警。     

Data classification and performance evaluation for the most commonly-used univariate alarm systems

Alarm systems are critically important for safe and efficient operations of industrial plants, but many industrial alarm systems are suffering from too many nuisance alarms. This paper proposes a method to classify normal and abnormal data segments and evaluate performance indices for the most commonly used univariate alarm systems. The proposed method consists of three steps. First, piece-wise linear representations are exploited in separating historical data samples of an analog process variable configured with alarms into data segments with same qualitative trends. Second, data segments are classified into normal, abnormal and unclassified conditions via a mean hypothesis test; a required assumption is that data segments in normal and abnormal conditions have different mean values being distinguishable from alarm thresholds. Third, based on the normal and abnormal data, performance indices of univariate alarm systems are calculated, including two newly formulated ones as the false alarm duration ratio and the missed alarm duration ratio. The effectiveness of the proposed method is illustrated by numerical and industrial examples.     

水蒸气引起感烟火灾探测器误报研究

针对水蒸气这种典型的火灾探测误报源．在自行研制的火灾探测综合模拟实验平台中,通过收集水沸腾形成的水雾模拟水蒸气干扰源,研究了冬季与夏季,即不同环境温度务件下,水蒸气对散射型光电感烟火灾探测器的误报影响。通过比较感烟火灾探测器的输出值与其附近湿度变化曲线,分析了误报发生的原因。结果表明在气温较低的冬季,水蒸气较易形成液态小水珠,容易导致感烟火灾探测器误报;而在夏季由于气温较高,这种误报不易发生。     

潮湿引起感烟火灾探测器误报研究

针对潮湿现象成为典型的火灾探测误报源 ,在火灾探测综合模拟实验平台中 ,通过收集水沸腾形成的水雾进行加湿 ,研究了冬季与夏季潮湿环境 ,对散射型光电感烟火灾探测器的发生误报影响。通过比较探测器的输出值与其附近湿度变化曲线 ,从原理上分析了误报发生的原因。实验结果表明 :在气温较低的冬季 ,水蒸气较易形成液态小水珠 ,容易导致感烟探测器误报警 ,而在夏季由于气温较高 ,这种情况较难发生。对相对湿度较高或达到饱和湿度 ,以及非火灾因素的雾气或微细水珠 ,对感烟探测器可靠性的影响 ,开展下进一步的工作进行了展望     

Fault diagnosis of pipeline and pump unit systems using status coupling analysis

Earlier studies on fault diagnosis of the pipeline and pump unit systems (PPU) relied mainly on independent equipment analyses, which usually lead to false alarms because of the loss of information fusion. The aim of this study is to utilize the status coupling relationship to improve fault detection sensitivity and reduce false alarm rate. A real-time status identification of related equipment step is added between capturing abnormal signals and listing out diagnosis results. For example, when the pipeline pressure fluctuation is found abnormal, a status analysis of pump units is performed immediately, if the pump units are proven to be operational normally, then the pipeline leak alarm is acknowledged valid. The logical reasoning algorithm is used to capture abnormal conditions of pipeline pressures. The pump unit faults are captured by combining information from multiple sources. Field applications show that the proposed method significantly improves the PPU fault detection capability on fault detection sensitive and accuracy.     

多传感器耦合区域火灾报警技术研究

早期预警与低误报率一直是建筑火灾探测面临的挑战与难题。已有研究多针对特殊场所特定燃烧产物或多种传感器耦合,普适性不强,探测设备成本高,无法大规模应用。通过将火灾烟气蔓延规律与探测器信号时空分布融合,在不增加探测器数量和分布的情况下,提出了一种基于建筑结构微元的多传感器耦合区域火灾报警模型。对典型火灾场景的烟气蔓延情况进行了模拟分析,狭长结构中探测器信号强度变化具有一定的规律性。应用区域火灾报警模型后,报警时间较传统模式提前了14.7%,基本杜绝了单个探测器误报引发建筑物火灾报警的问题。结果表明:多传感器耦合探测模式显著缩短了火灾报警时间,降低了火灾探测误报率,实现了火灾的早期准确识别与预警。     

火灾自动报警系统可靠性研究

火灾自动报警系统主要包括火灾探测器、火灾报警控制器、减灾装置和灭火装置4部分,从这4部分分析了其工作原理。在此基础上,着重分析了误报、漏报概率较高的火灾探测系统(包括火灾探测器和火灾报警控制器)在使用过程中可能出现的失效状态。其失效的根本原因是在探测器的设计、选型与安装中出现的问题以及各类控制器和控制软件出现的问题。火灾自动报警系统在设计、安装和使用过程中出现的一些问题可能导致整个系统失效,主要包括硬件故障、系统失误和管理缺陷3类。因此,从火灾自动报警系统设计、软硬件产品质量、选型与安装及维护保养等方面给出了提高火灾自动报警系统可靠性的措施。最后应用系统安全及可靠性理论建立了包括电源系统、触发装置、报警控制装置和警报装置4个指标的火灾自动报警系统可靠度计算模型。     

基于化工生产过程历史数据的报警优化方法研究

为了有效降低报警装置漏报率和误报率,基于化工生产的过程历史数据,探讨了报警优化的两种方法。以误报率和漏报率为优化指标,建立报警阈值目标函数,从最小化目标函数的角度出发,采用数值优化的方法进行报警阈值的优化设计。基于报警时长的变异系数,应用自适应报警延时方法来降低报警数量。实例研究表明,应用基于化工生产过程历史数据的方法,可有效减少无效报警数量,降低误报率和漏报率,提高报警质量,对于提高石化生产过程的安全性具有积极意义。     

Model-based information fusion investigation on fault isolation of subsea systems considering the interaction among subsystems and sensors

