Performance evaluation and design for variable threshold alarm systems through semi-Markov process

YesIn large industrial systems, alarm management is one of the most important issues to improve the safety and efficiency of systems in practice. Operators of such systems often have to deal with a numerous number of simultaneous alarms. Different kinds of thresholding or filtration are applied to decrease alarm nuisance and improve performance indices, such as Averaged Alarm Delay (ADD), Missed Alarm and False Alarm Rates (MAR and FAR). Among threshold-based approaches, variable thresholding methods are well-known for reducing the alarm nuisance and improving the performance of the alarm system. However, the literature suffers from the lack of an appropriate method to assess performance parameters of Variable Threshold Alarm Systems (VTASs). This study introduces two types of variable thresholding and proposes a novel approach for performance assessment of VTASs using Priority-AND gate and semi-Markov process. Application of semi-Markov process allows the proposed approach to consider industrial measurements with non-Gaussian distributions. In addition, the paper provides a genetic algorithm based optimized design process for optimal parameter setting to improve performance indices. The effectiveness of the proposed approach is illustrated via three numerical examples and through a comparison with previous studies.Noavaran Electronic Adar Sameh company [Grant NO: IRAM17S1]

Fault detection and identification combining process measurements and statistical alarms

Classification-based methods for fault detection and identification can be difficult to implement in industrial systems where process measurements are subject to noise and to variability from one fault occurrence to another. This paper uses statistical alarms generated from process measurements to improve the robustness of the fault detection and identification on an industrial process. Two levels of alarms are defined according to the position of the alarm threshold: level-1 alarms (low severity threshold) and level-2 alarms (high severity threshold). Relevant variables are selected using the minimal-Redundancy-Maximal-Relevance criterion of level-2 alarms to only retain variables with large variations relative to the level of noise. The classification-based fault detection and identification fuses the results of a discrete Bayesian classifier on level-1 alarms and of a continuous Bayesian classifier on process measurements. The discrete classifier offers a practical way to deal with noise during the development of the fault, and the continuous classifier ensures a correct classification during later stages of the fault. The method is demonstrated on a multiphase flow facility

S-4B orbital workshop attitude control system study

Saturn S-4B orbital workshop attitude control system analysi

Decision Support System for Improved Operations, Maintenance, and Safety: a Data-Driven Approach

With industry 4.0, a new era of the industrial revolution with a focus on automation, inter-connectivity, machine learning, and real-time data collection and analysis are emerging. The smart digital technology which includes smart sensors, data acquisition, processing, and control based on big data, machine learning, and Artificial Intelligence (AI) provides boundless opportunities for the end-users to operate their plants under more optimized, reliable, and safer conditions. During an abnormal event in an industrial facility, operators are inundated with information to infer and act. Hence, there is a critical need to develop solutions that assist operators during such critical events. Also, because of the obsolescence challenges of typical industrial control systems, a new paradigm of Open Process Automation (OPA) is emerging. OPA requires a Real-time Operational Technology (OT) services to analyze the data generated by the sensors and control loops to assist the process plant operations by developing applications for advanced computing platforms in open source software platforms. The aim of this research is to highlight the potential applications of big data analytics, machine learning, and AI methods and develop solutions for plant operation, maintenance, process safety and risk management for real industry problems. This research work includes: 1. an alarm management framework integrated with data-driven (Key Performance Indicators) KPIs bench-marking, and a visualization tool is developed to address alarm management challenges; 2. a deep learning-based data-driven process fault detection and diagnosis method on cloud computing to identify abnormal process conditions; and 3. applications such as predictive maintenance, dynamic risk mapping, incident database analysis, application of Natural Language Processing (NLP) for text classification, and barrier assessment for dynamic risk mapping, A unified workflow approach is used to define the data-sources, applicable domains, and develop proposed applications. This work integrates data generated by field instrumentation, expert knowledge with data analytics and AI techniques to provide guidance to the operator or engineer to effectively take proactive decisions through “action-boards”. The robustness of the developed methods and algorithms is validated using real and simulated data sets. The proposed methods and results provide a future road map for any organization to deal with data integration with such applications leading to productive, safer and more reliable operations

Design, construction and commissioning of the Thermal Screen Control System for the CMS Tracker detector at CERN