The offshore oil industry has expanded to deep water and Arctic. The harsh operating conditions (e.g., ice and strong wind) and increasing complicated system raise the occurrence likelihood of system faults. This requires timely fault isolation and management in the subsea system. However, the offshore oil industry mainly relies on humans to isolate faults based on alarms. With harsh operating conditions and increasing complicated system, this industry urgently needs research on more efficient fault isolation and cause diagnosis methods. Unfortunately, limited research is conducted on fault isolation method in the offshore oil industry. Furthermore, in industry 4.0 era, large amounts of information are obtained. This provides precondition for the application of information fusion technique which aims to improve diagnosis results. However, to the authors’ knowledge, information fusion has not been much studied in the fault isolation of the offshore oil industry. Moreover, the interaction of different subsystems contains valuable information. How the interaction of different subsystems can influence the fault diagnosis has not been explored. This paper proposes a Bayesian network (BN) based method for timely fault isolation and cause diagnosis for the offshore oil industry. The work fuses different information, and it also includes the dependency among different subsystems in the fault diagnosis. As an important alarm source, false alarms are also taken into account in the model. A case study on the subject of the subsea wellhead and chemical injection systems is conducted to demonstrate the functions and merits of the proposed method.     

Alarm management optimization in chemical installations based on adapted HAZOP reports

Most current alarm systems used in chemical installations show poor performance due to alarm flooding. This study focuses on alarm management systems optimization using the deviation propagation relationship hidden in the hazard and operability study (HAZOP) report, which can be transformed into a critical information source for alarm optimization management. More concretely, this means matching the alarm tag number with the process deviations in the deviation column, possible cause column, and consequence column. Furthermore, a backtracking method and a reasoning method were established to identify the initial alarm and associated alarms. Besides, a root fault diagnosis was carried out. A method of detecting hardware faults and unreasonable alarm thresholds is established using alarm causality corresponding to the deviation causality and associated alarm generation-skipping tracing method. According to the severity of the consequence corresponding to the deviation, a determined alarm priority method is constructed. The results show that the deviation propagation relationship in the HAZOP report is clear, and the topological relationship is easy to build based on the deviation propagation relationship. With comprehensive and in-depth HAZOP analysis reports in China, the alarm management optimization technology based on adapted HAZOP reports shows good prospects for application and promotion.     

Hazards equal trips or alarms or both

Anyone who has been involved in the application of IEC 61508 and IEC 61511 by undertaking the Safety Integrity Level (SIL) determination for Safety Instrumented Systems (SIS) will appreciate the amount of effort and tenacity that is required to undertake the task. SIL determination of Safety Instrumented Systems requires considerable commitment and tenacity to get the job done, but it is like climbing to the top of a hill only to be faced with a mountain when we come to consider what is involved in reviewing or configuring a typical alarm system.A medium sized process facility may have a few hundred or so primary Safety Instrumented Functions (SIF) or trips configured into a Safety Instrumented System, but the number of alarms configured into a process control system (PCS), that need to be assessed and prioritised, can often run into the thousands.There is synergy between safety instrumented functions and alarms because they both make a contribution to reduce the risk of having unwanted events, and both need an assigned appropriate criticality.This paper details various methods of criticality assessment which have been successfully applied to set the appropriate priority, identify the critical alarms that need to be upgraded to trips and to rationalise those of no value. It will also cover the use of software tools which can significantly reduce the effort involved in this process.     

An experimental comparison of conservative versus optimal collision avoidance warning system thresholds

In the distributed signal detection theoretic (DSDT) model, the human operator and the warning mechanism are independent decision makers who work together as a team. The DSDT demonstrates that the optimal warning threshold, in general, differs from the signal detection theoretic (SDT) threshold, which assumes a single decision maker. This prediction was tested in an experiment where drivers received monetary rewards for making safe passing decisions on a driving simulator. The experiment focused on evaluating the quality of the decision making of the drivers, and not on perceptual issues. A collision avoidance system provided a warning when the probability of an inadequate overtaking gap exceeded a threshold. Three thresholds were tested. The control threshold resulted in no detections or false alarms. The DSDT threshold resulted in some misses but no false alarms. The SDT threshold resulted in no misses but frequent false alarms. As predicted, (1) drivers performed the best when the warning system used the DSDT threshold, and (2) use of the SDT threshold improved performance over the control threshold, even though four of the 10 drivers occasionally ignored the warning and made risky passing attempts in the SDT conditions, possibly because of earlier false alarms. These findings support the conclusion that the DSDT model is a useful, quantitative tool that should be used by warning designers.     

Evaluation and comparison of alarm reset modes in advanced control room of nuclear power plants

An automation function has been widely applied in main control room of nuclear power plants (NPPs). The alarm system of fourth nuclear power plant (FNPP) in Taiwan is also going to be developed with automatic technology that is expected to support the operators’ performance and reduce the number of alarms. In this study, an experiment with a training simulator as an advanced alarm system was conducted to compare the effects of different alarm reset modes on performance and subjective ratings. The objective was to evaluate the practicability of alarm system with only auto-reset function in FNPP. Results revealed that, using the auto-reset mode, participants had lower task load index (TLX) on effort in the first test trial and was more satisfied under multi-task condition. In contrast, using manual reset mode, participants were more satisfied on alarm handling, monitoring, and decision making. In other words, both reset modes are necessary to assist the operator in different aspects, but with only single reset mode is insufficient. The reset function in advanced alarm system therefore should be very flexible.     

基于控制网络的输送机运行故障智能诊断

对煤矿井下胶带输送机运行过程中容易出现的故障,在计算机监控系统的基础上,研究了智能化的检测和判断方法。与传统的胶带机综合保护系统相比,减少了误报和漏报现象,既提高了故障诊断的可信度,又提高了胶带机运行的效率和可靠性。