The CERN (European Organization for Nuclear Research) laboratory is currently building the Large Hadron Collider (LHC). Four international collaborations have designed (and are now constructing) detectors able to exploit the physics potential of this collider. Among them is the Compact Muon Solenoid (CMS), a general purpose detector optimized for the search of Higgs boson and for physics beyond the Standard Model of fundamental interactions between elementary particles. This thesis presents, in particular, the design, construction, commissioning and test of the control system for a screen that provides a thermal separation between the Tracker and ECAL (Electromagnetic CALorimeter) detector of CMS (Compact Muon Solenoid experiment). Chapter 1 introduces the new challenges posed by these installations and deals, more in detail, with the Tracker detector of CMS. The size of current experiments for high energy physics is comparable to that of a small industrial plant: therefore, the techniques used for controls and regulations, although highly customized, must adopt Commercial Off The Shelf (COTS) hardare and software. The âﾜslow controlâ systems for the experiments at CERN make extensive use of PLCs (Programmable Logic Controllers) and SCADA (Supervisory Control and Data Acquisition) to provide safety levels (namely interlocks), regulations, remote control of high and low voltages distributions, as well as archiving and trending facilities. The system described in this thesis must follow the same philosophy and, at the same time, comply with international engineering standards. While the interlocks applications belong straightforwardly to the category of DES (Discrete Event System), and are therefore treated with a Finite State Machine approach, other controls are more strictly related to the regulation problem. Chapter 2 will focus on various aspects of modern process control and on the tools used to design the control system for the thermal screen: the principles upon which the controller is designed and tuned, and the model validated, including the Multiple Input-Multiple Output (MIMO) problematics are explained. The thermal screen itself, the constraints and the basis of its functioning are described in Chapter 3, where the thermodynamical design is discussed as well. For the LHC experiments, the aim of a control system is also to provide a well defined SIL (Safety Interlock Level) to keep the system in a safe condition; yet, in this case, it is necessary to regulate the temperature of the system within certain values and respect the constraints arising from the specific needs of the above mentioned subsystems. The most natural choice for a PLC-based controller is a PID (Proportional Integral Derivative) controller. This kind of controller is widely used in many industrial process, from batch production in the pharmaceutics or automotive field to chemical plants, distillation columns and, in general, wherever a reliable and robust control is needed. In order to design and tune PID controllers, many techniques are in use; the approach followed in this thesis is that of black-box modeling: the system is modeled in the time domain, a transfer function is inferred and a controller is designed. Then, a system identification procedure allows for a more thorough study and validation of the model, and for the controller tuning. Project of the thermal screen control including system modeling, controller design and MIMO implementation issues are entirely covered in Chapter 4. A systems engineering methodology has been followed all along to adequately manage and document every phase of the project, complying with time and budget constraints. A risk analysis has been performed, using Layer of Protection Analysis (LOPA) and Hazard and Operability Studies (HAZOP), to understand the level of protection assured by the thermal screen and its control components. Tests planned and then performed to validate the model and for quality assurance purposes are described in Chapter 5. A climatic chamber has been designed and built at CERN, where the real operating conditions of the thermal screen are simulated. Detailed test procedures have been defined, following IEEE standards, in order to completely check every single thermal screen panel. This installation allows for a comparison of different controller tuning approaches, including IAE minimization, Skogestad tuning rules, Internal Model Control (IMC), and a technique based upon the MatLab Optimization toolbox. This installation is also used for system identification purposes and for the acceptance tests of every thermal screen panel (allowing for both electrical and hydraulic checks). Also, tests have been performed on the West Hall CERN experimental area , where a full control system has been set up, for interlock high- and low- voltage lines. The interlock system operating procedures and behaviour have been validated during real operating conditions of the detector esposed to a particle beam. The satisfactory results of tests take the project to full completion, allowing the plan to reach the âﾜexitâ stage, when the thermal screen is ready to be installed in the Tracker and ready to be operational

Digital flight control software design requirements

The objective of the integrated digital flight control system is to provide rotational and translational control of the space shuttle orbiter in all phases of flight: from launch ascent through orbit to entry and touchdown, and during powered horizontal flights. The program provides a versatile control system structure while maintaining uniform communications with other programs, sensors, and control effects by using an executive routine/function subroutine format. The program reads all external variables at a single point, copies them into its dedicated storage, and then calls the required subroutines in the proper sequence. As a result, the flight control program is largely independent of other programs in the GN and C computer complex and is equally insensitive to the characteristics of the processor configuration. The integrated structure of the control system and the DFCS executive routine which embodies that structure are described. The specific estimation and control algorithms used in the various mission phases are shown. Attitude maneuver routines that interface with the DFCS are also described

Fault tolerant programmable digital attitude control electronics study

The attitude control electronics mechanization study to develop a fault tolerant autonomous concept for a three axis system is reported. Programmable digital electronics are compared to general purpose digital computers. The requirements, constraints, and tradeoffs are discussed. It is concluded that: (1) general fault tolerance can be achieved relatively economically, (2) recovery times of less than one second can be obtained, (3) the number of faulty behavior patterns must be limited, and (4) adjoined processes are the best indicators of faulty operation

Study of pump control in residential grid-tied solar domestic hot water photovoltaic-thermal (PV-T) systems

A study of pump control focusing on active residential grid-connected solar domestic hot water (SDHW) photovoltaic-thermal (PV-T) systems was conducted. The main goal was to determine how the two main pump controls for this segment compare, namely the differential temperature static two-level hysteretic control (DTSTLHC) and the differential temperature static saturated hysteretic-proportional control (DTSSHPC), given the dual outputs of PV-T technology: heat and electricity. In order to do so, a dynamic PV-T collector model was developed for use in transient simulations and incorporated into a SDHW PV-T system model. A substantial number of annual simulations for each of the various locations selected were conducted to encompass the best performances using each control, with emphasis on multiple combinations of controller setpoints and mass flow rates. The results show PV-T systems using DTSSHPC and optimised for maximum auxiliary energy savings consistently outperforming those using DTSTLHC and optimised using the same criterion, though the opposite was true when seeking to optimise the electrical efficiency, with those using DTSTLHC performing best. However, the advantages at best correspond to single-digit percentages of the annual thermal energy demand, and less than 0.1% of the annual electrical efficiency. Similarly low performance advantages were reached from the standpoint of primary energy efficiency and load provision cost-effectiveness by using DTSSHPC, though not consistently due to the inability to reconcile electrical, thermal and parasitic performance advantages over DTSTLHC. Moreover, the advantages presented by DTSSHPC are low enough to be offset by one additional maintenance operation, which systems using this control are likelier to require first due to its complexity and higher switching frequencies. Finally, a study on setpoint selection for differential temperature controllers, namely DTSSHPC and DTSTLHC, for use in PV-T systems was also conducted using steady-state methods, which revealed marginal differences between setpoint selection for hybrid and non-hybrid systems